HANNOVER INTENSIVE SCORE (HIS) IN MEDICAL INTENSIVE-CARE MEDICINE

Citation
A. Vonbierbrauer et al., HANNOVER INTENSIVE SCORE (HIS) IN MEDICAL INTENSIVE-CARE MEDICINE, Medizinische Klinik, 93(9), 1998, pp. 524-532
Citations number
26
Categorie Soggetti
Medicine, General & Internal
Journal title
ISSN journal
07235003
Volume
93
Issue
9
Year of publication
1998
Pages
524 - 532
Database
ISI
SICI code
0723-5003(1998)93:9<524:HIS(IM>2.0.ZU;2-G
Abstract
Background and Objectives: Scoring systems are important tools for qua lity control and stratification of study populations in intensive cars medicine. The study aims to systematically evaluate predictive abilit y and severity classification tv oi the combined physiologic-therapeut ic Hannover Intensiv Score (HIS). Such data are not existing regarding medical intensive care medicine. Methods: 1060 consecutive patients ( ICU stay > 4 hours) being admitted to a medical ICU were prospectively investigated. HIS was determined for all patients each day during ICU stay. The results were compared to the physiologically based APACHE I I and to the therapeutically based TISS, which both were determined as well. Results:HIS provided sufficient discrimination between survival and [hospital mortality; area under the ROC curve (AUC) = 0.822] with differences compared to APACHE II (AUC = 0.838) and TISS (AUC = 0.798 ), respectively. During longer course of ICU stay HIS offers better ou tcome prognostication compared to the unilateral systems with respect to specificity and total correct classification rate. There was a near ly Linear increase of hospital mortality with an increase of day-1-HIS . The same was observed with APACHE II and TISS. Mean day-1-scores for survivors were significantly higher compared to non-survivors with an systems (p < 00001). Day-1-HIS moderately correlates with both other systems (APACE II: r = 0.766; TISS: r = 0.814.) Conclusion: The Hannov er Intensiv Score as a model of a combined physiologic-therapeutic sco ring system was successfully validated concerning hospital outcome pre diction and severity of disease classification in a large medical ICU population. Thus, for these applications it can be used in similar Ger man ICUs. A main argument Eor applying the system is the employment of a fairly small set of easily accessible parameters.