A Model for Prediction of In-Hospital Mortality in Patients with Subarachnoid Hemorrhage

Abstract

Background. Despite being a rare cause of stroke, spontaneous subarachnoid hemorrhage (SAH) is associated with high mortality rates. The prediction models that are currently being used on SAH patients are heterogeneous, and few address premature mortality. The aim of this study was to develop a mortality risk stratification score for SAH.Methods. A retrospective study was carried out with 536 patients diagnosed with SAH who had been admitted to the intensive care unit (ICU) at the University Hospital Complex of A Coruña (Spain) between 2003 and 2013. A multivariate logistic regression model was developed to predict the likelihood of in-hospital mortality, adjusting it exclusively for variables present on admission. A predictive equation of in-hospital mortality was then computed based on the model's coefficients, along with a points-based risk-scoring system. Its discrimination ability was also tested based on the area under the receiver operating characteristics curve and compared with previously developed scores.Results. The mean age of the patients included in this study was 56.9 ± 14.1 years. Most of these patients (73.9%) had been diagnosed with aneurysmal SAH. Their median length of stay was 7 days in the ICU and 20 days in the general hospital ward, with an overall in-hospital mortality rate of 28.5%. The developed scales included the following admission variables independently associated with in-hospital mortality: coma at onset [odds ratio (OR) = 1.87; p = 0.028], Fisher scale score of 3-4 (OR = 2.27; p = 0.032), Acute Physiology and Chronic Health Evaluation II (APACHE II) score within the first 24 h (OR = 1.10; p < 0.001), and total Sequential Organ Failure Assessment (SOFA) score on day 0 (OR = 1.19; p = 0.004). Our predictive equation demonstrated better discrimination [area under the curve (AUC) = 0.835] (bootstrap-corrected AUC = 0.831) and calibration properties than those of the HAIR scale (AUC = 0.771; p ≤ 0.001) and the Functional Recovery Expected after Subarachnoid Hemorrhage scale (AUC = 0.814; p = 0.154).Conclusions. In addition to the conventional risk factors for in-hospital mortality, in our study, mortality was associated with the presence of coma at onset of the condition, the physiological variables assessed by means of the APACHE II scale within the first 24 h, and the total SOFA score on day 0. A simple prediction model of mortality was developed with novel parameters assessed on admission, which also assessed organ failure and did not require a previous etiological diagnosis.

A novel nomogram model for clinical outcomes of severe subarachnoid hemorrhage patients

“…Multiple predictive models have been established to estimate the prognosis of SAH patients (Jaja et al, 2018;Mourelo-Farina et al, 2021). However, the predictive models for poor-grade (Ironside et al, 2019;Ota et al, 2019;Wang et al, 2019;Zheng et al, 2019;Liu et al, 2020;Yoshikawa et al, 2020;Shen et al, 2021).…”

“…Multiple predictive models have been established to estimate the prognosis of SAH patients ( Jaja et al, 2018 ; Mourelo-Farina et al, 2021 ). However, the predictive models for poor-grade SAH patients are rarely reported.…”

Characteristics and Outcomes for Low-Risk Hospital Admissions Admitted to the ICU: A Multisite Cohort Study

“…score may be useful at hospital admission, it may have less value as an ICU prediction model given the heterogeneity of ICU admissions. Instead, diseasespecific ICU prediction models such as those used for cardiac arrest, cirrhosis, or subarachnoid hemorrhage are more useful for critical care practitioners (40)(41)(42). Finally, as an administrative database was used, details about mechanisms of death and hospital-associated infections, the exact ICD-10 diagnoses that comprise each adverse event (e.g., how many fluid management adverse events were dehydration related vs volume overload), and laboratory data are not available.…”

Bone-Marrow-Derived Mesenchymal Stem Cells Attenuate Behavioral and Cognitive Dysfunction after Subarachnoid Hemorrhage via HMGB1–RAGE Axis Mediation

“…Subarachnoid hemorrhage (SAH) is a neurological disease with a high rate of inhospital mortality, which ranges from 20 to 30%. The pooled incidence of SAH was reported to be 21.4 per 100,000 person-years [1,2]. The main focus of research on SAH is on improving patient survival by effectively preventing rebleeding (clipping vs. coiling) and minimizing neurological complications, such as delayed cerebral ischemia (DCI) and hydrocephalus.…”