Simultaneous prediction of new morbidity, mortality, and survival without new morbidity from pediatric intensive care: A new paradigm for outcomes assessment

Murray M. Pollack, Richard Holubkov, Tomohiko Funai, John T. Berger, Amy E. Clark, Kathleen Meert, Robert A. Berg, Joseph Carcillo, David L. Wessel, Frank Moler, Heidi Dalton, Christopher J.L. Newth, Thomas Shanley, Rick E. Harrison, Allan Doctor, Tammara L. Jenkins, Robert Tamburro, J. Michael Dean

Research output: Contribution to journalArticle

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Abstract

Objectives: Assessments of care including quality assessments adjusted for physiological status should include the development of new morbidities as well as mortalities. We hypothesized that morbidity, like mortality, is associated with physiological dysfunction and could be predicted simultaneously with mortality. Design: Prospective cohort study from December 4, 2011, to April 7, 2013. Setting: General and cardiac/cardiovascular PICUs at seven sites. Patients: Randomly selected PICU patients from their first PICU admission. Interventions: None. Measurements and Main Results: Among 10,078 admissions, the unadjusted morbidity rates (measured with the Functional Status Scale and defined as an increase of ? 3 from preillness to hospital discharge) were 4.6% (site range, 2.6-7.7%) and unadjusted mortality rates were 2.7% (site range, 1.3-5.0%). Morbidity and mortality were significantly (p < 0.001) associated with physiological instability (measured with the Pediatric Risk of Mortality III score) in dichotomous (survival and death) and trichotomous (survival without new morbidity, survival with new morbidity, and death) models without covariate adjustments. Morbidity risk increased with increasing Pediatric Risk of Mortality III scores and then decreased at the highest Pediatric Risk of Mortality III values as potential morbidities became mortalities. The trichotomous model with covariate adjustments included age, admission source, diagnostic factors, baseline Functional Status Scale, and the Pediatric Risk of Mortality III score. The three-level goodnessof-fit test indicated satisfactory performance for the derivation and validation sets (p > 0.20). Predictive ability assessed with the volume under the surface was 0.50 ± 0.019 (derivation) and 0.50 ± 0.034 (validation) (vs chance performance = 0.17). Sitelevel standardized morbidity ratios were more variable than standardized mortality ratios. Conclusions: New morbidities were associated with physiological status and can be modeled simultaneously with mortality. Trichotomous outcome models including both morbidity and mortality based on physiological status are suitable for research studies and quality and other outcome assessments. This approach may be applicable to other assessments presently based only on mortality.

Original languageEnglish (US)
Pages (from-to)1699-1709
Number of pages11
JournalCritical care medicine
Volume43
Issue number8
DOIs
StatePublished - Jan 1 2015

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Critical Care
Outcome Assessment (Health Care)
Pediatrics
Morbidity
Survival
Mortality
Quality of Health Care
Cohort Studies
Prospective Studies
Research

All Science Journal Classification (ASJC) codes

  • Critical Care and Intensive Care Medicine

Cite this

Pollack, Murray M. ; Holubkov, Richard ; Funai, Tomohiko ; Berger, John T. ; Clark, Amy E. ; Meert, Kathleen ; Berg, Robert A. ; Carcillo, Joseph ; Wessel, David L. ; Moler, Frank ; Dalton, Heidi ; Newth, Christopher J.L. ; Shanley, Thomas ; Harrison, Rick E. ; Doctor, Allan ; Jenkins, Tammara L. ; Tamburro, Robert ; Dean, J. Michael. / Simultaneous prediction of new morbidity, mortality, and survival without new morbidity from pediatric intensive care : A new paradigm for outcomes assessment. In: Critical care medicine. 2015 ; Vol. 43, No. 8. pp. 1699-1709.
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abstract = "Objectives: Assessments of care including quality assessments adjusted for physiological status should include the development of new morbidities as well as mortalities. We hypothesized that morbidity, like mortality, is associated with physiological dysfunction and could be predicted simultaneously with mortality. Design: Prospective cohort study from December 4, 2011, to April 7, 2013. Setting: General and cardiac/cardiovascular PICUs at seven sites. Patients: Randomly selected PICU patients from their first PICU admission. Interventions: None. Measurements and Main Results: Among 10,078 admissions, the unadjusted morbidity rates (measured with the Functional Status Scale and defined as an increase of ? 3 from preillness to hospital discharge) were 4.6{\%} (site range, 2.6-7.7{\%}) and unadjusted mortality rates were 2.7{\%} (site range, 1.3-5.0{\%}). Morbidity and mortality were significantly (p < 0.001) associated with physiological instability (measured with the Pediatric Risk of Mortality III score) in dichotomous (survival and death) and trichotomous (survival without new morbidity, survival with new morbidity, and death) models without covariate adjustments. Morbidity risk increased with increasing Pediatric Risk of Mortality III scores and then decreased at the highest Pediatric Risk of Mortality III values as potential morbidities became mortalities. The trichotomous model with covariate adjustments included age, admission source, diagnostic factors, baseline Functional Status Scale, and the Pediatric Risk of Mortality III score. The three-level goodnessof-fit test indicated satisfactory performance for the derivation and validation sets (p > 0.20). Predictive ability assessed with the volume under the surface was 0.50 ± 0.019 (derivation) and 0.50 ± 0.034 (validation) (vs chance performance = 0.17). Sitelevel standardized morbidity ratios were more variable than standardized mortality ratios. Conclusions: New morbidities were associated with physiological status and can be modeled simultaneously with mortality. Trichotomous outcome models including both morbidity and mortality based on physiological status are suitable for research studies and quality and other outcome assessments. This approach may be applicable to other assessments presently based only on mortality.",
author = "Pollack, {Murray M.} and Richard Holubkov and Tomohiko Funai and Berger, {John T.} and Clark, {Amy E.} and Kathleen Meert and Berg, {Robert A.} and Joseph Carcillo and Wessel, {David L.} and Frank Moler and Heidi Dalton and Newth, {Christopher J.L.} and Thomas Shanley and Harrison, {Rick E.} and Allan Doctor and Jenkins, {Tammara L.} and Robert Tamburro and Dean, {J. Michael}",
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Pollack, MM, Holubkov, R, Funai, T, Berger, JT, Clark, AE, Meert, K, Berg, RA, Carcillo, J, Wessel, DL, Moler, F, Dalton, H, Newth, CJL, Shanley, T, Harrison, RE, Doctor, A, Jenkins, TL, Tamburro, R & Dean, JM 2015, 'Simultaneous prediction of new morbidity, mortality, and survival without new morbidity from pediatric intensive care: A new paradigm for outcomes assessment', Critical care medicine, vol. 43, no. 8, pp. 1699-1709. https://doi.org/10.1097/CCM.0000000000001081

Simultaneous prediction of new morbidity, mortality, and survival without new morbidity from pediatric intensive care : A new paradigm for outcomes assessment. / Pollack, Murray M.; Holubkov, Richard; Funai, Tomohiko; Berger, John T.; Clark, Amy E.; Meert, Kathleen; Berg, Robert A.; Carcillo, Joseph; Wessel, David L.; Moler, Frank; Dalton, Heidi; Newth, Christopher J.L.; Shanley, Thomas; Harrison, Rick E.; Doctor, Allan; Jenkins, Tammara L.; Tamburro, Robert; Dean, J. Michael.

In: Critical care medicine, Vol. 43, No. 8, 01.01.2015, p. 1699-1709.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Simultaneous prediction of new morbidity, mortality, and survival without new morbidity from pediatric intensive care

T2 - A new paradigm for outcomes assessment

AU - Pollack, Murray M.

AU - Holubkov, Richard

AU - Funai, Tomohiko

AU - Berger, John T.

AU - Clark, Amy E.

AU - Meert, Kathleen

AU - Berg, Robert A.

AU - Carcillo, Joseph

AU - Wessel, David L.

AU - Moler, Frank

AU - Dalton, Heidi

AU - Newth, Christopher J.L.

AU - Shanley, Thomas

AU - Harrison, Rick E.

AU - Doctor, Allan

AU - Jenkins, Tammara L.

AU - Tamburro, Robert

AU - Dean, J. Michael

PY - 2015/1/1

Y1 - 2015/1/1

N2 - Objectives: Assessments of care including quality assessments adjusted for physiological status should include the development of new morbidities as well as mortalities. We hypothesized that morbidity, like mortality, is associated with physiological dysfunction and could be predicted simultaneously with mortality. Design: Prospective cohort study from December 4, 2011, to April 7, 2013. Setting: General and cardiac/cardiovascular PICUs at seven sites. Patients: Randomly selected PICU patients from their first PICU admission. Interventions: None. Measurements and Main Results: Among 10,078 admissions, the unadjusted morbidity rates (measured with the Functional Status Scale and defined as an increase of ? 3 from preillness to hospital discharge) were 4.6% (site range, 2.6-7.7%) and unadjusted mortality rates were 2.7% (site range, 1.3-5.0%). Morbidity and mortality were significantly (p < 0.001) associated with physiological instability (measured with the Pediatric Risk of Mortality III score) in dichotomous (survival and death) and trichotomous (survival without new morbidity, survival with new morbidity, and death) models without covariate adjustments. Morbidity risk increased with increasing Pediatric Risk of Mortality III scores and then decreased at the highest Pediatric Risk of Mortality III values as potential morbidities became mortalities. The trichotomous model with covariate adjustments included age, admission source, diagnostic factors, baseline Functional Status Scale, and the Pediatric Risk of Mortality III score. The three-level goodnessof-fit test indicated satisfactory performance for the derivation and validation sets (p > 0.20). Predictive ability assessed with the volume under the surface was 0.50 ± 0.019 (derivation) and 0.50 ± 0.034 (validation) (vs chance performance = 0.17). Sitelevel standardized morbidity ratios were more variable than standardized mortality ratios. Conclusions: New morbidities were associated with physiological status and can be modeled simultaneously with mortality. Trichotomous outcome models including both morbidity and mortality based on physiological status are suitable for research studies and quality and other outcome assessments. This approach may be applicable to other assessments presently based only on mortality.

AB - Objectives: Assessments of care including quality assessments adjusted for physiological status should include the development of new morbidities as well as mortalities. We hypothesized that morbidity, like mortality, is associated with physiological dysfunction and could be predicted simultaneously with mortality. Design: Prospective cohort study from December 4, 2011, to April 7, 2013. Setting: General and cardiac/cardiovascular PICUs at seven sites. Patients: Randomly selected PICU patients from their first PICU admission. Interventions: None. Measurements and Main Results: Among 10,078 admissions, the unadjusted morbidity rates (measured with the Functional Status Scale and defined as an increase of ? 3 from preillness to hospital discharge) were 4.6% (site range, 2.6-7.7%) and unadjusted mortality rates were 2.7% (site range, 1.3-5.0%). Morbidity and mortality were significantly (p < 0.001) associated with physiological instability (measured with the Pediatric Risk of Mortality III score) in dichotomous (survival and death) and trichotomous (survival without new morbidity, survival with new morbidity, and death) models without covariate adjustments. Morbidity risk increased with increasing Pediatric Risk of Mortality III scores and then decreased at the highest Pediatric Risk of Mortality III values as potential morbidities became mortalities. The trichotomous model with covariate adjustments included age, admission source, diagnostic factors, baseline Functional Status Scale, and the Pediatric Risk of Mortality III score. The three-level goodnessof-fit test indicated satisfactory performance for the derivation and validation sets (p > 0.20). Predictive ability assessed with the volume under the surface was 0.50 ± 0.019 (derivation) and 0.50 ± 0.034 (validation) (vs chance performance = 0.17). Sitelevel standardized morbidity ratios were more variable than standardized mortality ratios. Conclusions: New morbidities were associated with physiological status and can be modeled simultaneously with mortality. Trichotomous outcome models including both morbidity and mortality based on physiological status are suitable for research studies and quality and other outcome assessments. This approach may be applicable to other assessments presently based only on mortality.

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