Acute kidney injury incidence probability prediction system based on intensive care detection items

Abstract

The invention discloses an acute kidney injury incidence probability prediction system based on intensive care detection items. The acute kidney injury incidence probability prediction system obtainsdata of multiple detection items of a patient within 24 hours and demographic information related to gender, age and weight from a hospital database, marks the data of each item in chronological orderfrom far to near, performs front-to-back arrangement, completes extraction of related features according to the classified demographic data, serum creatinine, systolic blood pressure, urine volume,blood gas analysis, body temperature heart rate, and medication information, wherein the related features relate to age, gender, the change value, the mean value, the standard deviation, the minimum value, the maximum value, the most recent value and other digital features, of the related detection items within 24 hours, and the like: the data of total 38 detection items, and combined with the artificial intelligence machine learning algorithm, predicts the incidence of acute kidney injury of the patient 24 hours in advance, for creating conditions for early clinical intervention.

Description

technical field [0001] The invention relates to the technical field of medical monitoring, in particular to a system for predicting the incidence probability of acute kidney injury based on intensive care detection items. Background technique [0002] Acute Kidney Injury (AKI for short) refers to the clinical syndrome caused by the sudden decline of renal function in a short period of time (hours to weeks) caused by various reasons, which will lead to blood urea nitrogen (blood urea nitrogen) , BUN), creatinine, and other metabolic wastes that are normally excreted by the kidneys are elevated. Acute kidney injury is one of the most common acute and critical diseases in clinical departments, with high morbidity and mortality. [0003] According to foreign reports, the incidence rate of AKI in inpatients with AKI is 0.37%-5.0%, the incidence rate in intensive care unit (Intensive Care Unit) is 5.7%-26.7%, and the mortality rate is as high as 18.1%-69.6%; domestic clinical res...

AI Technical Summary

Problems solved by technology

[0006] At present, in the intensive care unit, the patient's vital signs indicators, such as heart rate, blood pressure, creatinine, urine output, etc. are frequently measured, but these data are mainly used to determine the patient's condition, as long as the data does not appear excessively abnormal The patient will be further treated, the maximum number of measurements is frequent or the nurse is asked to pay more attention

Therefore, the patient has done these examinations, and the detection data obtained by the examination has a low utilization effect and a relatively large delay in the judgment of the condition, which cannot achieve the effect of condition prediction and pretreatment in advance.

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