Evidence map›Paper›PMID 39906746›Full record

ArticleFrontiers in immunology2024

Piloting an automated query and scoring system to facilitate APDS patient identification from health systems.

Amy M FitzPatrick, Aaron T Chin, Sharon Nirenberg, Charlotte Cunningham-Rundles, Keith Sacco, Jesse Perlmutter, Joseph F Dasso, Athanasios Tsalatsanis, Jay Maru, Jessica Creech and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in immunology, 2024. 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. Review
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

18 authors.

Amy M FitzPatrickPrecision AQ, Bethesda, MD, United States.
Aaron T ChinDepartment of Pediatrics, University of California, Los Angeles, Los Angeles, CA, United States.
Sharon NirenbergDivision of Informatics and Data Architecture, Icahn School of Medicine, Departments of Scientific Computing and Data, Mount Sinai School of Medicine, New York, NY, United States.
Charlotte Cunningham-RundlesDivision of Clinical Immunology, Icahn School of Medicine, Departments of Medicine and Pediatrics, Mount Sinai School of Medicine, New York, NY, United States.
Keith SaccoDepartment of Child Health, University of Arizona College of Medicine and Division of Pulmonology, Section of Allergy-Immunology, Phoenix Children's Hospital, Phoenix, AZ, United States.
Jesse PerlmutterPhoenix Children's Hospital, Phoenix, AZ, United States.
Joseph F DassoDepartment of Pediatric Allergy and Immunology, University of South Florida at Johns Hopkins All Children's Hospital, St. Petersburg, FL, United States.
Athanasios TsalatsanisResearch Methodology and Biostatistics Core, Morsani College of Medicine, University of South Florida Health, St. Petersburg, FL, United States.
Jay MaruManagement Analyst, Research Methodology and Biostatistics Core, Morsani College of Medicine, University of South Florida Health, St. Petersburg, FL, United States.
Jessica CreechDepartment of Pediatrics, University of South Florida at Johns Hopkins All Children's Hospital, St. Petersburg, FL, United States.
Jolan E WalterDepartment of Pediatric Allergy and Immunology, University of South Florida at Johns Hopkins All Children's Hospital, St. Petersburg, FL, United States.
Nicholas HartogDivision of Allergy and Immunology, Helen DeVos Children's Hospital and Corewell Health, Grand Rapids, Michigan State University College of Human Medicine, East Lansing, MI, United States.
Neema IzadiDivision of Clinical Immunology and Allergy, Children's Hospital Los Angeles, University of Southern California, Los Angeles, CA, United States.
Mandy PalmucciDivision of Information Services, Children's Hospital Los Angeles, University of Southern California, Los Angeles, CA, United States.
Manish J ButteDepartment of Pediatrics and Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, United States.
Klaus LoewyDepartment of Information Services, Texas Children's Hospital, Houston, TX, United States.
Anurag RelanPharming Healthcare, Inc., Warren, NJ, United States.
Nicholas L RiderDepartment of Health Systems & Implementation Science, Virginia Tech Carilion School of Medicine, Division of Allergy-Immunology Carilion Clinic, Roanoke, VA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Patients with activated PI3Kδ syndrome (APDS) may elude diagnoses for nearly a decade. Methods to hasten the identification of these patients, and other patients with inborn errors of immunity (IEIs), are needed. We sought to demonstrate that querying electronic health record (EHR) systems by aggregating disparate signs into a risk score can identify these patients. Methods: We developed a structured query language (SQL) script using literature-validated APDS-associated clinical concepts mapped to Results: The query identified all but one known patient with APDS (98%; 45/46) as well as patients with other complex disease. Median score for all patients with APDS was 9 (IQR = 5.75; range 1-25). Sensitivity analysis suggested an optimal cutoff score of 7 (sensitivity = 0.70). Conclusion: Disease-specific queries are a relatively simple method to foster patient identification across the rare-disease spectrum. Such methods are even more important for disorders such as APDS where an approved, pathway-specific treatment is available in the US.

Indexed as

Class I Phosphatidylinositol 3-KinasesElectronic Health RecordsPrimary Immunodeficiency DiseasesHumansClass I Phosphatidylinositol 3-KinasesAIAPDSdiagnostic delayEHR queryIEI diagnosisinborn errors of immunity

Identifiers

PMID39906746
PMCPMC11790479

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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.