Comparison of Outcome From Intensive Care Admission After Adjustment for Case Mix by the APACHE III Prognostic System

Pappachan, John; Millar, B. W.; Bennett, E. D.; Smith, Gary B.

doi:10.1378/chest.115.3.802

Cited by 81 publications

(47 citation statements)

References 26 publications

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“…Our results accord with other reports on the performance of APACHE II and APACHE III in Britain [10,12]. The same pattern was observed in the external validation of the SAPS II, APACHE II and III models in Scottish intensive care patients [15] and was also reported for the SAPS II model applied to European patients [8,9].…”

Section: Discussionsupporting

confidence: 92%

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External validation of the SAPS II, APACHE II and APACHE III prognostic models in South England: a multicentre study

et al. 2003

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Disparity in case mix, a higher prevalence of outcome events and important unmeasured patient mix factors are possible sources for the decay of the models' predictive accuracy in our population. The lack of generalisability of standard prognostic models requires their validation and re-calibration before they can be applied with confidence to new populations. Customisation of existing models may become an important strategy to obtain authentic information on disease severity, which is a prerequisite for reliably measuring and comparing the quality and cost of intensive care.

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Section: Discussionsupporting

confidence: 92%

“…Introduction ods have been reported to adapt well to different environments [4,5], all but one of the published studies [6] that formally assessed the models' predictive accuracy when applied to new populations from other institutions or countries have shown the same pattern: good discrimination, but imperfect calibration [7,8,9,10,11,12,13,14,15,16].…”

mentioning

confidence: 99%

External validation of the SAPS II, APACHE II and APACHE III prognostic models in South England: a multicentre study

et al. 2003

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“…The patient-based protocol allows for assessment of the prevalence of HAIs and antimicrobial use according to the presence or absence of various risk factors and enables categorisation of hospitals by patient case-mix at national and/or European level. Indeed, adjustment for patient case-mix has been used in other studies, including for outcomes in intensive care [44,45] and surgical patients [46], and for comparing HAI rates [47]. Patient-based PPSs can also be used to identify patient-related factors that influence the prevalence of HAIs and thus help focus surveillance and infection prevention initiatives [48].…”

Section: Patient-based Versus Unit-based Protocolmentioning

confidence: 99%

The European Centre for Disease Prevention and Control (ECDC) pilot point prevalence survey of healthcare-associated infections and antimicrobial use

et al. 2012

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A standardised methodology for a combined point prevalence survey (PPS) on healthcare-associated infections (HAIs) and antimicrobial use in European acute care hospitals developed by the European Centre for Disease Prevention and Control was piloted across Europe. Variables were collected at national, hospital and patient level in 66 hospitals from 23 countries. A patient-based and a unit-based protocol were available. Feasibility was assessed via national and hospital questionnaires. Of 19,888 surveyed patients, 7.1% had an HAI and 34.6% were receiving at least one antimicrobial agent. Prevalence results were highest in intensive care units, with 28.1% patients with HAI, and 61.4% patients with antimicrobial use. Pneumonia and other lower respiratory tract infections (2.0% of patients; 95% confidence interval (CI): 1.8-2.2%) represented the most common type (25.7%) of HAI. Surgical prophylaxis was the indication for 17.3% of used antimicrobials and exceeded one day in 60.7% of cases. Risk factors in the patient-based protocol were provided for 98% or more of the included patients and all were independently associated with both presence of HAI and receiving an antimicrobial agent. The patient-based protocol required more work than the unit-based protocol, but allowed collecting detailed data and analysis of risk factors for HAI and antimicrobial use.

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“…[25][26][27][28][29][30]. Studien haben be reits gezeigt, dass Patienten, die einer ITS zugewiesen werden, in Großbritannien signifikant kränker sind als beispielswei se in den USA [21,22]. Aufgrund differie render Krankenhauskapazitäten bestehen selbst innerhalb eines Gesundheitssystems signifikante Unterschiede hinsichtlich der Liegedauer und der Krankheitsgrade von Intensivpatienten [23].…”

Section: Introductionunclassified

Medizinische Notfallteams

et al. 2007

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Severe clinical incidents occur in up to 10% of all non-intensive care unit (ICU) patients, which have an estimated mortality of 5-8%. As in the prehospital setting, early clinical warning signs can be identified in the majority of cases. Studies suggest that introduction of an in-hospital medical emergency team (MET) which responds to objective criteria of physiological deterioration, may effectively reduce the incidence of in-hospital cardiac arrests as well as unanticipated or readmissions to the ICU. According to this concept, METs would evaluate and treat non-ICU patients at risk at an early stage before a potentially fatal deterioration of cardiorespiratory parameters occurs. This article reviews available data on preventive in-hospital intensive care medicine and reflects on the circumstances for an implementation of METs in Germany, Austria and Switzerland.

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Comparison of Outcome From Intensive Care Admission After Adjustment for Case Mix by the APACHE III Prognostic System

Cited by 81 publications

References 26 publications

External validation of the SAPS II, APACHE II and APACHE III prognostic models in South England: a multicentre study

External validation of the SAPS II, APACHE II and APACHE III prognostic models in South England: a multicentre study

The European Centre for Disease Prevention and Control (ECDC) pilot point prevalence survey of healthcare-associated infections and antimicrobial use

Medizinische Notfallteams

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