Biomarkers as predictors of mortality in critically ill patients with solid tumors

Reis, Audrey Machado dos; Fruchtenicht, Ana Valéria Gonçalves; Athaydes, Luiza C. De; Loss, Sérgio Henrique; Moreira, Luís Fernando

doi:10.1590/0001-3765201720170601

Cited by 2 publications

(1 citation statement)

References 37 publications

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“…9 Some studies have described different types of new biomarkers, including plasma Mg, high-mobility group protein B1, and urokinase-type plasminogen activator receptor, in the ongoing search for better tools for prognosis of mortality. [10][11][12] However, eosinophil count would be a more attractive biomarker due to its availability, low cost, and minimum delay between taking blood samples and obtaining results, compared to standard scoring systems and other suggested biomarkers. This study therefore was aimed at determining whether or not eosinophil count can be used for prognostic estimates in non-traumatic patients who have undergone cardiopulmonary resuscitation (CPR) and were subsequently hospitalized in an ICU.…”

Section: Introductionmentioning

confidence: 99%

Eosinophil Cell Count Predicts Mortality in the Intensive Care Unit after Return of Spontaneous Circulation

Korkmaz¹,

Tekin²,

Tekin³

et al. 2022

Rambam Maimonides Med J

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Background: Eosinophils constitute 1%–5% of peripheral blood leukocytes, less in the presence of acute infections (referred to as eosinopenia). Studies indicate that eosinopenia can be used as a prognostic predictor for chronic obstructive pulmonary disease exacerbation, sepsis, or acute myocardial infarction disease. There are only a few studies about predicting mortality in emergency departments and intensive care units (ICUs). Prognostic studies about patients in ICUs are generally carried out using different scoring systems. We aimed to analyze if the eosinophil count can estimate the prognosis among non-traumatic patients who underwent cardiopulmonary resuscitation and were hospitalized in ICU thereafter. Methods: The data were evaluated of 865 non-traumatic adult patients (>18 years of age) who were admitted with cardiopulmonary arrest or developed cardiopulmonary arrest during clinical follow-ups. Admission venous blood sample tests, complete blood count, and biochemical laboratory results were recorded. Arterial blood gas results were also evaluated. The mean results of the recorded laboratory results were compared between the surviving and non-surviving patients groups. Results: There was a significant difference between the two groups in regard to platelet, eosinophil count, pH, PaO2, SaO2, and HCO3- (P<0.001 for all). In the multiple linear regression analysis, eosinophil counts were found to be an independent factor (odds ratio=0.03, 95% confidence interval 0.33–0.56, P<0.001) associated with the mortality after cardiopulmonary resuscitation. Conclusion: Because admission eosinophil counts can be measured easily, they are inexpensive biomarkers that can be used for predicting the prognosis among the patients who have return of spontaneous circulation and are treated in ICUs.

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Section: Introductionmentioning

confidence: 99%

Eosinophil Cell Count Predicts Mortality in the Intensive Care Unit after Return of Spontaneous Circulation

Korkmaz¹,

Tekin²,

Tekin³

et al. 2022

Rambam Maimonides Med J

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Paving the way for precision medicine v2.0 in intensive care by profiling necroinflammation in biofluids

Berghe

Hoste

2018

Cell Death Differ

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Current clinical diagnosis is typically based on a combination of approaches including clinical examination of the patient, clinical experience, physiologic and/or genetic parameters, high-tech diagnostic medical imaging, and an extended list of laboratory values mostly determined in biofluids such as blood and urine. One could consider this as precision medicine v1.0. However, recent advances in technology and better understanding of molecular mechanisms underlying disease will allow us to better characterize patients in the future. These improvements will enable us to distinguish patients who have similar clinical presentations but different cellular and molecular responses. Treatments will be able to be chosen more "precisely", resulting in more appropriate therapy, precision medicine v2.0. In this review, we will reflect on the potential added value of recent advances in technology and a better molecular understanding of necrosis and inflammation for improving diagnosis and treatment of critically ill patients. We give a brief overview on the mutual interplay between necrosis and inflammation, which are two crucial detrimental factors in organ and/or systemic dysfunction. One of the challenges for the future will thus be the cellular and molecular profiling of necroinflammation in biofluids. The huge amount of data generated by profiling biomolecules and single cells through, for example, different omic-approaches is needed for data mining methods to allow patient-clustering and identify novel biomarkers. The real-time monitoring of biomarkers will allow continuous (re)evaluation of treatment strategies using machine learning models. Ultimately, we may be able to offer precision therapies specifically designed to target the molecular set-up of an individual patient, as has begun to be done in cancer therapeutics.

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Biomarkers as predictors of mortality in critically ill patients with solid tumors

Cited by 2 publications

References 37 publications

Eosinophil Cell Count Predicts Mortality in the Intensive Care Unit after Return of Spontaneous Circulation

Eosinophil Cell Count Predicts Mortality in the Intensive Care Unit after Return of Spontaneous Circulation

Paving the way for precision medicine v2.0 in intensive care by profiling necroinflammation in biofluids

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