Evidence map›Paper›PMID 33010416›Full record

ArticleAnnals of epidemiology2021

Algorithm to identify transgender and gender nonbinary individuals among people living with HIV performs differently by age and ethnicity.

Jules Chyten-Brennan, Viraj V Patel, Mindy S Ginsberg, David B Hanna

Open access · greenAbstract read
In one paragraph

Article in Annals of epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.3field-weighted citation impact, top 17% of its field
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

11 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Article
  3. A scoping review of models to identify transgender patients in electronic health records.Journal of the American Medical Informatics Association : JAMIA · 2026
    Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Identifying and Characterizing the Transgender and Nonbinary Population Presenting to Pediatric Psychiatry Emergency Services.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024
    Article
  10. Article
  11. 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

4 authors at 1 institution in 1 country.

Jules Chyten-BrennanDivision of General Internal Medicine, Department of Medicine, Montefiore Medical Center-Albert Einstein College of Medicine, Bronx, NY. Electronic address: jules.chyten-brennan@hhs.sccgov.org.
Viraj V PatelDivision of General Internal Medicine, Department of Medicine, Montefiore Medical Center-Albert Einstein College of Medicine, Bronx, NY.
Mindy S GinsbergDepartment of Epidemiology and Population Health, Montefiore Medical Center-Albert Einstein College of Medicine, Bronx, NY.
David B HannaDepartment of Epidemiology and Population Health, Montefiore Medical Center-Albert Einstein College of Medicine, Bronx, NY.
Albert Einstein College of Medicine · US

Funding

Patient and Population Health Outcomes Research SWGP30AI124414 · NIAID · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI HARRIS GOLDSTEIN · 2017 to 2026
$28.3M
CTSA Administrative Supplement for Informatics Core: A novel AI/ML system to predict respiratory failure and ARDS in Covid-19 patientsUL1TR002556 · NCATS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI KELLER, MARLA J, KIM, MIMI Y · 2018 to 2022
$26.7M
Social Media Based Peer Led Intervention to Facilitate PrEP in YMSM of ColorK23MH102118 · NIMH · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI PATEL, VIRAJ V · 2014 to 2018
$953k
Prediction of heart failure in HIV-infected individualsK01HL137557 · NHLBI · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI HANNA, DAVID B. · 2017 to 2020
$711k
NCATS NIH HHS UL1 TR002556NHLBI NIH HHS K01 HL137557NIAID NIH HHS P30 AI124414NIMH NIH HHS K23 MH102118NIMH NIH HHS L30 MH117751
6 · The paper itself

Abstract

purposeHIV research among transgender and gender nonbinary (TGNB) people is limited by lack of gender identity data collection. We designed an EHR-based algorithm to identify TGNB people among people living with HIV (PLWH) when gender identity was not systematically collected.

methodsWe applied EHR-based search criteria to all PLWH receiving care at a large urban health system between 1997 and 2017, then confirmed gender identity by chart review. We compared patient characteristics by gender identity and screening criteria, then calculated positive predictive values for each criterion.

resultsAmong 18,086 PLWH, 213 (1.2%) met criteria as potential TGNB patients and 178/213 were confirmed. Positive predictive values were highest for free-text keywords (91.7%) and diagnosis codes (77.4%). Confirmed TGNB patients were younger (median 32.5 vs. 42.5 years, P < .001) and less likely to be Hispanic (37.1% vs. 62.9%, P = .03) than unconfirmed patients. Among confirmed patients, 15% met criteria only for prospective gender identity data collection and were significantly older.

conclusionEHR-based criteria can identify TGNB PLWH, but success may differ by ethnicity and age. Retrospective versus intentional, prospective gender identity data collection may capture different patients. To reduce misclassification in epidemiologic studies, gender identity data collection should address these potential differences and be systematic and prospective.

Indexed as

AlgorithmsGender IdentityHIV InfectionsTransgender PersonsAdultAge DistributionElectronic Health RecordsEthnicityFemaleHumansMaleMiddle AgedProspective StudiesReproducibility of ResultsRetrospective StudiesAlgorithmsElectronic health recordsHIVTransgender persons

Identifiers

PMID33010416
PMCPMC7883669
OpenAlexW3091633595

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.