Evidence map›Paper›PMID 38602621›Full record

ArticleDigestive diseases and sciences2024

Acute Pancreatitis in Pregnancy: A Propensity Score Matching Analysis and Dynamic Nomogram for Risk Assessment.

Xiaowei Tang, Yuan Chen, Shu Huang, Jiao Jiang, Bei Luo, Wensen Ren, Xueqin Zhou, Xiaomin Shi, Wei Zhang, Lei Shi and 2 more

Abstract read
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Article in Digestive diseases and sciences, 2024. 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

What it found

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Xiaowei Tang *Department of Gastroenterology, the Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Luzhou, 646099, Sichuan, China.
Yuan Chen *Department of Gastroenterology, the Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Luzhou, 646099, Sichuan, China.
Shu HuangDepartment of Gastroenterology, Lianshui County People' Hospital, Huaian, China.
Jiao JiangDepartment of Gastroenterology, the Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Luzhou, 646099, Sichuan, China.
Bei LuoDepartment of Gastroenterology, the Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Luzhou, 646099, Sichuan, China.
Wensen RenDepartment of Gastroenterology, the Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Luzhou, 646099, Sichuan, China.
Xueqin ZhouDepartment of Gastroenterology, the Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Luzhou, 646099, Sichuan, China.
Xiaomin ShiDepartment of Gastroenterology, the Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Luzhou, 646099, Sichuan, China.
Wei ZhangDepartment of Gastroenterology, the Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Luzhou, 646099, Sichuan, China.
Lei ShiDepartment of Gastroenterology, the Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Luzhou, 646099, Sichuan, China.
Xiaolin ZhongDepartment of Gastroenterology, the Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Luzhou, 646099, Sichuan, China.
Muhan LüDepartment of Gastroenterology, the Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Luzhou, 646099, Sichuan, China. lvmuhan@swmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcute pancreatitis is easily confused with abdominal pain symptoms, and it could lead to serious complications for pregnant women and fetus, the mortality was as high as 3.3% and 11.6-18.7%, respectively. However, there is still lack of sensitive laboratory markers for early diagnosis of APIP and authoritative guidelines to guide treatment.

objectiveThe purpose of this study was to explore the risk factors of acute pancreatitis in pregnancy, establish, and evaluate the dynamic prediction model of risk factors in acute pancreatitis in pregnancy patients. STUDY

designClinical data of APIP patients and non-pregnant acute pancreases patients who underwent regular antenatal check-ups during the same period were collected. The dataset after propensity matching was randomly divided into training set and verification set at a ratio of 7:3. The model was constructed using Logistic regression, least absolute shrinkage and selection operator regression, R language and other methods. The training set model was used to construct the diagnostic nomogram model and the validation set was used to validate the model. Finally, the accuracy and clinical practicability of the model were evaluated.

resultsA total of 111 APIP were included. In all APIP patients, hyperlipidemic pancreatitis was the most important reason. The levels of serum amylase, creatinine, albumin, triglyceride, high-density lipoprotein cholesterol, and apolipoprotein A1 were significantly different between the two groups. The propensity matching method was used to match pregnant pancreatitis patients and pregnant non-pancreatic patients 1:1 according to age and gestational age, and the matching tolerance was 0.02. The multivariate logistic regression analysis of training set showed that diabetes, triglyceride, Body Mass Index, white blood cell, and C-reactive protein were identified and entered the dynamic nomogram. The area under the ROC curve of the training set was 0.942 and in validation set was 0.842. The calibration curve showed good predictive in training set, and the calibration performance in the validation set was acceptable. The calibration curve showed the consistency between the nomogram model and the actual probability.

conclusionThe dynamic nomogram model we constructed to predict the risk factors of acute pancreatitis in pregnancy has high accuracy, discrimination, and clinical practicability.

Indexed as

NomogramsPancreatitisPregnancy ComplicationsPropensity ScoreAcute DiseaseAdultFemaleHumansPregnancyRetrospective StudiesRisk AssessmentRisk FactorsAcute pancreatitis in pregnancyDynamic nomogramPropensity score match

Identifiers

PMID38602621

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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.