Evidence map›Paper›PMID 36748770›Full record

ArticleUlusal travma ve acil cerrahi dergisi = Turkish journal of trauma & emergency surgery : TJTES2023

Construction of a nomogram predictive model for patients with liver rupture undergoing surgical intervention.

Gen-Fei Zhu, Xiao-Qing Wu, Yang Chen, Feng Jiang

Abstract read
In one paragraph

Article in Ulusal travma ve acil cerrahi dergisi = Turkish journal of trauma & emergency surgery : TJTES, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Gen-Fei ZhuDepartment of General Surgery, Zhejiang Hospital, Zhejiang Province-China.
Xiao-Qing WuDepartment of General Surgery, Zhejiang Hospital, Zhejiang Province-China.
Yang ChenDepartment of General Surgery, Affiliated Xiaoshan Hospital, Hangzhou Normal University, Zhejiang Province-China.
Feng JiangDepartment of General Surgery, Affiliated Xiaoshan Hospital, Hangzhou Normal University, Zhejiang Province-China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe incidence of blunt abdominal injury has significantly increased, and the liver is one of the most commonly damaged organs. In this study, we explored and established a nomogram model for patients with liver ruptures undergoing surgical treatment.

methodsA retrospective analysis was conducted for 66 adult patients with liver rupture, who were admitted to our hospital from January 2011 to October 2018. These patients were classified into two groups, according to whether the patient had surgery: surgery group (41 cases) and non-surgical group (25 cases). The following data were collected from these two groups of patients: gender, age, injury mechanism, liver damage, laboratory test results, and hospitalization. Multivariate logistic regression analysis was performed to screen the risk factors of patients who require surgical treatment, establish a predictive model based on the selected indicators, and draw the nomogram. Receiver operating characteristic curves and the calibration curve were used to evaluate the predictive value of the model.

resultsCompared to the non-surgical group, the body temperature decreased, the heart rate increased, the injury severity score grade increased, the blood urea nitrogen, blood uric acid, creatinine (Cr), arterial partial pressure of oxygen, alkali excess, blood lactic acid and creatine kinase isoenzymes MB (CK-MB) increased, and the HCO- and Glasgow Coma Scale (GCS) coma scores decreased for patients in the surgical group (all, p<0.05). The logistic regression analysis revealed that Cr, arterial partial pressure of oxygen, HCO3-, CK-MB, and the Glasgow coma score were the influencing factors for surgical intervention for liver rupture. The nomo-gram model constructed based on these five indicators had a good degree of discrimination (area under the curve = 0.971, 95% CI: 0.896-0.997) and accuracy.

conclusionA nomogram model established based on Cr, arterial partial pressure of oxygen, HCO3-, CK-MB, the GCS, and other parameters can accurately predict the surgical treatment of patients with liver rupture.

Indexed as

Liver DiseasesNomogramsAdultComaHumansRetrospective StudiesROC Curve

Identifiers

PMID36748770
PMCPMC10198341

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