Evidence map›Paper›PMID 37798030›Full record

Observational studyBMJ open2023

How to predict the death risk after an in-hospital cardiac arrest (IHCA) in intensive care unit? A retrospective double-centre cohort study from a tertiary hospital in China.

Youping Zhang, Caijun Rao, Xiao Ran, Hongjie Hu, Liang Jing, Shu Peng, Wei Zhu, Shusheng Li

Abstract readObservational Study
In one paragraph

Observational study in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Article
  4. 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

8 authors.

Youping ZhangDepartment of Emergency Medicine, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Caijun RaoDepartment of Geriatric, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Xiao RanDepartment of Emergency Medicine, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Hongjie HuDepartment of Emergency Medicine, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Liang JingDepartment of Emergency Medicine, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Shu PengDepartment of Thoracic Surgery, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Wei ZhuDepartment of Emergency Medicine, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Shusheng LiDepartment of Emergency Medicine, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China lishusheng@hust.edu.cn.ORCID 0000-0002-8799-6394

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesOur objective is to develop a prediction tool to predict the death after in-hospital cardiac arrest (IHCA).

designWe conducted a retrospective double-centre observational study of IHCA patients from January 2015 to December 2021. Data including prearrest diagnosis, clinical features of the IHCA and laboratory results after admission were collected and analysed. Logistic regression analysis was used for multivariate analyses to identify the risk factors for death. A nomogram was formulated and internally evaluated by the boot validation and the area under the curve (AUC). Performance of the nomogram was further accessed by Kaplan-Meier survival curves for patients who survived the initial IHCA.

settingIntensive care unit, Tongji Hospital, China.

participantsAdult patients (≥18 years) with IHCA after admission. Pregnant women, patients with 'do not resuscitation' order and patients treated with extracorporeal membrane oxygenation were excluded.

interventionsNone. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was the death after IHCA.

resultsPatients (n=561) were divided into two groups: non-sustained return of spontaneous circulation (ROSC) group (n=241) and sustained ROSC group (n=320). Significant differences were found in sex (p=0.006), cardiopulmonary resuscitation (CPR) duration (p<0.001), total duration of CPR (p=0.014), rearrest (p<0.001) and length of stay (p=0.004) between two groups. Multivariate analysis identified that rearrest, duration of CPR and length of stay were independently associated with death. The nomogram including these three factors was well validated using boot calibration plot and exhibited excellent discriminative ability (AUC 0.88, 95% CI 0.83 to 0.93). The tertiles of patients in sustained ROSC group stratified by anticipated probability of death revealed significantly different survival rate (p<0.001).

conclusionsOur proposed nomogram based on these three factors is a simple, robust prediction model to accurately predict the death after IHCA.

Indexed as

Cardiopulmonary ResuscitationHeart ArrestAdultChinaCohort StudiesFemaleHumansIntensive Care UnitsPregnancyRetrospective StudiesTertiary Care CentersAdult intensive & critical careCardiopulmonary ResuscitationINTENSIVE & CRITICAL CARE

Identifiers

PMID37798030
PMCPMC10565198

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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.