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AssigneeChildren's Hospital Medical Center
InventorsMihir ATREYA, Natalja STANSKI
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Methods and compositions disclosed herein generally relate to methods of identifying, validating, and measuring clinically relevant, quantifiable biomarkers of diagnostic and therapeutic responses for blood, vascular, cardiac, and respiratory tract dysfunction, particularly as those responses relate to septic shock in pediatric patients. Certain aspects of the invention relate to identifying one or more biomarkers associated with septic shock in pediatric patients in combination with one or more endothelial-derived biomarkers, receiving a dataset comprising biomarker concentrations, wherein the dataset is from a sample obtained from a pediatric patient having at least one indication of septic shock, then determining whether the biomarker concentrations of each of the at least one biomarkers are greater than one or more pre-determined cut-off biomarker concentration, wherein the level of said biomarker correlates with a predicted outcome.
A method of classifying a patient with septic shock as high risk of sepsis-associated acute kidney injury (SA-AKI) or other than high risk of SA-AKI, the method comprising:
The method of any preceding claim, wherein biomarker expression levels comprise serum protein biomarker concentrations.
The method of any preceding claim, wherein biomarker expression levels are determined by quantifying serum protein biomarker concentrations and/or by cycle threshold (CT) values.
The method of any preceding claim, wherein the determined biomarker expression levels comprise expression levels of one or more pairs of biomarkers selected from the group consisting of:
The method of any preceding claim, wherein the determined biomarker expression levels comprise expression levels of Tie-2, Angpt-2, and sTM.
The method of any preceding claim, wherein the determination of whether the levels of the at least two biomarkers are non-elevated above a cut-off level comprises applying the biomarker expression level data to a decision tree comprising the two or more biomarkers.
The method of any preceding claim, wherein a classification other than high risk comprises a classification of low risk or intermediate risk.
The method of any preceding claim, wherein SA-AKI comprises cardiovascular, respiratory, renal, hepatic, hematologic, and/or neurologic dysfunction, and/or systemic inflammation and/or microvascular endothelial dysfunction, and/or low or no urine output, fluid overload with edema, increased need for supplemental oxygen or intubation and mechanical ventilation, need for dialysis, multi-organ failure and/or death.
The method of any preceding claim, wherein high risk of SA-AKI by day 3 of septic shock or other than high risk of SA-AKI by day 3 of septic shock is determined.
The method of any preceding claim, wherein high risk of SA-AKI by day 7 of septic shock or other than high risk of SA-AKI by day 7 of septic shock is determined.
The method of any preceding claim, wherein the classification is combined with one or more patient demographic data and/or clinical characteristics and/or results from other tests or indicia of septic shock and/or one or more additional biomarkers and/or platelet count.
The method of any preceding claim, wherein the classification is combined with one or more additional population-based risk scores.
The method of any preceding claim, wherein the sample is obtained within the first hour of presentation with septic shock.
The method of any preceding claim, wherein the sample is obtained within the first 24 hours of presentation with septic shock.
The method of any preceding claim, further comprising administering a treatment comprising one or more high risk therapy to a patient that is classified as high risk, or administering a treatment excluding a high risk therapy to a patient that is not high risk, or to provide a method of treating a pediatric patient with septic shock.
The method of any preceding claim, wherein the patient is enrolled in a clinical trial.
The method of any preceding claim, wherein one or more biomarker cut-off level is determined by one or more trained machine learning models based on a dataset generated from a cohort of pediatric patients with and without SA-AKI.
The method of any preceding claim, wherein the data from the cohort of pediatric patients with and without SA-AKI is provided to one or more machine learning models as input, and wherein the one or more trained machine learning model is based on a dataset generated from the biomarker cutoff levels in the patients of the cohort.
The method of any preceding claim, wherein one or more biomarker cut-off level is determined by a trained machine learning model, and wherein one or more machine learning models is used to classify the patient as high risk of SA-AKI, or other than high risk of SA-AKI.
The method of any preceding claim, as part of a companion diagnostic or a point of care device or kit.
A diagnostic kit, test, or array comprising a reporter hybridization probe, and a capture hybridization probe specific for each of two or more mRNA, DNA, or protein biomarkers selected from the group consisting of:
An apparatus or processing device suitable for detecting two or more biomarkers selected from the group consisting of:
A composition comprising a reporter hybridization probe, and a capture hybridization probe specific for each of two or more biomarkers selected from the group consisting of:
Dependencies are inferred from the claim text.