Assessing and combining repeated prognosis of physicians and temporal models in the intensive care.

Objective: Recently, we devised a method to develop prognostic models incorporating patterns of sequential organ failure to predict the eventual hospital mortality at each day of intensive care unit (ICU) stay. In this study, we investigate using a real world setting how these models perform compared to physicians, who are exposed to additional information than the models.

Methods: We developed prognostic models for days 2-7 of ICU stay by data-driven discovery of patterns of sequential qualitative organ failure (SOFA) scores and embedding the patterns as binary variables in three types of logistic regression models.

Consistency of nurses' daily predictions of survival in the intensive care.

In the Intensive Care Unit, clinicians are continuously faced with the difficult task of prognosis, but their predictions of patient survival status may not always be consistent. Specifically very little is known about consistency of predictions over time. The aim of this paper is to assess the consistency of nurses' daily predictions of survival in terms of inter-observer variance and variance of observers over time.

Statistical process control for monitoring standardized mortality ratios of a classification tree model.

Objectives: The ratio of observed to expected mortality (standardized mortality ratio, SMR), is a key indicator of quality of care. We use PreControl Charts to investigate SMR behavior over time of an existing tree-model for predicting mortality in intensive care units (ICUs) and its implications for hospital ranking. We compare the results to those of a logistic regression model.

Effect of changes over time in the performance of a customized SAPS-II model on the quality of care assessment.

Purpose: The aim of our study was to explore, using an innovative method, the effect of temporal changes in the mortality prediction performance of an existing model on the quality of care assessment. The prognostic model (rSAPS-II) was a recalibrated Simplified Acute Physiology Score-II model developed for very elderly Intensive Care Unit (ICU) patients.

Methods: The study population comprised all 12,143 consecutive patients aged 80 years and older admitted between January 2004 and July 2009 to one of the ICUs of 21 Dutch hospitals.

Statistical process control for validating a classification tree model for predicting mortality--a novel approach towards temporal validation.

Prediction models are postulated as useful tools to support tasks such as clinical decision making and benchmarking. In particular, classification tree models have enjoyed much interest in the Biomedical Informatics literature. However, their prospective predictive performance over the course of time has not been investigated.

Characterizing predictive models of mortality for older adults and their validation for use in clinical practice.

Objectives: To systematically identify and characterize prognostic models of mortality for older adults, their reported potential use, and the actual level of their (external) validity.

Design: The Scopus database until January 2010 was searched for articles that developed and validated new models or validated existing prognostic models of mortality or survival in older adults.

Setting: All domains of health care.

Prognostic models for predicting mortality in elderly ICU patients: a systematic review.

Purpose: To systematically review prognostic research literature on development and/or validation of mortality predictive models in elderly patients.

Methods: We searched the Scopus database until June 2010 for articles aimed at validating prognostic models for survival or mortality in elderly intensive care unit (ICU) patients. We assessed the models' fitness for their intended purpose on the basis of barriers for use reported in the literature, using the following categories: (1) clinical credibility, (2) methodological quality (based on an existing quality assessment framework), (3) external validity, (4) model performance, and (5) clinical effectiveness.

Evaluation of SOFA-based models for predicting mortality in the ICU: A systematic review.

Introduction: To systematically review studies evaluating the performance of Sequential Organ Failure Assessment (SOFA)-based models for predicting mortality in patients in the intensive care unit (ICU).

Methods: Medline, EMBASE and other databases were searched for English-language articles with the major objective of evaluating the prognostic performance of SOFA-based models in predicting mortality in surgical and/or medical ICU admissions. The quality of each study was assessed based on a quality framework for prognostic models.