ASPECTS、DRAGON和THRIVE评分对我国接受静脉溶栓治疗的急性缺血性卒中患者3个月不良预后的预测价值分析 Predictive Value of ASPECTS, DRAGON and THRIVE Scores for 3-month Poor Prognosis after Intravenous Thrombolysis in Patients with Acute Ischemic Stroke in China
Bibliographic record
Abstract
【摘要】 目的 比较Alberta卒中项目早期CT评分（Alberta stroke program early CT score，ASPECTS）、DRAGON评分和血管事件患者总体健康风险评分（totaled health risks in vascular events score，THRIVE）对我国行静脉溶栓的急性缺血性卒中（acute ischemic stroke，AIS）患者3个月不良预后的预测价值。 方法 回顾性连续收集2012年12月-2017年12月在同济大学附属同济医院神经内科急诊入院行静脉溶栓的AIS患者214例的临床资料，并对患者使用ASPECTS、DRAGON和THRIVE量表进行评分。以卒中后3个月临床预后为观察终点，不良预后定义为mRS评分≥3分。应用受试者工作特征（receiver operating characteristic，ROC）曲线分析各评分对3个月不良预后的预测价值，ROC曲线下面积采用C值表示，通过C值比较3个评分的预测价值；应用Hosmer-Lemeshow（H-L）拟合优度[χ2（P）]检验评价各模型与实 际结果的拟合度；应用Spearman相关分析评估实际与预期结局事件的关联程度。 结果 最终纳入207例患者，有58例（28%）预后不良。ROC曲线分析，ASPECTS、DRAGON和THRIVE评分对应C值在总体患者分别为0.825、0.800、0.765，在前循环分别为0.850、0.817、0.797，在男性组分别为0.764、0.736、0.697，在女性组分别为0.909、0.878、0.861（均P﹤0.05）。对ASPECTS、DRAGON和THRIVE评分进行H-L拟合优度检验，各评分对应χ2（P）值在总体患者分别为4.865、6.758、7.836，在前循环分别为3.932、6.060、4.328，在男性组分别为7.021、6.631、4.647，在女性组分别为2.493、2.972、10.788（均P＞0.05）。对ASPECTS、DRAGON和THRIVE评分进行Spearman相关分析，各评分对应r值在总体患者分别为-0.532、0.473、0.418，在前循环分别为-0.572、0.501、0.471，在男性组分别为-0.427、0.359、0.300，在女性组分别为-0.688、0.626、0.601（均P﹤0.05）。 结论 ASPECTS、DRAGON和THRIVE评分模型都能预测静脉溶栓治疗的AIS患者3个月不良预后风险，其中ASPECTS评分预测诊断价值最高。 【Abstract】 Objective To investigate the predictive value of ASPECTS, DRAGON and THRIVE scores on the adverse prognosis at 3 months after intravenous thrombolysis in patients with acute ischemic stroke (AIS). Methods Clinical data of consecutive 214 AIS patients treated with intravenous thrombolysis from Department of Neurology of Tongji Hospital of Tongji University from December 2012 to December 2017 were retrospectively collected. All the patients were scored with ASPECTS, DRAGON and THRIVE scales. The primary endpoint was the prognosis at 3 months after symptoms onset, and the poor prognosis was defined as mRS ≥3. The predictive value of the three scales were compared by the area under the receive operating characteristic (ROC) curve (C value). The goodness of fit of the three scales were judged by Hosmer-Lemeshow (H-L) goodness-of-fit test. The correlation between actual and predictive outcome was evaluated by Spearman correlation analysis. Results 207 patients were enrolled in the final analysis, of which 58 (28%) patients had poor prognosis. The C value of ASPECTS, DRAGON and THRIVE scales in all patients were 0.825, 0.800 and 0.765, respectively; in anterior circulation were 0.850, 0.817 and 0.797, respectively; in man patients were 0.764, 0.736 and 0.697, respectively; in female patients were 0.909, 0.878 and 0.861 (all P<0.05). The χ2 value of H-L goodness-of-fit test of the three scales in all patients were 4.865, 6.758 and 7.836, respectively; in anterior circulation were 3.932, 6.060 and 4.328, respectively; in man patients were 7.021, 6.631 and 4.647, respectively; in female patients were 2.493, 2.972 and 10.788, respectively (all P>0.05). Spearman correlation coefficient (r) of the three scales in all patients were -0.532, 0.473 and 0.418, respectively; in anterior circulation were -0.572, 0.501 and 0.471, respectively; in man patients were -0.427, 0.359 and 0.300, respectively; in female patients were -0.688, 0.626 and 0.601, respectively (all P<0.05). Conclusions ASPECTS, DRAGON and THRIVE all can predict the risk of 3-month poor prognosis after intravenous thrombolysis in AIS patients, of which ASPECTS is superior to the other two predictive models.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.001 |
| 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".