BackgroundPrognostic tools for intracerebral hemorrhage (ICH) patients are potentially useful for ascertaining prognosis and recommended in guidelines to facilitate streamline assessment and communication between providers. In this systematic review with meta-analysis we identified and characterized all existing prognostic tools for this population, performed a methodological evaluation of the conducting and reporting of such studies and compared different methods of prognostic tool derivation in terms of discrimination for mortality and functional outcome prediction.MethodsPubMed, ISI, Scopus and CENTRAL were searched up to 15th September 2016, with additional studies identified using reference check. Two reviewers independently extracted data regarding the population studied, process of tool derivation, included predictors and discrimination (c statistic) using a predesignated spreadsheet based in the CHARMS checklist. Disagreements were solved by consensus. C statistics were pooled using robust variance estimation and meta-regression was applied for group comparisons using random effect models.ResultsFifty nine studies were retrieved, including 48,133 patients and reporting on the derivation of 72 prognostic tools. Data on discrimination (c statistic) was available for 53 tools, 38 focusing on mortality and 15 focusing on functional outcome. Discrimination was high for both outcomes, with a pooled c statistic of 0.88 for mortality and 0.87 for functional outcome. Forty three tools were regression based and nine tools were derived using machine learning algorithms, with no differences found between the two methods in terms of discrimination (p = 0.490). Several methodological issues however were identified, relating to handling of missing data, low number of events per variable, insufficient length of follow-up, absence of blinding, infrequent use of internal validation, and underreporting of important model performance measures.ConclusionsPrognostic tools for ICH discriminated well for mortality and functional outcome in derivation studies but methodological issues require confirmation of these findings in validation studies. Logistic regression based risk scores are particularly promising given their good performance and ease of application.Electronic supplementary materialThe online version of this article (10.1186/s12874-018-0613-8) contains supplementary material, which is available to authorized users.
Objectives: To systematically assess the discrimination and calibration of the Intracerebral Hemorrhage score for prediction of short-term mortality in intracerebral hemorrhage patients and to study its determinants using heterogeneity analysis. Data Sources: PubMed, ISI Web of Knowledge, Scopus, and CENTRAL from inception to September 15, 2018. Study Selection: Adult studies validating the Intracerebral Hemorrhage score for mortality prediction in nontraumatic intracerebral hemorrhage at 1 month/discharge or sooner. Data Extraction: Data were collected on the following aspects of study design: population studied, level of care, timing of outcome measurement, mean study year, and mean cohort Intracerebral Hemorrhage score. The summary measures of interest were discrimination as assessed by the C-statistic and calibration as assessed by the standardized mortality ratio (observed:expected mortality ratio). Random effect models were used to pool both measures. Heterogeneity was measured using the I 2 statistic and explored using subgroup analysis and meta-regression. Data Synthesis: Fifty-five studies provided data on discrimination, and 35 studies provided data on calibration. Overall, the Intracerebral Hemorrhage score discriminated well (pooled C-statistic 0.84; 95% CI, 0.82–0.85) but overestimated mortality (pooled observed:expected mortality ratio = 0.87; 95% CI, 0.78–0.97), with high heterogeneity for both estimates (I 2 80% and 84%, respectively). Discrimination was affected by study mean Intracerebral Hemorrhage score (β = –0.05), and calibration was affected by disease severity, with the score overestimating mortality for patients with an Intracerebral Hemorrhage score greater than 3 (observed:expected mortality ratio = 0.84; 95% CI, 0.78–0.91). Mortality rates were reproducible across cohorts for patients with an Intracerebral Hemorrhage score 0–1 (I 2 = 15%). Conclusions: The Intracerebral Hemorrhage score is a valid clinical prediction rule for short-term mortality in intracerebral hemorrhage patients but discriminated mortality worse in more severe cohorts. It also overestimated mortality in the highest Intracerebral Hemorrhage score patients, with significant inconsistency between cohorts. These results suggest that mortality for these patients is dependent on factors not included in the score. Further studies are needed to determine these factors.
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