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Record W4281776742 · doi:10.1089/aid.2021.0155

The Impact of Frailty on All-Cause Mortality in Patients with HIV Infection: A Systematic Review and Meta-Analysis

2022· review· en· W4281776742 on OpenAlexaboutno aff
Shanshan Liu, Qiao Yan, Yan Jiang, Mengmeng Xiao, Jing Zhao, Ying Wang, Rong Deng, Cong Wang, Zhibo Yang

Bibliographic record

VenueAIDS Research and Human Retroviruses · 2022
Typereview
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHazard ratioMeta-analysisCohort studyCochrane LibraryCohortProspective cohort studyInternal medicineSystematic reviewConfidence intervalMEDLINECause of deathDisease

Abstract

fetched live from OpenAlex

The aim of this study was to conduct a systematic review and meta-analysis of cohort studies that have examined the association between frailty and all-cause mortality in patients with HIV infection. We searched Embase, Medline through the Ovid interface, PubMed, Cochrane Library, and Web of Science to identify potential studies. Cohort studies of death outcomes in HIV patients under debilitating conditions were included and other ineligible or inadequate data were excluded. Data related to all-cause mortality in patients with HIV were extracted. The quality of the included studies was assessed using the Newcastle–Ottawa Scale for cohort studies. Hazard ratios (HRs) and their 95% confidence intervals (CIs) were pooled to estimate the association between frailty and all-cause mortality using Stata, version 12.0. We identified 845 unduplicated citations. Of these, six cohort studies were eligible for inclusion in the review after applying our inclusion and exclusion criteria. Pooled results demonstrated that patients with HIV experiencing frailty were at an increased risk of all-cause mortality (pooled HR = 2.69, 95% CI = 1.83–3.97, p < .001) compared with those without frailty. Frailty was significantly associated with an increased risk of all-cause mortality among patients with HIV, indicating that frailty is an important predictor of adverse clinical outcomes. Therefore, more attention should be paid to screen patients with HIV for frailty and adopt appropriate interventions and personalized treatment plans to prevent the occurrence of adverse events. However, these results need to be validated in further prospective cohort studies in ethnically or geographically diverse populations.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.492
Threshold uncertainty score0.568

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.002
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 head0.366
GPT teacher head0.524
Teacher spread0.158 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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
Published2022
Admission routes1
Has abstractyes

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