Gastroenterological and hepatic manifestations of patients with COVID-19, prevalence, mortality by country, and intensive care admission rate: systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND AND AIMS: Patients infected with the SARS-CoV-2 usually report fever and respiratory symptoms. However, multiple gastrointestinal (GI) manifestations such as diarrhoea and abdominal pain have been described. The aim of this study was to evaluate the prevalence of GI symptoms, elevated liver enzymes and mortality of patients with COVID-19. METHODS: A systematic review and meta-analysis of published studies that included a cohort of patients infected with SARS-CoV-2 were performed from 1 December 2019 to 15 December 2020. Data were collected by conducting a literature search using PubMed, Embase, Scopus, and Cochrane according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We analysed pooled data on the prevalence of individual GI symptoms and elevated liver enzymes and performed subanalyses to investigate the relationship between GI symptoms/elevated liver enzymes, geographical location, mortality, and intensive care unit (ICU) admission. RESULTS: The available data of 78 798 patients positive for SARS-CoV-2 from 158 studies were included in our analysis. The most frequent manifestations were diarrhoea (16.5%, 95% CI 14.2% to 18.4%), nausea (9.7%, 95% CI 9.0% to 13.2%) and elevated liver enzymes (5.6%, 95% CI 4.2% to 9.1%). The overall mortality and GI mortality were 23.5% (95% CI 21.2% to 26.1%) and 3.5% (95% CI 3.1% to 6.2%), respectively. Subgroup analysis showed non-statistically significant associations between GI symptoms/elevated liver enzymes and ICU admissions (OR=1.01, 95% CI 0.55 to 1.83). The GI mortality was 0.9% (95% CI 0.5% to 2.2%) in China and 10.8% (95% CI 7.8% to 11.3%) in the USA. CONCLUSION: GI symptoms/elevated liver enzymes are common in patients with COVID-19. Our subanalyses showed that the presence of GI symptoms/elevated liver enzymes does not appear to affect mortality or ICU admission rate. Furthermore, the proportion of GI mortality among patients infected with SARS-CoV-2 varied based on geographical location.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".