Evidence map›Paper›PMID 30505484›Full record

ArticleJournal of thoracic disease2018

A modified acute respiratory distress syndrome prediction score: a multicenter cohort study in China.

Jianfeng Xie, Ling Liu, Yi Yang, Wenkui Yu, Maoqin Li, Kaijiang Yu, Ruiqiang Zheng, Jie Yan, Xue Wang, Guolong Cai and 6 more

Registry-linked trialOpen access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of thoracic disease, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01666834 (Southeast Univerity), which is not on this map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.5field-weighted citation impact, top 17% 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.

NCT01666834 completednot on this map

Southeast Univerity

TypeobservationalSponsorSoutheast University, ChinaRan2012 to 2013Enrolled555ConditionsRespiratory Failure, Acute Respiratory Distress Syndrome
3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 17 citations in OpenAlex.

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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

16 authors at 9 institutions in 1 country.

Jianfeng XieDepartment of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing 210009, China.
Ling LiuDepartment of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing 210009, China.
Yi YangDepartment of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing 210009, China.
Wenkui YuDepartment of Critical Care Medicine, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China.
Maoqin LiDepartment of Critical Care Medicine, Xuzhou Central Hospital, Xuzhou 221009, China.
Kaijiang YuDepartment of Critical Care Medicine, Harbin Medical University Cancer Hospital, Harbin Medical University, Harbin 150040, China.
Ruiqiang ZhengDepartment of Critical Care Medicine, Subei People's Hospital, School of Medicine, Yangzhou University, Yangzhou 225001, China.
Jie YanDepartment of Critical Care Medicine, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi 214002, China.
Xue WangDepartment of Critical Care Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China.
Guolong CaiDepartment of Critical Care Medicine, Zhejiang Hospital, Hangzhou 310013, China.
Jianguo LiDepartment of Critical Care Medicine, Zhongnan Hospital, Wuhan University, 430071, Wuhan, China.
Qin GuDepartment of Critical Care Medicine, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing 210008, China.
Hongsheng ZhaoDepartment of Critical Care Medicine, The First Affiliated Hospital of Nantong University, Nantong 226001, China.
Xinwei MuDepartment of Critical Care Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China.
Xiaochun MaDepartment of Critical Care Medicine, The First Hospital of China Medical University, Shenyang 110001, China.
Haibo QiuDepartment of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing 210009, China.
Zhongda Hospital Southeast University · CNNanjing General Hospital of Nanjing Military Command · CNChina Medical University · CNFirst Affiliated Hospital of Xi'an Jiaotong University · CNHarbin Medical University · CNNanjing Medical University · CNXuzhou Central Hospital · CNYangzhou University · CNZhejiang Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEarly recognition of the risks of acute respiratory distress syndrome (ARDS) and prevention of the development of ARDS may be more effective in improving patient outcomes. We performed the present study to determine the ARDS risk factors in a Chinese population and validate a score to predict the development of ARDS.

methodsThis was an observational multicenter cohort study performed in 13 tertiary hospitals in China. Patients admitted into participating intensive care units (ICUs) from January 1 to January 31, 2012, and from January 1 to January 10, 2013, were enrolled in a retrospective derivation cohort and a prospective validation cohort, respectively. In the derivation cohort, the potential risk factors of ARDS were collected. The confirmed risk factors were determined with univariate and multivariate logistic regression analyses, and then the modified ARDS prediction score (MAPS) was established. We prospectively enrolled patients to verify the accuracy of MAPS.

resultsA total of 479 and 198 patients were enrolled into the retrospective derivation cohort and the prospective validation cohort, respectively. A total of 93 (19.4%) patients developed ARDS in the derivation cohort. Acute pancreatitis, pneumonia, hypoalbuminemia, acidosis, and high respiratory rate were the risk factors for ARDS. The MAPS discriminated patients who developed ARDS from those who did not, with an area under the curve (AUC) of 0.809 [95% confidence interval (CI), 0.758-0.859, P<0.001]. In the prospective validation cohort, performance of the MAPS was similar to the retrospective derivation cohort, with an AUC of 0.792 (95% CI, 0.717-0.867, P<0.001). The lung injury prediction score (LIPS) showed a predicted value of an AUC of 0.770 (95% CI, 0.728-0.812, P<0.001) in our patients, which was significantly lower than our score (P<0.046).

conclusionsThe MAPS based on risk factors could help the clinician to predict patients who will develop ARDS.

trial registrationClinicalTrials.gov NCT01666834.

Indexed as

Acute respiratory distress syndrome (ARDS)adultprediction scoreprevention

Identifiers

PMID30505484
PMCPMC6236166
OpenAlexW2895827636

What OpenQuestion holds

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Registered trials

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.