Evidence map›Paper›PMID 40610467›Full record

ArticleScientific reports2025

A novel nomogram for predicting the implementation of ultra-fast-track cardiac anesthesia for minimally invasive cardiac surgery.

Tian Jiang, Linting Xu, Haozhou Wang, Qinghui Zheng, Yihui Zhang, Jinchen Guo, Xiaokan Lou, Hanwei Wei, Meijuan Yan

Abstract read
In one paragraph

Article in Scientific reports, 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

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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. Article
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

9 authors.

Tian JiangWannan Medical College, Wuhu, Anhui Province, China.
Linting XuWannan Medical College, Wuhu, Anhui Province, China.
Haozhou WangWannan Medical College, Wuhu, Anhui Province, China.
Qinghui ZhengGeneral Surgery, Cancer Center, Department of Breast Surgery, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China.
Yihui ZhangJinzhou Medical University, Jinzhou, Liaoning Province, China.
Jinchen GuoHangzhou Normal University, Hangzhou, Zhejiang Province, China.
Xiaokan LouCenter for Rehabilitation Medicine, Department of Anesthesiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, 158 Shangtang Road, Gongshu District, Hangzhou, Zhejiang, China.
Hanwei WeiCenter for Rehabilitation Medicine, Department of Anesthesiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, 158 Shangtang Road, Gongshu District, Hangzhou, Zhejiang, China. omadrr@163.com.
Meijuan YanCenter for Rehabilitation Medicine, Department of Anesthesiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, 158 Shangtang Road, Gongshu District, Hangzhou, Zhejiang, China. yanmeijuan@hmc.edu.cn.ORCID http://orcid.org/0009-0000-4658-8645

Funding

Medical Science and Technology Project of Zhejiang Province 2022KY037Medical Science and Technology Project of Zhejiang Province 2022KY062Medical Science and Technology Project of Zhejiang Province 2024KY657Seed Fund Project of Zhejiang Provincial People's Hospital ZRY2022J011
6 · The paper itself

Abstract

Ultra-fast-track cardiac anesthesia (UFTCA) is a crucial component of enhanced recovery after cardiac surgery (ERACS). However, research on the factors influencing UFTCA implementation remains limited. This study aimed to identify predictors of UFTCA in right-thoracoscopic minimally invasive cardiac surgery (MICS) and develop a nomogram to predict UFTCA implementation. This retrospective study enrolled 947 patients who underwent right-thoracoscopic MICS from January 2021 to July 2023. Patients were randomly divided into derivation (70%) and validation (30%) cohorts. Univariable logistic regression analysis was used for variable selection, followed by a multivariable logistic regression model to determine significant predictors and construct a nomogram for predicting UFTCA implementation. The model's discrimination, calibration, and clinical effectiveness were evaluated using the validation cohort. Multivariate analysis identified six independent predictors of UFTCA implementation: operation type, fascial plane chest wall blocks (FPCWB), intraoperative sufentanil and dexamethasone dosage, operation later than 8 p.m., and cardiopulmonary bypass (CPB) duration. The nomogram demonstrated good discriminative ability, with areas under the receiver operating characteristic (ROC) curve of 0.869 and 0.862 for the derivation and validation sets, respectively. The calibration plot showed close alignment with the ideal diagonal line, and the decision curve analysis (DCA) confirmed the model's clinical practical significance. This study developed and validated a nomogram that could predict the implementation of UFTCA in patients undergoing MICS. The nomogram showed that more complexity of procedures, especially multiple valve surgery, higher doses of sufentanil, longer CPB duration and operation later than 8 p.m. were disadvantageous to UFTCA implementation, while administration of dexamethasone and FPCWB were beneficial for UFTCA.

Indexed as

AnesthesiaCardiac Surgical ProceduresMinimally Invasive Surgical ProceduresNomogramsAgedCardiopulmonary BypassFemaleHumansMaleMiddle AgedRetrospective StudiesROC CurveEnhanced recovery after surgeryMinimally invasive cardiac surgeryPerioperative managementPredictive modelingUltra-fast-track cardiac anesthesia

Identifiers

PMID40610467
PMCPMC12229641

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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.