Evidence map›Paper›PMID 33987406›Full record

ArticleAnnals of translational medicine2021

A model-based validation study of postoperative complications with considerations on operative timing.

Kun Qian, Simeng Wu, Weishan Lee, Shiwen Liu, Ailun Li, Jing Cang, Fang Fang

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2021. 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
0.3field-weighted citation impact, top 41% of its field
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

1 citing paper in PubMed, 4 citations in OpenAlex.

  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

7 authors at 4 institutions in 1 country.

Kun QianDepartment of Information and Intelligence Development, Zhongshan Hospital, Fudan University, Shanghai, China.
Simeng WuDepartment of Information and Intelligence Development, Zhongshan Hospital, Fudan University, Shanghai, China.
Weishan LeeDepartment of Anesthesia, Zhongshan Hospital, Fudan University, Shanghai, China.
Shiwen LiuDepartment of Anesthesia, Zhongshan Hospital, Fudan University, Shanghai, China.
Ailun LiDepartment of Anesthesia, Zhongshan Hospital, Fudan University, Shanghai, China.
Jing CangDepartment of Anesthesia, Zhongshan Hospital, Fudan University, Shanghai, China.
Fang FangDepartment of Anesthesia, Zhongshan Hospital, Fudan University, Shanghai, China.
The First Affiliated Hospital, Sun Yat-sen University · CNFudan University · CNSun Yat-sen University · CNZhongshan Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSurgery is a highly technical procedure relying on high mental acuity and manual dexterity. The possibility that surgical outcomes and post-operative complications could be subject to influence by fatigue and/or circadian rhythms in surgeons has been investigated with inconsistent results.

methodsWe conducted a retrospective study to assess the significance of operative timing on classifying surgical complications using an interpretable machine learning approach. We trained various linear, generative as well as tree models on the surgical record data collected from a university-affiliated, tertiary teaching hospital in China by performing parameter tuning using grid search cross-validation for optimizing the F1 score.

resultsThe results indicated that XGBoost was the best-performing model overall and its feature importance was shown to provide insight into possible timing-related associations with postoperative complications. We observed that the duration of surgery acted as the strongest indicator, and while surgery initiated at night (between 9 pm and 7 am) also ranked higher on the feature importance scale, it bore less significance than other factors such as the patient's age, gender, and type of surgery performed.

conclusionsWe showed that surgical records could be used to demonstrate that operative timing might affect the occurrence of postoperative complications, but only in a relatively mild way while potentially entangling with multiple factors.

Indexed as

circadian rhythmcross validationfeature importancemachine learningPostoperative complicationXGBoost

Identifiers

PMID33987406
PMCPMC8106084
OpenAlexW3152889284

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.