Association of digestive symptoms with severity and mortality of COVID-19
Bibliographic record
Abstract
BACKGROUND: Gastrointestinal manifestations are common in patients with COVID-19, but the association between specific digestive symptoms and COVID-19 prognosis remains unclear. This study aims to assess whether digestive symptoms are associated with COVID-19 severity and mortality. METHODS: We will search PubMed, Embase, Web of Science, and the Cochrane Central Register of Controlled Trials up to September, 2020, to identify studies that compared the prevalence of at least one specific digestive symptom between severe and non-severe COVID-19 patients or between non-survivors and survivors. Two independent reviewers will assess the risk of bias of the included cohort studies using the modified Newcastle-Ottawa Scale. Meta-analyses will be conducted to estimate the pooled prevalence of individual symptoms using the inverse variance method with the random-effects model. We will conduct subgroup analyses, sensitivity analyses, and meta-regression analyses to explore the sources of heterogeneity. The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach will be used to assess the quality of the evidence. RESULTS: The results of this study will be published in a peer-reviewed journal. CONCLUSION: Our meta-analysis will comprehensively evaluate the association between different digestive symptoms and the severity and mortality of patients infected with COVID-19. This study will provide evidence to help determine whether special protective measures and treatment options are needed for patients with digestive system comorbidities during the COVID-19 pandemic. INPLASY REGISTRATION NUMBER: INPLASY202090055.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 0.073 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".