基于磁敏感加权成像的pc-ASPECTS评分对后循环急性缺血性卒中预后的预测价值 Predictive Value of pc-ASPECTS Based on Susceptibility Weighted Imaging for Prognosis of Patients with Posterior Circulation Acute Ischemic Stroke
Bibliographic record
Abstract
【摘要】 目的 探讨基于SWI的后循环Alberta卒中项目早期CT评分（posterior circulation Alberta stroke program early CT score，pc-ASPECTS）对后循环急性缺血性卒中（acute ischemic stroke，AIS）患者临床3个月预后的预测价值。 方法 回顾性连续收集来自河南省濮阳市人民医院神经内科2014年12月-2016年12月期间未接受静脉或动脉溶栓及血管内再通治疗的后循环AIS患者的临床及影像学数据。采用mRS评分评估发病后3个月预后，mRS评分0～2分定义为预后良好，3～6分定义为预后不良。使用多因素Logistic回归分析确定良好临床预后的独立预测因素。采用受试者工作特征（receiver operating characteristic，ROC）曲线分析来评估基于SWI的pc-ASPECTS评分对后循环AIS患者3个月预后的预测诊断价值。 结果 研究共收录63例后循环AIS患者，预后良好组42例（66.7%），预后不良组21例（33.3%）。单因素分析显示，入院时基线NIHSS评分（P＜0.001）、pc-ASPECTS评分（P＜0.001）在预后良好和预后不良组差异具有统计学意义。多因素Logistic回归分析提示，pc-ASPECTS≥6分是后循环AIS患者3个月预后良好的独立预测因素（OR 2.03，95%CI 1.04～3.95，P=0.039）；ROC曲线分析显示，基于SWI的pcASPECTS曲线下面积为0.80（95%CI 0.69～0.91）。 结论 在后循环AIS患者中，基于SWI影像的pc-ASPECTS评分可独立预测患者的3个月临床预后。 【Abstract】 Objective To assess the value of posterior circulation ASPECTS (pc-ASPECTS) based on SWI in predicting the clinical outcome of patients with posterior circulation acute ischemic stroke (AIS). Methods The clinical and imaging data of posterior circulation AIS patients who were not treated with endovascular recanalization and intravenous or intra-arterial alteplase were analyzed. The prognosis at 3 months after symptom onset was assessed by mRS, good prognosis was defined as mRS 0-2, and poor prognosis was defined as mRS 3-6. Multivariate logistic regression analysis was used to determine the independent predictors of clinical outcome. The area under the receiver operating characteristic (ROC) curve was used to evaluate the predictive value of the pc-ASPECTS based on SWI for the prognosis of patients with posterior circulation AIS. Results A total of 63 patients with posterior circulation AIS were included in the study, 42 (66.7%) patients had a good prognosis, and 21 (66.7%) patients had a poor prognosis. The univariate analysis showed that there was significant difference in the NIHSS on admission (P<0.001) and pcASPECTS (P<0.001) between good and poor prognosis groups. The multivariate logistic regression analysis showed that the pc-ASPECTS≥6 could independently predict favorable outcome in posterior circulation AIS patients (OR 2.03; 95%CI 1.04-3.95, P=0.039). ROC analysis indicated that the area under the ROC curve of the pc-ASPECTS based on SWI was 0.80 (95%CI 0.69-0.91). Conclusions The pc-ASPECTS based on SWI can independently predict clinical outcome at 3 months after symptom onset in patients with posterior circulation AIS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".