COMPARISON OF AN EFFORT DEPENDENT PAIN
ASSESSMENT TOOL WITH THE VISUAL ANALOGUE
SCORE IN ORTHOPAEDIC POSTOPERATIVE PATIENTS
IN MULAGO HOSPITAL
DR KIMENYE SPECIOSA MBULA
MBChB (MAK)
DISSERTATION
SUPERVISORS
1. DR JVB TINDIMWEBWA MBChB, M.Med. Anaesthesia(MAK )
LECTURER, MAKERERE UNIVERSITY
2. DR
MARK
KASUMBA
MBChB,
M.Med.
Anaesthesia
(MAK)
REGISTRAR MULAGO HOSPITAL
DISSERTATION SUBMITTED IN PARTIAL FULFILMENT OF
THE REQUIREMENTS FOR THE AWARD OF A DEGREE IN
MASTERS OF MEDICINE IN ANAESTHESIOLOGY OF
MAKERERE UNIVERSITY
2010
DECLARATION
To the best of my knowledge, this work is original and has never been presented in any institution of
learning either in partial or total fulfilment for the requirements of the award of any degree. The
contributions used in this manuscript are appreciated and their sources quoted. I therefore present it
for the award of the degree of Master of Medicine in Anaesthesia of Makerere University.
Author: Dr Speciosa Mbula Kimenye
Signature:_______________________
Supervisors:
Dr JVB Tindimwebwa
Lecturer, Department of Anaesthesia
Makerere University
Dr Mark Kasumba
Registrar, Department of Anaesthesia
Mulago Hospital
i
DEDICATION
This book is dedicated to my Parents
Dr David Kimenye and Dr Lydia Kimenye
Who so tirelessly cheer me on through the academic path.
ii
ACKNOWLEDGEMENTS
I would like to acknowledge my supervisors Dr. JVB Tindimwebwa and Dr M Kasumba, who
without their continued support and encouragement, this study would have been a daunting task.
Their input was invaluable.
I would also like to thank my colleagues in the departments of anaesthesia and orthopaedics who
made the study possible by referring the patients and providing anaesthesia respectively.
Many thanks to my family and friends that has continually supported my stay in Uganda as I
pursued my masters degree. May the LORD reward you richly.
I would also like to acknowledge the Association of Great Britain and Ireland for both funding the
study and my studies at Makerere University.
I would also like to thank my greatest friend of all Dr Levis Mwanza Nguku, you are a jewel. Many
thanks.
And finally my utmost thanks are to my LORD for bringing all the above people my way to make
this study, my studies and the stay at Makerere University fulfilling.
iii
LIST OF TABLES
Table 1
Table showing education level.
Table 2
Table showing the validity of the EDPAT.
Table 3
Table showing the validity of the EDPAT for mild, moderate and severe pain.
Table 4
Table showing Inter-rater Coefficients (Kappa Statistic) of the EDPAT.
iv
LIST OF FIGURES
Figure 1
Pie chart showing gender distribution.
Figure 2
Bar chart showing the occupation of study participants
Figure 3
Pie chart showing the diagnosis of the study participants.
Figure 4
Histogram showing number of study participants with pain Pre-operatively and
postoperatively at O, 6 and 24 hours.
v
TABLE OF CONTENTS
DECLARATION ........................................................................................................................................ i
DEDICATION ........................................................................................................................................... ii
ACKNOWLEDGEMENTS ..................................................................................................................... iii
LIST OF TABLES .................................................................................................................................... iv
LIST OF FIGURES ................................................................................................................................... v
ABBREVIATIONS AND ACRONYMS ................................................................................................. ix
OPERATIONALDEFINITIONS .............................................................................................................. x
ABSTRACT .............................................................................................................................................11
CHAPTER 1 INTRODUCTION ............................................................................................................ 12
PROBLEM STATEMENT .................................................................................................................... 13
JUSTIFICATION .................................................................................................................................. 14
SIGNIFICANCE OF THE STUDY ...................................................................................................... 15
RESEARCH QUESTION ..................................................................................................................... 15
GENERAL OBJECTIVE ...................................................................................................................... 15
SPECIFIC OBJECTIVES ..................................................................................................................... 15
NULL HYPOTHESIS ........................................................................................................................... 16
ALTERNATE HYPOTHESIS ............................................................................................................... 16
CONCEPTUAL FRAMEWORK.......................................................................................................... 17
CHAPTER 2 LITERATURE REVIEW .................................................................................................. 18
PAIN ...................................................................................................................................................... 18
THE FACTORS AFFECTING THE PERCEPTION OF PAIN ............................................................ 18
PAIN ASSESSMENT............................................................................................................................ 18
POSTOPERATIVE ANALGESIA ........................................................................................................ 21
CHAPTER 3 METHODS ....................................................................................................................... 24
STUDY SETTING ................................................................................................................................ 24
STUDY DESIGN .................................................................................................................................. 24
vi
STUDY POPULATION ........................................................................................................................ 24
SELECTION CRITERIA OF STUDY PARTICIPANTS ..................................................................... 24
Inclusion criteria ........................................................................................................... 24
Exclusion Criteria ......................................................................................................... 25
SAMPLING PROCEDURE .................................................................................................................. 25
SAMPLE SIZE CALCULATION ......................................................................................................... 25
VARIABLES ......................................................................................................................................... 26
PROCEDURE ....................................................................................................................................... 26
QUALITY ASSURANCE ..................................................................................................................... 27
DATA MANAGEMENT ....................................................................................................................... 28
STATISTICAL ANALYSIS .................................................................................................................. 28
ETHICAL CONSIDERATION ............................................................................................................. 30
DISSEMINATION OF RESULTS ........................................................................................................ 31
LIMITATIONS ...................................................................................................................................... 31
CHAPTER 4 RESULTS .......................................................................................................................... 32
DEMOGRAPHICS ............................................................................................................................... 32
VALIDATION OF THE EDPAT ........................................................................................................... 36
ASSOCIATION BETWEEN DEMOGRAPHIC FACTORS AND THE EDPAT .............................. 39
CHAPTER 5: DISCUSSION .................................................................................................................. 43
CHAPTER 5: DISCUSSION .................................................................................................................. 43
DEMOGRAPHIC CHARACTERISTICS ............................................................................................ 43
VALIDATION OF THE EDPAT ........................................................................................................... 44
THE ASSOCIATION BETWEEN DEMOGRAPHIC VARIABLE AND EDPAT. .............................. 47
CHAPTER 6 CONCLUSION ................................................................................................................. 49
CHAPTER 7 RECOMMENDATIONS .................................................................................................. 50
REFERENCES ........................................................................................................................................ 51
vii
APPENDIX I: CONSENT FORM- ENGLISH ...................................................................................... 56
APPENDIX I: CONSENT FORM- ENGLISH ...................................................................................... 56
APPENDIX II: TRANSLATED CONSENT FORM (LUGANDA) ...................................................... 60
APPENDIX III: EFFORT-DEPENDENT PAIN-ASSESSMENT TOOL............................................... 63
APPENDIX
IV:
TRANSLATED
EFFORT-DEPENDENT
PAIN-ASSESSMENT
TOOL
(LUGANDA ) .......................................................................................................................................... 64
APPENDIX V: VISUAL ANALOGUE SCORE .................................................................................... 65
APPENDIX VI: AMERICAN SOCIETY OF ANAESTHESIOLOGIST CLASSFICATION OF
PHYSICAL STATUS .............................................................................................................................. 66
APPENDIX VII: DATA COLLECTION FORM: ................................................................................... 67
APPENDIX VIII: BUDGET ................................................................................................................... 71
APPENDIX IX: FORMULAE ................................................................................................................ 73
APPENDIX X: STUDY PERIOD: ......................................................................................................... 74
viii
ABBREVIATIONS AND ACRONYMS
EDPAT: Effort Dependent Pain Assessment Tool.
VAS: Visual Analogue Score
ASA: American Society of Anaesthesiologists
ORIF: Open Reduction Internal Fixation
ix
OPERATIONAL DEFINITIONS:
ANALGESIA: this is pain medication given to patients who have pain, also called pain killers.
POST OPERATIVE: the period immediately after surgery
TOOL: an instrument used for collecting data.
SENSITIVITY: proportion of the subjects with the disease (in this case pain) in whom the test gives
the right answer( i.e. positive).
SPECIFICITY: the proportion of subjects without the disease in whom the test gives the right
answer (i.e. negative)
VALIDITY: measurement of the diagnostic value of a test (includes specificity, sensitivity, positive
predictive value, negative predictive value) . It also includes the limits of agreement between 2
diagnostic tests.
TIME 0 HOURS: at the end of surgery, before the patient leaves the operating theatre.
RESCUE/BREAKTHROUGH ANALGESIA: this is the pain medication given to a patient who
complains of pain before the next scheduled time for analgesia.
PAIN: The International Association for the study of pain defines pain as an unpleasant sensory and
emotional experience associated with actual or potential tissue damage or described in terms of such
damage.
x
ABSTRACT
Introduction: Pain is a major concern to patients. Poorly treated postoperative pain leads to
several complications. Pain assessment helps to treat pain and improves patients’ outcome.
Problem statement: Pain assessment in orthopaedic patients poses a great challenge since most
validated tools are too abstract for patients to use. There is need to develop a subjective pain
assessment tool.
Justification: The effort dependent pain assessment tool was developed in Mulago hospital.
However this tool has not been validated. The purpose of this study is to validate it against the
gold standard.
Study objectives: The objectives of the study are to compare the Effort Dependent Pain
Assessment Tool with the Visual Analogue Scale in assessing pain among patients who have had
lower limb orthopaedic surgery.
Methods: This was a cross-sectional descriptive study conducted on ward seven, department of
orthopaedics, Mulago hospital. 92 patients were sequentially recruited and data on
demographics, injuries and circumstance surrounding injuries recorded. The data was analyzed
using Stata Ver. 10(Stata Corp LP, USA) and Microsoft Excel 2007 ( Microsoft Corporation
2007.).
11
CHAPTER 1 INTRODUCTION
Pain is a basic body sensation that is induced by a noxious stimulus or something that is
perceived as noxious. Trauma and inflammation stimulate naked nerve endings which evokes
physical discomfort and typically leads to evasive action.[1] However, in the context of a
surgical procedure for the benefit of the patient, pain loses its biological protective function.
In recent years there has been an increasing interest in postoperative pain management by both
the patients and medical workers. The aim of postoperative pain treatment is to provide
subjective comfort, inhibit trauma-induced nocioceptive impulses, improve clinical outcome and
enhance postoperative recovery. The outcome is improved by reducing the incidence of
postoperative complications like myocardial infarction or ischemia and impaired wound
healing[2]. The control of postoperative pain has been shown to reduce the length of in-hospital
stay for patients having lower limb orthopaedic surgery.[3]
Pain perception varies. Patients’ perception is influenced by factors such as different physiology
of pain mechanisms, psychological factors ( e.g. fear, cultural expectations) , environmental
factors and genetics[4]. Most current pain assessment tools rely on the intellect of the patient to
translate a sensory stimulus and hence communicate their score to the health worker and
therefore receive analgesia. Despite this, most analgesia is given as a standard dosage without
taking into consideration the pain scores. This leads to a need to individualise assessment and
therefore analgesia prescribing. The Effort Dependent Pain Assessment tool was developed in
Mulago hospital and hopes to lead to individualised pain assessment and hence treatment.
The current post operative prescriptions include opiates and non steroidal analgesics like
pethidine and diclofenac respectively[5]. In developing countries, the postoperative patient rarely
gets the required analgesia due to the large patient to nurse ratio and the lack of pain
assessment[6, 7]. Patients believe that intolerable postoperative pain is an expected sequel hence
they do not ask for an analgesic[7] . The health workers’ attitude, knowledge and practice will
affect whether or how the patient receives their postoperative analgesia because the patients
12
themselves fear to ask for analgesia. Pain assessment forms an integral part of pain management.
Health workers who don’t do pain assessment assume that patients who don’t complain of pain
don’t have pain. The complete absence of pain assessment could in part be attributed to the lack
of an appropriate pain assessment tool in Mulago hospital[8].
Acute pain can be reliably assessed both at rest (important for comfort) and during movement
(important for function and risk of postoperative complications), with one-dimensional tools
such as the visual analogue scale[9] For this reason the visual analogue scale has been widely
studied and hence used to validate new tools.
Validation of pain assessment tools involves calculation of specificity, sensitivity, positive
predictive value, negative predictive value and Bland Altman analysis of the tool being assessed
as compared to that of the gold standard.
Up to now, no documented study has been done to assess/ evaluate the pain experienced by
postoperative orthopaedic patients in Mulago hospital. Furthermore, an effort dependent pain
assessment tool has not been validated in these orthopaedic patients. The only way to ascertain
the benefits of good pain treatment such as improved patient outcome and decreased hospital
stay is to subjectively and objectively measure pain and the effect of pain treatment.
PROBLEM STATEMENT
Postoperative pain is significant concern for all surgical patients. The degree of postoperative
pain is usually moderate to severe following lower limb surgery[3]. Studies show that 93% of the
patients have some degree of postoperative pain and in 64.4% the pain was moderate, severe or
intolerable [7]. In Khartoum a study done showed that only 64.2% of the patients complained of
pain to the medical staff, the remainder kept silent despite their sufferings until pain assessment
was done [7]. The level of pain experienced by patients cannot be assessed in Mulago hospital
due to the lack of a validated subjective pain assessment tool. The existing pain assessment tools
all presuppose that the patient is literate. As such, in a population where the literacy rate remains
13
low, the use of scales such as the Visual Analogue Score, the Numeral Rating Scale and the
McGill pain assessment tools is questionable. These are subjective tools which are affected
adversely by a poor literacy level of the patient. Good pain control ensures early ambulation and
in postoperative orthopedic patients has been associated with a reduced hospital stay.[3].
JUSTIFICATION
There is little data available on the pain intensity and assessment in orthopaedic patients having
lower limb surgery in Africa. There are very few studies on pain assessment in Africa making it
difficult to ascertain the benefits it might bring in relieving postoperative pain & reducing in
hospital stay. Although the negative effects of postoperative pain are clearly evident, there exists
no validated objective assessment of pain in orthopaedic patients in Mulago Hospital. In Mulago
Hospital, an objective effort dependent pain assessment tool (EDPAT) was developed. This tool
has not been validated[8]. The VAS (visual analogue score) is considered the gold standard and
is used for pain assessment.[10] . The VAS has been found to be too abstract for patients with a
low educational level,.[10, 11] but has been used to validate other pain tools like the Oucher in
Africa. The EDPAT has not been validated for its use in patients having lower limb orthopaedic
surgery.
This study will provide more information on whether the EDPAT is comparable to the VAS in
assessing pain among patients who have had lower limb orthopaedic surgery. This objective pain
assessment tool will provide useful information and help to improve the pain management in
orthopaedic patients as well as hopefully other postoperative patients.
14
SIGNIFICANCE OF THE STUDY
The validation of the Effort dependent pain assessment tool will initially show whether it is
useful for patients who have had lower limb surgery in Mulago hospital. This objective pain
assessment tool will hopefully provide useful information, which will improve the pain
management practise in orthopaedic patients. Patients should will have less pain associated
complications and these patients will be discharged faster and have a shorter duration of stay in
hospital.
RESEARCH QUESTION
Is the Effort Dependent Pain Assessment Tool comparable to the Visual Analogue Scale in
assessing pain among patients who have had lower limb orthopaedic surgery?
GENERAL OBJECTIVE
To compare the Effort Dependent Pain Assessment Tool with the Visual Analogue Scale in
assessing pain among patients who have had lower limb orthopaedic surgery
SPECIFIC OBJECTIVES
1. To determine the validity of the Effort Dependent Pain Assessment Tool at assessing pain
in patients who have had lower limb orthopaedic surgery. Pain will be assessed when
they have pain pre operatively and at 0, 6 and 24 hours postoperatively.
2. To compare the validity of the Effort Dependent Pain Assessment Tool against the Visual
Analogue Scale in assessing the degree of postoperative pain in patients who have had
lower limb orthopaedic surgery pre operatively, at 0, 6 and 24 hours postoperatively.
3. To determine the association between demographic variables and the pain tool (EDPAT)
in patients who have had lower limb orthopaedic surgery in Mulago Hospital.
15
NULL HYPOTHESIS
The Effort Dependent Pain Assessment Tool is equivalent to the VAS for assessing the severity
of pain in patients who have had lower limb orthopaedic surgery.
ALTERNATE HYPOTHESIS
The Effort Dependent Pain Assessment Tool is the not equivalent to the VAS for assessing the
severity of pain in patients who have had lower limb orthopaedic surgery.
16
CONCEPTUAL FRAMEWORK
INSULT: SURGICAL





AGE
SEX
CULTURE


TYPE OF
SURGERY
PAIN
EXPERIENCE
CHRONIC PAIN
CHEMICAL &
NEURAL
MODULATION
PERCEPTION OF PAIN
PAIN TREATMENT
PAIN ASSESSMENT
 EDPAT
 VAS
IMPROVED OUTCOME
17
CHAPTER 2 LITERATURE REVIEW
PAIN
The International Association for the study of pain defines pain as an unpleasant sensory and
emotional experience associated with actual or potential tissue damage or described in terms of
such damage. Pain is what the patient says it is..[12] Pain is an expected outcome of surgery and
is a major concern to patients.[13, 14]
THE FACTORS AFFECTING THE PERCEPTION OF PAIN
The perception of pain varies between patients. [10, 11, 15] It has been documented that sociodemographic factors affect the perception of pain. These factors include:

Tribe/ culture[4]

Age:

Gender:some studies have shown that women perceive pain more than men. [15]
[4]

Socio-economic status

Occupation

Educational level.

If surgery is emergency or elective. Patients with fresh fractures (emergency
cases) have more pain than those who have old fractures.

Previous experience of pain
PAIN ASSESSMENT
Pain is a subjective sensation and therefore difficult to measure but it is important to try and
measure pain in order to improve patient outcomes [16]. Reliable quantification of pain is
18
necessary for effective pain treatment[14].
Nurses who handle postoperative pain found pain
assessment difficult. A study among nurses shows that there is a need to find a more objective
pain assessment tool[17]. This is highlighted by the fact that patients are found lying still in bed
and they report no pain, but report pain on movement[10]. There has been an incongruity noted
in the amount of pain reported by patients and that recorded by nurses. This has major
implications since the administration of analgesia is dependent on the nurses documentation of
pain[17]. It has been noted that no documentation of pain assessment shows that medical staff
believe that patients who do not report pain do not feel pain. [18]
Many studies have used the visual analogue score and the numerical rating score to assess pain
intensity in postoperative patients [10, 19, 20]. Currently used pain assessment scales are
inadequate in their ability to reflect various manifestations of pain[21]. Long inventories of
published instruments show that pain assessment poses challenges and continues to be a
challenge.[10]
Pain on movement can be detected using an objective pain assessment tool. A provocative
physical examination that involves certain manoeuvres that may provoke pain such as a range of
motion testing can help to quantify pain. Pain intensity will vary with the different analgesics
used, it is therefore essential to document pain intensity before and after analgesic treatment has
been given [10, 18, 22]. To estimate whether pain management is adequate requires a
comprehensive pain scoring system[23]
and therefore pain assessment has to be repeated at
regular intervals in order to increase the validity of the tool to assess different levels of pain.[22]
FLACC (Faces Legs Activity Cry Consolability), an observational behavioural pain assessment
tool has been validated in paediatric patients. This tool observes the different behaviour of
19
patients in pain and is partly dependent on movement of the patient. FLACC has been shown to
give reliable results when compared to faces pain scale that has been widely used in paediatrics
[24]. Previous studies had alluded to the difference between reported and observed pain
especially in patients who have low intensity pain [24, 25]. The FLACC shows that there was
significant and positive correlation with the faces pain scale.
The Visual analogue scale (VAS) is the gold standard used to assess the degree of pain. It has
been widely used to assess pain. [16, 26, 27] The VAS pain assessment consists of a 100mm line
with the endpoints of “no pain” and “the worst pain imaginable”and patients are asked to make a
mark on the line to represent their current pain intensity. The amount of pain is measured as the
distance( in millimetres) from the no pain end of the line [22]. The cut-off points for the VAS for
pain can be labelled as no pain (less than 5 mm), mild pain (5-44 mm), moderate pain (4574mm) and severe pain ( greater than 75mm)[22]. These cut offs vary with different pain sites
and even within the same study population. A study on pain assessment in patients who have
had an amputation changed the cut-off to 70mm for severe pain. [28, 29] This is also true when
differentiating between moderate and severe pain. [22, 29]
Reliability of the VAS for acute pain measurement is documented as being reproducible ( 95% )
within 9 millimetres[20]. The sensitivity and specificity of the VAS is 85% and 80 % in patients
who have low intensity pain : score of 0-3 [30] the VAS also has a large number of response
categories, which means that it is considered to be more sensitive to changes in pain intensity
than measures with a limited number of responses. However, it has been noted that while the
VAS may be sensitive to treatment effects if the same individual scores his or her pain before and
after the intervention, it may not produce reliable ratings across different groups of patients
because each patient may interpret the scale differently.[31, 32]
20
Globally the VAS is the gold standard used to assess new pain scales. In Africa a study in Nigeria
used VAS and the numerical rating scale to validate a pain scale called the Oucher. It correlated
well with the VAS and measured interclass correlation coefficient (ICC) of 0.63-0.69 at baseline.
The conclusion was that VAS, NRS and Oucher were valid pain scales[33].
In Uganda the pain scale used in palliative care patients is the 5 point verbal rating scale. A pain
scale, effort dependent pain assessment tool (EDPAT) was developed in the department of
anaesthesia and was used to assess the degree of postoperative pain in patients who had had
obstetric surgery. It was developed because the VAS was found to be complex and abstract in
patients with a low education level. [8] Upto now there is no objective pain assessment tool for
use in patients having lower limb orthopaedic surgery in Mulago hospital.
POSTOPERATIVE ANALGESIA
The traditional method of delivering postoperative analgesia is dependent on a prescription of a
standard dose of an opioid to be given either on demand (prn) [5, 8]or at a regular prescribed
interval. This has been shown to inadequately control postoperative pain because of the
following reasons: [11].

Responsibility for pain management is delegated to nursing staff who err on the
side of caution in administration of opioids. It has been noted that they give
smaller doses than those prescribed due to their unwarranted trepidation of
causing respiratory depression and or addiction[8, 11]. In Uganda it was noted in
a study in obstetrics, that nurses substituted pethidine with diclofenac in some
postoperative analgesia prescriptions.[8]
21

Drug administration is left to the discretion of the drug administration nurse[19].
This is further affected by the degree of empathy that the nurse feels towards the
patient. This is not related to pain assessment. This probably explains why the
mean dosage of morphine given for a standard operation varies among hospitals
and in one ward in the same hospital.[11]

Pain measurement is viewed as tedious [12] and in West Africa it has been
documented that pain assessment is not done prior to analgesia prescription[34].
It is hardly ever possible for nurses to adjust dosages to match the magnitude of
pain in patients.[11]

It has been noted that there is common use of intramuscular injections to control
pain[5] yet patients complain of severe postoperative pain. The onset of action is
delayed with this route of administration; hence the onset of analgesia is delayed.

The extent of analgesia requirement varies with the patient, type of surgery,
choice of anaesthetic technique, drug pharmacokinetics, pharmacodynamics.[8,
11, 35]

Reliance on single modal analgesia inspite of clear documentation that
multimodal analgesia is better is the norm. The health workers rely on one type of
analgesia. They prefer not to combine several drugs that have different
mechanisms of action and hence patients do not benefit from this.[36]

The “out of stock issue”[8] has been associated with inadequate administration of
postoperative analgesia because patients do not receive their prescribed analgesia
.
Optimal postoperative analgesia would include multimdal analgesia in conjunction with a
reliable pain assessment. This combination would not only decrease pain scores and enhance
22
patient satisfaction, but also facilitate earlier mobilisation & rehabilitation by reducing pain
related complications after surgery[37]. It has been documented that moderate to severe
postoperative pain prolongs the stay in the recovery room by 40 – 80 minutes and increases
hospital stay due to an increased incidence of complications. [38]
23
CHAPTER 3 METHODS
STUDY SETTING
The study was performed in Mulago Hospital which is a government owned national referral
hospital that offers specialized health services. It is situated in Kampala, 2 kilometres from the
city centre. Mulago Hospital has a 1500 bed capacity but can receive and admit 2000 patients.
It is also a teaching hospital affiliated to Makerere University. The hospital is constituted of
several Units, Departments and Directorates[39]. The study will be done on Ward Seven and in
the operating theatre of the Department of Orthopaedics. The ward deals with patients who are
scheduled for various orthopaedic surgeries including lower limb surgery. The approximate
number of patients having orthopaedic surgery in six months is 286( January to June 2010 ).
STUDY DESIGN
This was a cross-sectional analytical study.
STUDY POPULATION
The target population: patients who are having lower limb orthopaedic surgery in Mulago
Hospital. The accessible population are patients scheduled for orthopaedic surgeries in ward 7
operating theatre following admission to the unit through Casualty, 3BE Surgical and the SIGN
Nail Clinic. The study population are patients who meet the selection criteria.
SELECTION CRITERIA OF STUDY PARTICIPANTS
INCLUSION CRITERIA
1. Patients who have lower limb fractures and were scheduled for orthopaedic surgery in
ward 7 theatre
2. All patients who have consented to participate in the study
3. Patients who are of ASA physical status classification score of I and II.( see appendix)
4. Patients above 18 years.
24
EXCLUSION CRITERIA
1. Multiple injured patients who are scheduled for lower limb orthopaedic surgery.
2. Patients with chronic pain for example cancer patients, rheumatoid arthritis.
3. Orthopaedic patients with lower limb fractures but in coma or on mentation altering
medication ( except sedatives)
4. Psychiatric patients.
5. Patients with contraindications for spinal anaesthesia.
SAMPLING PROCEDURE
The study sample will be obtained using consecutive sampling of patients.
SAMPLE SIZE CALCULATION
The number of lower limb surgeries done in 6 months from ward seven theatres were 253
surgeries out of a total of 286 surgeries performed( entries from the operation record book
between January 2010 to June 2010) . Five percent of patients were paediatric patients. Studies
on post operative pain have shown that 93% of patients have some level of pain[7].
A sample size (N) of 101 patients was obtained by using the modified Kish Leslie [40] formula
shown below
Where,
N= zα2 x (p x (1-p)/δ2)
N= 1.962 x (0.93x (0.07)/0.052) = 101
N= estimated sample size
Zα = is the standard normal value corresponding to 95% level of significance (1.96)
P = 0.93 (Proportion of population anticipated to have severe pain)[8]
δ = 0.05 (Standardized error given by confidence interval )
25
VARIABLES
Demographic variables recorded included:
1. Age of patient
2. Gender of patient
3. Education Level
4. Tribe of the patient.
Clinical factors included:
1. Type of Injury i.e. Diagnosis, ,
2. Weight of the patient.
3. Pain scores- prior to surgery and after ( 0, 6 and 24 hours) surgery using the VAS and
EDPAT
4. Treatment given
5. Time to discharge
6. Duration of the injury
PROCEDURE
1. Patients were initially identified from the operation list in ward 7 and operating theatre.
2. They were interviewed and those who met the inclusion criteria were recruited.
3. The following variables were recorded preoperatively: age, education level, tribe, pulse
rate, blood pressure..
4. An assessment of pain was performed before surgery using the EDPAT and VAS.(see
appendix) Then the spinal anaesthesia was given with 0.5 % heavy or isobaric
Bupivacaine (Claris® Life Sciences, India ) for these patients.
5. The surgeons prescribed analgesia for the patient. [(Per Oral Paracetamol (Kamadol ®
Kampala Pharmaceutical Industries, Uganda) 1g 6 hourly and Intravenous or
intramuscular pethidine (Pethidine, Martindale Pharmaceticals, UK) 0.5-2 mg/kg
26
6hourly and Per Oral diclofenac (Diclofenac, Zhejiang Tianfeng Pharmaceutical
Company, China) 50mg eight hourly. The above prescription was used for rescue
analgesia.
6. Pain was assessed at intervals: immediately postoperatively counted as 0 then 6 hours
post operatively and then 24 hours later (before ambulation/sitting up for physiotherapy).
At these times- the pain score (using the EDPAT and the VAS), pulse rate, BP, number of
injections needed/ or analgesia tablets given were recorded.
7. Patients found in pain (a score above 4) were given analgesia by the drug administration
nurse. The nurse was informed and the prescribed analgesia given depending on their
pain score.
8. The drug administered was then charted in the data collection tool. Half an hour after
analgesia administration, the patient's pain was reassessed to ensure pain reduction.
9. If the patients had pain (above a score of 4 ) after 30 minutes of analgesia, step 7 & 8 was
repeated.
10. The data collected on the form was verified by the principal investigator and checked.
QUALITY ASSURANCE
1. The questionnaire was pre tested.
2. The two research assistants were trained prior to the commencement of the data
collection phase and this was to ensure consistency of data collected.
3. Data collection form was checked at the end of the day for completeness.
4. The data was entered into the computer software, cleaned to ensure accuracy and quality
and then analysed with the help of a statistician.
5. The data was backed up on a portable hard disc to ensure data safety and locked in a
cabinet.
27
6. The questionnaires and consent forms will be kept for 2 years after completion of the
study and then they will be destroyed.
DATA MANAGEMENT
All data was collected by the principal investigator and trained research assistants using a data
collection form. Role of the principle investigator:
1. Recruit patients in the study from the orthopaedic ward.
2. Assess the postoperative patients who were to have lower limb orthopaedic surgery and
record findings onto the data collection form.
3. Analyse data collected with the help of a statistician.
STATISTICAL ANALYSIS
Epidata was used for entry of data and exported to Stata® Ver. 10(Stata Corp LP, USA) and
Microsoft® Excel 2007 ( Microsoft Corporation 2007) for analysis.
Categorical variables (e.g. sex, tribe, educational level,) was to be summarised into frequencies
and percentages and presented in tabular form, bar charts and bar graphs. Numerical variables
were summarised into mean and Standard Deviation for normally distributed variables, median
and inter-quartile range for skewed data.
Logistic regression was used to look at the association between variables like age sex,
educational status and pain. The sensitivity, specificity, negative predictive value, positive
predictive value of the EDPAT as compared to the VAS was calculated. Kappa statistical analysis
to check for the limits of agreement between EPDAT and VAS were computed.
The following dummy tables were used to analyse data.
Table 1: table showing different variables and their percentages
28
Variable/ Characteristic
Number
Percentage
M= n
M= %
F= n
F= %
Age
Gender
Education level
Occupation
Age of injury
Diagnosis
Analgesia Pre-operatively
Never been to school= n Never been to school= %
Primary= n
Primary= %
Secondary =n
Secondary =%
Tertiary=n
Tertiary=%
Health worker=n
Health worker=%
Peasant farmer=n
Peasant farmer=%
Student=n
Student=%
Trader=n
Trader=%
Motor vehicle cyclist=n
Motor vehicle cyclist=%
Other= n
Other= %
Elective= n
Elective= %
Emergency= n
Emergency= %
#Femur= n
#Femur= %
#Tibia=n
#Tibia=%
Ankle= n
Ankle=%
Foot= n
Foot= %
Hip=n
Hip= %
Other= n
Other=%
Yes = n
Yes = %
No= n
No= n%
Analgesia intra-operatively Yes = n
No= n
Yes = %
No= %
Analgesia Post-operatively Yes = n
Yes = %
( 0 hour)
No= %
No= n
Analgesia Post-operatively Yes = n
Yes = %
(6 hours)
No= %
No= n
Analgesia Post-operatively Yes = n
Yes = %
(24 hours)
No= %
No= n
29
Table 2: Table showing number of patients with pain at O, 6, 24 hours
Time (hours)
VAS (n/ %)
EDPAT (n/%)
Mild Moderate Severe Mild Moderate Severe
Pre-operatively n/ % n/ %
n/ %
n/ % n/ %
n/ %
0
n/ % n/ %
n/ %
n/ % n/ %
n/ %
6
n/ % n/ %
n/ %
n/ % n/ %
n/ %
24
n/ % n/ %
n/ %
n/ % n/ %
n/ %
Table 3: calculating Specificity, sensitivity, positive predictive value, negative predictive value
VAS
+
-
Total
+
EDPAT
_
Total
ETHICAL CONSIDERATIONS
1. Permission to conduct the study was sought from the Department of Anaesthesia, the
Department of Orthopaedics and the Uganda National society of Science and Technology.
2. Approval was obtained from the Makerere University, college of health sciences, school
of medicine research and ethics committee in order to conduct the study.
3. Informed consent was obtained from all recruited subjects prior to the surgery
4. The orthopaedic surgical team were informed about patients found in severe pain and
rescue analgesia administered by the team.
5. All information obtained from and about the study participants was handled
confidentially.
30
DISSEMINATION OF RESULTS
The study findings will be compiled and availed to the following departments:
1) Faculty of Medicine, College of Health Sciences, Makerere University, Library
2) Department of Anaesthesia , Mulago Hospital,
3) Department of Orthopedics, Mulago Hospital, Library
4) School of postgraduate studies, Makerere University
5) Mulago Hospital
6) Peer reviewed scientific journals for publishing of findings
7) Ministry of Health
LIMITATIONS
1) The use of a photocopier to reproduce the VAS tends to enlarge the image slightly each
time they provide a copy. [32, 41]
2) The VAS is complex and requires the ability to translate a sensory experience into a
linear format. [32]
3) The VAS assumes that pain is a unidimensional item and doesn’t factor in emotional and
affect dimensions of pain. ([42])
31
CHAPTER 4 RESULTS
DEMOGRAPHICS
A total of 921 study participants were recruited during the study period of November 2010 to
March 2011.
Sixty-two (67.39 %) study participants were male and 30 (32.61%) female,
resulting in a male to female ratio of 2:1. The mean age of the study participants was 35.16 years
(±SD 14.57) with a range of 18 – 80 years.
Figure 1: pie chart showing gender distribution.
67.39 % Male
32.61% Female
female
male
The number of study participants who had never been to school was 8(30.4%). Fifty six (60.8%)
study participants had post secondary school education. Tertiary education was only present in
23 (25%) study participants as shown in Table 1 below.
1
The calculated sample size was 101. At the time of the conclusion of the study, it was not possible to get the
remaining 8.9%. On consultation with the statistician, it was noted that the remaining 8.9% would not have altered
the statistical results.
32
Table 1: Table showing education level.
Education level
Frequency Percent Cumulative percent
Never been to school 8
8.7
8.7
Primary
28
30.4
39.1
Secondary
33
35.9
75
Tertiary
23
25
100
Total
92
100
The orthopaedic procedures performed were:Open Reduction and Internal Fixations (ORIF) 67
(72.8%), debridement and external fixation 22 (23.91%), total joint arthroplasties 2 (2.17%) and
hemiathroplasty 1(1.1%). Thirty six (60.8%) study participants had a fracture femur and 22
(23.91%) had tibial fractures.
Five participants (5.4 %) found the VAS to be abstract and difficult to comprehend.
33
Figure 2: Bar chart showing the occupation of study participants
Twelve (13.04%)
study participants were motor cyclists. The bar chart above shows the
occupation of the
study participants. The largest number of participants 25 (27.17%) were
traders. The proportion of health workers was 3.26 % in the study population. The diagnosis of
participants in the study is shown below in the pie chart. Fifty six study participants had a
fracture femur, while fracture of the tibia was found in 22 participants. One participant had a
fractured calcaneus.
34
Figure 3: Pie chart showing the diagnosis of the study participants
The VAS and EDPAT pain assessment tools were compared in their assessment of pain before
the operation and after the operation at 0, 6 and 24 hours. The number of study participants who
had pain preoperatively and postoperatively is shown in figure 4. Preoperatively, the number of
study participants found in pain was comparable. However in severe pain, the EDPAT found a
higher proportion of study participants in pain (34.78%) in contrast to the VAS (28.26%)
preoperatively. Immediately after the operation (0 hours), the VAS had a lower proportion of
study participants (40.22%) found to be in severe pain, as compared to the EDPAT (45.65%).
The highest pain scores were found at 6 hours by both pain assessment tools. At 24 hours, a
higher proportion of study participants were found to have mild pain with the VAS (35.87 %) as
compared to the EDPAT (13.04 %).
35
Figure 4: Histogram showing number of study participants with pain Pre operatively,
postoperatively at O, 6 and 24 hours.
VALIDATION OF THE EDPAT
Validation of the EDPAT was done by calculation of the sensitivity, specificity, negative
predictive value, positive predictive value, likelihood ratios and accuracy. The negative
predictive value, positive predictive value of the EDPAT as compared to that of the VAS is
shown in the table 3 below for preoperative and post operative pain. The EDPAT has a high
sensitivity (100 %) at six and twenty four hours. It also has a high specificity (100%)
preoperatively and at zero hours postoperatively. It also has a good positive predictive value (
100%) preoperatively and postoperatively at zero hours.
36
Table 2 : Table showing the validity of the EDPAT.
PPV
NPV
LR+
LR -
SENSTIVITY
SPECIFICITY
Pre operatively
98.61
100.00
100.00
95.23
-1.39
-0.10
78.26
Zero hours
96.43
100.00
100.00
-3.57
-0.95
60.87
Six hours
100.00
90.91
98.78
94.73
100.0
0
9.09
-1.09
88.04
Twenty four
100.00
67.00
92.50 100.00 33.33
-1.49
hours
Average
98.76
89.4775
97.82
97.49
9.365
-0.90775
PPV= Positive predictive value; NPV= Negative predictive value; LR= Likelihood ratio
ACC
80.43
76.9
ACC= accuracy
The validity of the EDPAT was calculated for mild, moderate, severe pain at 0, 6 and 24 hours
postoperatively. It was also calculated preoperatively. The negative predictive value, positive
predictive value of the EDPAT is shown in the table 4 below for mild, moderate and severe pain.
The EDPAT has a high negative predictive value (90.77%) for mild pain preoperatively. At six
hours postoperatively, the negative predictive value is 94 %. The validity of the EDPAT is
reduced in moderate and mild pain. The EDPAT has a higher accuracy for severe pain. At 6
hours postoperatively, the sensitivity of the EDPAT is 72.91 as compared to 28.57% and 42.30
% for moderate and mild pain respectively. At 0 hours the specificity of the EPDAT for severe
pain is 85.45%, moderate pain is 95.18% and mild pain is 69.51%. 2
2
The results showing the number of participants with pain is attached in the appendices as appendix X . Validity is
measured using the specificity, sensitivity, PPV NPV LR and limits of agreement. The tool passed everything with
scores above 90% for measuring the presence of pain which is good for diagnostic tests. For that reason it is valid.
The other reason is also that it is less accurate when looking for mild and moderate pain. The reason why I don’t
quote 92 in the tables is that the sensitivity etc are quoted in percentages.
The dummy tables are used to enter data and for preliminary analysis to aid the data analysis for the validity.
These were entered into Stata. The data was summarised using tables, piechart and graphs.
.
37
Table 3: Table showing the validity of the EDPAT for mild, moderate and severe pain.
SEN
SPEC
PPV
NPV
Mild pain (pre)
76
88.06
70.37
90.77 -12.06
-0.85
27.17
Mild pain (0 hrs)
20
69.51
7.4
87.69 -49.51
-0.27
10.87
Mild pain ( 6 hrs)
28.57
70.59
7.4
92.31
42.02
0.39
7.61
Mild pain ( 24 hrs)
45.45
79.66
55.56
72.31
34.21
-0.56
35.86
Average mild pain
42.51
76.96
3.67
-0.32
Moderate (pre)
23.81
90.14
41.66
-66.3
-0.25
22.82
Moderate pain(0hrs)
22.22
95.18
33.33
91.86 -72.95
-0.22
9.78
Moderate pain(6hrs)
42.3
81.81
47.82
78.26 -39.51
-0.5
28.26
Moderate pain (24hrs)
53.57
79.69
53.57
79.69 -26.11
-0.66
30.43
Average moderate pain
35.48
86.71
44.1
Severe(pre)
76.92
81.81
62.5
Severe Pain(0hrs)
91.89
85.45
Severe pain(6hrs)
72.91
Severe pain( 24 hrs)
Average severe pain
35.18
LR+
85.77
80
ACC
20.38
-51.22
-0.41
90
-4.9
-0.93
28.26
80.95
94
6.44
-1.06
40.22
68.18
71.42
69.76
4.73
-1.05
52.17
38.46
89.87
38.46
89.87
-51.4
-0.41
14.13
70.05
81.33
-11.28
-0.86
33.7
63.33
82.45
LR -
85.91
22.82
SEN= ssenstivity; SPEC= specificity; PPV= Positive predictive value; NPV= Negative predictive value;
LR= Likelihood ratio, ACC= Accuracy
The limits of agreement (kappa statistic) between the VAS and EDPAT preoperatively is 0.0045, zero hours -0.028, six hours -0.048 and at 24 hours is -0.048. This shows that there was
no effective agreement between the VAS and the EDPAT. There was good inter-rater agreement
within the EDPAT: combined inter-rater correlation coefficient of 0.0952.
38
Table 5: Table showing Inter-rater coefficients(Kappa Statistic) of the EDPAT.
Outcome
Kappa
Preoperative EDPAT score 0.1064
0 hours EDPAT score
0.1224
6 hours EDPAT score
0.0964
24 hours EDPAT score
0.0514
Combined
0.0952
ASSOCIATION BETWEEN DEMOGRAPHIC FACTORS AND THE EDPAT
The association between demographic factors like education level, age, gender, tribe and the
EDPAT score was computed using logistic regression. A p value < 0.05 was considered
significant at a confidence interval of 95%.
Education Level
There was good correlation {P=0.002, CI (1.457-6.593)} between EDPAT score and the level of
education of the study participant.
Logistic regression
Number of obs =
Log likelihood = -23.714468
92
LR chi2(1)
=
2.09
Prob > chi2
=
0.1486
Pseudo R2
=
0.0421
-----------------------------------------------------------------------------avedpat1 |
Coef. Std. Err.
z
P>|z|
[95% Conf. Interval]
-------------+---------------------------------------------------------------edulevel | -.5377036
.402144
-1.34 0.181
-1.325891
.2504842
_cons | 4.025669 1.310315
3.07 0.002
1.457499
6.59384
------------------------------------------------------------------------------
39
Gender
There was good correlation {P=0.030, CI(0.426- 8.575)}between EDPAT score and the gender of
the study participants.
Logistic regression
Number of obs =
Log likelihood = -24.096423
92
LR chi2(1)
=
1.32
Prob > chi2
=
0.2501
Pseudo R2
=
0.0267
-----------------------------------------------------------------------------avedpat1 |
Coef. Std. Err.
z
P>|z|
[95% Conf. Interval]
-------------+---------------------------------------------------------------gender | -1.133704 1.104086
-1.03 0.305
-3.297673
_cons | 4.500999 2.079051
2.16 0.030
.4261336
1.030266
8.575865
------------------------------------------------------------------------------
Tribe
There was good correlation {P=0.000, CI(1.059 3.226)}between EDPAT score and tribe of the
study participants.
Logistic regression
Number of obs =
Log likelihood = -24.408361
92
LR chi2(1)
=
0.70
Prob > chi2
=
0.4031
Pseudo R2
=
0.0141
-----------------------------------------------------------------------------avedpat1 |
Coef. Std. Err.
z
P>|z|
[95% Conf. Interval]
-------------+---------------------------------------------------------------tribe | .0876911 .1104472
_cons | 2.142324 .5527871
0.79 0.427
3.88 0.000
-.1287814
1.058881
.3041635
3.225767
------------------------------------------------------------------------------
40
Occupation
There was good correlation {P=0.012, CI(0 .572- 4.554)}between EDPAT score and occupation
of the study participants.
Logistic regression
Number of obs =
Log likelihood = -24.755281
92
LR chi2(1)
=
0.01
Prob > chi2
=
0.9432
Pseudo R2
=
0.0001
-----------------------------------------------------------------------------avedpat1 |
Coef. Std. Err.
z
P>|z|
[95% Conf. Interval]
-------------+---------------------------------------------------------------occup | -.014168 .1988718
-0.07 0.943
-.4039497
_cons | 2.56314 1.015894
2.52 0.012
.5720256
.3756136
4.554255
------------------------------------------------------------------------------
Type of surgery performed
There was good correlation {P=0.002, CI (0 .7518- 3.3974)}between EDPAT score and type of
surgery performed.
Logistic regression
Number of obs =
Log likelihood = -24.47124
92
LR chi2(1)
=
0.57
Prob > chi2
=
0.4490
Pseudo R2
=
0.0116
-----------------------------------------------------------------------------avedpat1 |
Coef. Std. Err.
z
P>|z|
[95% Conf. Interval]
-------------+---------------------------------------------------------------surgery | .2647644 .3787555
0.70 0.485
-.4775828
1.007112
_cons | 2.074606 .6749292
3.07 0.002
.7517688
3.397443
------------------------------------------------------------------------------
41
Diagnosis
There was good correlation {P =0.001(CI 0.897- 3.649)} between EDPAT score and diagnosis of
the study participant.
Logistic regression
Number of obs =
LR chi2
=
0.15
Prob > chi2
=
0.6984
Pseudo R2
Log likelihood = -24.682743
92
=
0.0030
-----------------------------------------------------------------------------avedpat1 |
Coef. Std. Err.
z
P>|z|
[95% Conf. Interval]
-------------+---------------------------------------------------------------Fractype | .134902 .3675659
_cons | 2.273229
.701982
0.37 0.714
3.24 0.001
-.585514
.855318
.8973697
3.649088
------------------------------------------------------------------------------
42
CHAPTER 5: DISCUSSION
DEMOGRAPHIC CHARACTERISTICS
In this study 62(67.3 %)
study participants were male, the largest proportion of patient with
fractures. The number of respondents with a fractured femur were 56(60.8%). This is consistent
in Mulago hospital where the largest number of patients presenting with lower limb fractures are
male and motor cyclists.[43] Open reduction and internal fixation 72.8% was the most
frequently performed operation.
The VAS has a large number of response categories and different reporting of pain in different
patient groups. The VAS relies on the self-reporting by the patient. The EDPAT too relies on
self-reporting of pain by the study participant just like the numerical rating scales and the verbal
rating scale [44]. The EDPAT has been shown to be easier to comprehend by study participants
[8]. Five study participants (5.4%) found the VAS to be abstract and difficult to comprehend.
Five study participants were excluded from the study due to their inability to use the VAS. These
study participants were elderly, above 75 years and had never been to school. Concrete and
especially abstract thinking are a necessity to patients in comprehending the VAS. It is probable
that due to their low educational status, abstract thinking was not possible hence their inability to
use the VAS. It has been noted that the VAS limitation is in its complexity and that it requires an
instinctive ability to translate a sensory experience into a linear format. This is a major limitation
to the study population since a significant proportion of study participants( 25 % who have above
secondary school education) have lower literacy levels. [32] UNICEF statistics show that 32% of
the population finish primary school education. In addition to that , 15 percent of females finish
secondary school education while males is 16 %. Since it has been noted that literacy affect pain
assessement, it is therefore important to use a tool that is easily comprehended by the population.
43
Gender, ethnicity, temperament and genetic factors have been shown to affect pain assessment
and response to analgesia. [42] In the current study, there was good correlation between gender
and EDPAT pain scores.
The VAS also has been shown to be as sensitive in detecting age differences as compared to
other forms of pain assessment [45]. A study done in pain assessment in the acute care setting
noted that 13.6 % of study participants needed further clarification when using the VAS[46]. In
the current study, one elderly study participant failed to complete the VAS- citing that it was too
complex. One of the 5 (5.74%) study participants unable to use VAS said that “pain is pain how
do you expect me to put into a line” and another kept on saying- “I don’t understand please
repeat”. Despite multiple attempts to explain the use of the VAS she requested further
explanations again and again. The same patients commented that the EPDAT was easier to use
because it helped then to explain their pain when they did important movements like seating up
in bed to take a meal, or turning in bed to get more comfortable (twisting the leg and half leg
lifting which are assessed using the EDPAT).
VALIDATION OF THE EDPAT
Despite the long inventories of various pain assessment tools, pain assessment and treatment has
been shown to be difficult [44, 47]. Qualitative pain assessment tools like Mc Gill’s & Wisconsin
brief pain questionnaire have been shown to be too long and requiring intense concentration[44].
One dimensional pain assessment scales are commonly used for assessment of post-operative
pain in the acute setting. This includes instruments like the Visual analogue scale (VAS),
Numerical rating scale (NRS), verbal rating scale (VRS)[33, 44] . They have been shown to be
reproducible [48] The VAS has been used as a gold standard to validate new pain assessment
tools[33].
44
There is good correlation between assessment on the categorical pain intensity scales and the
visual analogue scale[47, 49]. The calculated sensitivity, specificity, negative predictive value,
positive predictive value and accuracy of the EDPAT as compared to that of the VAS are shown
in figure 5 above. The EDPAT has good validity when assessing pain preoperatively and
postoperatively at zero, six and twenty four hours. The sensitivity, specificity have been shown
to be 100%. Its sensitivity, specificity is low when assessing moderate and mild pain. When
assessing severe pain, its accuracy increases to 33.70% from 20.38 % for mild pain and 22.82%
for moderate pain. The EDPAT has a high negative predictive value (90.77%) for mild pain
preoperatively. At six hours postoperatively, the negative predictive value is 94 %. The validity
of the EDPAT is reduced in moderate and mild pain. The EDPAT has a higher accuracy for
severe pain. This possibly due to the fact that most of the pain in patients is triggered during
movement. The strength of the EDPAT is in detecting pain during movement. Severe pain
restricts movement and hence patients are more likely to complain of severe pain. In Sudan,
many patients who had pain didn’t complain since they considered it as a known and expected
complication of surgery.[7] Yet when asked about pain, 93% of patients admitted to having
severe pain. When there is no pain, the EDPAT is able to show that it is not present- hence a
high negative predictive value and specificity.
Reliability of the VAS for acute pain measurement is documented as being reproducible ( 95% )
within 9 millimetres[20]. The sensitivity and specificity of the VAS is 85% and 80 % in study
participants who have low intensity of pain : score of 0-3 [30] . In this study, the specificity
preoperatively was 100% when the patient had no pain. The EDPAT demonstrated good
sensitivity, positive predictive value, negative predictive value when used to assess for the
presence of pain in the study participants. This demonstrates that it has good validity.
45
On the other hand, the EDPAT has lower sensitivity for study participants with low pain (mild
and moderate pain). The sensitivity of the EDPAT at zero hours postoperatively is 91.89%. The
sensitivity drops to 45.45 % for mild pain at 24 hours. The specificity at zero hours for moderate
pain was 95.18%. This could have been attributable to its reliance in detecting pain during
movement which is at most times severe. The main responses to pain are during movements like
sitting up, twisting the leg (for example when they are turning in bed) and at rest when lying
down. It has 5 response categories. The VAS also has a large number of response categories,
which means that it is considered to be more sensitive to changes in pain intensity than measures
with limited numbers of responses. However, it has been noted that while the VAS may be
sensitive to treatment effects if the same individual scores his or her pain before and after the
intervention, it may not produce reliable ratings across different groups of
study participants
because each study participant may interpret the scale differently.[31, 32]
Globally the VAS is the gold standard used to assess new pain scales. In Africa a study in Nigeria
used the VAS and the numerical rating scale to validate a pain scale called the Oucher. It
correlated well with the VAS and measured interclass correlation coefficient (ICC) of 0.63-0.69
at baseline. The conclusion was that VAS, NRS and Oucher were valid pain scales[33]. The
EDPAT did not correlate well with the VAS with a correlation coefficient of -0.0456 for
preoperative pain,-0.0280 for postoperative pain at zero hours,-0.0482 at six hours
postoperatively and -0.0476 at 24 hours postoperatively. This could be attributable to opposite
finding by the EDPAT and VAS or also due to a small sample size. It has good reproducibility
(ICC 0.095) when it was repeated after preoperative pain assessment at 0, 6 and 24 hours
postoperatively. This means that the patients quickly learnt the tool.
46
Monitoring of postoperative pain should reflect not only pain intensity at rest, but also activityassociated and dynamic pain. [47] The effort dependent pain assessment tool (EDPAT) measures
pain intensity at rest and during movements. The orthopaedic patient in Mulago hospital is asked
to sit up in bed on the morning following surgery, and ambulation ( walking using crutches or by
a wheelchair) for x-rays 24- 48 hours after surgery. This needs to be a painless process for the
patient. If it is too painful, patient co-operation is minimal and it hinders physiotherapy. Pain has
been shown to have a distinct and affective quality. It is overwhelming and demand attention
from patients and disrupts ongoing activities [50]. For this reason, the patient is driven to stop all
activity that triggers pain as quickly as possible. The EDPAT could be useful in detecting if the
patient’s pain is well controlled before ambulation.
The EDPAT (see appendix) has three possible responses. The patient say their either have no
pain, moderate pain or severe pain. They are asked to give their response when they at rest- lying
in bed, sitting up, standing, twisting or turning the leg that was operated and half leg lifting of the
operated leg. This movement are the same movements that they usually engage in ( e.g. twistingthey turn or shift their position in bed as they try to get more comfortable or avoid getting bed
sores). This pain assessment tool has promise and will probably be used in the near future to
measure pain subjectively and also to evaluate the pain interventions.
THE ASSOCIATION BETWEEN DEMOGRAPHIC VARIABLES AND EDPAT.
There is a high correlation between pain scores and demographic variables. The gender showed a
positive correlation with EDPAT {p= 0.030 (CI 0.426-8.575)}. Other variables like
occupation{p= 0.012 (CI= 0572- 4.554), surgery {p=0.002 (CI 0.752- 3.397)}, education level
p=0.002 (CI 1.457-6.593) diagnosis of the fracture type p=0.001( CI 0.89-3.64) all showed good
correlation with the pain scores found by the EDPAT. This means that these factors affect the
47
assessment of pain. For this reason the EDPAT has been shown to be good in measuring pain in
patients with different demographic characteristics.
Other variables like previous experience of pain or surgery were not assessed in this study and
are possible confounders. A patient who has low education status may exhibit lower pain scores.
However it may not be the case if they had a relative who has cancer (and is on palliation) that
they took care of and they know extensively about pain assessment.
48
CHAPTER 6 CONCLUSION
The effort dependent pain assessment tool is valid. The EDPAT has lower accuracy for
measurement of mild and moderate pain. It’s the preferred method of pain assessment by study
participants. It is advantageous because it show pain during movement (e.g. turning in bed and
sitting up) which are important for the patient.
There is good correlation between the pain measured in patients using the EDPAT and
demographic factors.
49
CHAPTER 7 RECOMMENDATIONS
1. Implementation of the EPDAT for pain assessment at 6 and 24 hours postoperatively.
2. A further validation study to be carried out in study participants having other types of
surgery.
3. A further validation study (with a larger sample size) to be carried out to assess the level
of agreement between the VAS and the EDPAT.
50
REFERENCES
1.
WEBSTER, N. MERRIAM WEBSTER COLLEGIATE ONLINE DICTIONARY.
1847; 11:[
2.
THOMPSON, C., POST OPERATIVE PAIN, IN VIRTUAL ANAESTHESIA
TEXTBOOK2008, VITUAL ANAESTHESIA TEXTBOOK.
3.
ESSVING P, A.K., KJELLBERG J, WALLGREN O, GUPTA A, LUNDIN A.,
REDUCED HOSPITAL STAY, MORPHINE
INTENSITY
WITH
LOCAL
CONSUMPTION, AND PAIN
INFILTRATION
ANALGESIA
AFTER
UNICOMPARTMENTAL KNEE ARTHROPLASTY. ACTA ORTHOPAEDICA,
2009. 80(2): P. 213-219.
4.
RAYMOND A. DIONNE, L.B., JEFFREY MOGIL AND JAMES WITTER,
INDIVIDUAL RESPONDER ANALYSES FOR PAIN: DOES ONE PAIN SCALE
FIT ALL? TRENDS IN PHARMACOLOGICAL SCIENCES 2005. 26(3): P. 125129.
5.
KIMENYE, S.M. POSTOPERATIVE ANALGESIA PRESCRIPTION: AN AUDIT
OF ORTHOPAEDIC PAIN MANAGEMENT. IN ANAESHESIA IN AFRICA:
PRESENT & FUTURE. 2009. NAIROBI.
6.
CHARLTON, E., THE MANAGEMENT OF POST OPERATIVE PAIN. UPDATE
IN ANAESTHESIA, 1997(7): P. 1-18.
7.
BAGI I. A., A.M.E., POSTOPERATIVE PAIN AND ANALGESIC PRESCRIPTION
IN KHARTOUM : EVALUATION OF CURRENT PRACTICE. EAST AFRICAN
MEDICAL JOURNAL, 1993. 70(8): P. 502-505
8.
KASUMBA,
J.M.,
CURRENT
PERIOPERATIVE
PAIN
MANAGEMENT
PRACTISE AT MULAGO HOSPITAL, 2003, MAKERERE UNIVERSITY. P. 58.
9.
BREIVIK HARALD , P.C.B., ALLEN S. M, L. A. ROSSELAND, ET AL.,
ASSESSMENT OF PAIN. BRITISH
JOURNAL OF
ANAESTHESIA, 2008.
101(1): P. 17-24.
10.
BREIVIK H. , B.P.C., S. M. ALLEN, L. A. ROSSELAND, ET AL., ASSESSMENT
OF PAIN. BRITISH JOURNAL OF ANAESTHESIA, 2008. 101(1): P. 17-24.
11.
ALLAN
R
ATKINHEAD,
ANAESTHESIA.
4TH
D.J.R.,
EDITION
GRAHAM
ED2001,
SMITH,
TEXTBOOK
EDINBURG:
OF
CHURCHILL
LIVINGSTONE. 544-555.
51
12.
G
EDWARD
MORGAN,
M.S.M.,
MICHAEL
J
MURRAY,
CLINICAL
ANAESTHESIOLOGY. 4TH EDITION ED2006, NEW YORK: MC GRAW HILL.
361-411.
13.
HALLIVIS, R., T.A. DERKSEN, AND A.J. MEYR, PERI-OPERATIVE PAIN
MANAGEMENT. CLIN PODIATR MED SURG, 2008. 25(3): P. 443-63; VII.
14.
MACARIO A, W.M., CARNEY S ET AL, WHICH CLINICAL OUTCOMES ARE
IMPORTANT TO AVOID: THE PERSPECTIVE OF PATIENTS. ANAESTHESIA
AND ANALGESIA, 1999. 89: P. 652-658.
15.
CEM OKTAY, C.E., KEREM OZBEK, GULSUM ANKUN, OKTAY ERAY, AND
ALI BERKANT AVCI,, PAIN PERCEPTION OF PATIENTS PREDISPOSED TO
ANXIETY AND DEPRESSIVE DISORDERS IN EMERGENCY DEPARTMENT.
PAIN MANAGEMENT NURSING, 2008. 9(4): P. 150-153.
16.
R. C.CORK, I.I., A. ELSHARYDAH, S.SALEEMI, F.
ZAVISCA & L.
ALEXANDER, A COMPARISON OF THE VERBAL RATING SCALE AND THE
VISUAL ANALOG SCALE FOR PAIN ASSESSMENT . . THE INTERNET
JOURNAL OF ANESTHESIOLOGY. , 2004. 8(1).
17.
ENE KW, N.G., BERGH I, JOHANSSON FG, SJÖSTRÖM B., POSTOPERATIVE
PAIN MANAGEMENT - THE INFLUENCE OF SURGICAL WARD NURSES. J
CLIN NURSING, 2008. 17(15): P. 2042-2050.
18.
RAWAL, N., ACUTE PAIN SERVICE: ORGANISATION, FUNCTION AND
IMPLEMENTATION. 1ST ED. TEXT BOOK OF REGIONAL ANAESTHESIA
AND ACUTE PAIN MANAGEMENT, ED. A. HADZIC2007, NEW YORK: MC
GRAW HILL. 1120-1123.
19.
BELL L, D.A., PAIN ASSESSMENT AND MANAGEMENT IN SURGICAL
NURSING: A LITERATURE REVIEW. BR J NURSING, 2009. 18(3): P. 153-156.
20.
BIJUR PE, S.W., GALLAGHER EJ., RELIABILITY OF THE VISUAL ANALOG
SCALE FOR MEASUREMENT OF ACUTE PAIN. ACAD EMERG MED, 2001.
8(12): P. 1153-7.
21.
JOACHIM SCHOLZ, R.J.M., DANIELA E. HORD,ROBERT S. GRIFFIN,ET AL,
A NOVEL TOOL FOR THE ASSESSMENT OF PAIN: VALIDATION ON LOW
BACK PAIN. PLOS MED, 2009. 7(6): P. 4.
22.
MARK P. JENSEN, C.C., AND ANDREW M. BRUGGE, INTERPRETATION OF
VISUAL ANALOG SCALE RATINGS AND CHANGE SCORES: A REANALYSIS
52
OF TWO CLINICAL TRIALS OF POSTOPERATIVE PAIN. JOURNAL OF PAIN,
2003 4(7): P. 407-414.
23.
GATTI A, S.A., CARUCCI A, BERTINI L, MAMMUCARI M, OCCHIONI R.,
ADEQUACY
OF
ASSESSEMENT
OXYCODONE/PARACETAMOL(ACETAMINOPHEN)
IN
OF
MULTIMODAL
CHRONIC PAIN: A PROSPECTIVE OBSERVATIONAL STUDY. CLINICAL
DRUG INVESTIGATION, 2009. 29(1): P. 31-40.
24.
WILLIS MH, M.S., VOEPEL-LEWIS T, MALVIYA S., FLACC BEHAVIORAL
PAIN ASSESSMENT SCALE: A COMPARISON WITH THE CHILD'S SELFREPORT.
. PEDIATR NURS, 2003. 29(3): P. 194-8.
25.
BEYER JE, M.P., BERDE CB., DISCORDANCE BETWEEN SELF-REPORT AND
BEHAVIORAL PAIN MEASURES IN CHILDREN AGED 3-7 YEARS AFTER
SURGERY.
. J PAIN SYMPTOM MANAGE, 1990. 5(6): P. 350-6.
26.
KATZ J, M.R., MEASUREMENT OF PAIN. SURGERY CLINICAL NORTH
AMERICA
1999. 79(2): P. 231-52.
27.
CARLSSON, A.M., ASPECTS OF THE RELIABILITY AND VALIDITY OF THE
VISUAL ANALOGUE SCALE. ASSESSMENT OF CHRONIC PAIN, 1983. 16: P.
87-101.
28.
K. LEE AND G.M. KEICKHEFER, MEASURING HUMAN RESPONSES USING
VISUAL ANALOGUE SCALES. . WEST J NURS RES, 1989. 11: P. 128-32.
29.
M.P. JENSEN, D.G.S., D.M. EHDE AND L.R. ROBINSON, PAIN SITE AND THE
EFFECTS OF AMPUTATION PAIN: FURTHER CLARIFICATION OF THE
MEANING OF MILD, MODERATE, AND SEVERE PAIN. PAIN, 2001. 91: P. 317322.
30.
R.D.
SEARLEA,
B.A.M.I.B.,
PAIN
ASSESSMENT.
ANAESTHESIA
&
INTENSIVE CARE MEDICINE, 2008. 9(1): P. 13-15.
31.
D.B. MCGUIRE, THE MEASUREMENT OF CLINICAL PAIN. . NURS RES 33
1984. 33: P. 152-56.
32.
CLOSS, M.B.A.J.S., A DESCRIPTIVE STUDY OF THE USE OF VISUAL
ANALOGUE SCALESAND VERBAL RATING SCALES FOR THE ASSESSMENT
53
OF POSTOPERATIVE PAIN IN ORTHOPEDIC PATIENTS. JOURNAL OF PAIN
AND SYMPTOM MANAGEMENT, 1999. 18(6): P. 438-446.
33.
EYELADE OR, O.R., FATIREGUN AA., CONVERGENT VALIDITY OF PAIN
MEASURING TOOLS AMONG NIGERIAN CHILDREN. AFR J MED MED
SCIENCE, 2009. 38(4): P. 333-6.
34.
SOYANNWO,
O.,
POST-OPERATIVE
PAIN
CONTROL--PRESCRIPTION
PATTERN AND PATIENTS' EXPERIENCE. . WEST AFRICAN JOURNAL OF
MEDICINE, 1999. 18(3): P. 207-210.
35.
ABRAHAMS N, J.R., MVO Z INDIGENOUS HEALING PRACTICES AND SELFMEDICATION AMONGST PREGNANT WOMEN IN CAPE TOWN, SOUTH
AFRICA. AFRICAN JOURNAL OF REPRODUCTIVE HEALTH, 2002. 6(2): P.
79-86.
36.
WHITE, P.F., MULTIMODAL ANALGESIA: ITS ROLE IN PREVENTING
POSTOPERATIVE PAIN. CURRENT OPINION IN INVESTIGATIONAL DRUGS
2008. 1: P. 1-7.
37.
WHITE, P.F., ROLE OF NON-OPIOID ANALGESIC TECHNIQUES IN
MANAGEMENT OF POSTOPERATIVE PAIN. 1ST ED. TEXTBOOK OF
REGIONAL ANAESTHESIA AND ACUTE PAIN MANAGEMENT, ED. A.
HADZIC2007, NEW YORK: MC GRAW HILL. 1106-1117.
38.
PARLIN J, C.C., PENALOZA DA ET AL, PAIN AS A FACTOR COMPLICATING
RECOVERY
AND
DISCHARGE
AFTER
AMBULATORY
SURGERY.
ANAESTHESIA AND ANALGESIA, 2003. 97: P. 1627-1632.
39.
MULAGO
HOSPITAL
COMPLEX
.
ACCESSED
FROM
HTTP://WWW.MULAGO.OR.UG/INDEX.PHP , O.J.N.
40.
LESLIE, K.A., SURVERY SAMPLING1965, NEW YORK: JOHN WILEY AND
SONS. 35-70.
41.
K., S., PAIN, ANXIETY AND RECOVERY
IN PATIENTS UNDERGOING
SURGERY, IN ANAESTHESIA1987, UNIVERSITY OF LONDON LONDON.
42.
R, M., THE MC GILL PAIN QUESTIONAIRE: MAJOR PROPERTIES AND
SCORING METHODS. PAIN, 1975. 1(3): P. 277-299.
43.
J.W.M KIGERA, E.K.N., PATTERNS OF INJURIES AFTER ROAD TRAFFIC
CRASHES INVOLVING BODABODAS. ANNALS OF SURGERY, 2010. 5.
54
44.
MICHELLE BRIGGS, J.S.C., A DESCRIPTIVE STUDY OF THE USE OF VISUAL
ANALOGUE SCALES AND VERBAL RATING SCALES FOR THE ASSESSMENT
OF POSTOPERATIVE PAIN IN ORTHOPEDIC PATIENTS. JOURNAL OF PAIN
AND SYMPTOM MANAGEMENT, 1999. 18(6): P. 438-446.
45.
GAGLIESE, L. AND J. KATZ, AGE DIFFERENCES IN POSTOPERATIVE PAIN
ARE SCALE DEPENDENT: A COMPARISON OF MEASURES OF PAIN
INTENSITY AND QUALITY IN YOUNGER AND OLDER SURGICAL PATIENTS.
PAIN, 2003. 103(1-2): P. 11-20.
46.
CAREY, S.J., ET AL., IMPROVING PAIN MANAGEMENT IN AN ACUTE CARE
SETTING. THE CRAWFORD LONG HOSPITAL OF EMORY UNIVERSITY
EXPERIENCE. ORTHOP NURS, 1997. 16(4): P. 29-36.
47.
KEHLET, J.D.H., TEXTBOOK OF PAIN. 5TH ED. POST OPERTIVE PAIN AND
ITS MANAGEMENT, ED. M.K. STEPHEN B MC MAHON2006, LONDON:
ELSERVIER. 1239.
48.
GODDARD, G., H. KARIBE, AND C. MCNEILL, REPRODUCIBILITY OF
VISUAL ANALOG SCALE (VAS) PAIN SCORES TO MECHANICAL PRESSURE.
CRANIO, 2004. 22(3): P. 250-6.
49.
COLLINS S L, M.R.A., MC QUAY H J, THE VISUAL ANALOGUE INTENSITY
SCALE: WHAT IS MODERATE PAIN IN MILLIMETRES? PAIN, 1997
72: P. 95-97.
50.
KATZ, R.M.J., TEXTBOOK OF PAIN. PAIN ASSESSMENT IN ADULT
PATIENTS, ED. M.K. STEPHEN B MC MAHON1999, LONDON: ELSERVIER.
1239.
55
APPENDIX I: CONSENT FORM- ENGLISH
CONSENT FORM FOR A STUDY ON A COMPARISON OF AN
EFFORT DEPENDENT PAIN ASSESSMENT TOOL WITH THE
VISUAL ANALOGUE SCORE IN ORTHOPAEDIC POSTOPERATIVE
PATIENTS IN MULAGO HOSPITAL
Candidate
Dr. Speciosa Mbula Kimenye M.B.Ch.B. (MUK),
Makerere University, College of Health Sciences
Department of Anaesthesia
P.O. BOX 7051
Kampala,
Tel 0758 140 999
I’m a doctor pursuing a masters degree in anaesthesia. I’m carrying out research on a pain
assessment tool. This study is on the comparison of an effort dependent pain assessment tool
(checking for pain when you move) with the visual analogue score( a line that measures the pain
that you have) in postoperative patients who are scheduled to have leg surgery in Mulago
Hospital
Your rights as a research volunteer
This form will give you information that will be discussed with you once you understand the
study and agree to participate, you will be asked to sign this consent form. You will be given a
copy of the form to keep if you wish to do so. Please understand that your participation in this
research is entirely voluntary. You may decide to withdraw from the study at any time. Such a
56
decision will not affect your medical care or possible participation in future research studies in
any way.
Purpose and method of the study
The purpose of the study is to obtain information that will be used to compare these two pain
assessment tools (effort dependent pain assessment tool and visual analoque score). The
information obtained will aid clinicians in making better diagnoses of postoperative pain and
hence improve medical care for future patients. The study will involve history taking and
examination so see whether you have pain before and after the operation. This will be done by
the investigator( Dr Speciosa Mbula Kimenye). Thereafter, you shall be treated for your pain, if
it is present and this will be documented by the surgery team.
Risks to you
There are no added risks attributable to the study besides those associated with the management
of your injuries- postoperative pain as a result of surgery. The pain will be treated when you
complain or when you are asked if it is present.
Potential benefits to you
You shall not be required to make any payments towards the study. You will get information
about the proper treatment and follow up for your injuries and shall not be paid for the study. The
research team will advise the surgical team when they find you in extreme pain.
57
Confidentiality
A study number known to me and the study personnel will be used instead of your name.
Personal and medical information about you will not be released to anyone other than the
following without my permission: authorized study personnel, Department of Anaesthesia,
Faculty of Medicine Research Committee, Sir Albert Cook Library- Makerere University
Medical School and the School of Post Graduate Studies.
Ethical Issues.
If you have any questions or concerns regarding ethical issues in the conducting of this study,
you may contact the Faculty of Medicine Research and Ethics Committee Chairman( Dr Charles
Ibingira) on Telephone 256-41-533 541 .
Statement of Consent
Dr. Speciosa Mbula Kimenye has told me that she is carrying out a study on the comparison of
an effort dependent pain assessment tool (checking for your pain when you move) with the
visual analogue score ( the line that measures the amount of pain you have) in postoperative
patients who are scheduled to have leg surgery in Mulago Hospital. This study is being
conducted as a partial fulfillment for the award of a degree in Master of Medicine in
Anaesthesiology of Makerere University. By this form a written consent is being sought for my
participation in the study.
58
I have been informed by Dr Speciosa Mbula Kimenye on the study, its risks and benefits. I
understand that by signing this consent I accept to participate as a volunteer in the study and that
I don’t waive any of my legal rights; neither do I accept liability for anything.
Study participant’s Signature/ thumb print: _____________________________________
Date: ___________________________________________
Dr Speciosa Mbula Kimenye’s Signature:
___________________________________________
Date: ____________________________________________
Witness Signature:
____________________________________________
Study Number:
______________________________
59
APPENDIX II: TRANSLATED CONSENT FORM (LUGANDA)
OMUTWEGW’ O KUNONYEREZA: OKUNONYEREZA MU KUGERAGANYANYA
ENGERI BIIRI ( EFFORT DEPENDENT PAIN ASSESSMENT TOOL NE VISUAL
ANALOGUE SCORE) EZOKUZULA OKWENKANA KWO OBULUMI ABALWADDE
BWEBWOLINA OLUVANYUMA LWO KULONGOSEBWA KU MAGUMBA MU
DDWALIRO E MULAGO.
Omunonyereza omukulu:
Dr. Speciosa Mbula Kimenye M.B.Ch.B. (MUK),
Makerere University, College of Health Sciences
Department of Anaesthesia
P.O. BOX 7051
Kampala,
Essimu: 0758 140 999
Eddembe lyangge ng’omuntu agenda okwetaba mukunonyereza kuno.
Fomu eno entegezza byonna ebinagenda mumaso mu kunonyereza kuno. Nga maze okubitegera
n’okukiriza okwetabba mu kunonyereza , nja kusabibwa okutekako omukono gwange nja
kuwebwa kopi ya fomu eno okutereka. Nkitegera nti okwetaba kwange kwakyeyagalire.
Okusalawo obutetaba mukunonyereza oba okuva mu kunonyereza kuno ekisera kyona tekujja
kukontana na obujjanjabi bwenafuna kati oba munaku envanyuma.
Ebyobulabe mu kwetabba mukunonyereza kuno.
Tewali bulabebulala bwena tukako mu kiseera kyokunonyereza kuno okujako obulumi bwo
kulongosebwa kumagumba. Era nga nja kuwebwa edaggala okuweweza obulumi buno ekisera
kye mbulina.
Ebirungi ebiyinza okuva mukunonyereza.
Tewali kusaasanya nsimbi kugenda mukunonyereza kuno. Nange nja kutegezebwa egeri enungi
eyo kufunna obujanjabi bwo busagwe bwange mumaso. Sija kusasalibwa olwo kunonyereza
kuna.
60
Obutasaasanya byaama:
Ebizuulibwa ngabinkwatako bijja kukumirwa butiribiri omunonyereza omukulu ere bijja
kukozesebwa mukunonyereza kwoka. Erinya lyangge lijja kuwanyisibwamu ennamba nze no
munonyereza omukulu feka ze tumanyi okukuuma ebinfako nga byakyama eri abalala.
Nkimanyinti wajja kubaawo ekiwandiko ky’ebinaba bizuuliddwa mukunonyereza ku dipatimenti
y’ebyo kulongosa mu ddwaliro e Mulago, ne mu Somero lyabasawo e Makerere University,
dipatimenti ey’ebyokusirisa e Mulago, Sir Albert Cook Library ey’e Makerere Univerisity,
abayinzibwa mu kunonyereza kuno, ne mu ssomero bya Post graduate.
Ebibuuza:
Abetabi mukunonyereza baddembe okubuuza omunonyereza ebibuuzo, nokusaba okunyonyolwa
kwona okukwata kukunonyereza ekiseera kyonna awatali kutya.
Ndiwaddembe okwebuuza ku munonyereza omukulu/ amuyambako mukunonyereza kukizibu
kyonna oba ebibuuzo mu ddwaliro e Mulago ku mukulu wa basilisa mu dipatimenti ya basilisa e
Mulago(Dr Charles Ibingira ) 256-41-533 541
Okukiriza.
Amakulu ne ngeri kunonyereza kuno bwe kunakolebwamu:
Okunonyereza kujja kugeraganyanya engeri bbiri ezokuzula okwenkana kwo obulumi abalwadde
bwebwolina oluvanyuma lwo kulongosebwa ku magumba. Okunonyereza kuno kujja okuyamba
obasawo okuzula amangu abalwadde abalina obulumi oluvanyuma lwo kulongosebwa ku
magumba n’kulinyisa obutindo gw’o bujjanjabi gyebujja. Ebibuzo n’okukebererwa bijja
kukolebwa okuyamba omunenyereza omukulu okugeraganyana obulumi bwolina oluvanyuma
lwo kulongosebwa ku magumba. Oluvanyuma lwokuzula oba dala ndi mubulumi nja kuwebwa
eddagala okubuweweza.
Ntegezeddwa era nga nyinyozzedwa bulungi Dr Speciosa Mbula Kimenye amakulu , emitendera
ebyebigenda okukorebwa, ebyobulabe ne ebirungi ebiyinza okuva mukunonyereza.
61
Nkitegera nti okwetaba mukononyereza kuno kwakyeyagalire. Ndi muntu mukulu ategera
ebigenda mumaaso, era ntegera nti okusako omukono kukiwandiko kino, sitagira ddembe lyange
lyonna.
Kopi yekiwandiko kino empereddwa okutereka.
Omukono gwo mulwadde:………………………………….
Enaku z’omwezi……………………………………………
Oba
Omukono Dr Speciosa Mbula Kimenye :………………………………….
Enaku z’omwezi………………………………………………..
Omukono gw’abaddewo……………………………………….
Number kyokunyereza…………………………………………
62
APPENDIX III: EFFORT-DEPENDENT PAIN-ASSESSMENT TOOL
Pain level
None
Moderate
Severe
@ Rest when lying down
0
1
2
@ Maximal breath/walking
0
1
2
@ sitting up/ standing
0
1
2
@ Twisting
0
1
2
@ ½-leg lifting
0
1
2
Total ____/10
The above tool will help to assess how much pain you have. You will be asked at different times
whether you have pain. There are three possible answers that you can choose from to describe
the pain that you have. They are either none, moderate or severe. You will then be asked 5 other
questions. What amount of pain do you feel when?
1. Resting when lying down
2. Taking a maximal breath or walking
3. Seating up or standing
4. Twisting
5. ½ leg raising

Pain score 0 - no pain- no analgesia given- don’t give analgesia

Pain Score < 4 – Mild pain (adequate analgesia)- give Paracetamol + NSAID ( eg
Ibuprofen, diclofenac, aceclofenac/ meloxicam)

Pain Score 4 TO 7 – Moderate pain (Inadequate analgesia)- give NSAID+
Paracetamol + Weak Opioid eg tramadol / codeine[26]

Pain Score >7 SEVERE PAIN- give NSAID+ Paracetamol + Strong Opioid eg oral
morphine, pethidine, fentanyl
63
APPENDIX
IV:
TRANSLATED
EFFORT-DEPENDENT
PAIN-
ASSESSMENT TOOL (LUGANDA )
Pain level
None
Moderate
Severe
@ Rest when lying down
0
1
2
@ Maximal breath/walking
0
1
2
@ sitting up/ standing
0
1
2
@ Twisting
0
1
2
@ ½-leg lifting
0
1
2
Total ____/10
Ebibuuzo ebyo waggulu bijja kweyambisibwa okugerageranya obungi bw’obulumi bwolina.
Ojja kubuzibwa enfunda ezenjawulo oba olina obulumi. Waliwo engeri ssatu ezokuddamu
ng’obuziddwa okunyonyola obulumi bwolina. Ze zino: Tewali , Obwekigero, bungi nyo. Ojja
kubuuzibwa emirundi etaano. Bulumi bwa ngeri ki bwolina nga:
1. Owummudemu webase wansi
2. Ossizza nyo oba otambula
3. Otudde oba onyimiridde
4. Owese ekugulu
5. Ositudde ekitundu ky’okugulu

Pain score 0 - no pain- no analgesia given- don’t give analgesia

Pain Score < 4 – Mild pain (adequate analgesia)- give Paracetamol + NSAID ( eg
Ibuprofen, diclofenac, aceclofenac/ meloxicam)

Pain Score 4 TO 7 – Moderate pain (Inadequate analgesia)- give NSAID+
Paracetamol + Weak Opiod eg tramadol / codeine[26]

Pain Score >7 SEVERE PAIN- give NSAID+ Paracetamol + Strong Opiod eg oral
morphine, pethidine, fentanyl
64
APPENDIX V: VISUAL ANALOGUE SCORE
No pain
worst pain imaginable
Instructions to the patient:
The above line will help to assess how much pain you have. The left part of the line shows no
pain at all and the other end shows the worst pain imaginable. Think about the pain that you have
and then make a mark along the line, the place where you feel your pain is.
Omustale egwo waggulu gujja kuyamba okugerageranya obungi bw’obulumi bwolina. Ekitundu
kygwo ekyokukkono kiranga nti tewali bulumi nakamu ate ku ludda luli gulaga obulumi
abutogerekeka. Lowooza ku bungi bw’obulumi bwolina olyoke osse akabonero ku musitale ku
katundu gwowulira ng’obulumi bwo butuuse.
65
APPENDIX VI: AMERICAN SOCIETY OF ANAESTHESIOLOGIST
CLASSFICATION OF PHYSICAL STATUS
ASA
DESCRIPTION
CLASSIFICATION
1
A normally healthy individual
2
A patient with mild systemic disease
3
A patient with severe systemic disease that is not incapacitating
4
5
A patient with incapacitating systemic disease that is a constant
threat to life
Moribound patient not expected to survive with or without surgery
6
A brain stem dead patient whose organs are being removed for
donor purposes
E
Emergency
66
APPENDIX VII: DATA COLLECTION FORM:
1. Patient identification
1.1. Study number ___________
1.2. DATE of surgery (dd,mm,yyyy) _ _, _ _, _ _ _ _
1.3. DATE of discharge: (dd,mm,yyyy) _ _, _ _, _ _ _ _
1.4. DATE of injury (dd,mm,yyyy) _ _, _ _, _ _ _ _
2. Socio-demographic variables
2.1. date of birth ( dd,mm,yyyy)
2.2. Gender: Male [ ] female [ ]
2.3. Education level: never been to school [ ], primary [ ], secondary [ ], tertiary [ ].
2.4. Tribe: ______________
2.5. Occupation: health worker[ ], peasant farmer [ ], student [ ], trader [ ], motorvehicle cylist[ ], other _________
3. Patient Characsteristics
3.1. Diagnosis: fracture: femur [ ], tibia [ ], ankle [ ], foot [ ], hip( intratrocanteric,
neck of femur, head of femur) [ ] & other _________
3.2. Surgery: ORIF [ ], total joint arthroplasty [ ], hemi arthroplasty[ ]
other__________.
3.3. Weight: __ __ __ kg
3.4. Pulse: __ __ __ beats/min
3.5. Blood pressure: __ __ __/ __ __ __ mmHg
3.6. Pre-operative Pain score: __ __/ 10 using VAS ;
3.7. Preoperative pain score: __ __/10 using EDPAT
4. Analgesia given pre-op:
67
4.1. Has analgesia been given yes [ ], No [ ]
4.2. Drug -----------------------4.3. Dosage --------mg
4.4. Route of administration oral[ ], IV [ ], IM [ ].rectal [ ], s/c [ ].
5. Intra-operative analgesia given:
5.1. Analgesia given Yes [ ], No [ ]
5.2. Drug :______________
5.3. Dose: _____mg
5.4. Route: IV [ ], IM [ ], Nerve block [ ].
5.5. Number of times given: __ __
6. Post operative analgesia
6.1. Total number of requests for analgesia by patient __ __
6.2. Time from surgery to the first analgesia request __ __ hours
6.3. Highest pain score in 24 hours
6.3.1. Time from surgery __ __ hours
6.3.2. VASPain score __ __
6.3.3. EDPAT Pain score __ __
7. Patients level of satisfaction
7.1. Has your pain been adequately responded to? Yes [ ], No [ ].
7.2. Do you feel that the pain could have been treated better ? Yes [ ] , No [ ].
7.3. If yes how could it have been treated better __________________________
7.4. Do you feel your pain has been adequately treated and that you can be able to
follow the post operative instructions given to you?( Eg sit up in bed, able to
hang your legs, bend your knee etc.)Yes [ ], No [ ].
68
7.5. Are you able to go for your postoperative x-ray( either by wheel chair, stretcher
etc) without pain? Yes [ ], No[ ]
8. Reasons for delay of discharge: ( the patient stays beyond 3 days)
8.1. Medical conditions:
8.1.1. Anaemia [ ],
8.1.2. pneumonia [ ],
8.1.3.
malaria [ ]
8.1.4. Other ______________
8.2. Rehabilitation [ ]
8.2.1. Waiting for crutches [ ],
8.2.2. Physiotherapy [ ]
8.3. Surgery conplications:
8.3.1. DVT
8.3.2. Pneumonia
8.3.3. Other_______________
69
70
APPENDIX VIII: BUDGET
ITEM
QUANTITY UNIT COST TOTAL COST
1 Capital expenses
Laptop (USD 1300)
1
2,000,000
2,000,000
Portable Hard Disc
1
300,000
300,000
Flash Disc
1
30,000
30,000
250,000
250,000
Printer
2 Recurrent Stationary expenses
Internet services
400,000
Photocopying and Printing
312,500
3 Research Assistants
4
800,000
4 Statistician
1
500,000
6 Presentation
LCD projector hire
Miscellaneous
Total
3
50,000
150,000
300,000
5,042,500
71
Justification of the Budget
Recurrent costs
There will be a number of costs incurred on stationary; printing and photocopying of the
proposal and dissertation, including binding. Other costs include the internet services due to
irregularities in our internet services at the department; telephone communication for
coordination during the research. LCD projector will be required for the presentations.
Fixed costs
The fixed costs will be for the computer needed for developing the proposal and analyzing the
data collected. The printer and tonner will be used to produce the proposal and questionnaires.
Money has been set aside for the statistician and the research assistants. Funds will also be
required to buy facilities for data backup. This will be required to ensure the safety of the data
collected.
72
APPENDIX IX: FORMULAE
Calculation of Sensitivity
Sensitivity = True Positives x 100 / (True Positives + False Negatives)
Calculation of Specificity
Specificity = True Negatives x 100 / (True Negatives + False Positives)
Calculations of Positive Predictive Value
Positive Predictive Value = True Positives x 100 / (True Positives + False Positives)
Calculation of Negative Predictive Value
Negative Predictive Value = True Negatives x 100 / (True Negatives + False Negatives)
Calculation of Accuracy
Accuracy = (True Positives + False Negatives) x 100 / (True Positives + True Negatives + False
Positives + False Negatives)
Calculation of Missed Diagnoses
Missed diagnoses = False Negatives x 100 / (False Negatives + True Positives)
73
APPENDIX X: RESULT TABLES
Table 2: Table showing number of study subjects with pain Pre operatively, postoperatively
at O, 6 and 24 hours.
Time
VAS (n/ %)
EDPAT (n/%)
(hrs)
No pain
Mild
Pre
20(21.74)
0
Moderate Severe
No pain
Mild
Moderate
25(27.17) 21(22.83) 26(28.26) 21(22.83)
27(29.35)
12(13.04) 32(34.78)
36(39.13)
10(10.87) 9(9.78)
6(6.52)
6(6.52)
6
11(11.96)
7(7.61)
10(10.99)
23(25.27) 49(53.26)
24
18(19.57)
33(35.87) 28(30.43) 13(14.13) 12(13.14
39(13.04)
28(30.43) 13(14.13)
37(40.22) 38(41.30)
26(28.26) 48(52.17) 10(10.99)
Severe
42(45.65)
)
74
APPENDIX XI: STUDY PERIOD:
February 2010 to 2009 to March 2011
Item
Proposal
development
F M
A
M
J
J
A
S
O
N
D
J
F
M
Presentation
Data collection
and entry
Analysis
Dissertation
writing &
Submission
75