ArticleNeurocritical care2025
Aneurysmal Subarachnoid Hemorrhage Risk Assessment Model Identifies Patients for Safe Early Discharge at Day 15-The SAFE-SaH Score.
Article in Neurocritical care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPatients with aneurysmal subarachnoid hemorrhage (aSAH) are often hospitalized for 21 days after aneurysm rupture due to the risk of complications. However, some never experience complications and are unlikely to benefit from a prolonged hospitalization. The aim of this study is to derive a risk assessment model (RAM) using data from the first 14 days of hospitalization to identify low-risk patients for early discharge, at day 15 or after.
methodsPatients ≥ 18 years old with an acute aSAH at a Comprehensive Stroke Center from 2017 to 2024 were included. Baseline demographics, aSAH grading scales, and in-hospital complications requiring intervention were characterized. Complications included: vasospasm, delayed cerebral ischemia (DCI), cerebral salt wasting (CSW), cerebral edema, seizures, arrhythmias, respiratory failure, and hydrocephalus. Binary logistic regression with leave-one-out cross validation (LOOCV) was used to identify an optimal RAM.
resultsOf 165 patients, the mean Hunt Hess Score (HHS) was 2.5 (standard deviation, SD 1.2), modified Fisher Score (mFS) was 3.1 (SD 1), endovascular therapy was used for aneurysm securement in 73% of patients, and 54.5% of patients experienced complications during days 15-21. In bivariate analyses, days 0-14 variables associated with days 15 + complications were the following: HHS, mFS, middle cerebral artery (MCA) aneurysm, clinical or radiologic vasospasm, endovascular therapies, intraventricular hemorrhage, hydrocephalus, presence of external ventricular drain (EVD), mechanical ventilation, vasopressors, hypertonic solutions, antiseizure medications, milrinone, and fludrocortisone (all p < 0.05). LOOCV regression for a best fit RAM included six variables: Sum of Vasopressors, Artery (MCA aneurysm), Fludrocortisone, EVD, Scale (mFS and HHS), "SAFE-SaH" and had an area under the receiver operator characteristics curve of 0.90 (95% confidence interval 0.85-0.95), sensitivity of 0.94, specificity of 0.69, positive predictive value of 79%, and negative predictive value of 91% for predicting complications on day 15 + .
conclusionsThis is the first ever RAM to incorporate clinical data from the first 14 days of hospitalization to identify patients with an aSAH at low risk for complications after day 14. With 94% sensitivity, the RAM classifies patients who will not have complications and may assist in earlier disposition on day 15 or after.
Indexed as
Identifiers
40155577What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.