Evidence map›Paper›PMID 41068699›Full record

ArticleBMC surgery2025

Nomogram predictive model for the incidence and risk factors of persistent fever after cardiovascular surgery.

Feng Zang, Guangxu Mao, Ziyao Quan, Yongfeng Shao, Sheng Zhao, Liyun Wang, Zhanjie Li, Zhongqiu You, Lu Liu, Wensen Chen

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In one paragraph

Article in BMC surgery, 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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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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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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

10 authors.

Feng Zang *Department of Infection Management, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
Guangxu Mao *Department of Infection Management, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
Ziyao QuanDepartment of Infection Management, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
Yongfeng ShaoDepartment of Cardiovascular Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
Sheng ZhaoDepartment of Cardiovascular Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
Liyun WangDepartment of Infection Management, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
Zhanjie LiDepartment of Infection Management, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
Zhongqiu YouDepartment of Infection Management, Chengdu Pidu District People's Hospital, Chengdu, 610000, Sichuan, China.
Lu LiuDepartment of Infection Management, Yizheng People's Hospital, Yangzhou, 211400, Jiangsu, China.
Wensen ChenDepartment of Infection Management, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, Jiangsu, China. wensenchen@njmu.edu.cn.

Funding

Young Scholars Fostering Fund of the First Affiliated Hospital of Nanjing Medical University PY202435
6 · The paper itself

Abstract

backgroundA persistent fever following cardiovascular surgery presents a significant clinical challenge and often leads to adverse patient outcomes. This study aims to develop a nomogram predictive model for persistent postoperative fever, which could serve as a valuable tool for clinicians in making diagnostic and treatment decisions.

methodsThe medical records of patients who underwent cardiovascular surgery at the First Affiliated Hospital of Nanjing Medical University in 2023 were retrospectively analysed. The patients were divided into two groups based on whether their body temperature remained above 38℃ for three consecutive days after surgery: the persistent fever group and the control group. Independent risk factors for persistent postoperative fever were identified through univariate and multivariate logistic regression analyses. A predictive nomogram model was then developed and validated.

resultsThe study involved 343 patients who underwent cardiovascular surgery, revealing an overall postoperative fever rate of 70.55% and a persistent fever rate of 38.78%. The highest fever rates were observed on the first and second postoperative days. Multivariate logistic regression analysis identified several independent risk factors for persistent postoperative fever, including older age at admission, a history of smoking, a higher Controlling Nutritional Status Score (CONUT), an elevated Monocyte-to-Lymphocyte Ratio (MLR), a longer duration of surgery, the use of cardiopulmonary bypass, and intraoperative transfusion of machine-washed red blood cells. A nomogram prediction model showed good discriminatory and predictive ability, with an area under the receiver operating characteristic curve (AUC) of 0.821 (95% CI: 0.775–0.866).

conclusionThe nomogram developed in this research offers a quantitative and visually intuitive method for early evaluation of the probability of persistent postoperative fever in individuals undergoing cardiovascular surgery.

Indexed as

Cardiovascular Surgical ProceduresFeverNomogramsPostoperative ComplicationsAgedFemaleHumansIncidenceMaleMiddle AgedRetrospective StudiesRisk FactorsCardiovascular surgeryNomogram predictive modelPersistent postoperative feverRisk factors

Identifiers

PMID41068699
PMCPMC12512308

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