Renal complications in COVID-19: a systematic review and meta-analysis
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: Emerging data suggest that coronavirus disease 2019 (COVID-19) has extrapulmonary manifestations but its renal manifestations are not clearly defined. We aimed to evaluate renal complications of COVID-19 and their incidence using a systematic meta-analysis. DESIGN: Observational studies reporting renal complications in COVID-19 patients were sought from MEDLINE, Embase and the Cochrane Library from 2019 to June 2020. The nine-star Newcastle-Ottawa Scale was used to evaluate methodological quality. Incidence with 95% confidence intervals (CIs) were pooled using random-effects models. RESULTS: We included 22 observational cohort studies comprising of 17,391 COVID-19 patients. Quality scores of studies ranged from 4 to 6. The pooled prevalence of pre-existing chronic kidney disease (CKD) and end-stage kidney disease was 5.2% (2.8-8.1) and 2.3% (1.8-2.8), respectively. The pooled incidence over follow-up of 2-28 days was 12.5% (10.1-15.0) for electrolyte disturbance (e.g. hyperkalaemia), 11.0% (7.4-15.1) for acute kidney injury (AKI) and 6.8% (1.0-17.0) for renal replacement therapy (RRT). In subgroup analyses, there was a higher incidence of AKI in US populations and groups with higher prevalence of pre-existing CKD. CONCLUSIONS: PROSPERO 2020: CRD42020186873 KEY MESSAGES COVID-19 affects multiple organs apart from the respiratory system; however, its renal manifestations are not clearly defined. In this systematic meta-analysis of 22 observational cohort studies, the prevalence of pre-existing chronic kidney disease (CKD) in COVID-19 patients was 5.2%. The most frequent renal complication was electrolyte disturbance (particularly hyperkalaemia) with an incidence of 12.5% followed by acute kidney injury (AKI) with an incidence of 11.0%; US populations and groups with higher prevalence of CKD had higher incidence of AKI.
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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 | 0.005 | 0.176 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.022 | 0.003 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it