预测评分量表对卒中相关性肺炎的应用价值
2020-02-16舒兆瑞王兵张克飞
舒兆瑞 王兵 张克飞
摘要:目的 分析多種卒中相关性肺炎危险因素预测评分表的特点及其临床应用价值。方法 检索PubMed和CNKI中有关卒中相关性肺炎危险因素预测评分表的文献,包括针对SAP制定预测评分表的文献及应用现有卒中相关评分表预测SAP的文献,用诊断试验质量评价工具(QUADAS-2)对文献报道的预测评分量表进行危险因素评分,分析相关评分与卒中相关性肺炎诊断率的关系,评估相关预测评分的临床应用价值。结果 共检索到238篇相关研究文献,针对SAP制定预测评分表的文献162篇,应用现有卒中相关评分表预测SAP的文献76篇,共涉及13种预测评分表,其中年龄和NIHSS评分几乎在所有预测评分表中都有出现。对6种评分表进行了内部验证,5种评分表进行了外部验证,A2DS2评分是目前最受认可的,其敏感性和特异性均高于其他预测评分表。结论 临床预测模型在应用时简单易行,不同评分表之间的敏感性和特异性是相似的。目前预测评分表对卒中相关性肺炎有一定的应用价值,但缺乏相关大型研究评价这些评分表对临床决策和预后的影响,其实用性仍需更多的临床研究来验证。
关键词:卒中相关性肺炎;预测评分量表;危险因素;年龄;NIHSS评分
中图分类号:R743.3 文献标识码:A DOI:10.3969/j.issn.1006-1959.2020.01.038
文章编号:1006-1959(2020)01-0124-03
Application Value of Predictive Scoring Scale for Stroke-associated Pneumonia
SHU Zhao-rui,WANG Bing,ZHANG Ke-fei
(Department of Neurology,Huai'an Hospital,Nanjing University of Traditional Chinese Medicine,Huai'an 223001,Jiangsu,China)
Abstract:Objective To analyze the characteristics of multiple stroke-associated pneumonia risk factor prediction scores and their clinical application value. Methods Retrieve the relevant literature on the risk-related predictive scores for stroke-associated pneumonia in PubMed and CNKI, including the literature on the development of predictive scores for SAP and the literature on the use of existing stroke-related scores to predict SAP.The diagnostic test quality assessment tool (QUADAS-2) was used to evaluate the risk factor scores of the predictive score scales reported in the literature, and the relationship between the relevant scores and the diagnosis rate of stroke-associated pneumonia was analyzed to evaluate the clinical application value of the relevant predictive scores.Results A total of 238 related research literatures were retrieved, 162 were used to develop predictive scores for SAP, and 76 were used to predict SAP using existing stroke-related scores. A total of 13 predictive scores were involved, including age and NIHSS scores in almost all all appear in the forecast score sheet. 6 types of scoring tables were verified internally and 5 types of scoring tables were externally verified. The A2DS2 score is currently the most recognized, and its sensitivity and specificity are higher than other predictive score tables.Conclusion The clinical prediction model is simple and easy to apply, and the sensitivity and specificity are similar among different scoring tables. At present, the predictive scores have certain application value for stroke-related pneumonia, but there is a lack of large-scale studies to evaluate the impact of these scores on clinical decision-making and prognosis, and its practicality needs to be verified by more clinical studies.
Key words:Stroke-associated pneumonia;Predictive scoring scale;Risk factors;Age;NIHSS score
自Hilker R等[1]2003年提出卒中相关性肺炎(SAP)的概念后,临床上对该病的诊治在不断探索中取得了较大的进展,卒中相关性肺炎诊断专家共识[2]建议将卒中急性期并发的一系列下呼吸道感染统称为SAP,并将SAP的发病时间限定为卒中发病后7 d内,进一步明确了该病的诊断标准。为早期预测SAP的发生风险,针对该病的预测模型也在不断研究中,但目前仍缺乏高质量的循证医学证据,相关模型量表的建立不仅可以对SAP风险进行评估,也可以为相应治疗疗效的评定提供参考。本文主要对近年来SAP预测模型相关量表进行对比,以期为建立更有价值的预测模型提供参考依据。
1资料与方法
1.1数据来源 在PubMed和CNKI进行中,使用关键词肺炎、脑梗死、脑出血、脑卒中、危险评分、卒中相关性肺炎进行自动检索,检索时间设定为2003年1月~2019年5月。同时手动检索一些潜在的可能符合条件的文章。
1.2数据筛选和分组 检索目前已应用于临床、且有相关文献报道的预测评分模型(按时间先后顺序)并分组:组1:针对SAP制定预测评分表的文献;组2:应用现有卒中相关评分表预测SAP的文献。检索到的文献必须具备条件:相关研究文献应用Logistic回归模型分析SAP的独立危险因素,统计独立危险因素制定表。
1.3数据统计分析 分析检索到的评分表的组成、样本数量、内部验证、外部验证、特异性和敏感性,使用诊断试验质量评价工具(QUADAS-2)对评分表进行适用性和风险性评估,由两人分别独立完成评估。比较各个预测评分表的灵敏度和特异度,用Youde指数确定最佳诊断界值,检验水准α=0.05,P<0.05表示差异有统计学意义。
2结果
2.1检索情况 共检索到238篇相关研究文献,组1和组2分别为162篇、76篇,共涉及13种量表。组1中量表包括:The Pneumania Score[3]、VHA Score(Veteran's Health Administration Cohort Score)[4]、A2DS2[5]、PANTHERIS[6]、AIS-APS[7]、ICS-APS[8](ICS-APS-A;ICS-APS-B)、PNA(Pneumonia)Score[9]、ISAN (Prestroke Independence,Sex,Age,NIHSS)Score[10]及ACDD4[11]。組2中量表包括THRIVE Score[12]、IScore[13]、ASTRAL[14]、PLAN Score(Preadmission Comorbidities,Level of Consciousness,Age,Neurologic Deficit)[15]。其中年龄是每个预测评分量表都有的项目,NIHSS评分除PANTHERIS和IScore Score中没有外,其他预测评分表也都有。但IScore Score应用了CNS评分评估卒中严重程度,并且依据需要可相互转换。不同研究的Logistic回归模型结果均提示:心脏疾病(房颤、充血性心力衰竭)、吞咽障碍、意识障碍、性别、血糖异常、吸烟史、波谱成像、血压异常、COPD、白细胞增高可能为SAP的独立危险因素。但由于NIHSS评分与吞咽障碍、卒中类型、意识障碍均有较强的相关性,可能导致多因素Logistic回归部分结果偏差甚至无法解释,故部分研究在统计时未将NIHSS评分纳入多因素Logistic模型中。13种预测评分量表涉及的因素见表1。
2.2风险评分验证结果 分别统计不同量表的Youden指数并选择最大切点为临界点,即(灵敏度+特异度-1)达到最大所对应的值为SAP最佳诊断临界点,见表2。
3讨论
SAP本身的复杂性为临床诊疗带来了诸多困难,该病涉及的危险因素众多,针对患者不同病理生理阶段选择最佳的预防措施尤为重要,因此准确评估患者病情程度成为临床研究的重点。本次调查发现,目前临床中存在较多的SAP危险因素预测评分表,其中年龄和NIHSS评分在大部分量表中都有出现。不同研究的Logistic回归模型结果均提示:心脏疾病(房颤、充血性心力衰竭)、吞咽障碍、意识障碍、性别、血糖异常、吸烟史、波谱成像、血压异常、COPD、白细胞增高可能为SAP的独立危险因素。再一次验证了年龄、NIHSS、意识障碍、吞咽困难、心脏疾病可能为SAP独立危险因素。本次研究显示,A2DS2量表评分≥5分预测SAP的敏感性和特异性分别为95.00%和50.00%,A2DS2的评分项目较少,且均为患者临床资料,在计算NIHSS评分的前提下较易计算,临床操作性较强。同时,在现有的卒中预测量表中,ASTRAL SCORE量表也表现出较高的准确性。
结合本研究发现,所有文献报道都详细记录了研究样本的选择,除了一项前瞻性研究,其他都为回顾性评价。预测评分量表的定义和组成风险因素的方案是多种多样的,而且常受到数据可用性的限制。如:吞咽困难并不是在所有预测评分量表中都出现,并且卒中前功能障碍评估中就有该项目,只是描述方法不同。还有一些研究并没有记录患者入院前已经存在的残疾。在SAP诊断意见统一之前,各研究的诊断仍存在一定差异[16,17]。目前对于卒中相关性肺炎的诊断率仍偏低,本研究尚需要进一步随机对照临床研究以验证相关SAP独立危险因素,以制定符合本地区人群发病特点的相应评估量表,以提高对SAP的诊断率,早起预防治疗。
综上所述,SAP危险因素预测评分表使用简单易行,相应的计分数据也较容易获得,且在相应的研究中已经证实拥有不错的预测能力。这些量表不但可以协助临床医师提高对SAP的预测评估,制定出相应的治疗方案,还可以在患者家属咨询有关预后问题时帮助医患之间沟通。同时今后将进行前瞻性随机对照研究以验证相关SAP独立危险因素,制定符合本地区人群发病特点的相应评估量表,以提高对SAP的诊断率,早起预防治疗。
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收稿日期:2019-09-22;修回日期:2019-10-29
編辑/王朵梅