Hypertension as a prognostic factor in the prediction of mortality in patients with COVID-19: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background The coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) brought the majority of the world into a halt when it started to spread outside the virus epicenter in Wuhan, China. With the alarming increase in the number of cases and deaths worldwide, the possible risk factors should be determined in order to have a general idea on those who are more susceptible to have this disease. Hypertension, being one of the world's leading causes of noncommunicable diseases, was identified by the CDC to be one of underlying medical conditions that might pose an increased risk for severe illness from COVID-19. Objective The aim of this study is to determine the predictive value of hypertension as a comorbidity in COVID-19 mortality. Materials and methods Participants included all patients clinically diagnosed with COVID-19, and have hypertension as their pre-existing medical condition. Studies were selected based on study design, participants, exposure, outcome, timing, setting and language. The following databases were searched from June to August 2020 for case control and cohort studies on MEDLINE and CINAHL, ScienceDirect, Clinical Key, OVID database, Wiley Online library, and UpToDate. The criteria for evaluation of risk of bias were based on the selection bias, comparability bias and outcome bias. All information gathered were collated and evaluated using the Newcastle-Ottawa Quality Assessment Scale and CEBM. Results Individual studies all showed a significant relationship between hypertension and mortality in COVID-19 patients. Odds ratio ranging from 1.75 to 28.88, and hazard ratio ranging from 1.49 to 3.32 are present in the studies. For the data analysis, Mantel Haenszel method and random effects model was used for case control studies with odds ratio as effect measure; while Inverse variance method and fixed model was used for cohort studies with hazard ratio as effect measure. Both groups showed significant positive association between mortality and hypertension as a prognostic factor. Overall odds ratio is 5.25 (2.42–11.40) with a p value of <0.ehab724.23931, and the pooled hazard ratio is 2.21 (1.75–2.80) with a p value of <0.ehab724.23931. This shows that there is an increased risk of mortality among COVID-19 patients with hypertension as a comorbid condition. Conclusions Hypertension as a comorbid condition is a prognostic factor in the prediction of mortality in hospitalized COVID-19 patients. The ten included studies showed that there is a significant positive association suggesting an increased risk of mortality in COVID-19 patients with hypertension. Funding Acknowledgement Type of funding sources: Other. Main funding source(s): University of the East Ramon Magsaysay Memorial Medical Center College of Medicine Forest Plot HR Hypertension COVID
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.031 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".