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Performance of Three Mortality Prediction Scores and Evaluation of Important Determinants in Eight Pediatric Intensive Care Units in China

Background: The mortality prediction scores were widely used in pediatric intensive care units. However, their performances were unclear in Chinese patients and there were also no reports based on large sample sizes in China. This study aims to evaluate the performances of three existing severity as...

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Published in:Frontiers in pediatrics 2020-09, Vol.8, p.522-522
Main Authors: Zhang, Zhengzheng, Huang, Xiangyuan, Wang, Ying, Li, Ying, Miao, Hongjun, Zhang, Chenmei, Pan, Guoquan, Zhang, Yucai, Zhu, Xiaodong, Chen, Weiming, Li, Juanzhen, Su, Dongni, Bi, Yanlong, Chen, Zhenjie, Jin, Bingxin, Miao, Huijie, Kong, Xiangmei, Cheng, Ye, Chen, Yang, Yan, Gangfeng, Yan, Weili, Lu, Guoping
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container_title Frontiers in pediatrics
container_volume 8
creator Zhang, Zhengzheng
Huang, Xiangyuan
Wang, Ying
Li, Ying
Miao, Hongjun
Zhang, Chenmei
Pan, Guoquan
Zhang, Yucai
Zhu, Xiaodong
Chen, Weiming
Li, Juanzhen
Su, Dongni
Bi, Yanlong
Chen, Zhenjie
Jin, Bingxin
Miao, Huijie
Kong, Xiangmei
Cheng, Ye
Chen, Yang
Yan, Gangfeng
Yan, Weili
Lu, Guoping
description Background: The mortality prediction scores were widely used in pediatric intensive care units. However, their performances were unclear in Chinese patients and there were also no reports based on large sample sizes in China. This study aims to evaluate the performances of three existing severity assessment scores in predicting PICU mortality and to identify important determinants. Methods: This prospective observational cohort study was carried out in eight multidisciplinary, tertiary-care PICUs of teaching hospitals in China. All eligible patients admitted to the PICUs between Aug 1, 2016, and Jul 31, 2017, were consecutively enrolled, among whom 3,957 were included for analysis. We calculated PCIS, PRISM IV, and PELOD-2 scores based on patient data collected in the first 24 h after PICU admission. The in-hospital mortality was defined as all-cause death within 3 months after admission. The discrimination of mortality was assessed using the area under the receiver-operating characteristics curve (AUC) and calibrated using the Hosmer–Lemeshow goodness-of-fit test. Results: A total of 4,770 eligible patients were recruited (median age 18.2 months, overall mortality rate 4.7%, median length of PICU stay 6 days), and 3,957 participants were included in the analysis. The AUC (95% confidence intervals, CI) were 0.74 (0.71–0.78), 0.76 (0.73–0.80), and 0.80 (0.77–0.83) for PCIS, PRISM IV, and PELOD-2, respectively. The Hosmer–Lemeshow test gave a chi-square of 3.16 for PCIS, 2.16 for PRISM IV and 4.81 for PELOD-2 ( p ≥ 0.19). Cox regression identified five predictors from the items of scores better associated with higher death risk, with a C-index of 0.83 (95%CI 0.79–0.86), including higher platelet (HR = 1.85, 95% CI 1.59–2.16), invasive ventilation (HR = 1.40, 1.26–1.55), pupillary light reflex (HR = 1.31, 95% CI 1.22–1.42) scores, lower pH (HR 0.89, 0.84–0.94), and extreme PaO 2 (HR 2.60, 95% CI 1.61–4.19 for the 1st quantile vs. 4th quantile) scores. Conclusions: Performances of the three scores in predicting PICU mortality are comparable, and five predictors were identified with better prediction to PICU mortality in Chinese patients.
doi_str_mv 10.3389/fped.2020.00522
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However, their performances were unclear in Chinese patients and there were also no reports based on large sample sizes in China. This study aims to evaluate the performances of three existing severity assessment scores in predicting PICU mortality and to identify important determinants. Methods: This prospective observational cohort study was carried out in eight multidisciplinary, tertiary-care PICUs of teaching hospitals in China. All eligible patients admitted to the PICUs between Aug 1, 2016, and Jul 31, 2017, were consecutively enrolled, among whom 3,957 were included for analysis. We calculated PCIS, PRISM IV, and PELOD-2 scores based on patient data collected in the first 24 h after PICU admission. The in-hospital mortality was defined as all-cause death within 3 months after admission. The discrimination of mortality was assessed using the area under the receiver-operating characteristics curve (AUC) and calibrated using the Hosmer–Lemeshow goodness-of-fit test. Results: A total of 4,770 eligible patients were recruited (median age 18.2 months, overall mortality rate 4.7%, median length of PICU stay 6 days), and 3,957 participants were included in the analysis. The AUC (95% confidence intervals, CI) were 0.74 (0.71–0.78), 0.76 (0.73–0.80), and 0.80 (0.77–0.83) for PCIS, PRISM IV, and PELOD-2, respectively. The Hosmer–Lemeshow test gave a chi-square of 3.16 for PCIS, 2.16 for PRISM IV and 4.81 for PELOD-2 ( p ≥ 0.19). Cox regression identified five predictors from the items of scores better associated with higher death risk, with a C-index of 0.83 (95%CI 0.79–0.86), including higher platelet (HR = 1.85, 95% CI 1.59–2.16), invasive ventilation (HR = 1.40, 1.26–1.55), pupillary light reflex (HR = 1.31, 95% CI 1.22–1.42) scores, lower pH (HR 0.89, 0.84–0.94), and extreme PaO 2 (HR 2.60, 95% CI 1.61–4.19 for the 1st quantile vs. 4th quantile) scores. Conclusions: Performances of the three scores in predicting PICU mortality are comparable, and five predictors were identified with better prediction to PICU mortality in Chinese patients.</description><identifier>ISSN: 2296-2360</identifier><identifier>EISSN: 2296-2360</identifier><identifier>DOI: 10.3389/fped.2020.00522</identifier><identifier>PMID: 33014927</identifier><language>eng</language><publisher>Frontiers Media S.A</publisher><subject>cohort study ; model validation ; mortality ; pediatric intensive care unit ; Pediatrics ; prediction model</subject><ispartof>Frontiers in pediatrics, 2020-09, Vol.8, p.522-522</ispartof><rights>Copyright © 2020 Zhang, Huang, Wang, Li, Miao, Zhang, Pan, Zhang, Zhu, Chen, Li, Su, Bi, Chen, Jin, Miao, Kong, Cheng, Chen, Yan, Yan and Lu. 2020 Zhang, Huang, Wang, Li, Miao, Zhang, Pan, Zhang, Zhu, Chen, Li, Su, Bi, Chen, Jin, Miao, Kong, Cheng, Chen, Yan, Yan and Lu</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c436t-a17e140123204c9af5e4d9bb23d95dd55780e04aee2741e46692ebd1775d0c0c3</citedby><cites>FETCH-LOGICAL-c436t-a17e140123204c9af5e4d9bb23d95dd55780e04aee2741e46692ebd1775d0c0c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7505927/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7505927/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids></links><search><creatorcontrib>Zhang, Zhengzheng</creatorcontrib><creatorcontrib>Huang, Xiangyuan</creatorcontrib><creatorcontrib>Wang, Ying</creatorcontrib><creatorcontrib>Li, Ying</creatorcontrib><creatorcontrib>Miao, Hongjun</creatorcontrib><creatorcontrib>Zhang, Chenmei</creatorcontrib><creatorcontrib>Pan, Guoquan</creatorcontrib><creatorcontrib>Zhang, Yucai</creatorcontrib><creatorcontrib>Zhu, Xiaodong</creatorcontrib><creatorcontrib>Chen, Weiming</creatorcontrib><creatorcontrib>Li, Juanzhen</creatorcontrib><creatorcontrib>Su, Dongni</creatorcontrib><creatorcontrib>Bi, Yanlong</creatorcontrib><creatorcontrib>Chen, Zhenjie</creatorcontrib><creatorcontrib>Jin, Bingxin</creatorcontrib><creatorcontrib>Miao, Huijie</creatorcontrib><creatorcontrib>Kong, Xiangmei</creatorcontrib><creatorcontrib>Cheng, Ye</creatorcontrib><creatorcontrib>Chen, Yang</creatorcontrib><creatorcontrib>Yan, Gangfeng</creatorcontrib><creatorcontrib>Yan, Weili</creatorcontrib><creatorcontrib>Lu, Guoping</creatorcontrib><title>Performance of Three Mortality Prediction Scores and Evaluation of Important Determinants in Eight Pediatric Intensive Care Units in China</title><title>Frontiers in pediatrics</title><description>Background: The mortality prediction scores were widely used in pediatric intensive care units. However, their performances were unclear in Chinese patients and there were also no reports based on large sample sizes in China. This study aims to evaluate the performances of three existing severity assessment scores in predicting PICU mortality and to identify important determinants. Methods: This prospective observational cohort study was carried out in eight multidisciplinary, tertiary-care PICUs of teaching hospitals in China. All eligible patients admitted to the PICUs between Aug 1, 2016, and Jul 31, 2017, were consecutively enrolled, among whom 3,957 were included for analysis. We calculated PCIS, PRISM IV, and PELOD-2 scores based on patient data collected in the first 24 h after PICU admission. The in-hospital mortality was defined as all-cause death within 3 months after admission. The discrimination of mortality was assessed using the area under the receiver-operating characteristics curve (AUC) and calibrated using the Hosmer–Lemeshow goodness-of-fit test. Results: A total of 4,770 eligible patients were recruited (median age 18.2 months, overall mortality rate 4.7%, median length of PICU stay 6 days), and 3,957 participants were included in the analysis. The AUC (95% confidence intervals, CI) were 0.74 (0.71–0.78), 0.76 (0.73–0.80), and 0.80 (0.77–0.83) for PCIS, PRISM IV, and PELOD-2, respectively. The Hosmer–Lemeshow test gave a chi-square of 3.16 for PCIS, 2.16 for PRISM IV and 4.81 for PELOD-2 ( p ≥ 0.19). Cox regression identified five predictors from the items of scores better associated with higher death risk, with a C-index of 0.83 (95%CI 0.79–0.86), including higher platelet (HR = 1.85, 95% CI 1.59–2.16), invasive ventilation (HR = 1.40, 1.26–1.55), pupillary light reflex (HR = 1.31, 95% CI 1.22–1.42) scores, lower pH (HR 0.89, 0.84–0.94), and extreme PaO 2 (HR 2.60, 95% CI 1.61–4.19 for the 1st quantile vs. 4th quantile) scores. Conclusions: Performances of the three scores in predicting PICU mortality are comparable, and five predictors were identified with better prediction to PICU mortality in Chinese patients.</description><subject>cohort study</subject><subject>model validation</subject><subject>mortality</subject><subject>pediatric intensive care unit</subject><subject>Pediatrics</subject><subject>prediction model</subject><issn>2296-2360</issn><issn>2296-2360</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNpVkk1v2zAMho1hw1p0Pe-q4y5J9WlHlwFDlm4BOizA2rNAS3SiwpYySQnQv7BfPTspipYXEuTLhwe-VfWZ0bkQC33T7dHNOeV0Tqni_F11ybmuZ1zU9P2r-qK6zvmRjqEbqpj6WF0IQZnUvLms_m0wdTENECyS2JH7XUIkv2Iq0PvyRDYJnbfFx0D-2JgwEwiOrI7QH-DUHXfWw37Sh0K-Y8E0-DDWmfhAVn67K2QzIqAkb8k6FAzZH5EsISF5CP6sW-7GnU_Vhw76jNfP-ap6uF3dL3_O7n7_WC-_3c2sFHWZAWuQScq44FRaDZ1C6XTbcuG0ck6pZkGRSkDkjWQo61pzbB1rGuWopVZcVesz10V4NPvkB0hPJoI3p0ZMWwOpeNujqWmr0ErFrXaylW2rAaRWEm2HnNaLkfX1zNof2gGdxVAS9G-gbyfB78w2Hk2jqBofMAK-PANS_HvAXMzgs8W-h4DxkA2XclGL8WvTrZuz1KaYc8Lu5QyjZjKEmQxhJkOYkyHEf8YIqnw</recordid><startdate>20200908</startdate><enddate>20200908</enddate><creator>Zhang, Zhengzheng</creator><creator>Huang, Xiangyuan</creator><creator>Wang, Ying</creator><creator>Li, Ying</creator><creator>Miao, Hongjun</creator><creator>Zhang, Chenmei</creator><creator>Pan, Guoquan</creator><creator>Zhang, Yucai</creator><creator>Zhu, Xiaodong</creator><creator>Chen, Weiming</creator><creator>Li, Juanzhen</creator><creator>Su, Dongni</creator><creator>Bi, Yanlong</creator><creator>Chen, Zhenjie</creator><creator>Jin, Bingxin</creator><creator>Miao, Huijie</creator><creator>Kong, Xiangmei</creator><creator>Cheng, Ye</creator><creator>Chen, Yang</creator><creator>Yan, Gangfeng</creator><creator>Yan, Weili</creator><creator>Lu, Guoping</creator><general>Frontiers Media S.A</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20200908</creationdate><title>Performance of Three Mortality Prediction Scores and Evaluation of Important Determinants in Eight Pediatric Intensive Care Units in China</title><author>Zhang, Zhengzheng ; 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However, their performances were unclear in Chinese patients and there were also no reports based on large sample sizes in China. This study aims to evaluate the performances of three existing severity assessment scores in predicting PICU mortality and to identify important determinants. Methods: This prospective observational cohort study was carried out in eight multidisciplinary, tertiary-care PICUs of teaching hospitals in China. All eligible patients admitted to the PICUs between Aug 1, 2016, and Jul 31, 2017, were consecutively enrolled, among whom 3,957 were included for analysis. We calculated PCIS, PRISM IV, and PELOD-2 scores based on patient data collected in the first 24 h after PICU admission. The in-hospital mortality was defined as all-cause death within 3 months after admission. The discrimination of mortality was assessed using the area under the receiver-operating characteristics curve (AUC) and calibrated using the Hosmer–Lemeshow goodness-of-fit test. Results: A total of 4,770 eligible patients were recruited (median age 18.2 months, overall mortality rate 4.7%, median length of PICU stay 6 days), and 3,957 participants were included in the analysis. The AUC (95% confidence intervals, CI) were 0.74 (0.71–0.78), 0.76 (0.73–0.80), and 0.80 (0.77–0.83) for PCIS, PRISM IV, and PELOD-2, respectively. The Hosmer–Lemeshow test gave a chi-square of 3.16 for PCIS, 2.16 for PRISM IV and 4.81 for PELOD-2 ( p ≥ 0.19). Cox regression identified five predictors from the items of scores better associated with higher death risk, with a C-index of 0.83 (95%CI 0.79–0.86), including higher platelet (HR = 1.85, 95% CI 1.59–2.16), invasive ventilation (HR = 1.40, 1.26–1.55), pupillary light reflex (HR = 1.31, 95% CI 1.22–1.42) scores, lower pH (HR 0.89, 0.84–0.94), and extreme PaO 2 (HR 2.60, 95% CI 1.61–4.19 for the 1st quantile vs. 4th quantile) scores. Conclusions: Performances of the three scores in predicting PICU mortality are comparable, and five predictors were identified with better prediction to PICU mortality in Chinese patients.</abstract><pub>Frontiers Media S.A</pub><pmid>33014927</pmid><doi>10.3389/fped.2020.00522</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record>
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model validation
mortality
pediatric intensive care unit
Pediatrics
prediction model
title Performance of Three Mortality Prediction Scores and Evaluation of Important Determinants in Eight Pediatric Intensive Care Units in China
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