MétaCan
Menu
Back to cohort
Record W4405492129 · doi:10.1016/j.eclinm.2024.102993

Prevalence of post-acute sequelae of SARS-CoV-2 infection in people living with HIV: a systematic review with meta-analysis

2024· review· en· W4405492129 on OpenAlexafffund
Dimitra V Pouliopoulou, Nicole Billias, Joy C. MacDermid, Erin Miller, Kelly K. O’Brien, Kieran L. Quinn, Monali S. Malvankar‐Mehta, Tiago Pereira, Angela M. Cheung, Fahad Razak, Saverio Stranges, Pavlos Bobos

Bibliographic record

VenueEClinicalMedicine · 2024
Typereview
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsUniversity Health NetworkSinai Health SystemToronto Rehabilitation InstituteUniversity of TorontoWestern University
FundersCanadian Institutes of Health ResearchCanada Research ChairsForeign and Commonwealth OfficeArthritis Society
KeywordsMedicineMeta-analysisSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Human immunodeficiency virus (HIV)Coronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSystematic reviewIntensive care medicineSars virusMEDLINEVirologyInternal medicineDisease

Abstract

fetched live from OpenAlex

Background Given the chronic immune activation and inflammatory milieu associated with Long COVID and HIV, we assessed the prevalence of Long COVID in adults living with HIV; and investigated whether adults living with HIV were associated with increased chance of developing Long COVID compared to adults living without HIV Methods In this systematic review and meta-analysis, we searched Medline, EMBASE, CINHAL, PubMed and CENTRAL from inception until June 14th, 2024, for observational studies that measured the prevalence of Long COVID in adults living with HIV and the odds of developing Long COVID following a SARS-CoV-2 infection in people living with HIV compared to people living without HIV. Reviews, case reports, randomised control trials and editorials were excluded. The search was conducted without language restrictions. We performed meta-analysis of proportions to synthesise prevalence estimates using logit transformation and a sensitivity analysis using mixed-effects logistic regression. We used random-effects meta-analyses to summarize the odds ratio (OR) of developing Long COVID in adults living with HIV compared to adults living without HIV and conducted a sensitivity analysis including only studies with covariate-adjusted estimates that was planned a-priori. We used ROBINS-E for the risk of bias assessment and GRADE to rate the certainty of evidence. We identified statistical heterogeneity using Cochran's Q test and quantified it using the I 2 statistic. For the Q test, a P < 0.10 was considered statistically significant. PROSPERO registration: CRD42024577616. Findings Our search returned 831 results, of which 8 studies (4489 participants) were deemed eligible for inclusion in the systematic review and meta-analysis. The prevalence of Long COVID in adults with HIV was 43% (95% CI: 32–54%, 8 studies; 1227 participants; low certainty, P < 0.0001). The association of HIV status with Long COVID was inconclusive, with wide confidence intervals (OR: 1.16, 95% CI: 0.58–2.29; 4 studies; 3556 participants, low certainty, P = 0.013). When the analysis was restricted to studies reporting covariate-adjusted estimates, adults living with HIV were associated with a higher odds of Long COVID than those not living with HIV (OR: 2.21, 95% CI: 1.12–4.36; 2 studies; 374 participants, low certainty, P = 0.51). Interpretation Current evidence indicates that the prevalence of Long COVID in adults living with HIV may be high, suggesting the need for increased awareness and education of healthcare providers and policy makers. Evidence on whether HIV positivity increases the risk of Long COVID is limited and inconclusive, highlighting a need for further research to clarify this potential association. Funding None.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.389
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0220.004
Bibliometrics0.0010.005
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.093
GPT teacher head0.435
Teacher spread0.342 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations6
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueEClinicalMedicineSame topicLong-Term Effects of COVID-19French-language works237,207