Evidence mapPaperPMID 38965472Full record

ArticleBMC anesthesiology2024

Construction and validation of a risk prediction model for postoperative ICU admission in patients with colorectal cancer: clinical prediction model study.

Lu Wang, Yanan Wu, Liqin Deng, Xiaoxia Tian, Junyang Ma

Abstract readValidation Study
In one paragraph

Article in BMC anesthesiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

6 citing papers in PubMed.

  1. Article
  2. Intensive care unit outcomes and prognostic factors of colorectal cancer.World journal of gastrointestinal oncology · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. 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

5 authors.

Lu WangDepartment of Anesthesia and Perioperative Medicine, General Hospital of Ningxia Medical University, 804 Shengli South Street, Xingqing District, Yinchuan City, Ningxia, China.
Yanan WuDepartment of Anesthesia and Perioperative Medicine, General Hospital of Ningxia Medical University, 804 Shengli South Street, Xingqing District, Yinchuan City, Ningxia, China.
Liqin DengDepartment of Anesthesia and Perioperative Medicine, General Hospital of Ningxia Medical University, 804 Shengli South Street, Xingqing District, Yinchuan City, Ningxia, China. dengliqin@nxmu.edu.cn.
Xiaoxia TianDepartment of Anesthesia and Perioperative Medicine, General Hospital of Ningxia Medical University, 804 Shengli South Street, Xingqing District, Yinchuan City, Ningxia, China.
Junyang MaDepartment of Anesthesia and Perioperative Medicine, General Hospital of Ningxia Medical University, 804 Shengli South Street, Xingqing District, Yinchuan City, Ningxia, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTransfer to the ICU is common following non-cardiac surgeries, including radical colorectal cancer (CRC) resection. Understanding the judicious utilization of costly ICU medical resources and supportive postoperative care is crucial. This study aimed to construct and validate a nomogram for predicting the need for mandatory ICU admission immediately following radical CRC resection.

methodsRetrospective analysis was conducted on data from 1003 patients who underwent radical or palliative surgery for CRC at Ningxia Medical University General Hospital from August 2020 to April 2022. Patients were randomly assigned to training and validation cohorts in a 7:3 ratio. Independent predictors were identified using the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression in the training cohort to construct the nomogram. An online prediction tool was developed for clinical use. The nomogram's calibration and discriminative performance were assessed in both cohorts, and its clinical utility was evaluated through decision curve analysis (DCA).

resultsThe final predictive model comprised age (P = 0.003, odds ratio [OR] 3.623, 95% confidence interval [CI] 1.535-8.551); nutritional risk screening 2002 (NRS2002) (P = 0.000, OR 6.129, 95% CI 2.920-12.863); serum albumin (ALB) (P = 0.013, OR 0.921, 95% CI 0.863-0.982); atrial fibrillation (P = 0.000, OR 20.017, 95% CI 4.191-95.609); chronic obstructive pulmonary disease (COPD) (P = 0.009, OR 8.151, 95% CI 1.674-39.676); forced expiratory volume in 1 s / Forced vital capacity (FEV1/FVC) (P = 0.040, OR 0.966, 95% CI 0.935-0.998); and surgical method (P = 0.024, OR 0.425, 95% CI 0.202-0.891). The area under the curve was 0.865, and the consistency index was 0.367. The Hosmer-Lemeshow test indicated excellent model fit (P = 0.367). The calibration curve closely approximated the ideal diagonal line. DCA showed a significant net benefit of the predictive model for postoperative ICU admission.

conclusionPredictors of ICU admission following radical CRC resection include age, preoperative serum albumin level, nutritional risk screening, atrial fibrillation, COPD, FEV1/FVC, and surgical route. The predictive nomogram and online tool support clinical decision-making for postoperative ICU admission in patients undergoing radical CRC surgery.

trial registrationDespite the retrospective nature of this study, we have proactively registered it with the Chinese Clinical Trial Registry. The registration number is ChiCTR2200062210, and the date of registration is 29/07/2022.

Indexed as

Colorectal NeoplasmsIntensive Care UnitsNomogramsAgedFemaleHumansMaleMiddle AgedPatient AdmissionPostoperative ComplicationsRetrospective StudiesRisk AssessmentIntensive care unitNomogramPredictive modelRadical colorectal cancer surgeryRisk factors

Identifiers

PMID38965472
PMCPMC11223334

What Socratic holds

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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 Socratic graph.