Neuropsychological Rehabilitation An International Journal ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/pnrh20 Cognitive remediation therapy for post-acute persistent cognitive deficits in COVID-19 survivors: A proof-of-concept study Mariagrazia Palladini, Beatrice Bravi, Federica Colombo, Elisa Caselani, Camilla Di Pasquasio, Greta D’Orsi, Patrizia Rovere-Querini, Sara Poletti, Francesco Benedetti & Mario Gennaro Mazza To cite this article: Mariagrazia Palladini, Beatrice Bravi, Federica Colombo, Elisa Caselani, Camilla Di Pasquasio, Greta D’Orsi, Patrizia Rovere-Querini, Sara Poletti, Francesco Benedetti & Mario Gennaro Mazza (2022): Cognitive remediation therapy for post-acute persistent cognitive deficits in COVID-19 survivors: A proof-of-concept study, Neuropsychological Rehabilitation, DOI: 10.1080/09602011.2022.2075016 To link to this article: https://doi.org/10.1080/09602011.2022.2075016 View supplementary material Published online: 18 May 2022. Submit your article to this journal Article views: 422 View related articles View Crossmark data Citing articles: 1 View citing articles Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=pnrh20 NEUROPSYCHOLOGICAL REHABILITATION https://doi.org/10.1080/09602011.2022.2075016 Cognitive remediation therapy for post-acute persistent cognitive deficits in COVID-19 survivors: A proof-ofconcept study Mariagrazia Palladini a,b, Beatrice Bravi a,b, Federica Colomboa,b, Elisa Caselania, Camilla Di Pasquasioa, Greta D’Orsia, Patrizia Rovere-Querini Sara Polettia,c, Francesco Benedetti a,c and Mario Gennaro Mazzaa,b c,d , a Psychiatry & Clinical Psychobiology, Division of Neuroscience, IRCCS Scientific Institute Ospedale San Raffaele, Milano, Italy; bPhD Program in Cognitive Neuroscience, University Vita-Salute San Raffaele, Milan, Italy; cVita-Salute San Raffaele University, Milano, Italy; dDivision of Immunology, Transplantation and Infectious Diseases, IRCCS San Raffaele Scientific Institute, Milan, Italy ABSTRACT Cognitive impairments figure prominently in COVID-19 survivors. Cognitive remediation therapy (CRT) improves functional outcomes reducing long-term cognitive deficits in several neurological and psychiatric conditions. Our casecontrol study investigates the efficacy of a CRT programme administered to COVID-19 survivors in the post-acute phase of the illness. Seventy-three COVID-19 survivors presenting cognitive impairments at one-month follow-up were enrolled. Among them, 15 patients were treated with a two-month CRT programme, and 30 non-treated patients were matched conditional to their baseline cognitive functioning. Cognitive functions were assessed before and after treatment. Depression and quality of life were also evaluated. Mixed model ANOVA revealed a significant effect over time of the CRT programme on global cognitive functioning (F = 4.56, p = 0.039), while no significant effect was observed in the untreated group. We observed a significant effect of the improvement in verbal fluency (χ 2 = 7.20, p = 0.007) and executive functions (χ 2 = 13.63, p < 0.001) on quality of life. A positive significant correlation was found between depressive symptomatology and verbal fluency (r = −0.35), working memory (r = −0.44), psychomotor coordination (r = −0.42), and executive functions (r = −0.33). Our results could pave the way to a plausible innovative treatment targeting cognitive impairments and ameliorating the quality of life of COVID-19 survivors. ARTICLE HISTORY Received 24 August 2021 Accepted 4 May 2022 KEYWORDS Covid-19; SARS-CoV-2; Cognitive impairment; Cognitive remediation therapy; Depression Introduction The ongoing Coronavirus Disease 2019 (COVID-19) pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has led to CONTACT Mariagrazia Palladini palladini.mariagrazia@hsr.it Istituto Scientifico IRCCS Ospedale San Raffaele, Dipartimento di Neuroscienze Cliniche, San Raffaele Turro, Via Stamira d’Ancona 20, 20127 Milano, Italy Supplemental data for this article can be accessed online at https://doi.org/10.1080/09602011.2022.2075016 © 2022 Informa UK Limited, trading as Taylor & Francis Group 2 M. PALLADINI ET AL. nearly 500 million cases and over 6 million deaths worldwide (WHO, 2021). SARS-CoV-2 infection causes a broad spectrum of manifestations ranging from asymptomatic infection to life-threatening multiorgan disease, also inducing, among the others, neurologic and neuropsychiatric complications (Ellul et al., 2020; Varatharaj et al., 2020). Moreover, heterogeneous and systemic dysfunctions may persist in the post-acute phase and constitute the long-COVID syndrome (Huang et al., 2021; Nalbandian et al., 2021). In the context of the long-COVID syndrome, also characterized by fatigue, post-exertional malaise, anxiety, and depression, cognitive impairment is now recognized as one of the leading complaints in COVID-19 survivors (Davis et al. 2021; Nalbandian et al., 2021; World Health Organization, 2021). In addition, persistent subjective and objective neurocognitive impairments after acute infection have been reported at short and long-term follow-up (Almeria et al., 2020; Helms et al., 2020; Mendez et al., 2021). Executive functions and attention seem to be the most affected cognitive domain in COVID-19 survivors. In this context, we have previously observed that 78% of COVID-19 survivors showed a poor performance in at least one cognitive domain three months after hospital discharge, with the executive functions being impaired in about 50–60% of survivors (Mazza et al., 2021). Moreover, consistently with literature we found that cognitive performances were influenced both by depressive symptomatology (Almeria et al., 2020; Mendez et al., 2021) and by levels of inflammation at the time of hospital admittance (Mazza et al., 2021; Zhou et al., 2020). In this regard, recent studies from our group point toward a partially comparable cognitive profile between COVID-19 survivors and patients diagnosed with Major Depressive Disorder, with the two groups showing overlapping performances in verbal fluency and executive functions tasks (Poletti et al., 2021). Similar cognitive impairments and their relationship with depressive symptoms have been observed following acute respiratory distress syndrome (ARDS) of other aetiologies where up to 70% of ARDS survivors had presented deficits affecting predominantly, executive functions, and memory (Hopkins et al., 2005; Hopkins et al., 2006; Sasannejad et al., 2019). Little is known about the progression or remission of cognitive deficits over time in the aftermath of COVID-19, although a recent study from our group suggests that cognitive impairments tend to remain stable in a time frame from one to six months after hospital discharge (Poletti et al., 2021). Furthermore, available evidence suggests that cognitive dysfunctions seem to be independent of COVID-19 severity proxied by the need for hospitalization, NIV, and ICU admission (Beaud et al., 2021; Hopkins et al., 2006; Jaywant et al., 2021; Mazza et al., 2021; Woo et al., 2020). Notably, persistent cognitive impairment showed a detrimental effect on the quality of life and daily global functioning of COVID-19 survivors (Mantovani et al., 2020; Miskowiak et al., 2021). The underlying mechanism of the cognitive sequelae is multifactorial and mainly related to the COVID-19 associated systemic inflammation, hypoxia, and cerebrovascular NEUROPSYCHOLOGICAL REHABILITATION 3 events (Achar and Ghosh, 2020; Beaud et al., 2021; Couzin-Frankel, 2020; Varatharaj et al., 2020). Cognitive remediation therapy (CRT) encompasses a wide range of therapeutic cognitive interventions targeting cognitive deficits to improve functional outcomes by reinforcing, strengthening, or reestablishing previous cognitive abilities (Kim et al., 2018). In this regard, CRT seems to reduce long-term cognitive impairment and the related social and psychological consequences (Medalia and Bowie, 2016), showing potential benefits in several neurological and psychiatric conditions with cognitive impairment similar to that observed in COVID-19 survivors (Cappa et al., 2005; Kim et al., 2018). Moreover, existing evidence reveals enhanced restorative effects of CRT when implemented in the framework of a metacognitive therapeutic approach on severe medical and psychiatric populations (Birnboim and Miller, 2004; Breitborde et al., 2017). Despite the high rate of persistent and disabling cognitive sequelae, no report is available about the efficacy of CRT in COVID-19 survivors enrolled in the sub-acute stages. We hypothesized that a CRT focused on the rehabilitation of the most affected cognitive domains could be used to reduce the cognitive deficits observed in COVID-19 survivors in order to maximize the level of daily functioning and facilitate re-integration into daily activities. Following this line of reasoning, in a proof-of-concept study in a homogeneous cohort of COVID19 survivors presenting cognitive impairments at one-month follow-up here, we report the effects of a 2-month CRT programme compared with the naturalistic evolution of cognition in untreated patients. Materials and methods Participants COVID-19 survivors were recruited from 24 November 2020 to 27 April 27 2021 at one-month after hospital discharge during an ongoing longitudinal cohort study at IRCSS San Raffaele Hospital in Milan. The current study included only patients who were admitted to Emergency Department for COVID-19 pneumonia, as suggested by clinical and radiological findings. The infection was confirmed by positive real-time reverse-transcriptase polymerase chain reaction (RT–PCR) from a nasopharyngeal and/or throat swab. Exclusion criteria were: age above 70, non-Italian speakers, and patients with any form of documented or suspected neurological symptoms or intellectual disability. Given the small number of critical illness patients followed-up at our outpatients service and the remarkable neurocognitive implication of pneumonia-induced hypoxia, patients who need intensive care unit level care during the acute phase were also excluded from the study. Overall, 73 patients who meet the above criteria completed the neuropsychological assessment at one- and three-month followups and were therefore considered eligible for the study (48 male; mean age 4 M. PALLADINI ET AL. 58.2 ± 9.16). Among them, 16 were enrolled for the CRT, while 57 did not receive the treatment. The group of untreated patients included COVID-19 survivors who showed different levels of cognitive performance at the first neuropsychological assessment. In order to meet the clinical need and considering the limited health care resources, CRT was administered to COVID-19 survivors who exhibited cognitive deficits at the baseline and were in the position to conclude the entire CRT programme. One of the CRT participants did not complete the training sessions, and thus was excluded from the analysis (see online supplement Figure 1). CRT patients were matched based on cognitive functioning one month after discharge with untreated patients (1:2 ratio), reaching a final matched sample of 15 treated and 30 untreated COVID-19 survivors (for further details see Design Section). We followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. Written informed consent to participate in the study was obtained from all participants. All procedures involving human patients were approved by the Ethics Committee of San Raffaele Hospital (COVID-BioB protocol NCT04318366). Measures Assessment of cognitive functions was performed through the Brief Assessment of Cognition in Schizophrenia (BACS) (Keefe et al., 2004), a neuropsychological screening test covering the evaluation of verbal memory, verbal fluency, working memory, attention, and speed information processing, psychomotor coordination, and executive functions. The first neuropsychological assessment was performed one month after hospital discharge (33.53 ± 9.89 days), while the post-treatment evaluation was performed three months after discharge (89.16 ± 10.12 days). Two versions (A and B) of BACS were administered at the baseline and at follow-up respectively, to reduce recall effects. BACS scores were adjusted for age, sex, and educational level (years of schooling) and then converted into a 5-point interval scale to compute equivalent scores for each cognitive domain, where 0 reflects a deficient performance and 4 an optimal one (Anselmetti et al., 2008). As such, the equivalent scores standardization method also accounts for socio-demographics influencing cognitive performance and allows a direct comparison among different tests. We delivered CRT only for patients presenting a failure in one or more cognitive domains as proxied by 0 or 1 equivalent score, which reflect performance scores falling in the left tail of area 0.05 or 0.10 respectively under the normal distribution curve (Anselmetti et al., 2008). To assess the improvement of cognitive functions over time, a delta score was calculated for each cognitive domain (equivalent NEUROPSYCHOLOGICAL REHABILITATION 5 score at follow-up – equivalent score at baseline). Beyond equivalent scores for the single domains, also a global index of cognitive functioning was computed as the mean of the six equivalent scores for each participant. To evaluate the depressive symptomatology, participants completed the Zung Severity Rating Scale (ZSDS) (Zung, 1965), which, thanks to its behavioural and somatic orientation in assessing depressive symptomatology, proved a valid instrument to differentiate depressed from non-depressed groups in the general population (Sepehry, 2014), including COVID-19 survivors (Benedetti et al., 2021; Mazza et al., 2020; Mazza et al., 2021; Nie et al., 2021; Yuan et al., 2020). The commonly suggested ZSDS index ≥ 50 cut-off was considered indicative of relevant depressive symptomatology. In the treated group, the World Health Organization Quality of Life assessment (WHOQOL-BREF) (Skevington et al., 2004 Mar) was used to gather information about changes in quality of life before and after CRT. Sociodemographic and clinical data were available for all the included patients, thus we had no missing data. Design We implemented a matching strategy in order to limit confounding effects arising from non-random assignment of participants. Considering the investigation of CRT effect on cognitions as the primary aim of the current study, patients included in the analyses have been selected based on their a priori individual probability (i.e., propensity score) to be allocated to the treated group, conditional to their baseline equivalent scores. Propensity scores were derived through a logistic regression model fitted on equivalent scores obtained at the baseline neuropsychological assessment. Treated and untreated patients were matched using the optimal pair matching method without replacement and a matching ratio of 2:1. Therefore, CRT patients were matched with two untreated patients showing the same cognitive profile at baseline. A comparison of baseline equivalent scores between matched groups was performed using standardized mean difference (Ho et al., 2007), where a difference less than 0.05 was considered as an acceptable balance (Belitser et al., 2011) (see online supplement Methods 2). Matching routine was run within R version 3.6.3 using the package MatchIt version 4.2.0 (Stuart et al., 2011) (https:// www.jstatsoft.org/v42/i08/). The final matched sample of 45 COVID-19 survivors (15 in the CRT group and 30 in the control one) was considered for the following analysis, thus removing the selection bias introduced in the first phase of patients’ enrolment (see online supplement Table 1). Intervention A two-month CRT protocol was administered by trained psychologists to COVID-19 survivors enrolled at one-month follow-up after hospital discharge. 6 M. PALLADINI ET AL. The treatment started within 15 days from the baseline neuropsychological assessment (on average, 6.34 ± 3.33 days). The face-to-face CRT protocol was carried out through COGPACK® software version 6. (http://www. markersoftware.com/) under the supervision of trained psychologists who administered the neuropsychological assessment, motivating and assisting the patients during the cognitive remediation programme. This software includes 64 test and training programmes, with 537 different task sets to improve neurocognitive functioning. The package includes both domainspecific tasks in the same cognitive domains investigated by the BACS, and non-domain-specific exercises, focusing on everyday skills and knowledge. The protocol consisted of training series based on the impaired cognitive domains (i.e., equivalent score 0–1), with a maximum of 10 tasks per subject. According to the number of impaired domains and their severity, a training session was tailored for each participant, including up to five domain-specific exercises. This procedure allows customizing the training while maintaining a fixed duration of the session, resulting in comparable outcomes. Domainspecific exercises have been selected according to the general process involved and following the DSM taxonomy on neurocognitive domains (Sachdev et al., 2014) in order to match the domains measured by the BACS (i.e., Perceptual motor function – Psychomotor coordination; Language – Verbal Fluency; Executive Functions – decision making; Learning and Memory – free recall; Complex attention – selective attention and processing speed). Mainly adaptive exercises were chosen, thus setting training at a challenging level of difficulty. Once the training tasks were selected, a minimum of 2 non-domain-specific tasks were added as a placebo to complete the series. Each training session was 60 min long and was performed once a week over a period of 6 consecutive weeks, for a total of 6 sessions per subject. After 3 weeks of treatment, a new set of different domain-specific exercises was built, keeping the general structure of the series unchanged. Given the lack of literature directly proposing specific rehabilitation protocols targeting cognitive deficits in survivors of coronaviruses epidemics, the current CRT programme design partially overlap with previously implemented CRT protocols in psychiatric population (Cavallaro et al., 2009; Schneider et al., 2020). However, the duration and intensity of the intervention were moderated according to the target group’s clinical needs. Indeed, COVID19 survivors showed a less compromised cognitive profile compared to the clinical populations mentioned in the existing literature on CRT (Poletti et al., 2021). Data analysis Based on our previous findings showing an association between cognitive performances and depressive symptomatology in COVID-19 survivors (Mazza et al., 2021), we computed a non-parametric Spearman correlation between ZSDS scores and equivalent scores at baseline to test their association. NEUROPSYCHOLOGICAL REHABILITATION 7 Then, the effect of treatment on cognition was analysed in three sequential steps. First, in order to explore the effect of treatment on changes in cognitive performance over time, we performed a mixed model ANOVA analysis on the global cognitive index. According to Spearman correlations results, we considered ZSDS scores as confounding variable together with age, sex, and number of cognitive impaired domains at baseline as an index of cognitive impairment severity at baseline. Second, the effect of CRT on each cognitive domain was investigated through a mixed model ANOVA considering the equivalent scores of each domain both at the baseline and the follow-up. Time and domain were modelled as within effects, whereas CRT treatment as between effect. Age, sex, ZSDS, number of impaired domains at baseline were entered as covariates. Post-hoc Fisher’s least significant difference (LSD) was performed as appropriate. Third, to investigate whether CRT is specifically effective in recovering the most impaired cognitive functions, decomposition of single effects was performed only for cognitive domains which resulted severely impaired (equivalent scores ≤1). In accordance with this criterion, we further explore the effect of CRT on the recovery of verbal fluency, which resulted in the most damaged dimension on average. Analyses were computed within the generalized linear model (GLZM) with homogeneity of slope design, modelling CRT as group factor and considering CRT * baseline equivalent score in verbal fluency as the main effect of interest. We entered CRT and baseline equivalent score as predictors, and delta score in the target domain as dependent variable, also adjusting for sex, age, and ZSDS. As such, it was possible to figure out if the improvement in verbal fluency associated to CRT was affected by the initial equivalent score in that domain. In the presence of a significant interaction of CRT * baseline equivalent, stratification of patients was applied on the initial equivalent score. More specifically, only subjects who scored 0 in the domain of interest were considered in the following analysis. Given possible violation of parametric assumptions (e.g., normal distribution of dependent variable, homogeneity of variances) we tested the effect of CRT on the improvement of the performances using a GLZM model, again controlling for age, sex and ZSDS. Multinomial ordered distribution was assumed for the dependent variable, setting probit as link function. Finally, to test the effect of all single cognitive domain variations on changes in quality of life and considering the a priori expected significant interaction with other independent factors (age, sex, and ZSDS), independent variables were entered into a GLZM (McCullagh and Nelder, 1989). Likelihood Ratio statistic (LR) was used to calculate the significance of the effect for all the previous GLZM specified analysis, providing an estimate of the increment in the log-likelihood of the model attributed to each predictor. 8 M. PALLADINI ET AL. Results The optimal matching routine returned balanced baseline equivalent scores as evaluated through standardized mean difference (SMD) values, thus allowing meaningful comparison of cognitive improvement between the treated and the untreated group (SMD values for the matched sample ranged between -0.05 and 0.02). Demographic, clinical, and cognitive characteristics of the matched sample were summarized in Table 1. Spearman correlations highlighted a significant association (p < 0.05) between ZSDS scores and: (i) verbal fluency (r = −0.35), (ii) working memory (r = −0.44), (iii) psychomotor coordination (r = −0.42), and (iv) executive functions (r = −0.33). Mixed model ANOVA predicting the effect of CRT on the global cognitive index changes (i.e., mean of all the equivalent scores) revealed a significant time * CRT interaction (F = 4.56, p = 0.039, η 2 = 0.104) (shown in Figure 1) as well as a main effect of the number of impaired domains (F = 84.35, p < 0.001, η 2 = 0.662). No significant main effect of time was observed. Given the obtained significant result on the global cognitive index, each of the six cognitive functions was individually considered (shown in Figure 2). A significant interaction of time * CRT was detected (F = 4.56, p = 0.039, η 2 = 0.104) only for executive functions. Post-hoc inspection showed that the treated group performed better at the follow-up than controls in executive functions (p < 0.001). Furthermore, investigating the effect over time in single domains among the two groups, we observed a significant improvement among both treated and untreated patients in executive functions (treated: p < 0.001; untreated: p < 0.001) and verbal fluency (treated: p = 0.006; untreated: Table 1. Demographic, clinical, and cognitive characteristics of the matched sample according to treatment. ZSDS, Zung self-rating depression scale. Males (Females) Age (mean ± SD) ZSDS index score (mean ± SD) ZSDS index > 50 Yes (No) Hospitalization Duration in days (mean ± SD) Mean Equivalent Score (mean ± SD) Verbal Memory (Equivalent mean ± SD) Verbal Fluency (Equivalent mean ± SD) Working Memory (Equivalent mean ± SD) Speed Information Processing (Equivalent mean ± SD) Psychomotor Coordination (Equivalent mean ± SD) Executive Functions (Equivalent mean ± SD) Impaired Verbal Memory (n–%) Impaired Verbal Fluency (n–%) Impaired Working Memory (n–%) Impaired Speed of Information Processing (n–%) Impaired Psychomotor Coordination (n–%) Impaired Executive Functions (n–%) Controls (n = 30) Treated (n = 15) t or χ 2 pvalue 23 (7) 59.60 ± 10.00 44.25 ± 11.23 10 (20) 15.70 ± 14.41 1.73 ± 0.78 2.87 ± 1.17 0.43 ± 0.63 2.10 ± 1.30 2.03 ± 1.54 1.40 ± 1.16 1.57 ± 1.57 5–16.67% 28–93.33% 9–30% 12–40% 14–46.67% 18–60% 9 (6) 56.80 ± 7.09 46.43 ± 10.27 11 (4) 17.87 ± 19.45 1.74 ± 0.53 2.87 ± 0.83 0.40 ± 0.63 2.13 ± 1.30 2.07 ± 1.44 1.40 ± 1.45 1.60 ± 1.59 1–6.67% 14–93.33% 5–33.3 % 5–33.3% 8–53.33% 9–60% 1.32 0.97 −0.63 0.21 −0.42 −0.50 0.00 0.17 −0.08 −0.07 0.00 −0.07 0.87 0.00 0.05 0.19 0.18 0.00 0.245 0.339 0.531 0.649 0.675 0.496 1.000 0.868 0.936 0.945 1.000 0.947 0.352 1.000 0.819 0.664 0.673 1.000 NEUROPSYCHOLOGICAL REHABILITATION 9 Figure 1. Mixed model ANOVA considering the change over time of the mean equivalent score in the two groups, according to age, sex, ZSDS, number of impaired cognitive domains at baseline. Error bars represent the 95% Confidence Intervals. p = 0.016), while only the treated patients showed significant improvement in psychomotor coordination (p = 0.012). GLZM homogeneity of slopes highlighted a significant effect of CRT * baseline verbal fluency interaction on improvement in the same domain (χ 2 = 4.68, p = 0.030). Consistent with previous results, stratifying for baseline equivalent scores, the GLZM model showed a significant effect of CRT in predicting Figure 2. Mixed model ANOVA considering the change over time of the single domain equivalent scores in the two groups, according to age, sex, ZSDS, number of impaired cognitive domains at baseline. 10 M. PALLADINI ET AL. increment in verbal fluency in the most impaired patients only (equivalent score = 0) (χ 2 = 8.19, p = 0.004). With regards to the analysis on quality of life, we observed a significant effect of improvement in verbal fluency (χ 2 = 7.20, p = 0.007) and executive functions (χ 2 = 13.63, p < 0.001) on variation in WHOQOL-BREF scores. Discussion To the best of our knowledge, this is the first study to demonstrate the beneficial effect of a personalized CRT programme delivered one month after hospital discharge in a cohort of COVID-19 survivors showing cognitive impairment. Here we reported a significant global effect of CRT over time, while time per se did not affect cognition performances. When considering specific cognitive domains, we found a significant effect of CRT on executive functioning, verbal fluency, and psychomotor coordination, which interestingly were among the most compromised cognitive functions at baseline. Moreover, the improvements in verbal fluency and executive functions improved the global quality of life of survivors. Previous insights suggest high prevalence of cognitive impairment among COVID-19 survivors in short, middle, and long time, thus suggesting an enduring pattern of cognitive deterioration even following the complete virus clearance (Rabinovitz et al., 2020; Sheng et al., 2005). Accordingly, recent investigations from our group documented a large incidence of cognitive deficits (about 79%) one month after hospital discharge, that seem to remain stable up to three- and six-month follow-ups (about 75%) (Poletti et al., 2021). Cognitive impairments in the post-critical acute phase of COVID-19 are consistently reported irrespectively of the length of mechanical ventilation or intensive care unit stay (Beaud et al., 2021; Jaywant et al., 2021). These deficits, if not immediately addressed, seem to show a chronic course (Girard et al., 2018; Jaywant et al., 2021) with residual cognitive impairments being now considered a hallmark of the well-established long-covid syndrome (Nalbandian et al., 2021; Taquet et al., 2021; Taribagil et al., 2021). When investigating the specific cognitive domains, previous studies found that executive function and verbal fluency were among the most affected cognitive domains (Almeria et al., 2020; Beaud et al., 2021; Hampshire et al. 2020; Helms et al., 2020; Jaywant et al., 2021) both in acute and sub-acute stages. Consistently, with the long-lasting course of cognitive impairment, in the absence of the CRT, we found no spontaneous recovery of global cognitive functioning over time. Moreover, when investigating single cognitive domains, executive functions, and verbal fluency, which were found to be among the most affected dimensions in our sample, improved over time also in the untreated patients, but were especially susceptible to CRT-related enhancement. Interestingly, we found that psychomotor coordination benefits from CRT training, whereas deficits in this domain seem NEUROPSYCHOLOGICAL REHABILITATION 11 to be stable in the untreated group, as highlighted in our previous investigation (Mazza et al., 2021). These findings suggest only a partial spontaneous improvement in the most affected cognitive functions over time in the absence of treatment. This is critical, specifically considering defects in executive functions are notably reported over several months in patients with other acute respiratory distress syndrome diseases before the COVID-19 pandemic resulting in poor everyday functioning (Jackson et al., 2003 Apr; Sasannejad et al., 2019). Notwithstanding the partial overlap of cognitive sequelae in the ARDS survivors of other etiologies, COVID-19 patients typically exhibit broader cognitive dysfunctions (Lleó and Alcolea, 2020), encompassing also deficits in verbal fluency, psychomotor coordination, and sustained attention (Almeria et al., 2020; Poletti et al., 2021; Zhou et al., 2020). Furthermore, in COVID-19 survivors, objective cognitive complications usually associate with subjective cognitive complaints, poorer quality of life, and psychiatric outcomes (Almeria et al., 2020). In keeping with this, targeting post-covid cognitive outcomes with tailored CRT protocols is of the utmost importance to restore satisfying everyday functioning. Moreover, herein we detected a strong positive impact exerted by CRT in patients who showed severe verbal fluency impairment at baseline. These findings suggest that CRT not only is highly effective for those cognitive domains specifically impaired in COVID-19 patients but, again, it’s especially successful in recovering extremely compromised cognitive functions. Several mechanisms have been implicated in the pathophysiology of longlasting cognitive deficits after COVID (Alnefeesi et al., 2021). A major emphasis has been placed on the prolonged systemic inflammatory status triggered by the virus, with an exuberant immune response leading to a “cytokine storm” (Coperchini et al., 2020; Nalbandian et al., 2021). In this regard, we previously demonstrated that systemic inflammation at hospital admission influences several cognitive functions three months later, including verbal fluency (Mazza et al., 2021). Alongside with inflammatory hypothesis, mounting evidence supports a close link between persistent hypoxemia experienced during the hospitalization and following neuropsychiatric sequelae (Hosey and Needham, 2020; Mazza et al., 2021). This seems to be especially relevant for executive outcomes (Helms et al., 2020), which remain impaired up to one year from the clearance of the virus (Pandharipande et al., 2013). Furthermore, our results, consistent with the literature, outlined the association between depressive symptomatology and cognitive performance. Recent evidence suggests that depressive symptoms can affect neurocognitive impairment, the latter being in turn held responsible for depressive outcomes in those who contracted Sars-CoV-2 (Almeria et al., 2020; Miskowiak et al., 2021; Muthukrishnan, 2020). In this context, our precedent investigation provides early evidence about the detrimental impact of depressive symptoms on middle-term cognitive performances in a longitudinal cohort of covid-19 survivors (Mazza et al., 2021). In keeping with this, herein we found a correlation 12 M. PALLADINI ET AL. between depressive symptomatology and cognitive impairment. However, notwithstanding this association, depressive symptomatology accounted as a covariate, did not affect the CRT efficacy on global cognitive improvement suggesting specific action of CRT on cognitive functioning irrespectively of mood alterations and thus enhancing its clinical utility. Cognitive training programmes have proven advantageous in improving functional outcomes in several neurological and neuropsychiatric conditions (Rodakowski et al., 2015). CRT protocols are now considered a useful adjunctive therapy in MDD (McIntyre et al., 2013), characterized by a strict association between depressive symptomatology and cognitive impairments that negatively affect daily functioning and significantly worsen the prognosis of traditional treatments (Rock et al., 2014). In this context, CRT is able to enhance mood restoration and to promote substantial psychosocial recovery (Porter et al., 2013). CRT was also found to be a possible therapeutic strategy for mild cognitive impairment (Huckans et al., 2013). Additionally, survivors of critical illness with cognitive impairment had significant improvement after computerized CRT (Wilson et al., 2018). Moreover, CRT was found to be effective in reducing cognitive deficits in adults with HIV (Kanmogne et al., 2020) resulting again in a more fulfilling quality of life (Vance et al., 2012). In agreement with findings related to different clinical populations, we observed the clinical efficacy of CRT not only on cognitive functioning but also on the general well-being as reported on WHO-QOL. Interestingly, the effect on quality of life was proportional to the improvement in cognitive functions in the group of COVID-19 survivors who received the CRT. Nevertheless, these results must be viewed in light of some weaknesses. First, the limited sample size of the present investigation prevents us from generalizing the favourable effect of CRT. Second, both the neuropsychological assessment and the training sessions were conducted by the same psychologist, possibly inducing subjective influence in the post-treatment testing. As our work only involves a passive control group, further studies should include an active placebo condition in order to control for non-specific therapist/patientrelated effects, such as demand characteristics, attention or care. Notwithstanding the successful application of a matching routine afterward, the lack of a structured double-blind randomization design makes it challenging to disentangle the beneficial effect of CRT from the bias related to the ability/inability to regularly attend the full programme. However, our procedure allowed us to meet a clinical need and preserve a more naturalistic setting. Taken together, these findings support the clinical relevance to rapidly address cognitive dysfunctions in order to reverse the spontaneous chronicity of the post-COVID-19 cognitive impairments. As the world moves into the second year of COVID-19 pandemic, delayed cognitive sequelae are becoming increasingly appreciated. Although the calls for treatment targeting cognitive impairments are progressively emerging, cognitive-enhancement therapies NEUROPSYCHOLOGICAL REHABILITATION 13 have not received adequate attention thus far. Overall, we consider our results could pave the way to a plausible treatment line targeting cognitive impairments in the COVID-19 survivors. Although further investigations are required to replicate our findings in larger samples, we demonstrated favourable effects of CRT seem to extend beyond cognitive functioning per se, ameliorating quality of life of the treated subjects. Thus, we suggest mental health systems should consider integrating cognitive enhancing-therapy into their services to properly meet the clinical need and contribute to the full recovery of COVID19 survivors. Acknowledgements Authors thank Sara Bosio for directly participating in the recruitment phase and the COVID-19 BioB Outpatient Clinic Study group for general support. Disclosure statement No potential conflict of interest was reported by the author(s). Funding The author(s) reported there is no funding associated with the work featured in this article. Data availability statement The data that support the findings of this study are not publicly available but are available from the corresponding author MP upon reasonable request. Statement of ethics Study approval statement: this study protocol was reviewed and approved by Ethics Committee of San Raffaele Hospital (COVID-BioB protocol NCT04318366). Consent to participate statement: written informed consent to participate in the study was obtained from all participants. ORCID Mariagrazia Palladini http://orcid.org/0000-0003-4616-4185 Beatrice Bravi http://orcid.org/0000-0003-2568-4181 Patrizia Rovere-Querini http://orcid.org/0000-0003-2615-3649 Francesco Benedetti http://orcid.org/0000-0003-4949-856X References Achar, A., & Ghosh, C. (2020). COVID-19-associated neurological disorders: The potential route of CNS invasion and blood-brain barrier relevance. Cells, 9(11), Article 2360. https://doi.org/ 10.3390/cells9112360 14 M. PALLADINI ET AL. Almeria, M., Cejudo, J. C., Sotoca, J., Deus, J., & Krupinski, J. (2020). Cognitive profile following COVID-19 infection: Clinical predictors leading to neuropsychological impairment. Brain, Behavior, & Immunity-Health, 9. https://doi.org/10.1016/j.bbih.2020.100163 Alnefeesi, Y., Siegel, A., Lui, L. M., Teopiz, K. M., Ho, R., Lee, Y., Nasri, F., Gill, H., Lin, K., Cao, B., Rosenblat, J. D., & McIntyre, R. S. (2021). Impact of SARS-CoV-2 infection on cognitive function: A systematic review. Frontiers in Psychiatry, 11, 55–64. https://doi.org/10.3389/fpsyt. 2020.621773. Anselmetti, S., Poletti, S., Ermoli, E., Bechi, M., Cappa, S., Venneri, A., Smeraldi E., & Cavallaro R. (2008). The brief assessment of cognition in schizophrenia. Normative data for the Italian population. Neurological Sciences, 29(2), 85–92. https://doi.org/10.1007/s10072-008-0866-9 Beaud, V., Crottaz-Herbette, S., Dunet, V., Vaucher, J., Bernard-Valnet, R., Du Pasquier, R., Bart P.-A., & Clarke S. (2021). Pattern of cognitive deficits in severe COVID-19. Journal of Neurology, Neurosurgery & Psychiatry, 92(5), 567–568. https://doi.org/10.1136/jnnp-2020325173 Belitser, S. V., Martens, E. P., Pestman, W. R., Groenwold, R. H., De Boer, A., & Klungel, O. H. (2011). Measuring balance and model selection in propensity score methods. Pharmacoepidemiology and Drug Safety, 20(11), 1115–1129. https://doi.org/10.1002/pds. 2188 Benedetti, F., Mazza, M., Cavalli, G., Ciceri, F., Dagna, L., & Rovere-Querini, P. (2021). Can cytokine blocking prevent depression in COVID-19 survivors? Journal of Neuroimmune Pharmacology, 16(1), 1–3. https://doi.org/10.1007/s11481-020-09966-z Birnboim, S., & Miller, A. (2004). Cognitive rehabilitation for multiple sclerosis patients with executive dysfunction. Journal Cognitive Rehabilitation, 22(4), 8–11. 22513513 Breitborde, N. J., Woolverton, C., Dawson, S. C., Bismark, A., Bell, E. K., Bathgate, C. J., & Norman, K. (2017). Meta-cognitive skills training enhances computerized cognitive remediation outcomes among individuals with first-episode psychosis. Early Intervention in Psychiatry, 11 (3), 244–249. https://doi.org/10.1111/eip.12289 Cappa, S., Benke, T., Clarke, S., Rossi, B., Stemmer, B., & Heugten, C. M. Task Force on Cognitive Rehabilitation. (2005). EFNS guidelines on cognitive rehabilitation: Report of an EFNS task force. European Journal of Neurology, 12(9), 665–680. https://doi.org/10.1111/j.1468-1331. 2005.01330.x Cavallaro, R., Anselmetti, S., Poletti, S., Bechi, M., Ermoli, E., Cocchi, F., Stratta, P., Vita, A., Rossi, A., & Smeraldi, E. (2009). Computer-aided neurocognitive remediation as an enhancing strategy for schizophrenia rehabilitation. Psychiatry Research, 169(3), 191–196. https:// doi.org/10.1016/j.psychres.2008.06.027 Coperchini, F., Chiovato, L., Croce, L., Magri, F., & Rotondi, M. (2020). The cytokine storm in COVID-19: An overview of the involvement of the chemokine/chemokine-receptor system. Cytokine Growth Factor Reviews, 53, 25–32. https://doi.org/10.1016/j.cytogfr.2020. 05.003 Couzin-Frankel, J. (2020). The mystery of the pandemic’s ‘happy hypoxia’. Science, 368(6490), 455–456. https://doi.org/10.1126/science.368.6490.455. Davis, H. E., Assaf, G. S., McCorkell, L., Wei, H., Low, R. J., Re’em, Y., Redfield, S, Austin, J.P, Akrami, A.J., (2021). Characterizing long COVID in an international cohort: 7 months of symptoms and their impact. SSRN 3820561. Ellul, M. A., Benjamin, L., Singh, B., Lant, S., Michael, B. D., Easton, A., Kneen, R., Defres, S., Sejvar, J., Solomon, T., (2020). Neurological associations of COVID-19. The Lancet Neurology, 19(9), 767–783. https://doi.org/10.1016/S1474-4422(20)30221-0 Girard, T. D., Thompson, J. L., Pandharipande, P. P., Brummel, N. E., Jackson, J. C., Patel, M. B., Hughes, C. G., Chandrasekhar, R., Pun, B. T., Boehm, L. M., Elstad, M. R., Goodman, R. B., Bernard, G. R., Dittus, R. S., & Ely, E. W. (2018). Clinical phenotypes of delirium during critical NEUROPSYCHOLOGICAL REHABILITATION 15 illness and severity of subsequent long-term cognitive impairment: A prospective cohort study. The Lancet Respiratory Medicine, 6(3), 213–222. https://doi.org/10.1016/S2213-2600 (18)30062-6 Hampshire, A., Trender, W., Chamberlain, S., Jolly, A., Grant, J. E., Patrick, F., Mazibuko, N., Williams, S., Barnby, J.M., Hellyer, P., (2020) Cognitive deficits in people who have recovered from COVID-19 relative to controls: An N=84,285 online study. MedRxiv. Helms, J., Kremer, S., Merdji, H., Clere-Jehl, R., Schenck, M., Kummerlen, C., Collange, O., Boulay, C., Fafi-Kremer, S., Ohana, M., Anheim, M., & Meziani, F. (2020). Neurologic features in severe SARS-CoV-2 infection. New England Journal of Medicine, 382(23), 2268–2270. https://doi.org/10.1056/NEJMc2008597 Ho, D., Imai, K., King, G., & Stuart, E. A. (2011). MatchIt: Nonparametric Preprocessing for Parametric Causal Inference. Journal of Statistical Software, 42(8), 1–28. https://doi.org/ 10.18637/jss.v042.i08 Ho, D. E., Imai, K., King, G., & Stuart, E. A. (2007). Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Political Analysis, 15(3), 199– 236. https://doi.org/10.1093/pan/mpl013 Hopkins, R. O., Gale, S. D., & Weaver, L. K. (2006). Brain atrophy and cognitive impairment in survivors of acute respiratory distress syndrome. Brain Injury, 20(3), 263–271. https://doi. org/10.1080/02699050500488199 Hopkins, R. O., Weaver, L. K., Collingridge, D., Parkinson, R. B., Chan, K. J., & Orme, Jr., J. F. (2005). Two-year cognitive, emotional, and quality-of-life outcomes in acute respiratory distress syndrome. American Journal of Respiratory Critical Care Medicine, 171(4), 340– 347. https://doi.org/10.1164/rccm.200406-763OC Hosey, M. M., & Needham, D. M. (2020). Survivorship after COVID-19 ICU stay. Nature Reviews Disease Primers, 6(1), 1–2. https://doi.org/10.1038/s41572-020-0201-1 Huang, C., Huang, L., Wang, Y., Li, X., Ren, L., Gu, X., Kang, L., Guo, L., Liu, M., Zhou, X., Luo, J., Huang, Z., Tu S., Zhao, Y., Chen, L., Xu, D., Li, Y., Li, C., & Peng, L., … Cao, B. (2021). 6-month consequences of COVID-19 in patients discharged from hospital: A cohort study. The Lancet, 397(10270), 220–232. https://doi.org/10.1016/S0140-6736(20)32656-8 Huckans, M., Hutson, L., Twamley, E., Jak, A., Kaye, J., & Storzbach, D. (2013). Efficacy of cognitive rehabilitation therapies for mild cognitive impairment (MCI) in older adults: Working toward a theoretical model and evidence-based interventions. Neuropsychology Review, 23 (1), 63–80. https://doi.org/10.1007/s11065-013-9230-9 Jackson, J. C., Hart, R. P., Gordon, S. M., Shintani, A., Truman, B., May, L., & Ely, E. W. (2003). Sixmonth neuropsychological outcome of medical intensive care unit patients. Critical Care Medicine, 31(4), 1226–1234. https://doi.org/10.1097/01.CCM.0000059996.30263.94 Jaywant, A., Vanderlind, W. M., Alexopoulos, G. S., Fridman, C. B., Perlis, R. H., & Gunning, F. M. (2021). Frequency and profile of objective cognitive deficits in hospitalized patients recovering from COVID-19. Neuropsychopharmacology, 46, 2235–2240 . https://doi.org/10. 1038/s41386-021-00978-8 Kanmogne, G. D., Fonsah, J. Y., Umlauf, A., Moul, J., Doh, R. F., Kengne, A. M., Tang, B., Tagny, C. T., Nchindap, E., Kenmogne, L., Franklin, D., Njamnshi, D. M., Mbanya, D., Njamnshi, A. K., & Heaton, R. K. (2020). Attention/working memory, learning and memory in adult Cameroonians: Normative data, effects of HIV infection and viral genotype. Journal of the International Neuropsychological Society, 26(6), 607–623. https://doi.org/10.1017/ S1355617720000120 Keefe, R. S., Goldberg, T. E., Harvey, P. D., Gold, J. M., Poe, M. P., & Coughenour, L. (2004). The brief assessment of cognition in schizophrenia: Reliability, sensitivity, and comparison with a standard neurocognitive battery. Schizophrenia Research, 68(2-3), 283–297. https://doi. org/10.1016/j.schres.2003.09.011 16 M. PALLADINI ET AL. Kim, E. J., Bahk, Y.-C., Oh, H., Lee, W.-H., Lee, J.-S., & Choi, K.-H. (2018). Current status of cognitive remediation for psychiatric disorders: A review. Frontiers in Psychiatry, 9(461). https:// doi.org/10.3389/fpsyt.2018.00461 Lleó, A., & Alcolea, D. (2020). The cognitive aftermath of COVID-19. Brain Communications, 2 (2), Article fcaa072. https://doi.org/10.1093/braincomms/fcaa072 Mantovani, E., Zucchella, C., Bottiroli, S., Federico, A., Giugno, R., Sandrini, G., Chiamulera, C., Tamburin, S., (2020). Telemedicine and virtual reality for cognitive rehabilitation: A roadmap for the COVID-19 pandemic. Frontiers in Neurology, 11(926). https://doi.org/10. 3389/fneur.2020.00926 Mazza, M. G., De Lorenzo, R., Conte, C., Poletti, S., Vai, B., Bollettini, I., Melloni, E. M. T., Furlan, R., Ciceri, F., Rovere-Querini, P., & Benedetti, F. (2020). Anxiety and depression in COVID-19 survivors: Role of inflammatory and clinical predictors. Brain, Behavior, and Immunity, 89, 594– 600. https://doi.org/10.1016/j.bbi.2020.07.037 Mazza, M. G., Palladini, M., De Lorenzo, R., Magnaghi, C., Poletti, S., Furlan, R., Ciceri, F., RovereQuerini, P., Benedetti, F., (2021). Persistent psychopathology and neurocognitive impairment in COVID-19 survivors: Effect of inflammatory biomarkers at three-month followup. Brain, Behavior, and Immunity, 94, 138–147. https://doi.org/10.1016/j.bbi.2021.02.021 McCullagh, P., & Nelder, J. (1989). Generalized linear models II. Chapman and Hall. McIntyre, R. S., Cha, D. S., Soczynska, J. K., Woldeyohannes, H. O., Gallaugher, L. A., Kudlow, P., Alsuwaidan, M., & Baskaran, A. (2013). Cognitive deficits and functional outcomes in major depressive disorder: Determinants, substrates, and treatment interventions. Depression and Anxiety, 30(6), 515–527. https://doi.org/10.1002/da.22063 Medalia, A., & Bowie, C. R. (2016). Cognitive remediation to improve functional outcomes. Oxford University Press. Mendez, R., Balanzá-Martínez, V., Luperdi, S. C., Estrada, I., Latorre, A., González-Jiménez, P., Feced, L., Bouzas, L., Yepez, K., Ferrando, A., (2021). Short-term neuropsychiatric outcomes and quality of life in COVID-19 survivors. Journal of Internal Medicine, 290(3), 621–631. 10. 1111/joim.13262 Miskowiak, K., Johnsen, S., Sattler, S., Nielsen, S., Kunalan, K., Rungby, J., Lapperre, T., & Porsberg, C. M. (2021). Cognitive impairments four months after COVID-19 hospital discharge: Pattern, severity and association with illness variables. European Neuropsychopharmacology, 46, 39– 48. https://doi.org/10.1016/j.euroneuro.2021.03.019 Muthukrishnan, H. (2020). The cognitive impact of coronavirus. The Journal of Science and Medicine, 3(Special Issue), 1–3. https://doi.org/10.37714/josam.v3i0.61 Nalbandian, A., Sehgal, K., Gupta, A., Madhavan, M. V., McGroder, C., Stevens, J. S., Cook, J. R., Nordvig, A. S., Shalev, D., Sehrawat, T. S., Ahluwalia, N., Bikdeli, B., Dietz, D., DerNigoghossian, C., Liyanage-Don, N., Rosner, G. F., Bernstein, E. J., Mohan, S., Beckley, A. A., … Wan, E. Y. (2021). Post-acute COVID-19 syndrome. Nature Medicine, 27(4), 601–615. https://doi.org/10.1038/s41591-021-01283-z Nie, X.-D., Wang, Q., Wang, M.-N., Zhao, S., Liu, L., Zhu, Y.-L., Chen, H., (2021). Anxiety and depression and its correlates in patients with coronavirus disease 2019 in Wuhan. International Journal of Psychiatry in Clinical Practice, 25(2), 109–114. https://doi.org/10. 1080/13651501.2020.1791345 Pandharipande, P. P., Girard, T. D., Jackson, J. C., Morandi, A., Thompson, J. L., Pun, B. T., Brummel, N. E., Hughes, C. G., Vasilevskis, E. E., Shintani, A. K., Moons, K. G., Geevarghese, S. K., Canonico, A., Hopkins, R. O., Bernard, G. R., Dittus, R. S., & Ely, E. W. (2013). Long-term cognitive impairment after critical illness. New England Journal of Medicine, 369(14), 1306–1316. https://doi.org/10.1056/NEJMoa1301372 Poletti, S., Palladini, M., Mazza, M. G., De Lorenzo, R., COVID-19 BioB Outpatient Clinic Study group, Furlan, R., Ciceri, F., Rovere-Querini, P., Benedetti, F., (2021). Long-term NEUROPSYCHOLOGICAL REHABILITATION 17 consequences of COVID-19 on cognitive functioning up to 6 months after discharge: Role of depression and impact on quality of life. European Archives of Psychiatry and Clinical Neuroscience, 1–10. https://doi.org/10.1007/s00406-021-01346-9 Porter, R. J., Bowie, C. R., Jordan, J., & Malhi, G. S. (2013). Cognitive remediation as a treatment for major depression: A rationale, review of evidence and recommendations for future research. Australian New Zealand Journal of Psychiatry, 47(12), 1165–1175. https://doi. org/10.1177/0004867413502090 Rabinovitz, B., Jaywant, A., & Fridman, C. B. (2020). Neuropsychological functioning in severe acute respiratory disorders caused by the coronavirus: Implications for the current COVID19 pandemic. The Clinical Neuropsychologist, 34(7-8), 1453–1479. https://doi.org/10.1080/ 13854046.2020.1803408 Rock, P., Roiser, J., Riedel, W., & Blackwell, A. (2014). Cognitive impairment in depression: A systematic review and meta-analysis. Psychological Medicine, 44(10), 2029–2040. https:// doi.org/10.1017/S0033291713002535 Rodakowski, J., Saghafi, E., Butters, M. A., & Skidmore, E. R. (2015). Non-pharmacological interventions for adults with mild cognitive impairment and early stage dementia: An updated scoping review. Molecular Aspects of Medicine, 43, 38–53. https://doi.org/10.1016/j.mam. 2015.06.003 Sachdev, P. S., Blacker, D., Blazer, D. G., Ganguli, M., Jeste, D. V., Paulsen, J. S., & Petersen, R. C. (2014). Classifying neurocognitive disorders: The DSM-5 approach. Nature Reviews Neurology, 10(11), 634–642. https://doi.org/10.1038/nrneurol.2014.181 Sasannejad, C., Ely, E. W., & Lahiri, S. (2019). Long-term cognitive impairment after acute respiratory distress syndrome: A review of clinical impact and pathophysiological mechanisms. Critical Care, 23(1), 1–12. https://doi.org/10.1186/s13054-019-2626-z Schneider, I., Schmitgen, M. M., Bach, C., Listunova, L., Kienzle, J., Sambataro, F., Depping, M. S., Kubera, K. M., Roesch-Ely, D, Wolf, R. C., (2020). Cognitive remediation therapy modulates intrinsic neural activity in patients with major depression, 50(14), 2335–2345. https://doi. org/10.1017/S003329171900240X Sepehry, A. A. (2014). Self-rating depression scale (SDS). In A. C. Michalos (Ed.), Encyclopedia of quality of life and well-being research (pp. 5790–5798). Springer. Sheng, B., Cheng, S. K. W., Lau, K. K., Li, H. L., & Chan, E. L. Y. (2005). The effects of disease severity, use of corticosteroids and social factors on neuropsychiatric complaints in severe acute respiratory syndrome (SARS) patients at acute and convalescent phases. European Psychiatry, 20(3), 236–242. https://doi.org/10.1016/j.eurpsy.2004.06.023 Skevington, S. M., Lotfy, M., & O’Connell, K. A. (2004). The World Health Organization’s WHOQOL-BREF quality of life assessment: Psychometric properties and results of the international field trial. A report from the WHOQOL group. Quality of Life Research: An International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation, 13(2), 299–310. Taquet, M., Geddes, J. R., Husain, M., Luciano, S., & Harrison, P. J. (2021). 6-month neurological and psychiatric outcomes in 236 379 survivors of COVID-19: A retrospective cohort study using electronic health records. The Lancet Psychiatry, 8(5), 416–427. https://doi.org/10. 1016/S2215-0366(21)00084-5 Taribagil, P., Creer, D., & Tahir, H. (2021). ‘Long COVID’ syndrome. BMJ Case Reports CP, 14(4), Article e241485. https://doi.org/10.1136/bcr-2020-241485 Vance, D. E., Fazeli, P. L., Ross, L. A., Wadley, V. G., & Ball, K. K. (2012). Speed of processing training with middle-age and older adults with HIV: A pilot study. Journal of the Association of Nurses in AIDS Care, 23(6), 500–510. https://doi.org/10.1016/j.jana.2012.01.005 Varatharaj, A., Thomas, N., Ellul, M. A., Davies, N. W., Pollak, T. A., Tenorio, E. L., Sultan, M., Easton, A., Breen, G., Zandi, M., Coles, J. P., Manji, H., Al-Shahi Salman, R., Menon, D. K., 18 M. PALLADINI ET AL. Nicholson, T. R., Benjamin, L. A., Carson, A., Smith, C., Turner, M. R., Solomon, T., … Plant, G. (2020). Neurological and neuropsychiatric complications of COVID-19 in 153 patients: A UK-wide surveillance study. The Lancet Psychiatry, 7(10), 875–882. https://doi.org/10. 1016/S2215-0366(20)30287-X WHO. (2021). COVID-19 Dashboard. World Health Organization. Wilson, J. E., Collar, E. M., Kiehl, A. L., Lee, H., Merzenich, M., Ely, E. W., & Jackson, J. (2018). Computerized cognitive rehabilitation in intensive care unit survivors: Returning to everyday tasks using rehabilitation networks–computerized cognitive rehabilitation pilot investigation. Annals of the American Thoracic Society, 15(7), 887–891. https://doi.org/10.1513/ AnnalsATS.201709-744RL Woo, M. S., Malsy, J., Pöttgen, J., Seddiq Zai, S., Ufer, F., Hadjilaou, A., Schmiedel, S., Addo, M. M., Gerloff, C., Heesen, C., Schulze Zur Wiesch, J., & Friese, M. A. (2020). Frequent neurocognitive deficits after recovery from mild COVID-19. Brain Communications, 2(2), Article fcaa205. https://doi.org/10.1093/braincomms/fcaa205 World Health Organization. (2021). A clinical case definition of post COVID-19 condition by a Delphi consensus. Yuan, B., Li, W., Liu, H., Cai, X., Song, S., Zhao, J., Hu, X., Li, Z., Chen, Y., Zhang, K., Liu, Z., Peng, J., Wang, C., Wang, J., & An, Y. (2020). Correlation between immune response and selfreported depression during convalescence from COVID-19. Brain, Behavior, and Immunity, 88, 39–43. https://doi.org/10.1016/j.bbi.2020.05.062 Zhou, H., Lu, S., Chen, J., Wei, N., Wang, D., Lyu, H., Shi, C, & Hu, S. (2020). The landscape of cognitive function in recovered COVID-19 patients. Journal of Psychiatric Research, 129, 98–102. https://doi.org/10.1016/j.jpsychires.2020.06.022 Zung, W. W. (1965). A self-rating depression scale. Archives of General Psychiatry, 12(1), 63–70. https://doi.org/10.1001/archpsyc.1965.01720310065008