Determinants of AIDS and non-AIDS related mortality among people living with HIV in Shiraz, southern Iran: a 20-year retrospective follow-up study
Bibliographic record
Abstract
BACKGROUND: Human Immunodeficiency Virus (HIV) infection has become a global concern. Determining the factors leading to death among HIV patients helps controlling Acquired Immune Deficiency Syndrome (AIDS) epidemic. Up to now, little is known about mortality and its determinants among people living with HIV in the Middle East and North Africa (MENA) region, including Iran. The purpose of this study was to assess the risk factors of AIDS-Related Mortality (ARM) and Non-AIDS-Related Mortality (NARM) among people with HIV in Iran. METHODS: This 20-year retrospective study was conducted on 1160 people with HIV whose data were collected from 1997 to 2017. The association of the study outcomes (ARM and NARM) with various study variables, including demographic status at the time of diagnosis and clinical indexes during the follow-up were examined to define the predictors of mortality among the patients. Regarding, Cox proportional hazard and competing risk models were fitted and Adjusted Hazard Ratios (AHR), Sub-distribution Hazard Ratio (SHR) and the 95% Confidence Intervals (CI) were reported. RESULTS: during the follow-up period, 391 individuals (33.7%) died with 86,375 person-years of follow-up. Of the total deaths, 251 (64.2%) and 140 (35.8%) were ARM and NARM, respectively. Rates of the mortality caused by AIDS and non-AIDS were 3.2 and 4.5 per 1000 person-months, respectively. Responding to combined Antiretroviral Treatment (cART) 6 months after initiation, receiving Pneumocystis Pneumonia (PCP) prophylaxis, and higher CD4 count at diagnosis, reduced the hazard of ARM and NARM. However, older age, late HIV diagnosis, and last HIV clinical stages increased the hazard of AIDS related to mortality. Additionally, male gender, older age, incarceration history, and last HIV clinical stages increased the non-AIDS mortality. CONCLUSIONS: Mortality caused by AIDS and non-AIDS remains high among people with HIV in Iran, particularly among males and those with late diagnosis. It seems that applying effective strategies to identify infected individuals at earlier stage of the infection, and targeting individuals with higher risk of mortality can decrease the mortality rate among HIV infected people.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".