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Prediction of Sepsis Progression in Critical Illness Using Artificial Neural Network

机译:人工神经网络预测危重疾病中脓毒症进展

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Early treatment of sepsis can reduce mortality and improve a patient condition. However, the lack of clear information and accurate methods of diagnosing sepsis at an early stage makes it become a significant challenge. The decision to start, continue or stop antimicrobial therapy is normally base on clinical judgment since blood cultures will be negative in the majority of cases of septic shock or sepsis. However, clinical guidelines are still required to provide guidance for the clinician caring for a patient with severe sepsis or septic shock. Guidelines based on patient's unique set of clinical variables will help a clinician in the process of decision making of suitable treatment for the particular patient. Therefore, biomarkers for sepsis diagnosis with a reasonable sensitivity and specificity are a requirement in ICU settings, as a guideline for the treatment. Moreover, the biomarker should also allow availability in real-time and prediction of sepsis progression to avoid delay in treatment and worsen the patient condition.
机译:早期治疗败血症可以减少死亡率并改善患者状况。然而,缺乏明确的信息和准确的方法在早期阶段诊断败血症使其成为一个重大挑战。开始,继续或停止抗菌治疗的决定通常基于临床判断,因为血液培养在大多数脓毒症休克或败血症病例中。然而,仍然需要临床指南,为患有严重脓毒症或脓毒症休克的患者提供临床医生的指导。基于患者独特的临床变量的指南将帮助临床医生在特定患者的合适治疗过程中。因此,具有合理敏感性和特异性的败血症诊断的生物标志物是ICU环境的要求,作为治疗的指导。此外,生物标志物还应允许实时和预测脓毒症进展的可用性,以避免延迟治疗并恶化患者状况。

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