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More Than 50 Long-Term Effects of COVID-19: A Systematic Review and Meta-Analysis.

ABSTRACT: Background. COVID-19, caused by SARS-CoV-2, can involve sequelae and other medical complications that last weeks to months after initial recovery, which has come to be called Long-COVID or COVID long-haulers. This systematic review and meta-analysis aims to identify studies assessing long-term effects of COVID-19 and estimates the prevalence of each symptom, sign, or laboratory parameter of patients at a post-COVID-19 stage. Methods . LitCOVID (PubMed and Medline) and Embase were searched by two independent researchers. All articles with original data for detecting long-term COVID-19 published before 1 ^st of January 2021 and with a minimum of 100 patients were included. For effects reported in two or more studies, meta-analyses using a random-effects model were performed using the MetaXL software to estimate the pooled prevalence with 95% CI. Heterogeneity was assessed using I ² statistics. This systematic review followed Preferred Reporting Items for Systematic Reviewers and Meta-analysis (PRISMA) guidelines, although the study protocol was not registered. Results. A total of 18,251 publications were identified, of which 15 met the inclusion criteria. The prevalence of 55 long-term effects was estimated, 21 meta-analyses were performed, and 47,910 patients were included. The follow-up time ranged from 14 to 110 days post-viral infection. The age of the study participants ranged between 17 and 87 years. It was estimated that 80% (95% CI 65-92) of the patients that were infected with SARS-CoV-2 developed one or more long-term symptoms. The five most common symptoms were fatigue (58%), headache (44%), attention disorder (27%), hair loss (25%), and dyspnea (24%). All meta-analyses showed medium (n=2) to high heterogeneity (n=13). Conclusions . In order to have a better understanding, future studies need to stratify by sex, age, previous comorbidities, the severity of COVID-19 (ranging from asymptomatic to severe), and duration of each symptom. From the clinical perspective, multi-disciplinary teams are crucial to developing preventive measures, rehabilitation techniques, and clinical management strategies with whole-patient perspectives designed to address long COVID-19 care.

SUBMITTER: Lopez-Leon S

PROVIDER: S-EPMC7941645 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:COVID-19, caused by SARS-CoV-2, can involve sequelae and other medical complications that last weeks to months after initial recovery, which has come to be called Long-COVID or COVID long-haulers. This systematic review and meta-analysis aims to identify studies assessing long-term effects of COVID-19 and estimates the prevalence of each symptom, sign, or laboratory parameter of patients at a post-COVID-19 stage. LitCOVID (PubMed and Medline) and Embase were searched by two independent researchers. All articles with original data for detecting long-term COVID-19 published before 1st of January 2021 and with a minimum of 100 patients were included. For effects reported in two or more studies, meta-analyses using a random-effects model were performed using the MetaXL software to estimate the pooled prevalence with 95% CI. Heterogeneity was assessed using I2 statistics. The Preferred Reporting Items for Systematic Reviewers and Meta-analysis (PRISMA) reporting guideline was followed. A total of 18,251 publications were identified, of which 15 met the inclusion criteria. The prevalence of 55 long-term effects was estimated, 21 meta-analyses were performed, and 47,910 patients were included. The follow-up time ranged from 15 to 110 days post-viral infection. The age of the study participants ranged between 17 and 87 years. It was estimated that 80% (95% CI 65-92) of the patients that were infected with SARS-CoV-2 developed one or more long-term symptoms. The five most common symptoms were fatigue (58%), headache (44%), attention disorder (27%), hair loss (25%), and dyspnea (24%). All meta-analyses showed medium (n=2) to high heterogeneity (n=13). In order to have a better understanding, future studies need to stratify by sex, age, previous comorbidities, severity of COVID-19 (ranging from asymptomatic to severe), and duration of each symptom. From the clinical perspective, multi-disciplinary teams are crucial to developing preventive measures, rehabilitation techniques, and clinical management strategies with whole-patient perspectives designed to address long COVID-19 care.

Project description:While ground-glass opacity, consolidation, and fibrosis in the lungs are some of the hallmarks of acute SAR-CoV-2 infection, it remains unclear whether these pulmonary radiological findings would resolve after acute symptoms have subsided. We conducted a systematic review and meta-analysis to evaluate chest computed tomography (CT) abnormalities stratified by COVID-19 disease severity and multiple timepoints post-infection. PubMed/MEDLINE was searched for relevant articles until 23 May 2023. Studies with COVID-19-recovered patients and follow-up chest CT at least 12 months post-infection were included. CT findings were evaluated at short-term (1-6 months) and long-term (12-24 months) follow-ups and by disease severity (severe and non-severe). A generalized linear mixed-effects model with random effects was used to estimate event rates for CT findings. A total of 2517 studies were identified, of which 43 met the inclusion (N = 8858 patients). Fibrotic-like changes had the highest event rate at short-term (0.44 [0.3-0.59]) and long-term (0.38 [0.23-0.56]) follow-ups. A meta-regression showed that over time the event rates decreased for any abnormality (β = -0.137, p = 0.002), ground-glass opacities (β = -0.169, p < 0.001), increased for honeycombing (β = 0.075, p = 0.03), and did not change for fibrotic-like changes, bronchiectasis, reticulation, and interlobular septal thickening (p > 0.05 for all). The severe subgroup had significantly higher rates of any abnormalities (p < 0.001), bronchiectasis (p = 0.02), fibrotic-like changes (p = 0.03), and reticulation (p < 0.001) at long-term follow-ups when compared to the non-severe subgroup. In conclusion, significant CT abnormalities remained up to 2 years post-COVID-19, especially in patients with severe disease. Long-lasting pulmonary abnormalities post-SARS-CoV-2 infection signal a future public health concern, necessitating extended monitoring, rehabilitation, survivor support, vaccination, and ongoing research for targeted therapies.

Project description:IntroductionPrior reviews synthesized findings of studies on long-term cardiac complications of COVID-19. However, the reporting and methodological quality of these studies has not been systematically evaluated. Here, we conducted a systematic review and meta-analysis on long-term cardiac complications of COVID-19 and examined patterns of reported findings by study quality and characteristics.MethodsWe searched for studies examining long-term cardiac complications of COVID-19 that persisted for 4 weeks and over. A customized Newcastle-Ottawa scale (NOS) was used to evaluate the quality of included studies. Meta-analysis was performed to generate prevalence estimates of long-term cardiac complications across studies. Stratified analyses were further conducted to examine the prevalence of each complication by study quality and characteristics. The GRADE approach was used to determine the level of evidence for complications included in the meta-analysis.ResultsA total number of 150 studies describing 57 long-term cardiac complications were included in this review, and 137 studies reporting 17 complications were included in the meta-analysis. Only 25.3% (n = 38) of studies were of high quality based on the NOS quality assessment. Chest pain and arrhythmia were the most widely examined long-term complications. When disregarding study quality and characteristics, summary prevalence estimates for chest and arrhythmia were 9.79% (95% CI 7.24-13.11) and 8.22% (95% CI 6.46-10.40), respectively. However, stratified analyses showed that studies with low-quality scores, small sample sizes, unsystematic sampling methods, and cross-sectional design were more likely to report a higher prevalence of complications. For example, the prevalence of chest pain was 22.17% (95% CI 14.40-32.55), 11.08% (95% CI 8.65-14.09), and 3.89% (95% CI 2.49-6.03) in studies of low, medium, and high quality, respectively. Similar patterns were observed for arrhythmia and other less examined long-term cardiac complications.ConclusionThere is a wide spectrum of long-term cardiac complications of COVID-19. Reported findings from previous studies are strongly related to study quality, sample sizes, sampling methods, and designs, underscoring the need for high-quality epidemiologic studies to characterize these complications and understand their etiology.

Project description:BackgroundThe aim of this study was to systematically synthesise the global evidence on the prevalence of persistent symptoms in a general post COVID-19 population.MethodsA systematic literature search was conducted using multiple electronic databases (MEDLINE and The Cochrane Library, Scopus, CINAHL, and medRxiv) until January 2022. Studies with at least 100 people with confirmed or self-reported COVID-19 symptoms at ≥28 days following infection onset were included. Patient-reported outcome measures and clinical investigations were both assessed. Results were analysed descriptively, and meta-analyses were conducted to derive prevalence estimates. This study was pre-registered (PROSPERO-ID: CRD42021238247).Findings194 studies totalling 735,006 participants were included, with five studies conducted in those <18 years of age. Most studies were conducted in Europe (n = 106) or Asia (n = 49), and the time to follow-up ranged from ≥28 days to 387 days. 122 studies reported data on hospitalised patients, 18 on non-hospitalised, and 54 on hospitalised and non-hospitalised combined (mixed). On average, at least 45% of COVID-19 survivors, regardless of hospitalisation status, went on to experience at least one unresolved symptom (mean follow-up 126 days). Fatigue was frequently reported across hospitalised (28.4%; 95% CI 24.7%-32.5%), non-hospitalised (34.8%; 95% CI 17.6%-57.2%), and mixed (25.2%; 95% CI 17.7%-34.6%) cohorts. Amongst the hospitalised cohort, abnormal CT patterns/x-rays were frequently reported (45.3%; 95% CI 35.3%-55.7%), alongside ground glass opacification (41.1%; 95% CI 25.7%-58.5%), and impaired diffusion capacity for carbon monoxide (31.7%; 95% CI 25.8%-3.2%).InterpretationOur work shows that 45% of COVID-19 survivors, regardless of hospitalisation status, were experiencing a range of unresolved symptoms at ∼ 4 months. Current understanding is limited by heterogeneous study design, follow-up durations, and measurement methods. Definition of subtypes of Long Covid is unclear, subsequently hampering effective treatment/management strategies.FundingNo funding.

Project description:Background/objectivesThe coronavirus disease 2019 (COVID-19) pandemic has taken a disproportionate toll on long-term care facility residents and staff. Our objective was to review the empirical evidence on facility characteristics associated with COVID-19 cases and deaths.DesignSystematic review.SettingLong-term care facilities (nursing homes and assisted living communities).ParticipantsThirty-six empirical studies of factors associated with COVID-19 cases and deaths in long-term care facilities published between January 1, 2020 and June 15, 2021.MeasurementsOutcomes included the probability of at least one case or death (or other defined threshold); numbers of cases and deaths, measured variably.ResultsLarger, more rigorous studies were fairly consistent in their assessment of risk factors for COVID-19 outcomes in long-term care facilities. Larger bed size and location in an area with high COVID-19 prevalence were the strongest and most consistent predictors of facilities having more COVID-19 cases and deaths. Outcomes varied by facility racial composition, differences that were partially explained by facility size and community COVID-19 prevalence. More staff members were associated with a higher probability of any outbreak; however, in facilities with known cases, higher staffing was associated with fewer deaths. Other characteristics, such as Nursing Home Compare 5-star ratings, ownership, and prior infection control citations, did not have consistent associations with COVID-19 outcomes.ConclusionGiven the importance of community COVID-19 prevalence and facility size, studies that failed to control for these factors were likely confounded. Better control of community COVID-19 spread would have been critical for mitigating much of the morbidity and mortality long-term care residents and staff experienced during the pandemic. Traditional quality measures such as Nursing Home Compare 5-Star ratings and past deficiencies were not consistent indicators of pandemic preparedness, likely because COVID-19 presented a novel problem requiring extensive adaptation by both long-term care providers and policymakers.

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More Than 50 Long-Term Effects of COVID-19: A Systematic Review and Meta-Analysis.

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