Effect of changes over time in the performance of a customized SAPS-II model on the quality of care assessment.
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The prognostic factors for patients with hematological malignancies admitted to the intensive care unitA calibration study of SAPS II with Norwegian intensive care registry data.Critical appraisal and data extraction for systematic reviews of prediction modelling studies: the CHARMS checklist.International comparison of the performance of the paediatric index of mortality (PIM) 2 score in two national data sets.External validation of the Intensive Care National Audit & Research Centre (ICNARC) risk prediction model in critical care units in Scotland.The Next Generation of Clinical Decision Making Tools: Development of a Real-Time Prediction Tool for Outcome of Prostate Biopsy in Response to a Continuously Evolving Prostate Cancer Landscape.Improving patient prostate cancer risk assessment: Moving from static, globally-applied to dynamic, practice-specific risk calculators.Predictive Performance of the Simplified Acute Physiology Score (SAPS) II and the Initial Sequential Organ Failure Assessment (SOFA) Score in Acutely Ill Intensive Care Patients: Post-Hoc Analyses of the SUP-ICU Inception Cohort StudyPrognostic performance of the Simplified Acute Physiology Score II in major Croatian hospitals: a prospective multicenter study.Treatment intensity, age and outcome in medical ICU patients: results of a French administrative database.Year in review in Intensive Care Medicine 2012: I. Neurology and neurointensive care, epidemiology and nephrology, biomarkers and inflammation, nutrition, experimentalsNational Veterans Health Administration inpatient risk stratification models for hospital-acquired acute kidney injury.Simplified Mortality Score for the Intensive Care Unit (SMS-ICU): protocol for the development and validation of a bedside clinical prediction rule.Calibration drift in regression and machine learning models for acute kidney injury.Validation and Comparison of Seven Mortality Prediction Models for Hospitalized Patients With Acute Decompensated Heart FailureHow objective is the observed mortality following critical care?Comparison between SAPS II and SAPS 3 in predicting hospital mortality in a cohort of 103 Italian ICUs. Is new always better?Development and internal validation of the Simplified Mortality Score for the Intensive Care Unit (SMS-ICU).Calibration Drift Among Regression and Machine Learning Models for Hospital Mortality.
P2860
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P2860
Effect of changes over time in the performance of a customized SAPS-II model on the quality of care assessment.
description
2011 nî lūn-bûn
@nan
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
2011年论文
@zh
2011年论文
@zh-cn
name
Effect of changes over time in ...... he quality of care assessment.
@ast
Effect of changes over time in ...... he quality of care assessment.
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type
label
Effect of changes over time in ...... he quality of care assessment.
@ast
Effect of changes over time in ...... he quality of care assessment.
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prefLabel
Effect of changes over time in ...... he quality of care assessment.
@ast
Effect of changes over time in ...... he quality of care assessment.
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P2093
P2860
P1476
Effect of changes over time in ...... he quality of care assessment.
@en
P2093
Ameen Abu-Hanna
Evert de Jonge
Lilian Minne
Saeid Eslami
Sophia E de Rooij
P2860
P2888
P356
10.1007/S00134-011-2390-2
P577
2011-10-28T00:00:00Z