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Biomarker-based score for predicting in-hospital mortality of children admitted to the intensive care unit
  1. Yin Zhang1,2,
  2. Qingxia Shi1,
  3. Guochao Zhong3,
  4. Xun Lei4,
  5. Jilei Lin5,
  6. Zhou Fu1,
  7. Jihong Dai1
  1. 1Department of Respiratory Disease, Children’s Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing, China
  2. 2Department of Respiratory and Critical Care Medicine, West China School of Medicine and West China Hospital, Sichuan University, Chengdu, China
  3. 3Department of Hepatobiliary Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
  4. 4School of Public Health and Management, Chongqing Medical University, Chongqing, China
  5. 5Department of Respiratory Disease, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
  1. Correspondence to Professor Jihong Dai, Children's Hospital of Chongqing Medical University, Chongqing 400014, China; danieljh{at}163.com

Abstract

This study aims to establish a new scoring system based on biomarkers for predicting in-hospital mortality of children admitted to the pediatric intensive care unit (PICU). The biomarkers were chosen using the least absolute shrinkage and selection operator (LASSO)-logistic regression in this observational case-control study. The performance of the new predictive model was evaluated by the area under the receiver operating characteristic curve (AUC). Calibration plot was established to validate the new score accompanied by the Hosmer-Lemeshow test. There were 8818 patients included in this study. Finally, six predictors were included in the LASSO-regression model. Albumin <40 g/L, lactate dehydrogenase >452 U/L, lactate >3.2 mmol/L, urea >5.6 mmol/L, arterial PH <7.3 and glucose >6.9 mmol/L were treated as risk factors for higher mortality. The new score ranged from 1 to 6 among all the included patients. In the training set, the AUC of the probability of in-hospital mortality for the new predictive model was 0.81 (95% CI 0.79 to 0.84), which is larger than for the Pediatric Critical Illness Score (PCIS) (0.69, 95% CI 0.66 to 0.72). Similarly, in the validating set, the AUC of the probability of in-hospital mortality was larger for the new score (0.80, 95% CI 0.77 to 0.84) than for PCIS (0.67, 95% CI 0.63 to 0.72). The calibration plot and Hosmer-Lemeshow test showed excellent calibration. The calculated ORs showed a trend that higher scores indicated higher risk of death (p value for trend <0.001). In summary, this study develops and validates a totally biomarker-based new score to predict in-hospital mortality for pediatric patients admitted to PICU. More attention and more positive care and treatment should be given to children with a higher score.

  • biomarkers
  • children
  • in-hospital mortality
  • intensive care unit

Data availability statement

Data are available upon reasonable request.

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Data availability statement

Data are available upon reasonable request.

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Footnotes

  • Contributors YZ conceptualized and designed the study, supervised data collection, carried out the initial analyses, drafted the initial manuscript. QS designed the data collection instruments, collected data. GZ and XL coordinated and supervised data collection, assisted in the statistical analysis and carried out the initial analyses. JL and ZF coordinated and supervised data collection, and critically reviewed the manuscript for important intellectual content. JD conceptualized and designed the study, supervised data collection, reviewed and revised the manuscript. All authors read and approved the final manuscript.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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