Lulu Wan, Gan Lin, Jiale Yang, Anwei Liu, Xuezhi Shi, Jinhu Li, Lian Xie, Ronglin Chen, Huasheng Tong
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The predictive models based on these risk factors were constructed and externally validated, and their predictive efficacy was evaluated using receiver operating characteristic curves.</p><p><strong>Results: </strong>A total of 219 HS patients, including 49 with DIC, were included. The independent risk factors for DIC were identified as follows: neutrophil percentage (Neu%), lymphocyte count, lymphocyte percentage (Lym%), creatine kinase-MB (CKMB), lactate dehydrogenase (LDH), aspartate aminotransferase (AST), neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), and rhabdomyolysis (RM). After logarithmization, the final predictive model based on the logarithm of lactate dehydrogenase (InLDH; odds ratio (OR) = 9.266, 95% confidence interval (95%CI; 4.379-19.607), <i>p</i> < 0.0001) and the logarithm of neutrophil-lymphocyte ratio (InNLR; OR = 3.393, 95%CI (1.834-6.277), <i>p</i> < 0.0001) was constructed with the largest area under the curve (0.928). A nomogram incorporating InLDH and InNLR was developed and showed excellent discrimination and calibration capabilities.</p><p><strong>Conclusion: </strong>Nine independent risk factors were identified for the occurrence of DIC in HS patients. The predictive model based on InLDH and InNLR can effectively predict the incidence of DIC. A nomogram based on InLDH and InNLR was developed to facilitate early identification and timely treatment of DIC in HS patients.</p>","PeriodicalId":23048,"journal":{"name":"Therapeutic Advances in Hematology","volume":"16 ","pages":"20406207241311386"},"PeriodicalIF":3.4000,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11719444/pdf/","citationCount":"0","resultStr":"{\"title\":\"A nomogram based on InLDH and InNLR for predicting disseminated intravascular coagulation in patients with heat stroke.\",\"authors\":\"Lulu Wan, Gan Lin, Jiale Yang, Anwei Liu, Xuezhi Shi, Jinhu Li, Lian Xie, Ronglin Chen, Huasheng Tong\",\"doi\":\"10.1177/20406207241311386\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Heat stroke (HS), a potentially fatal heat-related illness, is often accompanied by disseminated intravascular coagulation (DIC) early, resulting in a poorer prognosis. Unfortunately, diagnosis by current DIC scores is often too late to identify DIC. This study aims to investigate the predictors and predictive model of DIC in HS to identify DIC early.</p><p><strong>Methods: </strong>This retrospective study analyzed clinical data of patients with HS in a tertiary hospital from January 1, 2008 to December 31, 2020. Univariate and multivariate logistic regression analyses were employed to identify the risk factors for DIC in HS. The predictive models based on these risk factors were constructed and externally validated, and their predictive efficacy was evaluated using receiver operating characteristic curves.</p><p><strong>Results: </strong>A total of 219 HS patients, including 49 with DIC, were included. The independent risk factors for DIC were identified as follows: neutrophil percentage (Neu%), lymphocyte count, lymphocyte percentage (Lym%), creatine kinase-MB (CKMB), lactate dehydrogenase (LDH), aspartate aminotransferase (AST), neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), and rhabdomyolysis (RM). After logarithmization, the final predictive model based on the logarithm of lactate dehydrogenase (InLDH; odds ratio (OR) = 9.266, 95% confidence interval (95%CI; 4.379-19.607), <i>p</i> < 0.0001) and the logarithm of neutrophil-lymphocyte ratio (InNLR; OR = 3.393, 95%CI (1.834-6.277), <i>p</i> < 0.0001) was constructed with the largest area under the curve (0.928). A nomogram incorporating InLDH and InNLR was developed and showed excellent discrimination and calibration capabilities.</p><p><strong>Conclusion: </strong>Nine independent risk factors were identified for the occurrence of DIC in HS patients. The predictive model based on InLDH and InNLR can effectively predict the incidence of DIC. A nomogram based on InLDH and InNLR was developed to facilitate early identification and timely treatment of DIC in HS patients.</p>\",\"PeriodicalId\":23048,\"journal\":{\"name\":\"Therapeutic Advances in Hematology\",\"volume\":\"16 \",\"pages\":\"20406207241311386\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2025-01-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11719444/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Therapeutic Advances in Hematology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/20406207241311386\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"HEMATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Therapeutic Advances in Hematology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/20406207241311386","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"HEMATOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
背景:中暑(HS)是一种具有潜在致命性的热相关疾病,早期常伴有弥散性血管内凝血(DIC),预后较差。不幸的是,目前的DIC评分诊断往往太晚,无法识别DIC。本研究旨在探讨HS患者DIC的预测因素及预测模型,以期早期发现DIC。方法:回顾性分析某三级医院2008年1月1日至2020年12月31日HS患者的临床资料。采用单因素和多因素logistic回归分析确定HS患者发生DIC的危险因素。构建基于这些危险因素的预测模型并进行外部验证,利用受试者工作特征曲线评价其预测效果。结果:共纳入HS患者219例,其中合并DIC患者49例。DIC的独立危险因素确定为:中性粒细胞百分比(Neu%)、淋巴细胞计数、淋巴细胞百分比(Lym%)、肌酸激酶- mb (CKMB)、乳酸脱氢酶(LDH)、天冬氨酸转氨酶(AST)、中性粒细胞-淋巴细胞比率(NLR)、单核细胞-淋巴细胞比率(MLR)和横纹肌溶解(RM)。对数化后,最终的预测模型基于乳酸脱氢酶(InLDH;优势比(OR) = 9.266, 95%可信区间(95% ci;4.379-19.607), p < 0.0001)和中性粒细胞-淋巴细胞比率的对数(InNLR;OR = 3.393, 95%CI (1.834-6.277), p < 0.0001),曲线下面积最大(0.928)。结合InLDH和InNLR的nomogram,显示出良好的判别和校准能力。结论:确定了HS患者发生DIC的9个独立危险因素。基于InLDH和InNLR的预测模型能有效预测DIC的发生。建立了基于InLDH和InNLR的图,以促进HS患者DIC的早期识别和及时治疗。
A nomogram based on InLDH and InNLR for predicting disseminated intravascular coagulation in patients with heat stroke.
Background: Heat stroke (HS), a potentially fatal heat-related illness, is often accompanied by disseminated intravascular coagulation (DIC) early, resulting in a poorer prognosis. Unfortunately, diagnosis by current DIC scores is often too late to identify DIC. This study aims to investigate the predictors and predictive model of DIC in HS to identify DIC early.
Methods: This retrospective study analyzed clinical data of patients with HS in a tertiary hospital from January 1, 2008 to December 31, 2020. Univariate and multivariate logistic regression analyses were employed to identify the risk factors for DIC in HS. The predictive models based on these risk factors were constructed and externally validated, and their predictive efficacy was evaluated using receiver operating characteristic curves.
Results: A total of 219 HS patients, including 49 with DIC, were included. The independent risk factors for DIC were identified as follows: neutrophil percentage (Neu%), lymphocyte count, lymphocyte percentage (Lym%), creatine kinase-MB (CKMB), lactate dehydrogenase (LDH), aspartate aminotransferase (AST), neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), and rhabdomyolysis (RM). After logarithmization, the final predictive model based on the logarithm of lactate dehydrogenase (InLDH; odds ratio (OR) = 9.266, 95% confidence interval (95%CI; 4.379-19.607), p < 0.0001) and the logarithm of neutrophil-lymphocyte ratio (InNLR; OR = 3.393, 95%CI (1.834-6.277), p < 0.0001) was constructed with the largest area under the curve (0.928). A nomogram incorporating InLDH and InNLR was developed and showed excellent discrimination and calibration capabilities.
Conclusion: Nine independent risk factors were identified for the occurrence of DIC in HS patients. The predictive model based on InLDH and InNLR can effectively predict the incidence of DIC. A nomogram based on InLDH and InNLR was developed to facilitate early identification and timely treatment of DIC in HS patients.
期刊介绍:
Therapeutic Advances in Hematology delivers the highest quality peer-reviewed articles, reviews, and scholarly comment on pioneering efforts and innovative studies across all areas of hematology. The journal has a strong clinical and pharmacological focus and is aimed at clinicians and researchers in hematology, providing a forum in print and online for publishing the highest quality articles in this area.