Human Immunodeficiency Virus (HIV) and outcomes from coronavirus disease 2019 (COVID-19) pneumonia: A Meta-Analysis and Meta-Regression
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
AIDS Research and Human Retroviruses officially retracts the Instant Online/Just Accepted version of the article entitled, "Human Immunodeficiency Virus (HIV) and Outcomes from Coronavirus Disease 2019 (COVID-19) Pneumonia: A Meta-Analysis and Meta-Regression" (epub 27 Jan 2021; doi.org/10.1089/AID.2020.0307). A technical issue caused the accepted version to post online before all plagiarism checks were finalized. Those checks determined that there was too much duplication from previously published sources which prevented the continuance to final publication. The technical issue that caused the premature posting has since been corrected. AIDS Research and Human Retroviruses and its Publisher are committed to upholding the standards of scientific publishing and the community it serves. BACKGROUND: The number of positive and death cases from coronavirus disease 2019 (COVID-19) is still increasing until now. One of the most prone individuals, even in normal situations is patients with HIV. Currently, the evidence regarding the link between HIV and COVID-19 is still limited and conflicting. This study aims to analyze the relationship between HIV and poor outcomes of COVID-19 infection. METHODS: We systematically searched the PubMed and Europe PMC database using specific keywords related to our aims until January 12th, 2021. All articles published on COVID-19 and HIV were retrieved. The quality of the study was assessed using the Newcastle Ottawa Scale (NOS) tool for observational studies. Statistical analysis was done using Review Manager 5.4 and Comprehensive Meta-Analysis version 3 software. RESULTS: A total of 38 studies with 18,271,025 COVID-19 patients were included in this meta-analysis. This meta-analysis showed that HIV was not associated with composite poor outcome [OR 1.08 (95% CI 0.95 - 1.23), p = 0.26, I2 = 68%, random-effect modelling]. Meta-regression showed that the association with composite poor outcome was influenced by hypertension (p < 0.00001) and diabetes (p = 0.0007). Subgroup analysis which involves only studies from African region showed that HIV was associated with composite poor outcomes [OR 1.11 (95% CI 1.03 - 1.21), p = 0.01, I2 = 0%, random-effect modelling]. CONCLUSIONS: Patients with HIV should still be considered as a population for whom precautions are needed to prevent the COVID-19. The availability of antiretroviral therapy should be ensured.
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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 | 0.015 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.045 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".