Browsing by Subject "APACHE-II"

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  • Fallenius, Marika; Skrifvars, Markus B.; Reinikainen, Matti; Bendel, Stepani; Raj, Rahul (2017)
    Background: Intensive care scoring systems are widely used in intensive care units (ICU) around the world for case-mix adjustment in research and benchmarking. The aim of our study was to investigate the usefulness of common intensive care scoring systems in predicting mid-term mortality in patients with spontaneous intracerebral hemorrhage (ICH) treated in intensive care units (ICU). Methods: We performed a retrospective observational study including adult patients with spontaneous ICH treated in Finnish ICUs during 2003-2012. We used six-month mortality as the primary outcome of interest. We used logistic regression to customize Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) II and Sequential Organ Failure Assessment (SOFA) for six-month mortality prediction. To assess the usefulness of the scoring systems, we compared their discrimination and calibration with two simpler models consisting of age, Glasgow Coma Scale (GCS) score, and premorbid functional status. Results: Totally 3218 patients were included. Overall six-month mortality was 48%. APACHE II and SAPS II outperformed SOFA (area under the receiver operator curve [AUC] 0.83 and 0.84, respectively, vs. 0.73) but did not show any benefit over the simpler models in terms of discrimination (AUC 0.84, p > 0.05 for all models). SAPS II showed satisfactory calibration (p = 0.058 in the Hosmer-Lemeshow test), whereas all other models showed poor calibration (p <0.05). Discussion: In this retrospective multi-center study, we found that SAPS II and APACHE II were of no additional prognostic value to a simple model based on only age and GCS score for patients with ICH treated in the ICU. In fact, the major predictive ability of APACHE II and SAPS II comes from their age and GCS score components. SOFA performed significantly poorer than the other models and is not applicable as a prognostic model for ICH patients. All models displayed poor calibration, highlighting the need for improved prognostic models for ICH patients. Conclusion: The common intensive care scoring systems did not outperform a simpler model based on only age and GCS score. Thus, the use of previous intensive care scoring systems is not warranted in ICH patients.
  • HEALICS Consortium; Keuning, Britt E.; Kaufmann, Thomas; Wiersema, Renske; Pettilä, Ville; van der Horst, Iwan C. C. (2020)
    Background Mortality prediction models are applied in the intensive care unit (ICU) to stratify patients into different risk categories and to facilitate benchmarking. To ensure that the correct prediction models are applied for these purposes, the best performing models must be identified. As a first step, we aimed to establish a systematic review of mortality prediction models in critically ill patients. Methods Mortality prediction models were searched in four databases using the following criteria: developed for use in adult ICU patients in high-income countries, with mortality as primary or secondary outcome. Characteristics and performance measures of the models were summarized. Performance was presented in terms of discrimination, calibration and overall performance measures presented in the original publication. Results In total, 43 mortality prediction models were included in the final analysis. In all, 15 models were only internally validated (35%), 13 externally (30%) and 10 (23%) were both internally and externally validated by the original researchers. Discrimination was assessed in 42 models (98%). Commonly used calibration measures were the Hosmer-Lemeshow test (60%) and the calibration plot (28%). Calibration was not assessed in 11 models (26%). Overall performance was assessed in the Brier score (19%) and the Nagelkerke's R-2 (4.7%). Conclusions Mortality prediction models have varying methodology, and validation and performance of individual models differ. External validation by the original researchers is often lacking and head-to-head comparisons are urgently needed to identify the best performing mortality prediction models for guiding clinical care and research in different settings and populations.
  • Raj, Rahul; Bendel, Stepani; Reinikainen, Matti; Hoppu, Sanna; Luoto, Teemu; Ala-Kokko, Tero; Tetri, Sami; Laitio, Ruut; Koivisto, Timo; Rinne, Jaakko; Kivisaari, Riku; Siironen, Jari; Skrifvars, Markus (2016)
    Background: Differences in outcomes after traumatic brain injury (TBI) between neurosurgical centers exist, although the reasons for this are not clear. Thus, our aim was to assess the association between the annual volume of TBI patients and mortality in neurosurgical intensive care units (NICUs). Methods: We collected data on all patients treated in the five Finnish university hospitals to examine all patients with TBI treated in NICUs in Finland from 2009 to 2012. We used a random effect logistic regression model to adjust for important prognostic factors to assess the independent effect of ICU volume on 6-month mortality. Subgroup analyses were performed for patients with severe TBI, moderate-to-severe TBI, and those who were undergoing mechanical ventilation or intracranial pressure monitoring. Results: Altogether 2,328 TBI patients were treated during the study period in five NICUs. The annual TBI patient volume ranged from 61 to 206 patients between the NICUs. Univariate analysis, showed no association between the NICUs' annual TBI patient volume and 6-month mortality (p = 0.063). The random effect model showed no independent association between the NICUs' annual TBI patient volume and 6-month mortality (OR = 1.000, 95% CI = 0.996-1.004, p = 0.876). None of the pre-defined subgroup analyses indicated any association between NICU volume and patient mortality (p > 0.05 for all). Discussion and Conclusion: We did not find any association between annual TBI patient volume and 6-month mortality in NICUs. These findings should be interpreted taking into account that we only included NICUs, which by international standards all treated high volumes of TBI patients, and that we were not able to study the effect of NICU volume on neurological outcome.