Literature DB >> 33710074

Pediatric Index of Mortality 3-An Evaluation of Function Among ICUs In South Africa.

Lincoln J Solomon1, Kuban D Naidoo, Ilse Appel, Linda G Doedens, Robin J Green, Michael A Long, Brenda Morrow, Noor M Parker, Denise Parris, Afke H Robroch, Shamiel Salie, Shivani A Singh, Andrew C Argent.   

Abstract

OBJECTIVES: To evaluate the performance of the Pediatric Index of Mortality 3 as mortality risk assessment model.
DESIGN: This prospective study included all admissions 30 days to 18 years old for 12 months during 2016 and 2017. Data gathered included the following: age and gender, diagnosis and reason for PICU admission, data specific for the Pediatric Index of Mortality 3 calculation, PICU outcomes (death or survival), and length of PICU stay.
SETTING: Nine units that care for children within tertiary or quaternary academic hospitals in South Africa. PATIENTS: All admissions 30 days to 18 years old, excluding premature infants, children who died within 2 hours of admission, or children transferred to other PICUs, and those older than 18 years old.
INTERVENTIONS: None.
MEASUREMENTS AND MAIN RESULTS: There were 3,681 admissions of which 2,253 (61.3%) were male. The median age was 18 months (interquartile range, 6-59.5 mo). There were 354 deaths (9.6%). The Pediatric Index of Mortality 3 predicted 277.47 deaths (7.5%). The overall standardized mortality ratio was 1.28. The area under the receiver operating characteristic curve was 0.81 (95% CI 0.79-0.83). The Hosmer-Lemeshow goodness-of-fit test statistic was 174.4 (p < 0.001). Standardized mortality ratio for all age groups was greater than 1. Standardized mortality ratio for diagnostic subgroups was mostly greater than 1 except for those whose reason for PICU admission was classified as accident, toxin and envenomation, and metabolic which had an standardized mortality ratio less than 1. There were similar proportions of respiratory patients, but significantly greater proportions of neurologic and cardiac (including postoperative) patients in the Pediatric Index of Mortality 3 derivation cohort than the South African cohort. In contrast, the South African cohort contained a significantly greater proportion of miscellaneous (including injury/accident victims) and postoperative noncardiac patients.
CONCLUSIONS: The Pediatric Index of Mortality 3 discrimination between death and survival among South African units was good. Case-mix differences between these units and the Pediatric Index of Mortality 3 derivation cohort may partly explain the poor calibration. We need to recalibrate Pediatric Index of Mortality 3 to the local setting.
Copyright ©2021The Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies.

Entities:  

Year:  2021        PMID: 33710074     DOI: 10.1097/PCC.0000000000002693

Source DB:  PubMed          Journal:  Pediatr Crit Care Med        ISSN: 1529-7535            Impact factor:   3.624


  3 in total

1.  Mortality risk prediction models: Methods of assessing discrimination and calibration and what they mean.

Authors:  L J Solomon
Journal:  South Afr J Crit Care       Date:  2022-05-06

2.  An Artificial Neural Network Model for Pediatric Mortality Prediction in Two Tertiary Pediatric Intensive Care Units in South Africa. A Development Study.

Authors:  Michael A Pienaar; Joseph B Sempa; Nicolaas Luwes; Lincoln J Solomon
Journal:  Front Pediatr       Date:  2022-02-25       Impact factor: 3.418

3.  Performance of Pediatric Risk of Mortality III and Pediatric Index of Mortality III Scores in Tertiary Pediatric Intensive Unit in Saudi Arabia.

Authors:  Ahmed S Alkhalifah; Abdulaziz AlSoqati; Jihad Zahraa
Journal:  Front Pediatr       Date:  2022-07-07       Impact factor: 3.569

  3 in total

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