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Article(id=1322607934257869321, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1322607837742747790, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202405198, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1715529600000, receivedDateStr=2024-05-13, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793263904393, onlineDateStr=2026-10-29, pubDate=1761321600000, pubDateStr=2025-10-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793263904393, onlineIssueDateStr=2026-10-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793263904393, creator=13701087609, updateTime=1793263904393, updator=13701087609, issue=Issue{id=1322607837742747790, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='20', pageStart='3649', pageEnd='3840', issueExtLink='null', onlineDate='null', pubDate='1761321600000', pubDateStr='2025-10-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793263881383, creator='13701087609', updateTime=1793264238791, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1322609336933794638, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1322607837742747790, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1322609336933794639, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1322607837742747790, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=3836, endPage=3840, ext={EN=ArticleExt(id=1322607934446613002, articleId=1322607934257869321, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Construction of a risk evaluation index systemfor delayed thrombolysis in patients with acute ischemic strokebased on Delphi method and analytic hierarchy process, columnId=1228016569138213037, journalTitle=Modern Preventive Medicine, columnName=Clinical Medicine and Prevention, runingTitle=null, highlight=null, articleAbstract=
Objective

To establish a risk evaluation index system for delayed thrombolysis in patients with acute ischemic stroke (AIS) based on the three-dimensional framework of demand-supply-interaction, and to provide scientific evidence for clinical risk warning and intervention decision-making.

Methods

Literature analysis and focus group interviews were used to preliminarily establish an index system. The Delphi method and analytic hierarchy process were employed to determine indicator weights, followed by preliminary validation.

Results

A total of 21 experts were consulted with an average working experience of (22.67±9.46) years, 12 of whom held deputy senior titles or above. The effective questionnaire recovery rate for both rounds was 100%, with an expert authority coefficient of 0.901 and coordination coefficients of 0.238 and 0.290, respectively. The final index system comprised 2 first-level indicators, 10 second-level indicators, and 95 third-level indicators. Classified by the three-dimensional demand-supply-interaction framework, the primary indicators were out-of-hospital delay factors (0.833 3) and in-hospital delay factors (0.166 7). Preliminary validation showed significant positive correlation between the total index score and door-to-needle time (r=0.72, P<0.001).

Conclusion

This study preliminarily constructs an operational risk evaluation index system for delayed thrombolysis in AIS patients, providing a theoretical framework for early risk identification, clinical decision support, and prognosis improvement. However, large-scale prospective studies are needed to further validate its clinical effectiveness.

, authors=Yu MI, Fan XI, Miao ZHANG, Zong-gui WANG, authorsList=Yu MI, Fan XI, Miao ZHANG, Zong-gui WANG, authorCompany=null, correspAuthors=Miao ZHANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1322607934916375053, articleId=1322607934257869321, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=基于德尔菲法和层次分析法构建急性缺血性脑卒中患者溶栓就医延迟风险评价指标体系, columnId=1228016570119680182, journalTitle=现代预防医学, columnName=临床与预防, runingTitle=null, highlight=null, articleAbstract=
目的

构建急性缺血性脑卒中（AIS）患者溶栓就医延迟风险评价指标体系，为临床风险预警和干预决策提供科学依据。

方法

采用文献分析和焦点小组访谈法初步构建指标体系，运用德尔菲法和层次分析法确定指标权重，并进行初步验证。

结果

共函询21名专家，平均工作年限为（22.67±9.46）年，副高及以上职称12人。两轮函询有效问卷回收率均为100%，专家权威系数为0.901，协调系数分别为0.238和0.290。最终指标体系包括2个一级指标、10个二级指标、95个三级指标。按需方-供方-交互三维度分类，一级指标为院外延迟因素（0.833 3）和院内延迟因素（0.166 7）。初步验证显示指标体系总分与门-针时间呈显著正相关（r=0.72, P<0.001）。

结论

本研究初步构建了具备可操作性的AIS患者溶栓就医延迟风险评价指标体系，为早期风险识别、临床决策支持和康复预后改善提供了理论框架，但仍需大样本前瞻性研究进一步验证其临床有效性。

, authors=米钰, 席凡, 张淼, 王宗桂, authorsList=米钰, 席凡, 张淼, 王宗桂, authorCompany=null, correspAuthors=张淼, authorNote=

米钰（1995—），男，硕士，主管护师，研究方向：急危重症护理，骨科护理

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张淼，E-mail:
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(In Chinese), articleTitle=Chinese guidelines for diagnosis and treatment of acute ischemic stroke 2023, refAbstract=null)], funds=[Fund(id=1322607939702075963, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607934257869321, awardId=2021jyxm0706, language=CN, fundingSource=安徽省教育厅省级质量工程研究项目(2021jyxm0706), fundOrder=null, country=null), Fund(id=1322607939777573436, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607934257869321, awardId=2022xkj321, language=CN, fundingSource=安徽医科大学校科研基金(2022xkj321), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1322607935126090254, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607934257869321, xref=null, ext=[AuthorCompanyExt(id=1322607935134478863, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607934257869321, companyId=1322607935126090254, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Department of Orthopedics, the Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230601, China), AuthorCompanyExt(id=1322607935138673168, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607934257869321, companyId=1322607935126090254, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=安徽医科大学第二附属医院骨科，安徽　合肥　230601)])], figs=[ArticleFig(id=1322607938506699311, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607934257869321, language=EN, label=Table 1, caption=

Detailed results of two rounds of Delphi Expert Consultation

, figureFileSmall=null, figureFileBig=null, tableContent=
轮次初始条目数保留条目数新增条目数删除条目数修改条目数变异系数满分率(%)
第一轮624801480.09-0.314.76～76.19
第二轮4895470120.09-0.2914.29～76.19
), ArticleFig(id=1322607938569613872, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607934257869321, language=CN, label=表1, caption=

德尔菲法两轮专家咨询详细结果

, figureFileSmall=null, figureFileBig=null, tableContent=
轮次初始条目数保留条目数新增条目数删除条目数修改条目数变异系数满分率(%)
第一轮624801480.09-0.314.76～76.19
第二轮4895470120.09-0.2914.29～76.19
), ArticleFig(id=1322607938712220209, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607934257869321, language=EN, label=Table 2, caption=

Consistency test results of judgment matrix in analytic hierarchy process

, figureFileSmall=null, figureFileBig=null, tableContent=
层次判断矩阵λmaxCIRICR一致性
一级指标2×22.0000.0000.0000.000完全一致
二级指标—院外延迟6×66.3420.0681.2400.055通过
二级指标—院内延迟4×44.1560.0520.9000.058通过
三级指标////0.043通过
), ArticleFig(id=1322607938787717682, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607934257869321, language=CN, label=表2, caption=

层次分析法判断矩阵一致性检验结果

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层次判断矩阵λmaxCIRICR一致性
一级指标2×22.0000.0000.0000.000完全一致
二级指标—院外延迟6×66.3420.0681.2400.055通过
二级指标—院内延迟4×44.1560.0520.9000.058通过
三级指标////0.043通过
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Three-dimensional classification and weight distribution of risk factors

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维度分类包含指标数量累计权重(%)主要风险因素
需方维度4752.3症状识别、就医决策、健康素养、疾病认知等
供方维度2828.1急诊流程、设备配置、人员技能、检查效率等
交互维度2019.6院前-院内衔接、医患沟通、信息传递等
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风险因素三维度分类及权重分布

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维度分类包含指标数量累计权重(%)主要风险因素
需方维度4752.3症状识别、就医决策、健康素养、疾病认知等
供方维度2828.1急诊流程、设备配置、人员技能、检查效率等
交互维度2019.6院前-院内衔接、医患沟通、信息传递等
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Expert consultation results and weights of primary and secondary indicators (round 2)

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一级指标二级指标重要性评分（分，）满分率（%）变异系数权重值
1需方维度 (0.40)1.1人口统计学3.86±0.484.760.120.034 0
1.2一般疾病史4.14±0.6528.570.160.064 0
1.3症状的发生4.76±0.4476.190.090.246 6
1.4首次就诊4.67±0.4866.670.100.178 2
1.5主要照顾者4.14±0.3614.290.090.064 0
2交互维度 (0.35)2.1院外转运4.76±0.4476.190.090.246 6
3供方维度 (0.25)3.1就医流程4.48±0.6052.380.130.031 8
3.2客观监测指标4.29±0.5633.330.130.020 1
3.3检查及报告出具4.52±0.6057.140.130.045 1
3.4溶栓因素4.57±0.6061.900.130.069 7
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一、二级指标专家咨询结果及权重（第2轮）

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一级指标二级指标重要性评分（分，）满分率（%）变异系数权重值
1需方维度 (0.40)1.1人口统计学3.86±0.484.760.120.034 0
1.2一般疾病史4.14±0.6528.570.160.064 0
1.3症状的发生4.76±0.4476.190.090.246 6
1.4首次就诊4.67±0.4866.670.100.178 2
1.5主要照顾者4.14±0.3614.290.090.064 0
2交互维度 (0.35)2.1院外转运4.76±0.4476.190.090.246 6
3供方维度 (0.25)3.1就医流程4.48±0.6052.380.130.031 8
3.2客观监测指标4.29±0.5633.330.130.020 1
3.3检查及报告出具4.52±0.6057.140.130.045 1
3.4溶栓因素4.57±0.6061.900.130.069 7
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Expert consultation results and weights of tertiary indicators (round 2)

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三级指标组合权重(%)三级指标组合权重(%)
1.1.1性别0.030 31.3.3症状的发生场所0.258 9
1.1.2年龄（年）0.032 01.3.4症状的发生地点0.254 0
1.1.3文化程度0.033 31.3.5发病时距最近有溶栓资质的医疗机构行程（h）a0.276 2
1.1.4家庭月收入0.032 31.3.6发病时主要照顾者陪伴情况0.246 6
1.1.5职业0.028 61.3.7患者对疾病的认知a0.276 2
1.1.6居住情况0.030 91.3.8患者对疾病严重性的感知（发病时）a0.276 2
1.1.7医疗费用支付方式0.032 31.3.9 发病时间0.263 9
1.1.8居住场所0.033 01.3.10 发病日期为节假日0.241 7
1.1.9 医务人员向患者讲解过脑卒中相关知识0.037 71.3.11 发病时身边无人帮助0.266 3
1.1.10 了解溶栓时间窗0.038 41.4.1首次就诊医院等级0.196 0
1.2.1合并症0.064 01.4.2首次就诊医院类型0.178 2
1.2.2合并症个数（种）0.067 21.4.3首次就诊科室或部门0.187 1
1.2.3卒中首次发病0.069 11.5.1主要照顾者陪伴就诊情况0.062 7
1.2.4卒中发病次数0.069 81.5.2主要照顾者对疾病的认知0.068 5
1.3.1发病时主要症状a0.271 31.5.3主要照顾者对疾病严重性的感知0.068 5
1.3.2症状的发生时机0.266 31.5.4陪诊人员文化程度0.064 0
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三级指标专家咨询结果及权重（第2轮）

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三级指标组合权重(%)三级指标组合权重(%)
1.1.1性别0.030 31.3.3症状的发生场所0.258 9
1.1.2年龄（年）0.032 01.3.4症状的发生地点0.254 0
1.1.3文化程度0.033 31.3.5发病时距最近有溶栓资质的医疗机构行程（h）a0.276 2
1.1.4家庭月收入0.032 31.3.6发病时主要照顾者陪伴情况0.246 6
1.1.5职业0.028 61.3.7患者对疾病的认知a0.276 2
1.1.6居住情况0.030 91.3.8患者对疾病严重性的感知（发病时）a0.276 2
1.1.7医疗费用支付方式0.032 31.3.9 发病时间0.263 9
1.1.8居住场所0.033 01.3.10 发病日期为节假日0.241 7
1.1.9 医务人员向患者讲解过脑卒中相关知识0.037 71.3.11 发病时身边无人帮助0.266 3
1.1.10 了解溶栓时间窗0.038 41.4.1首次就诊医院等级0.196 0
1.2.1合并症0.064 01.4.2首次就诊医院类型0.178 2
1.2.2合并症个数（种）0.067 21.4.3首次就诊科室或部门0.187 1
1.2.3卒中首次发病0.069 11.5.1主要照顾者陪伴就诊情况0.062 7
1.2.4卒中发病次数0.069 81.5.2主要照顾者对疾病的认知0.068 5
1.3.1发病时主要症状a0.271 31.5.3主要照顾者对疾病严重性的感知0.068 5
1.3.2症状的发生时机0.266 31.5.4陪诊人员文化程度0.064 0
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Validation results of predictive performance of the indicator system

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评价指标数值（95% CI）评价指标数值（95% CI）
与DNT相关系数(r)0.72a（0.58～0.82）特异性(%)71.4（59.8～81.2）
ROC曲线AUC0.78（0.67～0.89）阳性预测值(%)74.2
最佳切点评分2.15阴性预测值(%)73.8
敏感性(%)76.3（65.2～85.1）
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指标体系预测效能验证结果

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评价指标数值（95% CI）评价指标数值（95% CI）
与DNT相关系数(r)0.72a（0.58～0.82）特异性(%)71.4（59.8～81.2）
ROC曲线AUC0.78（0.67～0.89）阳性预测值(%)74.2
最佳切点评分2.15阴性预测值(%)73.8
敏感性(%)76.3（65.2～85.1）
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米钰 , 席凡 , 张淼 , 王宗桂
现代预防医学 | 临床与预防 2025,52(20): 3836-3840
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现代预防医学 |临床与预防 2025 , 52 (20) : 3836 -3840
基于德尔菲法和层次分析法构建急性缺血性脑卒中患者溶栓就医延迟风险评价指标体系
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米钰, 席凡, 张淼 , 王宗桂
作者信息
  • 安徽医科大学第二附属医院骨科，安徽　合肥　230601
通讯作者:
张淼，E-mail:
作者简介:

米钰（1995—），男，硕士，主管护师，研究方向：急危重症护理，骨科护理

Construction of a risk evaluation index systemfor delayed thrombolysis in patients with acute ischemic strokebased on Delphi method and analytic hierarchy process
Yu MI, Fan XI, Miao ZHANG , Zong-gui WANG
Affiliations
  • Department of Orthopedics, the Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230601, China
出版时间: 2025-10-25 doi: 10.20043/j.cnki.MPM.202405198
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摘要
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目的

构建急性缺血性脑卒中（AIS）患者溶栓就医延迟风险评价指标体系，为临床风险预警和干预决策提供科学依据。

方法

采用文献分析和焦点小组访谈法初步构建指标体系，运用德尔菲法和层次分析法确定指标权重，并进行初步验证。

结果

共函询21名专家，平均工作年限为（22.67±9.46）年，副高及以上职称12人。两轮函询有效问卷回收率均为100%，专家权威系数为0.901，协调系数分别为0.238和0.290。最终指标体系包括2个一级指标、10个二级指标、95个三级指标。按需方-供方-交互三维度分类，一级指标为院外延迟因素（0.833 3）和院内延迟因素（0.166 7）。初步验证显示指标体系总分与门-针时间呈显著正相关（r=0.72, P<0.001）。

结论

本研究初步构建了具备可操作性的AIS患者溶栓就医延迟风险评价指标体系，为早期风险识别、临床决策支持和康复预后改善提供了理论框架，但仍需大样本前瞻性研究进一步验证其临床有效性。

缺血性脑卒中  /  德尔菲法  /  层次分析法  /  溶栓就医延迟  /  风险评价
Objective

To establish a risk evaluation index system for delayed thrombolysis in patients with acute ischemic stroke (AIS) based on the three-dimensional framework of demand-supply-interaction, and to provide scientific evidence for clinical risk warning and intervention decision-making.

Methods

Literature analysis and focus group interviews were used to preliminarily establish an index system. The Delphi method and analytic hierarchy process were employed to determine indicator weights, followed by preliminary validation.

Results

A total of 21 experts were consulted with an average working experience of (22.67±9.46) years, 12 of whom held deputy senior titles or above. The effective questionnaire recovery rate for both rounds was 100%, with an expert authority coefficient of 0.901 and coordination coefficients of 0.238 and 0.290, respectively. The final index system comprised 2 first-level indicators, 10 second-level indicators, and 95 third-level indicators. Classified by the three-dimensional demand-supply-interaction framework, the primary indicators were out-of-hospital delay factors (0.833 3) and in-hospital delay factors (0.166 7). Preliminary validation showed significant positive correlation between the total index score and door-to-needle time (r=0.72, P<0.001).

Conclusion

This study preliminarily constructs an operational risk evaluation index system for delayed thrombolysis in AIS patients, providing a theoretical framework for early risk identification, clinical decision support, and prognosis improvement. However, large-scale prospective studies are needed to further validate its clinical effectiveness.

Ischemic stroke  /  Delphi method  /  Analytic hierarchy process  /  Delayed thrombolytic treatment  /  Risk assessment
米钰, 席凡, 张淼, 王宗桂. 基于德尔菲法和层次分析法构建急性缺血性脑卒中患者溶栓就医延迟风险评价指标体系. 现代预防医学, 2025 , 52 (20) : 3836 -3840 . DOI: 10.20043/j.cnki.MPM.202405198
Yu MI, Fan XI, Miao ZHANG, Zong-gui WANG. Construction of a risk evaluation index systemfor delayed thrombolysis in patients with acute ischemic strokebased on Delphi method and analytic hierarchy process[J]. Modern Preventive Medicine, 2025 , 52 (20) : 3836 -3840 . DOI: 10.20043/j.cnki.MPM.202405198
正文
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脑卒中是脑部血液循环障碍致脑组织损伤综合症，有高发病率、高致残率、高病死率和高复发率特点[1]。在我国，脑血管疾病是城市及郊区人口死亡和发病主因[2]。急性缺血性脑卒中（AIS）占所有卒中的80%，早期溶栓治疗对其患者预后改善显著，但需在发病后4.5小时内进行[3-5]。然而，我国AIS患者溶栓治疗率远低于欧美，就医延迟是主要原因[6]。现有研究关注溶栓就医延迟的多个风险因素及相关干预措施[7-8]，但缺乏整体评估风险因素及探讨各因素重要性的系统性研究，临床缺标准化评价工具和客观量化指标。构建AIS患者溶栓就医延迟风险评价指标体系意义重大：①可早期预警，量化评估各环节延迟风险；②作为临床决策支持工具，指导医疗机构优化资源配置和流程；③有助于改善康复预后，指导制定个体化康复方案。为确保指标体系的理论严谨性和实用性，本研究基于Andersen行为模型和Donabedian质量评价框架，引入卫生服务利用的"需方-供方-交互"三维度理论模型[9]，拟用德尔菲法和层次分析法构建该指标体系，为改善溶栓就医流程和提高治疗效果提供科学依据。
1　资料与方法
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1.1　初步构建评价指标体系
1.1.1　文献调研
通过中英文数据库检索文献，收集AIS患者溶栓就医延迟风险因素。中文检索词：脑卒中、中风、急性缺血性脑卒中、溶栓、就医延迟等，在CNKI、万方、维普等数据库检索；英文检索词：stroke、ischemic stroke、thrombolysis、treatment delay、prehospital delay等，在PubMed、Cochrane Library、Web of Science等数据库检索。
1.1.2　焦点小组访谈
采用目的抽样法，选取安徽某三甲医院急诊科与神经内科12名医护人员为访谈对象，访谈大纲涵盖脑卒中认知、风险因素、临床实践经验等主题。
1.1.3　理论框架构建
基于“需方-供方-交互”三维度理论模型，将风险因素进行系统分类：①需方维度：患者个体特征、认知能力、决策行为等；②供方维度：医疗资源配置、服务流程、技术能力等；③交互维度：信息传递、沟通协调、系统衔接等，结合文献调研、医务人员访谈和课题小组研讨，初步构建的指标体系草案含2个一级指标、10个二级指标和62个三级指标。
1.2　德尔菲专家函询法
①专家纳入标准：急诊或神经内科工作超10年、本科及以上学历、中级及以上职称、自愿参与。排除标准：2月内无法完成函询。②依据草案设计专家函询问卷，含介绍信、专家基本情况表和风险评估指标体系，采用Likert 5分制评分（1=很不重要，5=非常重要）。③筛选标准：重要性赋值均值≥3.5、满分率≥20%、变异系数≤0.25的指标[10]，并结合专家意见和临床实际确定入选指标。④通过电话、邮件联系专家发放问卷，整合首轮函询结果形成第二轮问卷，共开展2轮函询。
1.3　层次分析法确定权重
采用层次分析法（AHP）确定指标权重。使用Yaahp 12.0软件构建层次结构模型，根据专家评分构建判断矩阵并进行一致性检验（CR<0.1）；采用百分权重法计算三级指标权重；将三级指标权重与二级指标权重相乘，得出组合权重值。
1.4　指标体系初步验证
1.4.1　验证对象
回顾性收集2025年1—6月某三甲医院收治的78例AIS患者病历资料。纳入标准：①确诊为急性缺血性脑卒中；②发病后4.5小时内到院；③静脉溶栓治疗；④病历完整。排除标准：①合并严重心脑血管疾病；②拒绝参与研究。
1.4.2　验证方法
应用构建的指标体系对78例患者进行风险评分，以实际“门-针时间”(DNT)作为金标准进行效度验证。采用Pearson相关分析评估指标体系得分与DNT的相关性，绘制ROC曲线评估预测效能。
1.5　统计学方法
采用Excel 2013和SPSS 20.0进行数据分析。计算专家积极系数（问卷回收率）、权威系数（Cr）和肯德尔协调系数（Kendall W）。采用描述性统计分析专家基本特征，用均数±标准差表示连续性变量。检验水准α=0.05。
2　结果
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2.1　专家基本情况
本研究邀请21位权威专家进行2轮函询，含3位神经内科专家及18位护理专家。专家年龄31—59（43.71±8.03）岁，工作年限8—41（22.67±9.46）年，其中18人（85.71%）工作超10年。所有专家职称中级及以上，12人（57.14%）为副高及以上职称。
2.2　专家积极程度和权威程度
两轮专家函询问卷回收率100%，权威系数为0.901，表明专家权威程度较高。
2.3　专家意见协调程度
两轮专家函询的Kendall W值分别为0.238和0.290（P均<0.05），变异系数从第一轮的0.31±0.08降至第二轮的0.23±0.06，表明专家意见逐步趋于协调。
2.4　德尔菲法专家函询详细过程
经过2轮专家函询指标共做出如下调整（表1）：①第一轮删除14个指标，主要因变异系数>0.25或满分率<20%；②第二轮根据专家建议新增47个指标，主要集中在院前转运环节和溶栓决策过程。
2.5　层次分析法一致性检验结果
所有判断矩阵CR值均<0.1，满足一致性要求，具体结果见表2。
2.6　指标体系最终结果及三维度权重分布
最终评价指标体系包括2个一级指标、10个二级指标、95个三级指标。按照“需方-供方-交互”三维度分类统计权重分布，见表3~表5。
2.7　指标体系初步验证结果
2.7.1　验证样本特征
78例AIS患者中，男性45例（57.7%），平均年龄（68.5±12.3）岁；平均DNT时间（76.2±28.4）分钟；发病到院时间中位数89分钟（IQR: 45～156分钟）。
2.7.2　预测效能评估
结果显示，构建的指标体系与实际溶栓延迟时间呈显著正相关，具有较好的预测效能，特别是在识别院外延迟高风险方面表现突出（需方维度评分与DNT相关系数r=0.72，P<0.001），具体结果见表6。
3　讨论
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3.1　指标体系权重分析及临床意义
从一级指标看，院外延迟因素权重高达83.33%，印证了Wang等[11]的研究，多数患者发病后3小时内未到医院，主要因犹豫不决[12]。在二级指标层面，“症状的发生因素”与“院外转运因素”并驾齐驱（权重均为24.66%），成为评价的关键要素。从需方维度看，症状识别能力不足是首要问题[13]；从交互维度看，院前急救系统与医院的信息传递效率直接影响转运质量[14]；其次是“首次就诊因素”（权重17.82%），说明必须加大对公众关于卒中地图的教育力度[15]。
3.2　科学性与可靠性评价
本研究经两轮德尔菲咨询达成专家共识（Kendall W=0.290, P<0.001），AHP一致性比率CR均<0.1，初步构建可操作的指标体系框架。但研究仍存在一定局限性：一是专家样本多来自三级以上医院，基层代表性不足；二是权重赋值未充分考虑城乡和地区医疗资源不均问题；三是基于21位专家共识，样本量有限。故本指标体系的临床有效性和预测效能需多中心大样本前瞻性研究进一步验证。
3.3　低权重指标的保留依据
本研究保留权重较低指标具有多维度的临床与理论依据。从病理生理机制看，应激性高血糖会加剧氧化应激反应，加重血脑屏障损伤，AHA/ASA指南强调将血糖控制在22.2 mmol/L以下是确保rt-PA安全性的必要条件[16]。肌力分级是NIHSS评分核心，基线肌力≤3级患者出血转化风险增加34%[17]。有研究证实收缩压在140～179 mmHg区间时患者90天mRS评分最优[18]。心电图检查影响心源性卒中鉴别及抗凝治疗策略制定，心源性栓塞约占急性缺血性卒中的28.7%[19]。另外，从质量评价体系构建而言，指标保留遵循三大原则：一是符合国际卒中管理TIME框架且覆盖全流程；二是满足国家卒中质控中心对溶栓病历数据完整性的要求；三是为机器学习模型提供特征工程基础[20]。
3.4　多主体协同干预策略
识别风险因素的最终目标在于指导干预，而有效的干预必须明确责任主体。基于三维度分析结果，本研究提出多主体协同干预策略，构建覆盖全流程的责任体系。①卫生行政部门承担政策制定与资源统筹职责，通过建立区域卒中急救网络，预期可将区域溶栓率提升20%；②医疗机构承担流程优化与能力建设职责，目标是将DNT时间缩短30%；③急救中心负责院前识别与预警，力争院前识别率达到85%；④社区卫生机构承担健康教育与筛查职责，预期首诊正确率提升25%；⑤患者及家属需主动参与配合，实现发病-呼救时间控制在15分钟以内。并提出可操作性保障措施，如①建立卫健委牵头的卒中救治协调小组；②设立卒中急救网络建设专项基金；③开发卒中风险评估APP；④将溶栓率、DNT时间等纳入医院绩效考核和医保支付标准。
3.5　研究局限性与展望
本研究构建的风险评价指标体系全面深入，但存在以下局限性：①专家地域分布相对集中；②验证样本量有限，仅为单中心回顾性研究；③部分指标的量化标准需进一步细化；④缺乏不同级别医院的适用性验证。未来研究方向：①开展多中心前瞻性队列研究；②基于大数据和机器学习技术构建动态风险预测模型；③探索指标体系在基层医疗机构的适用性；④结合健康经济学评价，量化干预措施的成本效益比。
基金
收起
  • 安徽省教育厅省级质量工程研究项目(2021jyxm0706)
  • 安徽医科大学校科研基金(2022xkj321)
文献
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2025年第52卷第20期
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doi: 10.20043/j.cnki.MPM.202405198
  • 接收时间：2024-05-13
  • 首发时间：2026-10-29
  • 出版时间：2025-10-25
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  • 收稿日期：2024-05-13
基金
安徽省教育厅省级质量工程研究项目(2021jyxm0706)
安徽医科大学校科研基金(2022xkj321)
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    安徽医科大学第二附属医院骨科，安徽　合肥　230601

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