Influence of Novel Coronavirus COVID – 19 and HIV: A Scoping Review of Hospital Course and Symptomatology
Bibliographic record
Abstract
Abstract Background An outbreak of novel coronavirus (SARS- CoV-2) was observed on December 2019 in Wuhan, China which led to a global pandemic declared in March 2020. As a consequence, it imposed delirious consequences in patients with underlying co – morbid conditions that make them immunocompromised. The purpose of this paper is to provide an in - depth review of influence of COVID – 19 in patients with underlying HIV in terms of mortality and hospitalization. Authors also aim to provide a thorough risk analysis of hospitalization, ICU admission and mortality of PLWH and COVID-19. The secondary objective was to analyze the CD4+ count variations and outcome of COVID - 19 and to correlate if ART provided a protective role. Authors also aim to provide an evaluation of typical clinical presentation of COVID-19 in PLWH. ART is found to show activity against SARS-CoV-2 in vitro, and there is some similarity in the structure of HIV-1 gp41 and S2 proteins of SARS-CoV since they both belong to +ssRNA type. Methods We conducted a literature review using search engines namely, Cochrane, PubMed and Google Scholar. The following keywords were targeted: “COVID-19,” “SARS-CoV-2,” and “HIV.” We included case reports, case series, and cohort (retrospective and prospective) studies. We excluded clinical trials and review articles. We came across 23 articles that met the inclusion criteria. PRISMA guidelines were followed for study acquisition (Fig. 9). Results From the 23 studies, we found a total of 651 PLWH with confirmed COVID-19 (549, 91, and 11 in cohorts, case series, and case reports, respectively). The overall risk of hospital admission from pooled data of the 23 reviewed articles was 69.13% (450/651), ICU admission was 12.90% (84/651) in total infected patients, and 18.67% (84/450) among hospitalized patients. The overall case fatality rate from the 23 reviewed articles was 11.21 (73/651).A weak positive correlation was found between CD4+ counts and hospital admissions in case series and case reports, while the weak negative correlation was found in cohorts. For mortality, there was a negative weak association in the cohorts and in case series, while a weak positive was seen in case reports (Fig.7). We assessed the presenting symptoms of PLWH with COVID-19, and our review demonstrated this group does not greatly differ from the rest of the population, as their common presenting symptoms were cough, fever, and SOB. Conclusion Our results indicated that there was a high rate of hospitalization, ICU admission, and mortality among patients living with HIV and COVID-19. PLWH needs to be noted as a high-risk group for COVID-19 complications and severity. We recommend that PLWH be closely monitored by their physicians and strictly adhere to antiretroviral therapy and standard universal COVID-19 precautions.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.021 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".