Articles: intensive-care-units.
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Critical care medicine · Aug 1999
Multicenter Study Clinical TrialEvaluation of an interdisciplinary data set for national intensive care unit assessment.
To evaluate the ability of an interdisciplinary data set (recently defined by the Austrian Working Group for the Standardization of a Documentation System for Intensive Care [ASDI]) to assess intensive care units (ICUs) by means of the Simplified Acute Physiology Score II (SAPS II) for the severity of illness and the simplified Therapeutic Intervention Scoring System (TISS-28) for the level of provided care. ⋯ Implementation of an interdisciplinary data set for ICUs provided data with which to evaluate performance in terms of severity of illness and provided care. The SAPS II did not accurately predict outcomes in Austrian ICUs and must, therefore, be customized for this population. A combination of indicators for both severity of illness and amount of provided care is necessary to evaluate ICU performance. Further data acquisition is needed to customize the SAPS II and to validate the TISS-28.
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To determine whether obstetric admissions to the intensive care unit (ICU) are useful quality-assurance indicators. ⋯ The most common precipitants of ICU admission were obstetric hemorrhage and uncontrolled hypertension. Improved management strategies for these problems may significantly reduce major maternal morbidity.
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Multicenter Study Comparative Study
Prediction of outcome in intensive care unit trauma patients: a multicenter study of Acute Physiology and Chronic Health Evaluation (APACHE), Trauma and Injury Severity Score (TRISS), and a 24-hour intensive care unit (ICU) point system.
To conduct a multicenter study to validate the accuracy of the Acute Physiology and Chronic Health Evaluation (APACHE) II system, APACHE III system, Trauma and Injury Severity Score (TRISS) methodology, and a 24-hour intensive care unit (ICU) point system for prediction of mortality in ICU trauma patient admissions. ⋯ For the overall estimation of aggregate ICU mortality, the APACHE III system was the most reliable; however, performance was most accurate for subsets of patients with head trauma. The 24-hour ICU point system also demonstrated acceptable overall performance with improved performance for patients with head trauma. Overall, APACHE II and TRISS did not meet acceptable thresholds of performance. When estimating ICU mortality for subsets of patients without head trauma, none of these systems had an acceptable level of performance. Further multicenter studies aimed at developing better outcome prediction models for patients without head injuries are warranted, which would allow trauma care providers to set uniform standards for judging institutional performance.
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Critical care medicine · Aug 1999
Evaluation of patient-perceived health status using the Medical Outcomes Survey Short-Form 36 in an intensive care unit population.
Baseline patient functional status as assessed by providers is correlated with mortality after intensive care unit (ICU) admission. We wanted to see if patient self-perception of health status before admission to an ICU correlated with functional outcome. ⋯ We conclude that use of the SF-36 is time efficient in an ICU setting and correlates with 6-wk and 6-month functional outcome. It correlates as well with functional outcome as either the baseline Zubrod functional status or the APACHE II severity of illness measurement. The five-question general health evaluation portion correlated almost as well with outcome as the more extensive 36-item questionnaire. Use of the SF-36 may define patient populations for comparison across hospitals. It may also target individuals with needs for additional posthospitalization care, including rehabilitation services or nursing home placement.
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J Clin Monit Comput · Aug 1999
Artifact detection in the PO2 and PCO2 time series monitoring data from preterm infants.
Artifacts in clinical intensive care monitoring lead to false alarms and complicate later data analysis. Artifacts must be identified and processed to obtain clear information. In this paper, we present a method for detecting artifacts in PCO2 and PO2 physiological monitoring data from preterm infants. PATIENTS AND DATA: Monitored PO2 and PCO2 data (1 value per minute) from 10 preterm infants requiring intensive care were used for these experiments. A domain expert was used to review and confirm the detected artifact. ⋯ Based on the judgement of the expert, our detection method detects most PO2 and PCO2 artifacts and artifactual episodes in the 10 randomly selected preterm infants. The method makes little use of domain knowledge, and can be easily extended to detect artifacts in other monitoring channels.