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Published on: January 18, 2018
A practical nomogram incorporating inflammatory markers for predicting short-term prognosis in conservatively managed
Jiandong Wang1, Shiqiang Hou1, Xinwei Li1
1Department of Neurosurgery, The Affiliated Chuzhou Hospital of Anhui Medical University, The First People's Hospital of Chuzhou, Chuzhou, China.
Background:
We investigated whether systemic inflammatory indices improve prediction of short-term outcomes in conservatively treated spontaneous basal ganglia hemorrhage (BGH).
Methods:
We retrospectively analyzed 137 patients (2020-2023) and classified 90-day outcomes as good (mRS 0-2, n = 73) or poor (mRS 3-5, n = 64). A Basic model (age, hematoma volume, NIHSS, IVH) and an Inflammation model (Basic + CAR + NLR) were developed. Discrimination (ROC/DeLong) and calibration (Hosmer-Lemeshow) were assessed; Patients with mRS = 6 were excluded from the primary analysis but included in a prespecified sensitivity analysis. A nomogram was internally validated (1,000 bootstrap) with Brier score and decision curve analysis (DCA).
Results:
The Inflammation model outperformed the Basic model (AUC 0.823 [95%CI 0.754-0.892] vs 0.658 [0.568-0.749]; DeLong Z = 3.375, P = 0.001) with acceptable calibration (HL P = 0.896 vs 0.451). In sensitivity analyses including deaths, performance remained superior (AUC 0.815 [0.747-0.882] vs 0.656 [0.568-0.745]; Z = 3.238, P = 0.001). The nomogram showed good internal validity (C-index 0.794; Brier 0.1899) and net benefit across thresholds 0.05-0.95.
Conclusions:
Adding CAR and NLR to a clinical model significantly improves short-term outcome prediction after conservatively treated spontaneous BGH and supports individualized risk stratification.
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