Imaging phenotype is more strongly associated with early neurological deterioration after acute isolated pontine infarction: a retrospective cohort study
- 1Xiaolan Clinical Institute of Shantou University Medical College
- 2Department of Neurology, Xiaolan People's Hospital of Zhongshan (The Fifth People's Hospital of Zhongshan)
- 3Department of Encephalopathy, Zhongshan Chenxinghai Hospital of Integrated Traditional Chinese and Western Medicine
Abstract
Background: Early neurological deterioration (END) is common after acute isolated pontine infarction (IPI), but the relative associations of imaging phenotype and metabolic or coagulation markers with END remain uncertain. We evaluated these domains and developed an exploratory prediction model.
Methods: We retrospectively analyzed 162 patients with acute IPI. END was a ≥2-point increase in total National Institutes of Health Stroke Scale (NIHSS) score or a ≥1-point increase in NIHSS motor item 5 or 6 from the admission baseline within 7 days after admission. Imaging was modeled nominally (BAD, LAA, or SAD; SAD as reference). Primary associations were estimated by Firth logistic regression. Four prespecified Firth models were compared by AUC, and the full model underwent 1,000-resample bootstrap validation.
Results: END occurred in 49 patients (30.2%). In the full Firth model, BAD (OR 20.70, 95% CI 7.10–70.04; P < 0.001) and LAA (OR 5.06, 95% CI 1.84–15.41; P = 0.001), relative to SAD, were associated with END. Thrombin time (TT) was also associated with END (OR 1.34 per second, 95% CI 1.04–1.73; P = 0.020); diabetes showed borderline evidence of association ( P = 0.057), whereas TyG was not independently associated ( P = 0.603). The apparent AUC was 0.652 (95% CI 0.562–0.742) for the base model, 0.814 (95% CI 0.745–0.883) for the base-plus-imaging model, 0.716 (95% CI 0.631–0.802) for the base-plus-metabolic/coagulation model, and 0.852 (95% CI 0.792–0.911) for the full model. Discrimination did not differ significantly between the base-plus-imaging and base-plus-metabolic/coagulation models (ΔAUC 0.098, bootstrap 95% CI −0.015–0.180; paired DeLong P = 0.066). All 1,000 bootstrap iterations succeeded; the optimism-corrected AUC was 0.818, with a calibration intercept of −0.023, calibration slope of 0.870, and Brier score of 0.162.
Conclusion: In this cohort, BAD and LAA imaging phenotypes were independently associated with END, whereas TyG was not independently associated. However, the direct discrimination advantage of the imaging model over the metabolic/coagulation model was not statistically established. The association with TT is exploratory, and the full model and nomogram require external validation before clinical use.
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BibTeX
@article{chen2026imaging,
title = {{Imaging phenotype is more strongly associated with early neurological deterioration after acute isolated pontine infarction: a retrospective cohort study}},
author = {Yanxiang Chen and Xiaoqiang Li and Hui Wang and Guonan Zhou},
journal = {Frontiers in Neurology},
year = {2026},
month = oct,
doi = {10.3389/fneur.2026.1913826},
url = {https://www.frontiersin.org/articles/10.3389/fneur.2026.1913826/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Imaging phenotype is more strongly associated with early neurological deterioration after acute isolated pontine infarction: a retrospective cohort study
AU - Yanxiang Chen
AU - Xiaoqiang Li
AU - Hui Wang
AU - Guonan Zhou
PY - 2026
DA - 2026/10/08
JO - Frontiers in Neurology
DO - 10.3389/fneur.2026.1913826
UR - https://www.frontiersin.org/articles/10.3389/fneur.2026.1913826/full
AB - Background: Early neurological deterioration (END) is common after acute isolated pontine infarction (IPI), but the relative associations of imaging phenotype and metabolic or coagulation markers with END remain uncertain. We evaluated these domains and developed an exploratory prediction model. Methods: We retrospectively analyzed 162 patients with acute IPI. END was a ≥2-point increase in total National Institutes of Health Stroke Scale (NIHSS) score or a ≥1-point increase in NIHSS motor item 5 or 6 from the admission baseline within 7 days after admission. Imaging was modeled nominally (BAD, LAA, or SAD; SAD as reference). Primary associations were estimated by Firth logistic regression. Four prespecified Firth models were compared by AUC, and the full model underwent 1,000-resample bootstrap validation. Results: END occurred in 49 patients (30.2%). In the full Firth model, BAD (OR 20.70, 95% CI 7.10–70.04; P < 0.001) and LAA (OR 5.06, 95% CI 1.84–15.41; P = 0.001), relative to SAD, were associated with END. Thrombin time (TT) was also associated with END (OR 1.34 per second, 95% CI 1.04–1.73; P = 0.020); diabetes showed borderline evidence of association ( P = 0.057), whereas TyG was not independently associated ( P = 0.603). The apparent AUC was 0.652 (95% CI 0.562–0.742) for the base model, 0.814 (95% CI 0.745–0.883) for the base-plus-imaging model, 0.716 (95% CI 0.631–0.802) for the base-plus-metabolic/coagulation model, and 0.852 (95% CI 0.792–0.911) for the full model. Discrimination did not differ significantly between the base-plus-imaging and base-plus-metabolic/coagulation models (ΔAUC 0.098, bootstrap 95% CI −0.015–0.180; paired DeLong P = 0.066). All 1,000 bootstrap iterations succeeded; the optimism-corrected AUC was 0.818, with a calibration intercept of −0.023, calibration slope of 0.870, and Brier score of 0.162. Conclusion: In this cohort, BAD and LAA imaging phenotypes were independently associated with END, whereas TyG was not independently associated. However, the direct discrimination advantage of the imaging model over the metabolic/coagulation model was not statistically established. The association with TT is exploratory, and the full model and nomogram require external validation before clinical use.
SN - 1664-2295
ER -