Supplementary Material for: Validity of Nonspecific Stroke Location ICD-10 Subcodes: A Descriptive Study

Background: We aimed to describe imaging characteristics in stroke hospitalizations with nonspecific/unspecified vascular region subcodes and to assess for systematic bias in the use of these subcodes. Methods: We captured first ischemic stroke hospitalizations from 2018-2022 at a single stroke center. We reviewed imaging studies to classify a gold standard of vascular region blinded to ICD-10 subcodes in 200 randomly selected hospitalizations: 100 with nonspecific/unspecified subcodes and 100 with specific subcodes oversampled for posterior circulation strokes. We assessed for systematic bias in the use of nonspecific/unspecified subcodes using multilevel logistic regression, with primary provider included as a random intercept. Separate models were applied to the full population of strokes and to those that underwent imaging review. Results: We identified 5,234 first ischemic stroke hospitalizations, of which 2,224 (43%) received a nonspecific/unspecified vascular region subcode. Out of the 100 ICD-10 nonspecific/unspecified stroke location cases that underwent imaging review, 85 had acute infarcts in specific locations: 45 anterior circulation, 40 posterior circulation, and 15 with no infarct. Factors associated with the use of nonspecific/unspecified subcodes were low NIHSS scores and non-neurological specialist but not anterior versus posterior vascular distribution. The proportion of variance explained by the models was modest (pseudo-R² 0.16). Conclusions: Most ischemic stroke hospitalizations coded with nonspecific/unspecified ICD-10 vascular region subcodes had imaging-confirmed infarcts in specific vascular regions. These strokes tended to have a lower NIHSS and were overrepresented by posterior circulation lesions. The modest variance explained in the use of nonspecific/unspecified codes indicates that much of the coding is influenced by random variation or unmeasured factors. Future studies in other healthcare systems are needed to verify these findings and evaluate for other predictors. Researchers using these subcodes should recognize the limitations and incorporate sensitivity analyses to evaluate potential bias in results.研究背景：本研究旨在描述伴有非特异性/未明确血管区域亚编码的卒中住院病例的影像学特征，并评估此类亚编码使用中的系统偏倚。 研究方法：本研究收集了2018-2022年某单一卒中中心收治的首发性缺血性卒中住院病例。针对200例随机选取的住院病例，我们通过盲法（即不了解国际疾病分类第10版(ICD-10)亚编码信息）审阅其影像学检查结果，对血管区域进行分类以确立金标准：其中100例采用非特异性/未明确亚编码，另外100例为针对后循环卒中过度抽样的特异性亚编码病例。我们采用多水平逻辑回归(multilevel logistic regression)评估非特异性/未明确亚编码使用中的系统偏倚，并将主要接诊医师作为随机截距项纳入模型。分别针对全部卒中人群及接受影像学复查的人群构建独立分析模型。 研究结果：本研究共纳入5234例首发性缺血性卒中住院病例，其中2224例（43%）被赋予非特异性/未明确血管区域亚编码。在接受影像学复查的100例ICD-10非特异性/未明确卒中定位病例中，85例存在特定部位的急性梗死：45例为前循环梗死，40例为后循环梗死，另有15例未发现梗死灶。与非特异性/未明确亚编码使用相关的因素为较低的美国国立卫生研究院卒中量表(NIHSS)评分及非神经专科医师，而非前循环与后循环的血管分布差异。模型解释的变异程度较低（伪决定系数pseudo-R²为0.16）。 研究结论：大多数被编码为非特异性/未明确ICD-10血管区域亚编码的缺血性卒中住院病例，经影像学证实存在特定血管区域的梗死灶。此类卒中多表现为较低的NIHSS评分，且后循环病变占比偏高。本研究模型仅能解释较少的亚编码使用变异，提示大部分编码决策受随机变异或未测量因素影响。未来需在其他医疗体系中开展研究以验证本研究结果，并评估其他潜在预测因子。使用此类亚编码的研究者应认识到其局限性，并纳入敏感性分析以评估研究结果中的潜在偏倚。