1. Introduction
Aneurysmal subarachnoid hemorrhage, aneurysm, neurological impairment, aSAH, vasospasm, cerebral vasospasm, aneurysmal subarachnoid hemorrhage, rebleeding, external ventricular drain, DCI
DELAYED CEREBRAL ISCHEMIA, SEQUELA, ANEURYSM, EVENT, DISEASE, VASOSPASM, DCI, CEREBRAL VASOSPASM
Aneurysmal subarachnoid hemorrhage (aSAH) is a dangerous and devastating cerebrovascular event with a mortality rate of up to 50% [Delayed cerebral ischemia, as one of the main causes of neurological impairment after aneurysmal subarachnoid hemorrhage, was once understood to be a sequela caused by cerebral vasospasm alone, and some scholars have even defined DCI directly as a poor prognosis for the occurrence of cerebral vasospasm [Improvements in available neurocritical care equipment and techniques have led to a slight decrease in the overall prevalence and mortality of aSAH in recent years [Nomograms are reliable statistical models that construct graphical predictive tools that incorporate several risk factors for the development of the disease and provide personalized, easily accessible, evidence-based, and highly accurate risk assessments for targeted clinical decision making [Patients with aneurysmal subarachnoid hemorrhage are critical and require intensive care, and mechanical ventilation is a routine treatment in intensive care [Our research is a post hoc analysis of a dataset shared by Chalard et al. [We will analytically review the impact of age, sex, location of the responsible aneurysm (anterior/posterior circulation), surgical approach, time to diagnosis and treatment, rebleeding, external ventricular drain (EVD), angiographic vasospasm, duration of mechanical ventilation, and admission and follow-up-related rating scales on the incidence of DCI after aneurysmal subarachnoid hemorrhage in patients.The DCI-related nomograms were constructed based on the identification of relevant risk factors, and the feasibility of the model was validated by three dimensions: discrimination, calibration, and clinical decision making.This study established and validated a clinical prediction model, for the occurrence of DCI in patients with aSAH who require mechanical ventilation, with reference to the reporting specifications for the establishment, validation, and updating of clinical prediction models and explored its value in risk prediction to provide a theoretical basis to reduce the incidence of DCI risk in such patients.