Evidence map›Paper›PMID 39670399›Full record

ArticlePacific Symposium on Biocomputing. Pacific Symposium on Biocomputing2025

Electronic Health Record Analysis for Personalized Medicine: Predicting Malnutrition-Related Health Outcomes and Secondary Neuropsychiatric Health Concerns.

Pinar Gurkas, Gunnur Karakurt

Abstract read
In one paragraph

Article in Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2025. 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

2 authors.

Pinar GurkasClayton State University, Department of Psychology Morrow, GA 30260, USA, PinarGurkas@clayton.edu.
Gunnur KarakurtCase Western Reserve University, Department of Psychiatry Cleveland, OH 44109, USA, gunnur.karakurt@case.edu.

Funding

Decision-Making Modeling for Treating Intimate Partner ViolenceR01LM012518 · NLM · CASE WESTERN RESERVE UNIVERSITY · PI KARAKURT KOYUTURK, GUNNUR · 2018 to 2022
$1.3M
NLM NIH HHS R01 LM012518
6 · The paper itself

Abstract

Malnutrition poses risks regarding cognitive, behavioral, and physical well-being. The aim of this study was to investigate the prevalent health issues associated with malnutrition by utilizing electronic health records (EHR) data. The IBM Watson Health, Explorys platform was used to access the EHR data. Two cohorts were created by two queries; patients with a history of malnutrition (n=5180) and patients without a history of malnutrition diagnosis (n= 413890). The log odds ratio and χ2 statistic were used to identify the statistically significant differences between these two cohorts. We found that there were 35 terms that were more common among the cohort with the malnutrition diagnosis. These terms were categorized under developmental anomalies, infectious agents, respiratory system issues, digestive system issues, pregnancy/prenatal problems, mental, behavioral, or neurodevelopmental disorders, diseases of the ear or mastoid process, diseases of the visual system, and chromosomal anomalies. The management of malnutrition in children is a complex problem that can be addressed with a multifactorial approach. Based on the key themes emerging from among the commonly prevalent terms identified in our study, infection prevention, education in appropriate nutritional solutions for digestive health issues, supportive services to address neurodevelopmental needs, and quality prenatal healthcare would constitute beneficial prevention efforts. Improving our understanding of malnutrition is necessary to develop new interventions for prevention and treatment.

Indexed as

Computational BiologyElectronic Health RecordsMalnutritionPrecision MedicineChildChild, PreschoolCohort StudiesFemaleHumansMaleMental Disorders

Identifiers

PMID39670399
PMCPMC11649008

What OpenQuestion holds

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LicenceCC BY-NC
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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.