Novita Lusiana
Hidayah General Hospital, Purwokerto Regency, Central Java, Indonesia

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Relationship Between Intracerebral Hemorrhage Volume on CT Scan and Glasgow Coma Scale Score: A Systematic Review of Randomized Controlled Trials and Primary Studies Novita Lusiana
The International Journal of Medical Science and Health Research Vol. 48 No. 3 (2026): The International Journal of Medical Science and Health Research
Publisher : International Medical Journal Corp. Ltd

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70070/8f24qw51

Abstract

Introduction Intracerebral hemorrhage (ICH) constitutes approximately 10–15% of all strokes globally and remains one of the most devastating forms of acute cerebrovascular disease, with 30-day mortality rates exceeding 40%. The Glasgow Coma Scale (GCS) and hematoma volume measured via non-contrast CT scan are two of the most widely studied clinical and radiological parameters in the acute prognostication of ICH. Despite robust individual evidence, comprehensive systematic synthesis examining the direct quantitative relationship between ICH volume on CT and GCS score is lacking. This systematic review aims to consolidate existing evidence on this critical association to inform clinical decision-making, risk stratification, and therapeutic planning. Methods A systematic literature search was conducted from inception through June 2025, in accordance with PRISMA 2020 guidelines. Studies were included if they reported quantitative data on both ICH volume (measured by CT-based ABC/2 or planimetric method) and GCS score in adult patients with spontaneous supratentorial or infratentorial ICH. Results A total of 18 eligible studies comprising 8,247 patients were included. ICH volume was consistently and inversely correlated with GCS score across all included studies (r = -0.58 to -0.82; all p < 0.001). Patients with GCS 3–8 (severe depression) demonstrated hematoma volumes significantly greater than those with GCS 9–12 (moderate) or GCS 13–15 (mild-to-normal): mean difference of 28.4 mL (95% CI: 22.1–34.7 mL; p < 0.001). An ICH volume threshold of ≥30 mL independently predicted GCS ≤ 8 (OR 4.21; 95% CI 3.15–5.63; p < 0.001). Intraventricular hemorrhage extension, deep ICH location, and hematoma expansion further amplified the GCS-volume relationship. The ICH Score (which integrates both GCS and volume) demonstrated superior prognostic accuracy (AUC 0.86–0.91) compared to either parameter alone. Discussion The strong inverse relationship between ICH volume and GCS score reflects the direct effect of hematoma mass on intracranial pressure and cortical/subcortical functional depression. Location-specific volume thresholds modulate this relationship: deep-seated hemorrhages (thalamic, basal ganglia) produce greater neurological depression at smaller volumes compared to lobar hemorrhages. Serial neurological assessment using GCS at 6 hours post-admission adds incremental prognostic value beyond baseline imaging. Clinicians must avoid prognostic nihilism, as aggressive neurocritical care may significantly attenuate predicted mortality. Conclusion ICH volume on CT scan is a robust, independent predictor of GCS score and neurological outcome. A cut-off volume of ≥30 mL represents a clinically meaningful threshold associated with severe consciousness depression (GCS ≤ 8) and adverse outcomes. Integration of both GCS and ICH volume into composite scoring (e.g., ICH Score, max-ICH Score) maximizes prognostic accuracy. Future prospective multicenter studies and well-powered RCTs are warranted to validate volume-specific GCS cut-points across diverse populations.
The Association Between Teleradiology Accuracy and the Speed of Stroke Diagnosis in Remote Areas: A Systematic Review of Randomized Controlled Trials and Primary Studies Novita Lusiana
The International Journal of Medical Science and Health Research Vol. 48 No. 3 (2026): The International Journal of Medical Science and Health Research
Publisher : International Medical Journal Corp. Ltd

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70070/79p7t834

Abstract

Background: Stroke is a leading cause of mortality and disability worldwide, with time-to-diagnosis being a critical determinant of functional outcomes. In remote and rural areas, access to neuroimaging expertise is severely limited, creating a significant care disparity. Teleradiology—the electronic transmission of radiological images to remote specialists for interpretation—has emerged as a promising solution to bridge this diagnostic gap. However, the aggregate evidence regarding its diagnostic accuracy and impact on diagnosis speed in remote settings has not been comprehensively synthesized. Methods: The study strictly adhered to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020 guidelines. Studies reporting on teleradiology use for stroke imaging in remote or rural settings were eligible. Risk of bias was assessed using the Cochrane RoB 2.0 tool for RCTs and the Newcastle-Ottawa Scale (NOS) for observational studies. Primary outcomes included diagnostic accuracy metrics (sensitivity, specificity, kappa agreement) and time-to-treatment metrics. Results: Seventeen studies encompassing 89,412 patients met the inclusion criteria. Teleradiology demonstrated consistently high diagnostic accuracy for intracranial hemorrhage (sensitivity 91–100%, specificity 89–100%, kappa 0.69–1.0). Telestroke-equipped hospitals achieved significantly faster door-to-imaging times (median reduction 15–147 minutes) and door-to-needle times (median reduction 3.7–77 minutes/year). Thrombolysis rates increased from 2.6% to 15.5% over 10-year network maturation. Functional outcomes (mRS 0-2) improved by 19% and 30-day mortality decreased by 0.5 percentage points in telestroke-capable hospitals. Multimodal CT with teleradiology interpretation added 19.5 percentage points in ischemic stroke detection sensitivity. Discussion: The synthesis of evidence confirms that teleradiology systems maintain diagnostic accuracy equivalent to on-site neuroradiology services while substantially reducing time-to-diagnosis in remote settings. Hub-and-spoke network models demonstrate the greatest sustained impact, with telemedical stroke networks showing progressive improvement in both process and clinical outcome metrics over time. Challenges persist regarding initial implementation, connectivity infrastructure, and healthcare workforce training in low-resource environments. Conclusion: Teleradiology significantly accelerates stroke diagnosis in remote areas without compromising diagnostic accuracy. The implementation of teleradiology-enabled telestroke networks is strongly supported by the evidence and should be prioritized in healthcare policy for underserved populations.