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Kidney injury risk data prediction system and method, computer equipment and medium

A data prediction and risk prediction technology, applied in health index calculation, computer parts, computer-aided medical procedures, etc., can solve the problems of inaccurate data, inability to apply, single variables, etc. obtained effect

Pending Publication Date: 2022-03-01
青岛市第六人民医院
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AI Technical Summary

Problems solved by technology

[0012] (1) The prior art does not have a prediction or assessment model for the risk of TDF-induced nephrotoxicity in PLWH
[0013] (2) At the same time, the existing risk analysis technology selects a single variable, and the data is inaccurate, so it cannot be applied in actual scenarios

Method used

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  • Kidney injury risk data prediction system and method, computer equipment and medium
  • Kidney injury risk data prediction system and method, computer equipment and medium
  • Kidney injury risk data prediction system and method, computer equipment and medium

Examples

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Embodiment 1

[0093] 1. Method

[0094] 1.1 Crowds and Screening Rules

[0095] The present invention recruited PLWH who were treated and treated in Qingdao Sixth People's Hospital during 2014.07.08-2019.07.30. The research population required age ≥ 18 years, patients receiving TDF antiviral treatment, and normal baseline eGFR. Patients with a history of hypertension, chronic kidney disease, chronic liver disease, heart disease, or diabetes; pregnant and / or lactating women; those with incomplete laboratory data; or those who lost follow-up for non-TDF-related reasons were excluded from this invention outside. Laboratory examination data included blood routine, blood lipid and CD4+ T lymphocyte count, biochemical indicators, eGFR and blood sugar, transpeptidase, cystatin C, and β2 microglobulin (β2MG) levels. The present invention was approved by the Ethics Committee of Qingdao Sixth People's Hospital (2014014). All patients signed an informed consent form at the start of ART.

[0096] 1...

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Abstract

The invention belongs to the technical field of model construction, and discloses a renal injury risk data prediction system and method, computer equipment and a medium, and the renal injury risk data prediction system comprises a data screening module, a data extraction and classification module, a variable extraction module, a variable screening module, a model construction module and a verification module. The machine learning prediction model for evaluating the renal toxicity risk caused by the TDF in the PLWH is innovatively provided, and the situation that the renal injury risk exists in the TDF treatment of the PLWH can be effectively recognized. The variables in the model are easy to reproduce, the method can be applied to clinical practice, and the prospect of prospective machine learning is highlighted. Predictive variables used in the model are easy to assess during clinical follow-up visit, and data with risks can be easily identified and prognosis can be guided.

Description

technical field [0001] The invention belongs to the technical field of model building, and in particular relates to a kidney injury risk data prediction system, a prediction method, computer equipment and media. Background technique [0002] Currently, antiretroviral therapy (ART) provides effective viral suppression and accelerates CD4+ T lymphocyte recovery and prolongs lifespan, but long-term side effects associated with ART significantly reduce human immunodeficiency virus (HIV)-infected (PLWH ) quality of life. [0003] Diseases defined as non-acquired immunodeficiency syndrome (AIDS) are gaining recognition, and data suggest a significant noncommunicable disease burden in PLWH receiving long-term ART. The incidence of chronic kidney disease from drug-related nephrotoxicity and age-related decline in renal function in PLWH is of concern. The prevalence of chronic kidney disease in PLWH ranges from 2-30%. Existing techniques have identified traditional risk factors, s...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/30G06Q10/04G06K9/62
CPCG16H50/30G06Q10/04G06F18/241G06F18/24323G06F18/214
Inventor 徐光勇张洋
Owner 青岛市第六人民医院
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