Prognostic models for intracerebral hemorrhage: systematic review and meta-analysis

Abstract

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.

Possibilities of verification of a short-term functional outcome prognosis in the acute period of spontaneous supratentorial intracerebral hemorrhage using modified variants of the Intracerebral Hemorrhage Scale

“…In our opinion, a high informative value of these scales was supported by the integral assessment of clinical and neuroimaging data, which were associated with the outcome of disease in the acute period. The obtained data are consistent with the results of meta-analysis, which proved the prognostic value of the patient's age, initial level of consciousness and intracerebral hemorrhage volume in patients with cerebral hemorrhagic hemispheric stroke [10]. Based on the ROC analysis, the mICH-A Scale score (>2) and the mICH-B Scale score (>1) were determined along with an optimal sensitivity and specificity ratio, being associated with the risk of the mRS score >3 on the 21 st day of the disease, multiplied by 3.6 (RR 95 % CI 3.1-4.1, P ˂ 0.0001) and 3.2, respectively, (RR 95 % CI 2.8-3.6, P ˂ 0.0001).…”

Use of the Bispectral Index to Predict Recovery of Consciousness in Patients with Spontaneous Intracerebral Hemorrhage After Surgical Hematoma Evacuation: A Prospective Cohort Study

“…Factors associated with early deterioration and long-term outcome of spontaneous ICH have been systematically reviewed recently [4]. Typically, predictors of poor outcome included increasing age, decreasing GCS and ICH severity, such as ICH volume and distribution.…”

“…For patients with spontaneous ICH, several scoring systems have been introduced to predict functional outcomes, in which comprehensive items are used that mostly include age, level of consciousness, hematoma volume, and location [4]. However, none of these systems can incorporate all potential prognostic factors.…”

“…However, none of these systems can incorporate all potential prognostic factors. This might be the reason why new predicting scores are constantly being developed [4,5].…”

Development and usability testing of Understanding Stroke, a tailored life-sustaining treatment decision support tool for stroke surrogate decision makers

“…Ordinal prognostic models for Understanding Stroke were developed separately for ischemic stroke (IS) and intracerebral hemorrhage (ICH). We chose to develop a novel model rather than use an existing model as most existing models predict a binary outcome rather than a full ordinal range of outcomes after stroke [ 21 , 22 ]. Detailed statistical methods for model development will be reported separately [ 23 ].…”