Comparison of Cox and Gray’s survival models in severe sepsis*

Kasal, Jan; Jovanovic, Zlatko; Clermont, Gilles; Weissfeld, Lisa A.; Kaplan, Vladimír; Watson, R. Scott; Angus, Derek C.

doi:10.1097/01.ccm.0000114819.37569.4b

Cited by 29 publications

(28 citation statements)

References 23 publications

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“…We examined time to mortality censored at 1 year between the three FB groups using Kaplan Meier failure plots and compared using Log-rank test. We fitted Gray’s model (20) (supplement S5) to estimate risk-adjusted hazard ratios (AHR) for association between positive or negative FB, compared with even FB (reference category), and time to mortality censored at 1 year using five time nodes and six intervals, since Cox models failed proportionality assumptions for several covariates. We also fitted multivariable logistic regression and estimated risk-adjusted odds ratios (AOR) for mortality and renal recovery.…”

Section: Methodsmentioning

confidence: 99%

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Both Positive and Negative Fluid Balance May Be Associated With Reduced Long-Term Survival in the Critically Ill

Balakumar

Murugan

Sileanu

et al. 2017

Critical Care Medicine

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115

102

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Objective Among critically ill patients with acute kidney injury, exposure to positive fluid balance (FB), compared with negative FB, has been associated with mortality and impaired renal recovery. However, its unclear whether positive and negative FB are associated with poor outcome compared to patients with even fluid balance (euvolemia). In this study, we examined the association between exposure to positive or negative FB, compared with even FB, on one-year mortality and renal recovery. Design Retrospective cohort study. Setting Eight medical-surgical ICUs at the University of Pittsburgh Medical Center, Pittsburgh, PA. Patients Critically ill patients admitted between July 2000 through October 2008. Interventions None Measurements & Main Results Among 18,084 patients, FB was categorized as negative (<0%); even (0 % – < 5%); or positive (≥5%). Following propensity matching, positive FB, compared with even or negative FB, was associated with increased mortality (30.3% vs. 21.1% vs. 22%, respectively, P<0.001). Using Gray’s model, negative compared with even FB, was associated with lower short-term mortality (adjusted hazard ratio range [AHR], 0.81, 95%CI, 0.68–0.96) but higher long-term mortality (AHR range, 1.16–1.22, P=0.004). Conversely, positive FB, was associated with higher mortality throughout one-year (AHR range, 1.30–1.92, P<0.001), which was attenuated in those who received RRT (Positive FB*RRT interaction AHR range, 0.43–0.89, P<0.001). Of patients receiving RRT, neither positive (adjusted odds ratio [AOR], 95% CI, 0.98, 0.68–1.4) nor negative (AOR, 0.81, 95% CI, 0.43–1.55) FB was associated with renal recovery. Conclusions Among critically ill patients, exposure to positive or negative FB, compared with even FB, was associated with higher one-year mortality. This mortality risk associated with positive FB, however, was attenuated by use of RRT. We found no association between FB and renal recovery.

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Section: Methodsmentioning

confidence: 99%

“… $ Shown are adjusted hazard ratios (AHR) estimated from Gray’s model (20) for association between FB and mortality for each time interval. Models for all subjects, non-RRT, and non-AKI subgroups included six time intervals and five time nodes.…”

Section: Figurementioning

confidence: 99%

Both Positive and Negative Fluid Balance May Be Associated With Reduced Long-Term Survival in the Critically Ill

Balakumar

Murugan

Sileanu

et al. 2017

Critical Care Medicine

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115

102

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“…Compared with subjects with normal vital signs at hospital discharge, the 225 (13%) subjects with abnormal vital signs had higher IL-6 concentrations (10.5 vs. 6.5 pg/ml, P , 0.001), but no differences in IL-10 concentrations were seen between the * Ranges of hazards ratios are reported for 10 time points over 1 year using the Gray's model (20).…”

Section: Cytokine Concentrations and All-cause Mortalitymentioning

confidence: 99%

“…Maximum likelihood estimation is used to obtain estimates of the regression coefficients. We used a Gray's survival model to estimate hazard ratios (HRs) for circulating cytokine concentrations and death over 1 year because the hazards failed Cox's proportionality assumption (20). The Gray's model estimates HRs over 10 intervals (with 11 time nodes) and thus provides a detailed description of the change in HRs over 1 year.…”

Section: Statistical Analysesmentioning

confidence: 99%

Inflammatory Markers at Hospital Discharge Predict Subsequent Mortality after Pneumonia and Sepsis

Yende

D’Angelo

Kellum

et al. 2008

Am J Respir Crit Care Med

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386

283

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Rationale: Survivors of hospitalization for community-acquired pneumonia (CAP) are at increased risk of cardiovascular events, repeat infections, and death in the following months but the cause is unknown. Objectives: To investigate whether persistent inflammation, defined as elevating circulating inflammatory markers at hospital discharge, is associated with subsequent outcomes. Methods: Prospective cohort study at 28 sites. Measurements and Main Results: We used standard criteria to define CAP and the National Death Index to determine all-cause and causespecific 1-year mortality. At hospital discharge, 1,799 subjects (77.5%) were alive and vital signs had returned to normal in 1,512 (87%) subjects. The geometric means (6SD) for circulating IL-6 and IL-10 concentrations were 6.9 (61) pg/ml and 1.2 (61.1) pg/ml. At 1 year, 307 (17.1%) subjects had died. Higher IL-6 and IL-10 concentrations at hospital discharge were associated with an increased risk of death, which gradually fell over time. Using Gray's survival model, the associations were independent of demographics, comorbidities, and severity of illness (for each log-unit increase, the range of adjusted hazard ratios [HRs] for IL-6 were 1.02-1.46, P , 0.0001, and for IL-10 were 1.17-1.44, P 5 0.01). The ranges of HRs for each log-unit increase in IL-6 and IL-10 concentrations among subjects who did and did not develop severe sepsis were 0.95-1.27 and 1.07-1.55, respectively. High IL-6 concentrations were associated with death due to cardiovascular disease, cancer, infections, and renal failure (P 5 0.008). Conclusions: Despite clinical recovery, many patients with CAP leave hospital with ongoing subclinical inflammation, which is associated with an increased risk of death.

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“…It makes entire sense that wider genetic screens might be more predictive than early physiology in teasing late death. Different classes of predicative models are required to tease out time-varying hazard ratios [53]. Such a study would be a natural extension of this work.…”

Section: Discussionmentioning

confidence: 99%

Using Data-Driven Rules to Predict Mortality in Severe Community Acquired Pneumonia

Rosenfeld

Clermont

2014

PLoS ONE

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Prediction of patient-centered outcomes in hospitals is useful for performance benchmarking, resource allocation, and guidance regarding active treatment and withdrawal of care. Yet, their use by clinicians is limited by the complexity of available tools and amount of data required. We propose to use Disjunctive Normal Forms as a novel approach to predict hospital and 90-day mortality from instance-based patient data, comprising demographic, genetic, and physiologic information in a large cohort of patients admitted with severe community acquired pneumonia. We develop two algorithms to efficiently learn Disjunctive Normal Forms, which yield easy-to-interpret rules that explicitly map data to the outcome of interest. Disjunctive Normal Forms achieve higher prediction performance quality compared to a set of state-of-the-art machine learning models, and unveils insights unavailable with standard methods. Disjunctive Normal Forms constitute an intuitive set of prediction rules that could be easily implemented to predict outcomes and guide criteria-based clinical decision making and clinical trial execution, and thus of greater practical usefulness than currently available prediction tools. The Java implementation of the tool JavaDNF will be publicly available.

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Comparison of Cox and Gray’s survival models in severe sepsis*

Abstract: We confirm that many of the important predictors of mortality in severe sepsis are nonproportional and find that Gray's model seems best suited for modeling survival in this condition.

Cited by 29 publications

References 23 publications

Both Positive and Negative Fluid Balance May Be Associated With Reduced Long-Term Survival in the Critically Ill

Both Positive and Negative Fluid Balance May Be Associated With Reduced Long-Term Survival in the Critically Ill

Inflammatory Markers at Hospital Discharge Predict Subsequent Mortality after Pneumonia and Sepsis

Using Data-Driven Rules to Predict Mortality in Severe Community Acquired Pneumonia

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