Background Major organ complications have been reported in patients hospitalised for COVID-19; most studies lacked controls.
Objective Examine major organ damage postdischarge among adults hospitalised for COVID-19 versus non-COVID-19 controls.
Data sources MEDLINE, Embase and Cochrane Library from 1 January 2020 to 19 May 2021.
Study eligibility criteria English language studies of adults discharged from hospital for COVID-19; reporting major organ damage. Single review of abstracts; independent dual review of full text.
Study appraisal and synthesis methods Study quality was assessed using the Joanna Briggs Institute Appraisal Checklist for Cohort Studies. Outcome data were not pooled due to heterogeneity in populations, study designs and outcome assessment methods; findings are narratively synthesised.
Results Of 124 studies in a full evidence report, 9 included non-COVID controls and are described here. Four of the nine (three USA, one UK) used large administrative databases. Four of the remaining five studies enrolled <600 COVID-19 patients. Mean or median age ranged from 49 to 70 years with 46%–94% male and 48%–78% White race; 10%–40% had been in intensive care units. Follow-up ranged from 4 weeks to 22 weeks postdischarge. Four used hospitalised controls, three non-hospitalised controls and two were unclear. Studies used various definitions of, and methods to assess, major organ damage outcomes. While the magnitude of effect differed across studies, incident cardiac, pulmonary, liver, acute and chronic kidney, stroke, diabetes, and coagulation disorders were consistently greater in adults hospitalised for COVID-19 compared with non-COVID-19 controls.
Limitations Applicability to subgroups (age, gender, COVID-19 severity, treatment, vaccination status) and non-hospitalised patients is unknown.
Conclusions and implications of key findings Postacute COVID-19 major organ damage is common and likely higher than controls. However, there is substantial uncertainty. More consistent reporting of clinical outcomes and pre-COVID health status along with careful selection of control groups are needed to address evidence gaps.
PROSPERO registration number CRD42020204788.
- STATISTICS & RESEARCH METHODS
- INFECTIOUS DISEASES
Data availability statement
All data relevant to the study are included in the article or uploaded as online supplemental information. Not applicable.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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Strengths and limitations of this study
This systematic review examines clinically relevant major organ damage following hospitalisation for COVID-19 as reported in studies with a non-COVID-19 comparator group.
We defined ‘postacute COVID-19’ as posthospital discharge; applicability of findings to non-hospitalised patients with acute COVID-19 symptoms is unclear.
Meta-analysis was inappropriate due to heterogeneity in populations, study designs and methods of outcome assessment.
COVID-19 is a viral illness that, as of 2 May 2022, was identified in over 511 million individuals (https://www.who.int/emergencies/diseases/novel-coronavirus-2019). Over 6.2 million deaths worldwide are attributed to COVID-19. In addition to the potential for severe acute pulmonary disease associated with coronavirus infections, there have been numerous reports of other major organ system manifestations and complications in patients hospitalised for COVID-19.1–12 These studies typically lacked controls without COVID-19 and it is not clear if postdischarge major organ system damage differs in patients hospitalised for COVID-19 from similar individuals without COVID-19.
Multiorgan damage13 and long-term clinical outcomes14 following infection with other coronaviruses, such as SARS and Middle East respiratory syndrome, have been previously reported. Because many COVID-19 patients are admitted to intensive care units (ICUs), outcomes similar to those observed in postintensive care syndrome or postsepsis syndrome may be long-term consequences of COVID-19.15
We assessed postacute care major organ damage prevalences in adults hospitalised for COVID-19 and determined if these differ compared with adults without COVID-19. Our review is limited to posthospital major organ damage; a subset of postacute sequelae of SARS-CoV-2 infection (https://www.nih.gov/about-nih/who-we-are/nih-director/statements/nih-launches-new-initiative-study).
This manuscript is based on a living review conducted for the Department of Veterans Affairs (VA) Evidence Synthesis Programme (ESP). The full review, now finalised, is available at: https://www.hsrd.research.va.gov/publications/esp/covid-organ-damage.cfm.
This review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses standards. For the initial ESP living review (December 2020) and first update (June 2021), we included studies of adults hospitalised for or with laboratory confirmed COVID-19. We prioritised postacute major organ damage of greatest clinical relevance. We defined postacute to include major organ damage reported at discharge or any time postdischarge. We included studies reporting relevant symptoms (such as dyspnoea), laboratory data or radiologic studies consistent with presence of a disease. We excluded studies reporting only general symptoms or studies reporting only mean/median values. For September 2021 (final) update, we reported outcomes postdischarge and limited to studies with >50 COVID-19 patients.
We focus this manuscript on major organ damage from studies with at least 50 COVID-19 cases and any non-COVID-19 controls. In all studies, cases were hospitalised for COVID-19 (ie, none were hospitalised for another condition with a subsequent positive test for SARS-CoV-2).
Data sources and searches
We searched MEDLINE, Embase and the Cochrane Library from 1 January 2019 to 19 May 2021. The search strategy (online supplemental table 1) was developed with input from expert medical librarians. We reviewed non-peer-reviewed public postings about post-COVID-19 complications for links to peer-reviewed data reports.
Consistent with rapid review methods, abstracts were reviewed by one investigator. A subset of 200 abstracts underwent dual independent review with substantial agreement between the two investigators. All articles identified as potentially eligible based on abstract review were independently reviewed by two investigators at the full-text level. Reasons for exclusion were noted. Conflicts were resolved by discussion. Inclusion and exclusion criteria are reported in table 1.
Data extraction and quality assessment
Study characteristics (location, design, funding), inclusion and exclusion criteria, baseline demographic data (age, sex, race, comorbidities), hospitalisation characteristics (COVID-19 severity, ICU admission, mechanical ventilation, length of hospital stay), length of time posthospital and outcomes were extracted by one investigator and verified by a second. Discrepancies were resolved by discussion.
We assessed study quality using the Joanna Briggs Institute Appraisal Checklist for Cohort Studies16 taking into account similarity between groups, assessment of the exposure and outcomes, adjustment for confounding factors and completeness of follow-up.
Data synthesis and analysis
Due to heterogeneity in populations, study designs and methods of outcome assessment, we were unable to pool outcomes data. We narratively synthesised the evidence.
Patient and public involvement
Neither patients nor the public were involved in this research.
Role of the funding source
This review is based on a living rapid review (final version completed) conducted for the VA ESP and funded by the Veterans Health Administration Office of Research and Development, Health Services Research and Development Service. The funding source assigned the topic but was not involved in the study design, data collection, analysis, manuscript preparation or submission.
Overview of studies
Our literature search and study selection process are depicted in figure 1. From the 124 eligible references, 9 included controls.17–25 Study inclusion and exclusion criteria, patient demographics, COVID-19 and hospitalisation characteristics are reported in online supplemental table 2.
In seven of the nine studies, controls were required to have either no positive COVID-19 test, diagnosis or hospital admission for COVID-19,19–21 23 been quarantined at home for at least 3 months prior to study enrollment,25 or been a patient in 2019 prior to COVID-19.17 24 Four studies included hospitalised controls,17 19 21 24 three included non-hospitalised controls18 23 25 and two were unclear.20 22 Six studies created matched COVID-19 and control groups, matching on age, sex, race/ethnicity, geographic location, prior patient encounters and comorbidities (online supplemental table 2).17–20 22 23 One study adjusted for demographic and comorbidity factors21 and one recruited volunteers with ‘similar demographic characteristics’.25
A total of 109 591 COVID-19 patients and 127 089 controls were enrolled. Four studies used administrative databases (three from the USA and one from the UK) with sample sizes ranging from 13 654 to 47 780 COVID-19 patients.17–20 The other five studies (two from the UK and one each from the USA, Germany and China) enrolled from 58 to 1877 COVID-19 patients.21–25 Five studies reported outcomes (online supplemental table 3) for multiple organ systems17–20 23 while four focused on a single system—cardiovascular,22 25 renal21 or haematological.24
In five studies reporting age, mean or median age ranged from 49 to 70 years.17 22 23 25 The percentage of males, reported in six studies, ranged from 46% to 94%.17–19 22–25 There were no statistically significant differences between COVID-19 and control groups for age or sex in any study.
Race was reported in five studies. In a study of US Veterans, 58% of the COVID-19 group and 73% of the seasonal influenza control group were White.17 In a UK study, 78% of the COVID-19 group and 97% of community-based controls were White.23 In a US study, 41% of the COVID-19 group and 75% of the non-COVID-19 group were White.21 In two other studies reporting race, the COVID-19 and control groups were similar.18 19
None of the large database studies reported on COVID-19 severity. Among the other five studies, one identified the hospitalised subgroup as having severe COVID-19.22 One study included only patients with moderate to severe COVID-1923 while in another, 39% were identified as severe or critical.25 The percentage of COVID-19 patients receiving invasive mechanical ventilation or extracorporeal membrane oxygenation ranged from 6% to 29% (k=3).
Study quality assessments are reported in online supplemental table 4. Only two studies recruited COVID-19 and control patients from the same populations (ie, concurrent, hospitalised patients).19 21 All but two24 25 dealt with potential confounders using matching or adjusted analyses. In most studies, the outcome of interest was a new, post-COVID-19 event. In the database studies, events were identified with International Classification of Diseases version 10 (ICD-10) codes while the smaller studies used laboratory testing, imaging or self-report. Follow-up ranged from 48 to 150 days. Most studies provided reasons for incomplete follow-up via a patient flow diagram.
Five studies provided pulmonary outcomes (online supplemental table 3).17–20 23 Two reported on baseline COPD or current smoking status with 5%–14% of COVID-19 patients (0%–12% of controls) having COPD and 8%–35% of COVID-19 patients (8%–23% of controls) being current smokers.
Three large database studies reported incident respiratory disease. A UK study reported that patients with COVID-19, at 146 days postdischarge, had significantly higher new onset respiratory disease (ICD-10 codes J00-99) (22% (6085/28 335)) compared with general population, non-hospitalised controls (0.8% (240/28 335); p<0.001).18 A US study, with over 54 000 records, reported a significantly increased odds for new onset pneumonia at 1–30 days postdischarge in the COVID-19 group versus hospitalised non-COVID controls (OR 5.5 (95% CI 4.1 to 7.5)).19 The difference was no longer statistically significant at 31–60, 61–90 and 91–120 days postdischarge. Similarly, patients with COVID-19 were more likely to have ‘respiratory failure, insufficiency or arrest’ at 0–30 days postdischarge as compared with non-COVID controls (OR 3.3 (95% CI 2.6 to 4.1)), but not at later follow-up. A US study, with over 36 000 records, reported a higher incidence of the combined outcome of ‘overall respiratory failure at 4 months after acute illness’ in the COVID-19 group (2.6%) compared with non-COVID controls (0.2%) (p<0.001).20 A higher incidence in the non-COVID-19 group was also noted for acute respiratory failure, chronic respiratory failure and interstitial lung disease.
Only one study reported pulmonary function tests and found no statistically significant difference among COVID-19 cases (n=56) and non-hospitalised, non-COVID controls (n=30) in the percentage of individuals having an abnormal (<80% predicted) forced expiratory volume in 1 s (11% COVID-19, 0.4% control; p=0.42) or forced vital capacity (13% COVID-19, 0% control; p=0.09) at 48 days postdischarge.23
Measures of dyspnoea were reported in two studies. Shortness of breath was greater in hospitalised US Veterans with COVID-19 (n=13 654) compared with historical controls hospitalised for seasonal influenza (n=13 997) (HR 1.14 (95% CI 1.04 to 1.26); excess burden per 1000 hospitalised at 6 months: 13.2 (95% CI 3.7 to 21.9)).17 In another study ‘significant breathlessness’ based on the mMRC dyspnoea scale (https://mrc.ukri.org/research/facilities-and-resources-for-researchers/mrc-scales/mrc-dyspnoea-scale-mrc-breathlessness-scale/) was reported in 36/56 (64%) COVID-19 patients compared with 3/29 (10%) non-hospitalised, non-COVID cases at 48 days postdischarge.23
Five studies reported cardiovascular outcomes (online supplemental table 3).17 18 20 22 25 Two reported presence of cardiovascular disease at baseline (3%–13% of COVID-19 patients, 5%–16% of controls) and three reported hypertension at baseline (15%–52% of COVID-19 patients, 17%–52% of controls).
Three large database studies reported diagnoses of cardiovascular disease following hospitalisation for COVID-19. The study of over 27 000 Veterans reported greater incident acute coronary disease (HR 1.3 (95% CI 1.1 to 1.5)) and heart failure (HR 1.2 (95% CI 1.03 to 1.4))) for the COVID-19 group versus historical controls hospitalised with seasonal influenza during the 6 months following hospitalisation.17
A second study from the USA, including over 36 000 individuals in COVID-19 and concurrent non-COVID control groups, reported new cardiac diagnoses over 4 months follow-up.20 Coronary disease (including myocardial infarction, acute coronary syndrome and cardiogenic shock) was reported in 1.1% of the COVID-19 group and 0.2% of controls (p<0.001). Congestive heart failure was reported in 1.5% of the COVID-19 group and 0.2% of controls (p<0.001). Myocarditis incidence was rare and the difference between groups was not statistically significant (COVID-19: 0.09%, Control: 0.01%; p=1.0).
A study from the UK reported major adverse cardiovascular events defined as heart failure, myocardial infarction, stroke and arrhythmia, during a mean of 146 days postdischarge.18 New events were reported in 2.6% (945/36 130) of the COVID-19 group and 0.5% (190/36 130) of the general population control group (p<0.001).
One smaller study used echocardiography to assess left ventricular ejection fraction at 48 days postdischarge.23 Left ventricular function was normal and comparable between the COVID-19 group and a community-dwelling, non-COVID group.
Two studies used cardiovascular MRI (CMR) to assess myocardial injury. In a study from Germany, 100 patients (33 of whom had been hospitalised) were assessed at a median of 71 days following diagnosis.22 Late gadolinium enhancement (LGE), reflecting scarring, was observed in 32% (32/100) (myocardial) and 22% (22/100) (pericardial) of the COVID-19 group. Myocardial LGE was significantly more prevalent (p<0.05) in COVID-19 patients than in healthy controls (0%) or risk factor-matched controls (17% (9/57)). Pericardial LGE was significantly more prevalent (p<0.05) in COVID-19 patients than in healthy controls (0%) but not risk factor-matched controls (14% (8/57)).
A second study assessed outcomes at a median of 48 days postdischarge. LGE (myocarditis pattern) was observed in 12% (6/52) of the COVID-19 group (moderate to severe disease) and 7% (2/28) of community-dwelling, non-COVID controls (p=0.47).
The studies also reported on presence of pericardial effusion based on CMR. The study from Germany reported pericardial effusion (>10 mm) in 20% (20/100) of COVID-19 patients, 0% of healthy controls, and 7% (4/57) of risk factor-matched controls (p<0.05 for the COVID-19 group vs each control group) at a median of 71 days following diagnosis.22 The other study reported pericardial effusion (>10 mm) in 2% (1/52) of the COVID-19 group and 0% (0/28) of community-dwelling, non-COVID controls at a median of 48 days postdischarge.23
The CMR study from Germany22 reported detectable high-sensitivity troponin T (hsTNT) (>3 pg/mL) in 71% (71/100) of the COVID-19 group, with significantly elevated hsTNT (>13.9 pg/mL) in 5% (5/100) at a median of 71 days following diagnosis. The percentage of patients with detectable hsTNT was significantly higher (p<0.05) in the COVID-19 group than in healthy (22% (11/50) or risk factor-matched controls (54% (31/57)). The second study, with a control group of non-COVID-19 community members reported no cases of abnormal troponin T in either the COVID-19 or control groups at a median of 48 days postdischarge.23
Neurologic and cognitive outcomes
The study of over 27 000 US Veterans reported an increased risk of stroke 6 months after hospitalisation for COVID-19 among individuals without a history of stroke in the past year, as compared with historical, matched controls with seasonal influenza (HR 1.30; 95% CI 1.05 to 1.60).17 Another US study reported the prevalence of new onset stroke during the 4 months posthospitalisation.20 Ischaemic and haemorrhagic stroke was reported in 1.1% of the COVID-19 group and 0.3% of matched non-COVID controls (risk difference 0.8% (95% CI 0.4 to 1.2), p<0.001).
For incident neurocognitive disorders, US Veterans hospitalised for COVID-19 had an excess burden per 1000 COVID-19 persons at 6 months of 16.2 (95% CI 10.4 to 21.2) compared with hospitalised seasonal influenza cases.17 In another database study, neurocognitive disorders, defined using the Clinical Classification Software Refined categories, were more likely in patients hospitalised with COVID-19 versus non-COVID controls (OR 1.6 (95% CI 1.2 to 2.1)) in the first 30 days after discharge but not at 60, 90, or 120 days.19
In a US database study enrolling adults age 18–65 years, newly diagnosed dementia through 120 days postacute infection was greater in the COVID-19 group compared with non-COVID controls (0.2% vs 0.03%; risk difference 0.2% (95% CI 0.7 to 0.3), p<0.001).20 In the same study, Alzheimer-type dementia was noted in 0.04% of the COVID-19 group and 0% of controls (p<0.001).
One study reported Montreal Cognitive Assessment (MoCA) scores of less than 26 (ie, cognitive impairment) in 28% of the COVID-19 group and 17% of community-based controls (p=0.30) at a median of 48 days postdischarge.23
Renal outcomes were reported by six studies (online supplemental table 3).17–21 23 A history of chronic kidney disease (CKD) at baseline, reported in two studies, was noted in 13% of patients in both the COVID-19 and the control groups in one study18 and 33% of the COVID-19 group and 35% of controls in the other.21
CKD post-COVID-19, identified by ICD-10 codes, was reported in three large database studies.17 18 20 In the study of US Veterans, the HR for a new diagnosis of CKD during the 6 months after acute infection in the COVID-19 group vs seasonal influenza controls was 1.4 (95% CI 1.1 to 1.7).17 A second US study, with data from over 36 000 individuals, reported new diagnoses of CKD (all stages) at 4 months after acute illness in 2.1% of the COVID-19 group and 0.7% of non-COVID controls (p<0.001).20 The third study, completed in the UK, included data from over 82 000 individuals and reported new onset CKD stages 3–5 in 0.6% of the COVID-19 group and 0.3% of general population controls at a mean of approximately 146 days postdischarge.18
A new diagnosis of acute kidney injury (AKI) following discharge was reported in three large database studies.17 19 20 The study of US Veterans reported an adjusted HR for AKI during the 6 months following COVID-19 infection for the COVID-19 group vs seasonal influenza controls (HR 1.2 (95% CI 1.1 to 1.4)).17 A second US study reported ORs for ‘acute and unspecified kidney failure’ versus hospitalised non-COVID-19 controls.19 ORs decreased from 1.3 (95% CI 1.0 to 1.6) at 30 days postdischarge to 0.6 (95% CI 0.4 to 0.8) at 120 days postdischarge. The third study, also from the USA, reported a new diagnosis of AKI during the 4 months after acute infection in 2.9% of the COVID-19 group and 0.5% of non-COVID controls (p<0.001).20
In a study of patients with COVID-19-associated AKI, defined as >50% increase in creatinine over baseline or 0.3 mg/dL increase over lowest level at 48 hours, and a control group with non-COVID associated AKI, the COVID-19 group demonstrated lower rates of AKI recovery post hospital discharge (HRadj 0.57 (95% CI 0.35 to 0.92); p=0.02).21
Three database studies, two from the USA17 20 and one from the UK,18 reported the presence of diabetes (online supplemental table 3). Diabetes at baseline was reported in one study (24%).18 A US study, with data from over 27 000 Veterans without a history of diabetes in the previous year, reported greater risk for diabetes in the COVID-19 group than in a matched, seasonal influenza control group (HR 1.6 (95% CI 1.4 to 1.9)).17 The excess burden per 1000 hospitalised COVID-19 patients was 21.4 (95% CI 15.1 to 26.8) at 6 months following COVID-19 infection. The second US study included over 36 000 hospitalised patients in COVID-19 and matched non-COVID-19 groups. Through 4 months after acute illness, a new clinical diagnoses of type 2 diabetes was reported in 3% of the COVID-19 group and 0.8% of controls (risk difference 2.2% (95% CI 1.4 to 3.2)).20
The UK study, with data from over 72 000 individuals (COVID-19 and matched, general population controls) reported new onset type 1 diabetes, during a mean of approximately 146 days after discharge, in 1.1% (400/36 100) of the COVID-19 group and 0.3% (125/36 100) of controls.18 Rates per 1000 person-years were 28.7 for the COVID-19 group and 8.2 for controls.
Three studies reported gastrointestinal outcomes (online supplemental table 3).17 18 20 Two database studies identified gastrointestinal disease using ICD-10 codes.17 18 The study of Veterans identified incidence of gastrointestinal disorders (eg, dysphagia) in over 27 000 individuals hospitalised for either COVID-19 or seasonal influenza.17 During 6 months follow-up, the excess burden per 1000 COVID-19 persons was 19.3 (95% CI 12.8 to 25.1). The second study, from the UK (46 395 matched pairs), identified new onset chronic liver disease over a mean follow-up of 140 days among individuals hospitalised with COVID-19 (0.2% (70/46 395)) compared with a non-hospitalised general population (0.04% (15/46 395)).18 The difference was statistically significant (p<0.001). The third study, enrolling over 18 000 matched pairs, reported liver test abnormalities at 4 months after acute illness in 3.3% of the COVID-19 group and 1.4% of the control group (p<0.001).20
Three studies reported venous thromboembolism outcomes postdischarge (online supplemental table 3).17 19 20 A US study, including data from over 54 000 individuals, reported ORs for acute pulmonary embolism (PE) versus non-COVID controls of 1.5 (95% CI 1.0 to 2.1) at 30 days postdischarge and 1.4 (95% CI 0.9 to 2.1) at 60 days. ORs at 90 and 120 days were also not statistically significant.19 Another US study, with data from over 36 000 individuals, reported PE in 1.3% of the COVID-19 group and 0.1% of the non-COVID controls through 120 days postinfection.20 Deep venous thrombosis was reported in 2.3% of the COVID-19 group and 0.3% of controls. The study of over 27 000 US Veterans observed an excess burden for PE per 1000 COVID-19 persons (vs seasonal influenza controls) of 18.3 (95% CI 15.8 to 20.3) and an HR for thromboembolism of 2.3 (95% CI 1.9 to 2.6) through 150 days postdischarge.17
The same studies reported coagulation disorders (with varying definitions of ‘coagulation’ between studies). The study of over 27 000 US Veterans reported an excess burden of coagulation (defined by ICD-10 codes, not specified) per 1000 COVID-19 persons of 14.3 (95% CI 10.1 to 17.9) compared with seasonal influenza controls.17 Another US study reported a higher risk of hypercoagulability (ICD-10 codes D68 and I82) in the COVID-19 group (3.2%) than in non-COVID controls (0.4%) during the 4 months after acute illness.20 The risk difference was 2.8% (95% CI 2.3% to 3.6%) (p<0.001). The third study, also from the USA, reported odds ratios (COVID-19 vs hospitalised non-COVID-19 controls) for the overall category of coagulation and haemorrhagic disorders.19 The ORs at 30, 60, 90 and 120 days were 1.3 (95% CI 1.0 to 1.6), 1.3 (95% CI 0.95 to 1.7), 0.65 (95% CI 0.5 to 0.9) and 0.66 (95% CI 0.5 to 0.97), respectively. It was noted that the top five coagulation and haemorrhagic disorders were ‘unspecified thrombocytopenia, other primary thrombophilia, other secondary thrombocytopenia, unspecified coagulation defect and other thrombophilia’.
Our review of COVID-19 postacute major organ damage found that incident respiratory disease may be higher in posthospitalisation COVID-19 cases as compared with non-COVID controls. Prevalence ranged from 2% to 22% in COVID-19 groups compared with less than 1% in controls. Dyspnoea was much more prevalent (64% vs 10%) and there was greater risk for dyspnoea in COVID-19 groups than in controls.
Patients with COVID-19 were also at greater risk for incident cardiovascular disease outcomes (including acute myocardial infraction, coronary disease and heart failure) compared with controls. Prevalence of new cardiovascular events ranged from approximately 1% to 3% in the COVID-19 groups and less than 1% in controls. One large database study reported that a clinical diagnosis of myocarditis based on ICD-10 codes was rare and did not differ between those with COVID-19 and controls (0.09% vs 0.01%; p=1.0). However, two small studies used MRI to assess prevalence of myocarditis based on LGE patterns. One specifically excluded individuals with active cardiac symptoms and the other did not require symptoms to proceed to MRI. LGE based ‘myocarditis’ in these two studies was much higher compared with the database report and was noted in 12% vs 7% (p=0.47) and 32 vs 17% (p<0.05) of COVID-19 patients and controls, respectively.
Among other organ systems, the prevalence of, or risk for, stroke, new-onset CKD, acute kidney injury, new-onset diabetes, incident gastrointestinal disorders and new-onset chronic liver disease was higher in COVID-19 groups than in matched controls. The incidence of dementia post-COVID-19 was low but may exceed that of non-COVID cases. The prevalence of, or risk for, coagulation and haemorrhagic disorders was higher in COVID-19 groups than in control groups though disorder definitions were unclear and varied.
Limitations of the evidence exist. Although evidence includes four large database studies with controls, most data, cited in the living review, are from small single centre convenience sample studies with poorly described populations or measures of major organ damage. Among the nine studies with controls cited in this manuscript, control groups varied. Three studies included historical controls and six included concurrent controls. In four of the concurrent control studies, control group patients were not hospitalised. Reported prevalence rates are likely highly dependent on pre-existent demographics and comorbidities of the study population, COVID-19 disease severity, the measures used to assess and define major organ damage and the timing of assessment relative to hospital discharge. Follow-up times for the nine studies with control groups ranged from 30 to 150 days; only one study reported outcomes at multiple time points post-COVID. Long-term major organ damage (ie, ≥6 months) prevalence and duration of major organ damage remain unknown. There are no data reporting on outcomes based on patient living situation prior to COVID-19 infection (ie, community dwelling vs nursing home or assisted care centres). No data exist to ascertain if outcomes differ based on treatments received for COVID-19, COVID-19 vaccination status or infection with different COVID-19 variants. Disease diagnosis relied on clinician coding rather than a standardised physiologic/laboratory value. There are also limitations of our review methods. We defined ‘postacute COVID-19’ as posthospital discharge. The applicability of these findings to non-hospitalised patients with acute COVID-19 symptoms is unclear.
We are aware of several systematic reviews reporting persistent symptoms following recovery from acute COVID-19.26–30 Fatigue, dyspnoea, chest pain, sleep disorders, cognitive impairment and difficulty concentrating are commonly reported symptoms. Our review complements these reviews by focusing on (1) patients requiring hospitalisation for laboratory-confirmed COVID-19, (2) major organ damage from all organ systems rather than symptoms and (3) controlled studies.
In conclusion, postacute COVID-19 major organ damage following hospitalisation for COVID-19 infection is common and likely higher than non-COVID controls. However, there is substantial uncertainty due to evidence limitations. More consistent reporting of clinically relevant outcomes and pre-COVID-19 health status as well as use of appropriately matched controls is needed to address evidence gaps.
Data availability statement
All data relevant to the study are included in the article or uploaded as online supplemental information. Not applicable.
Patient consent for publication
This study does not involve human participants. This study does not involve animal subjects.
Contributors Contributors: Conception/design: NG, BB, CJB, SJD, KEE, AK, MK, ACM, SR, AS, KS, JS, OV, WD-P and TJW. Acquisition, analysis or interpretation of data: NG, BB, CJB, SJD, KEE, AK, MK, ACM, SR, AS, KS, JS, OV, LM, BS, RM, KS, WD-P and TJW. First draft of the manuscript: NG and TJW. Manuscript drafting, revision, approval: NG, BB, CJB, SJD, KEE, AK, MK, ACM, SR, AS, KS, JS, OV, LM, BS, RM, KS, WD-P and TJW. Overall guarantors: NG and TJW.
Funding This work was supported by the Department of Veterans Affairs, Veterans Health Administration, Health Services Research and Development, Evidence Synthesis Programme, Grant #09-009
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
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