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Model capable of predicting acute kidney injury caused by sepsis

A technology of acute kidney injury and prediction model, applied in the biological field, can solve problems that have not been reported, and achieve the effects of simple measurement method, improved discrimination and calibration, and strong practicability

Pending Publication Date: 2021-09-17
SHANGHAI FIRST PEOPLES HOSPITAL
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] There is no report about a model of the present invention that can predict acute kidney injury in sepsis

Method used

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  • Model capable of predicting acute kidney injury caused by sepsis
  • Model capable of predicting acute kidney injury caused by sepsis
  • Model capable of predicting acute kidney injury caused by sepsis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0033] 1 case selection

[0034] This is an observational study. According to "Sepsis3.0", we recruited adult patients aged 18 years or older with sepsis. This prospective study included data from a tertiary teaching hospital (Shanghai First People's Hospital). This prospective observational study was conducted between March 2018 and December 2020. We recruited eligible patients, tracked hospital admissions, and conducted a 28-day follow-up survey by telephone. All patients participating in the study signed informed consent. This study was approved by the Ethical Review Committee of Shanghai First People's Hospital.

[0035] 1.1 Inclusion criteria

[0036] (1) Age ≥ 18, ≤ 85 years old, male or female;

[0037] (2) Patients admitted to ICU;

[0038] (3) Confirmed or clinically diagnosed infection;

[0039] (4) The acute change of Sequential Organ Failure Score ≥ 2 points, that is, the △SOFA score ≥ 2 points (the baseline SOFA score for patients with unknown organ dysfun...

Embodiment 2

[0101] The purpose of this embodiment is to carry out internal verification, and the Bootstrap self-sampling method is used to verify the prediction effect of the model by using the data of the modeling itself. The new samples generated by Bootstrap self-sampling were used to evaluate the accuracy of the nomogram model, and the validation ROC curve of sepsis-related AKI was obtained using R software internal validation, and the area under the curve was 0.9903.

Embodiment 3

[0103] The purpose of this embodiment is to carry out external verification. A new sample data set (test, n=159) was reselected, and R software was used to verify and obtain a verification ROC curve for sepsis-related AKI, and the area under the curve was 0.9897.

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Abstract

The invention relates to the technical field of biology, in particular to a model capable of predicting sepsis-related acute kidney injury (AKI), and the sepsis-related acute kidney injury (AKI) is high in morbidity and death rate. At present, a single biomarker has certain defects in prediction of sepsis acute kidney injury and prognosis, and sensitivity and specificity are uneven. The invention provides a prediction model established based on plasma ATIII, gender, serum creatinine, whether hypertension history exists or not and age for the first time. The model can identify sepsis-related renal injury in an early stage and improve prognosis, and experiments prove that the model has very high accuracy. The result shows that the area under the simulated ROC curve is 0.9906, and the method has high discrimination and calibration degree. And a basis is provided for clinical medication.

Description

technical field [0001] The invention relates to the field of biotechnology, in particular, it is a predictable model of sepsis acute kidney injury. Background technique [0002] Sepsis and sepsis-associated AKI involve a dysregulated inflammatory response arising from the interaction between the host immune system and microbes. Despite recent advances in clinical research, sepsis and sepsis-related AKI are still associated with high morbidity and mortality. The value of ATIII in predicting sepsis-related AKI has been proposed above. At the same time, our previous research found that male sex and low ATIII level are independent risk factors for sepsis-related AKI in the elderly. Whether these factors can be combined to predict sepsis-related AKI? Prediction of sexual AKI is still worthy of further research. [0003] Sex hormones have been reported to have modulatory effects on immune responses. Estradiol induces the production of proinflammatory cytokines and the activatio...

Claims

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Application Information

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IPC IPC(8): G16H50/30G16H50/50C12Q1/6883G01N33/50G01N33/573
CPCG16H50/30G16H50/50C12Q1/6883G01N33/573G01N33/50C12Q2600/158G01N2333/8128
Inventor 谢云王瑞兰
Owner SHANGHAI FIRST PEOPLES HOSPITAL
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