Evidence map›Paper›PMID 42151893›Full record

Observational studyBMC geriatrics2026

Cohort profile: PeRiOperative sTress risk assEssment and Clinical decision cohorT (PROTECT), a multi-center observational study based on real-world data.

Xudong Chen, Ruihao Zhou, Xiran Peng, Yaqiang Wang, Ke Li, Mengchan Ou, Guo Chen, Rui Shi, E Wang, He Huang and 3 more

Abstract readMulticenter StudyObservational Study
In one paragraph

Observational study in BMC geriatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Xudong Chen *Department of Anesthesiology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China.
Ruihao Zhou *Department of Anesthesiology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China.
Xiran Peng *Department of Anesthesiology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China.
Yaqiang WangCollege of Software Engineering, Chengdu University of Information Technology, Chengdu, Sichuan, China.
Ke LiCenter of Statistical Research, School of Statistics, Southwestern University of Finance and Economics, Chengdu, China.
Mengchan OuDepartment of Anesthesiology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China.
Guo ChenDepartment of Anesthesiology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China.
Rui ShiEngineering Research Center of Medical Information Technology, Ministry of Education, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
E WangDepartment of Anesthesiology, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital Central South University, Changsha, Hunan, China.
He HuangDepartment of Anesthesiology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Xuechao HaoDepartment of Anesthesiology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China. aneshxc@163.com.
Tao ZhuDepartment of Anesthesiology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China. xwtao.zhu@foxmail.com.
Anesthesiology & Intelligence Research Collaboration Group (AIR-CG)

Funding

CAMS Innovation Fund for Medical Sciences 2023-I2M-C&T-B-121CAMS Innovation Fund for Medical Sciences 2023-I2M-C&T-B-122National Natural Science Foundation of China 72304197National Natural Science Foundation of China 82371280Noncommunicable Chronic Diseases-National Science and Technology Major Project 2023ZD0501801Science and Technology Department of Sichuan Province 2023NSFSC1565Science and Technology Department of Sichuan Province 2024YFFK0100Science and Technology Department of Sichuan Province 2024ZDZX0017Sichuan Province Health Research Project ZH2025-103
6 · The paper itself

Abstract

backgroundGlobal surgical volumes continue to rise, yet postoperative morbidity and mortality remain substantial, particularly among geriatric patients. The scarcity of multi-center prospective perioperative cohorts with active follow-up and large-scale, high-quality data limits the understanding of risk profiles and hinders individualized perioperative management in this population. To address this gap, the PeRiOperative sTress risk assEssment and Clinical decision cohorT (PROTECT) was established by creating a dedicated perioperative data platform for geriatric patients. This cohort profile specifically describes the study design, recruitment strategy, data structure, and current status of PROTECT.

methodsPROTECT is an ongoing, ambispective, real-world observational cohort across three tertiary medical centers. The study continuously enrolls inpatients aged ≥ 65 years undergoing surgery under anesthesia. Preoperatively, standardized pre-anesthesia assessments are conducted to collect comprehensive medical information. Intraoperatively, anesthetic and surgical data, along with high-frequency biosignals are recorded. Postoperative outcomes are evaluated at 48 hours, 7 days, and 30 days. Descriptive analyses were performed to summarize baseline characteristics and postoperative outcomes.

resultsThe first participant was enrolled in August 2019. As of May 2025, 61,289 participants aged 65-100 years have been included. The median age is 71 years, and 44.4% are female. 52.2% are classified as American Society of Anesthesiologists physical status III or higher. The most common surgeries are abdominal (42.8%) and orthopedic (19.9%). Since October 2023, postoperative follow-up response rates have reached 96.5% at 48 hours, 77.7% at 7 days, and 72.1% at 30 days. The 30-day all-cause mortality rate is 0.7%. The most frequent postoperative adverse outcomes are pulmonary infection (13.0%), nausea (11.9%), hepatic dysfunction (9.9%), and intensive care unit admission (8.6%). Leveraging the PROTECT dataset, several prediction models for major postoperative complications have already been developed and implemented in clinical practice.

conclusionsPROTECT provides one of the largest and most comprehensive perioperative datasets for geriatric population. It enables detailed characterization of risk profiles, morbidity, and mortality in geriatric patients, supports identification of contributors to adverse outcomes, and offers a robust platform for developing perioperative risk assessment tools and multivariable models to support clinical decision-making. Future expansions will include extending follow-up to 90, 180, and 365 days and recruiting additional participating centers.

trial registrationRegistered at chictr.org.cn on 15/10/2025 (ChiCTR2500110517).

Indexed as

Clinical Decision-MakingPerioperative CarePostoperative ComplicationsAgedAged, 80 and overCohort StudiesFemaleGeriatric AnesthesiaHumansMaleProspective StudiesRisk AssessmentAnesthesiaCohort studyGeriatricPerioperativeReal-world dataSurgery

Identifiers

PMID42151893
PMCPMC13359416

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.