Jean Pierre Aashika Raagavi, Green Siva Ranganathan, Anandaraj Lokeshmaran, Sivaprakasam Manikandan, Kasirajan Anand, Devaraju Panneer, Anumulapuri Srilekha, Mutheneni Srinivasa Rao, Balakrishna Pillai Agieshkumar
MGM Advanced Research Institute (MGMARI), Sri Balaji Vidyapeeth (Deemed to be University), Puducherry, India.
Department of General Medicine, Mahatma Gandhi Medical College and Research Institute (MGMCRI), Sri Balaji Vidyapeeth (Deemed to be University, Puducherry, India.
Biomarkers. 2024 Dec;29(8):557-564. doi: 10.1080/1354750X.2024.2430997. Epub 2024 Nov 28.
Dengue virus causes illnesses with or without warning indicators for severe complications. There are no clear prognostic signs linked to the disease outcomes.
Clinical and laboratory parameters among 102 adult including 17 severe dengue (SD), 33 with warning and 52 without warning signs during early and critical phases were analysed by statistical and machine learning (ML) models.
In classical statistics, abnormal ultrasound findings, platelet count and low lymphocytes were significantly linked with SD during the febrile phase, while low creatinine, high sodium and elevated AST/ALT during the critical phase. ML models highlighted AST/ALT and lymphocytes as key markers for distinguishing SD from non-severe dengue, aiding clinical decisions.
Parameters like liver enzymes, platelet counts and USG findings were linked with SD.USG testing at an earlier phase of dengue and a point-of-care system for the quantification of AST/ALT levels may lead to an early prediction of SD.
登革病毒引发的疾病可能伴有或不伴有严重并发症的预警指标。目前尚无与疾病预后相关的明确预后迹象。
采用统计和机器学习（ML）模型，对102名成年人在疾病早期和关键阶段的临床和实验室参数进行分析，其中包括17例重症登革热（SD）、33例有预警症状者和52例无预警症状者。
在经典统计学中，发热期异常超声检查结果、血小板计数和淋巴细胞减少与重症登革热显著相关，而在关键阶段则表现为肌酐降低、血钠升高和AST/ALT升高。ML模型突出了AST/ALT和淋巴细胞是区分重症登革热与非重症登革热的关键标志物，有助于临床决策。
肝酶、血小板计数和超声检查结果等参数与重症登革热相关。在登革热早期进行超声检查以及采用即时检测系统定量检测AST/ALT水平，可能有助于早期预测重症登革热。
