Evidence map›Paper›PMID 41959659›Full record

ArticleOpen forum infectious diseases2026

Data-driven Modeling of Long-term CD4 Cell Recovery Trajectories Under Modern Antiretroviral Therapy in People Living With HIV.

You Ge, Chunqin Bai, Anni Liu, Zheng Qian, Ziyao Liu, Chenyu Ma, Jinjin Yang, Zhixiang Dai, Kai Wang, YuanYuan Xu and 4 more

Abstract read
In one paragraph

Article in Open forum infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

You GeDepartment of Infectious Diseases, Nanjing Public Health Medical Center, the Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing, China.ORCID https://orcid.org/0000-0003-4497-7916
Chunqin BaiDepartment of Infectious Diseases, Nanjing Public Health Medical Center, the Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing, China.
Anni LiuDepartment of Infectious Diseases, Nanjing Public Health Medical Center, the Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing, China.
Zheng QianDepartment of Infectious Diseases, Nanjing Public Health Medical Center, the Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing, China.
Ziyao LiuSchool of Public Health, Nanjing Medical University, Nanjing, China.
Chenyu MaSchool of Public Health, Nanjing Medical University, Nanjing, China.
Jinjin YangSchool of Public Health, Nanjing Medical University, Nanjing, China.
Zhixiang DaiSchool of Public Health, Nanjing Medical University, Nanjing, China.
Kai WangSchool of Public Health, Nanjing Medical University, Nanjing, China.
YuanYuan XuDepartment of AIDS/STD Control and Prevention, Nanjing Municipal Central for Disease Control and Prevention, Nanjing, China.
Hongxia WeiDepartment of Infectious Diseases, Nanjing Public Health Medical Center, the Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing, China.
Zhengping ZhuDepartment of AIDS/STD Control and Prevention, Nanjing Municipal Central for Disease Control and Prevention, Nanjing, China.
Zhihang PengNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Zhiliang HuDepartment of Infectious Diseases, Nanjing Public Health Medical Center, the Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing, China.ORCID https://orcid.org/0000-0001-8543-821X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Although CD4 recovery has been widely studied, its long-term temporal dynamics and phase-specific characteristics in the modern ART era remain incompletely characterized. Methods: This retrospective cohort study included adults with HIV in Nanjing, China, who initiated ART between 2010 and 2019 and maintained viral suppression. The optimal CD4 recovery trajectory model was identified using piecewise linear mixed-effects models with exhaustive grid search. Cumulative probability curves estimated probabilities of CD4 count recovery to ≥500 and ≥350 cells/μL. Results: 2611 individuals contributing 22 970 person-years and 37 959 observations were analyzed. The best-fitting model identified a 4-phase CD4 recovery trajectory with breakpoints at 0.5, 2.5, and 6 years, characterized by the fastest increase during 0-0.5 years (265.4 cells/μL/year), progressive slowing during 0.5-2.5 and 2.5-6 years, and modest growth beyond 6 years (8.6 cells/μL/year). Cumulative probabilities of reaching both thresholds rose steadily but decelerated markedly after 6 years. When stratified by baseline CD4 counts at ART initiation, compared with the 350-499 subgroup, the <200 subgroup showed slower early CD4 count gains (≤49: -57.9; 50-199: -40.3 cells/μL/year) during 0-0.5 years, but accelerated increases during 0.5-2.5 years (≤49: +28.3; 50-199: +10.2 cells/μL/year) that persisted after 6 years (≤49: +4.7; 50-199: +5.3 cells/μL/year). Cumulative probabilities of reaching both thresholds in the <200 subgroup increased continuously throughout follow-up, whereas those with higher baseline levels plateaued at 6 years. Conclusions: CD4 recovery under sustained viral suppression followed a phase-specific trajectory. Individuals with advanced immunosuppression showed delayed but sustained CD4 recovery. These findings may help understand when CD4 recovery approaches its maximal potential.

Indexed as

ARTCD4 recovery trajectoryHIVpiecewise linear mixed-effects model

Identifiers

PMID41959659
PMCPMC13061125

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.