Evidence map›Paper›PMID 39946377›Full record

ArticlePloS one2025

Identification of early predictors and model for bacterial infection in diabetic ketoacidosis patients: A retrospective study.

Yaping Hao, Lei Yang, Xiaomei Meng, Yuxiao Tang, Liang Wang

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Yaping HaoDepartment of Endocrinology, Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, Shandong, China.
Lei YangDepartment of Endocrinology, Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, Shandong, China.
Xiaomei MengDepartment of Endocrinology, Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, Shandong, China.
Yuxiao TangDepartment of Endocrinology, Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, Shandong, China.
Liang WangDepartment of Endocrinology, Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, Shandong, China.ORCID https://orcid.org/0009-0008-6691-3175

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe purpose of this report was to identify effective indicators capable of predicting bacterial infection during the early stages of diabetic ketoacidosis (DKA) and to establish a diagnostic model suitable for clinical application.

methodsThis was a retrospective cross-sectional study. Between February 2018 and May 2023, Yuhuangding Hospital admitted 101 DKA patients, of whom 45 were diagnosed with bacterial infections. A confirmed bacterial infection was defined as documented bacteriological evidence in any bacterial sample. Clinical parameters and biological markers (including cortisol, C-reactive protein (CRP), procalcitonin, etc.) were recorded during the initial DKA phase. Multivariate regression analysis was employed to construct a diagnostic model.

resultsCRP (OR = 1.014, 95% CI: 1.002-1.026, p = 0.017) and cortisol (OR = 1.007, 95% CI: 1.002-1.012, p = 0.003) were found to have an independent association with bacterial infection in DKA patients. The area under the receiver operating characteristic curve (AUC) for CRP in identifying bacterial infection was 0.855 (95% CI, 0.771-0.917), with a sensitivity of 76.1% and a specificity of 83.6%. The AUC for cortisol in identifying bacterial infection was 0.847 (95% CI, 0.761-0.911), with a sensitivity of 71.7% and a specificity of 89.1%. A joint diagnostic model based on cortisol and CRP was developed through multifactor regression analysis. The AUC of this diagnostic model was 0.930 (95% CI, 0.862-0.972), resulting in a sensitivity of 93.5% and a specificity of 80.0%.

conclusionCRP and cortisol are early indicators of bacterial infection in DKA patients. Furthermore, based on their combination, the regression diagnostic model exhibits enhanced diagnostic performance.

Indexed as

Bacterial InfectionsDiabetic KetoacidosisAdultBiomarkersC-Reactive ProteinCross-Sectional StudiesFemaleHumansHydrocortisoneMaleMiddle AgedProcalcitoninRetrospective StudiesROC CurveBiomarkersC-Reactive ProteinHydrocortisoneProcalcitonin

Identifiers

PMID39946377
PMCPMC11825026

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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.