Evidence map›Paper›PMID 34764177›Full record

ArticleBMJ open2021

Neutrophil-to-lymphocyte ratio as a predictor of mortality in intensive care unit patients: a retrospective analysis of the Medical Information Mart for Intensive Care III Database.

Xie Wu, Qipeng Luo, Zhanhao Su, Yinan Li, Hongbai Wang, Qiao Liu, Su Yuan, Fuxia Yan

Abstract read
In one paragraph

Article in BMJ open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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  8. Developing Augmented Pro-SOFA and Pro-SAPS Models by Integrating Biomarkers PCT, NLR, and CRP with SOFA and SAPS-III Scores.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2024
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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

8 authors.

Xie WuDepartment of Anesthesiology, Chinese Academy of Medical Sciences and Peking Union Medical College Fuwai Hospital, Xicheng District, Beijing, China.
Qipeng LuoDepartment of Pain Medicine, Peking University Third Hospital, Beijing, China.
Zhanhao SuDepartment of Pediatric Cardiac Surgery, Chinese Academy of Medical Sciences and Peking Union Medical College Fuwai Hospital, Beijing, China.
Yinan LiDepartment of Anesthesiology, Chinese Academy of Medical Sciences and Peking Union Medical College Fuwai Hospital, Xicheng District, Beijing, China.
Hongbai WangDepartment of Anesthesiology, Chinese Academy of Medical Sciences and Peking Union Medical College Fuwai Hospital, Xicheng District, Beijing, China.
Qiao LiuDepartment of Anesthesiology, Chinese Academy of Medical Sciences and Peking Union Medical College Fuwai Hospital, Xicheng District, Beijing, China.
Su YuanDepartment of Anesthesiology, Chinese Academy of Medical Sciences and Peking Union Medical College Fuwai Hospital, Xicheng District, Beijing, China.ORCID 0000-0003-3924-7548
Fuxia YanDepartment of Anesthesiology, Chinese Academy of Medical Sciences and Peking Union Medical College Fuwai Hospital, Xicheng District, Beijing, China yanfuxia@sina.com.ORCID 0000-0001-5054-0775

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesIdentifying high-risk patients in the intensive care unit (ICU) is important given the high mortality rate. However, existing scoring systems lack easily accessible, low-cost and effective inflammatory markers. We aimed to identify inflammatory markers in routine blood tests to predict mortality in ICU patients and evaluate their predictive power.

designRetrospective case-control study.

settingSingle secondary care centre.

participantsWe analysed data from the Medical Information Mart for Intensive Care III database. A total of 21 822 ICU patients were enrolled and divided into survival and death groups based on in-hospital mortality. PRIMARY AND SECONDARY OUTCOME MEASURES: The predictive values of potential inflammatory markers were evaluated and compared using receiver operating characteristic curve analysis. After identifying the neutrophil-to-lymphocyte ratio (NLR) as having the best predictive ability, patients were redivided into low (≤1), medium (1-6) and high (>6) NLR groups. Univariate and multivariate logistic regression analyses were performed to evaluate the association between the NLR and mortality. The area under the curve (AUC), net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were used to assess whether incorporating the NLR could improve the predictive power of existing scoring systems.

resultsThe NLR had the best predictive ability (AUC: 0.609; p<0.001). In-hospital mortality rates were significantly higher in the low (OR (OR): 2.09; 95% CI 1.64 to 2.66) and high (OR 1.64; 95% CI 1.50 to 1.80) NLR groups than in the medium NLR group. Adding the NLR to the Simplified Acute Physiology Score II improved the AUC from 0.789 to 0.798, with an NRI and IDI of 16.64% and 0.27%, respectively.

conclusionsThe NLR predicted mortality in ICU patients well. Both low and high NLRs were associated with elevated mortality rates, including the NLR may improve the predictive power of the Simplified Acute Physiology Score II.

Indexed as

LymphocytesNeutrophilsCase-Control StudiesCritical CareHumansIntensive Care UnitsPrognosisRetrospective Studiesadult intensive & critical careadverse eventsrisk management

Identifiers

PMID34764177
PMCPMC8587351

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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.