Method for prognosis evaluation of infected patients and multi-cytokine detection kit

A detection kit and prognosis evaluation technology, applied in the field of medical testing, can solve the problems of different patient standards, different results, and no unified conclusion, etc., achieve high diagnostic efficiency, simple calculation method, and improve prognosis

Pending Publication Date: 2021-08-10
ZHONGSHAN HOSPITAL FUDAN UNIV
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Problems solved by technology

Although studies on cytokines and the progression and prognosis of infected patients have emerged in an endless stream in recent years, the criteria for selecting patients are often different between different studies, the research methods are different, and the results are not the same, and there is no uniform in conclusion

Method used

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  • Method for prognosis evaluation of infected patients and multi-cytokine detection kit

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Embodiment

[0042] A patient who was clinically diagnosed as infection was selected, and the patient was divided into 30 days of living group and 30 days of death group according to 30 days, and plasma multi-cytokine level detection was used to detect the cytokine specimens of clinical residual plasma. : IL-1Rα, IL-2Rα, IL-1β, IL-6, IL-16, IL-12, IL-9, MIG, MIP-1α, MIP-1β, IFN-α2, SDF-1α, LIF, TNF -α, TNF-β, MIF, RANTES, CTACK, M-CSF, HGF, SCF, TRAIL, EOTAXIN, PDGF-BB, IP-10, SCGF-β. The above plasma cytokine level is incorporated into single factor Logistic regression. The results showed that IL-1Rα, IL-16, LIF, HGF, SCF, M-CSF and CTACK were associated with 30 days prognosis (P <0.05); P <0.05 was analyzed by a subject working characteristic curve (ROC) curve. The plasma cytokine level is converted to a two-class variable and incorporates multiple factors Logistic regression, resulting in a variable associated with the patient's 30 days prognosis. The proposed independently related variable...

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Abstract

The invention relates to a method for prognosis evaluation of infected patients and a multi-cell factor detection kit, and belongs to the technical field of medical examination. The levels of plasma cytokines among infected patients are compared through single-factor Logistic regression analysis, variables with P smaller than 0.05 are included in multi-factor regression, and results show that IL-1R alpha, IL-16 and SCF are independently related to 30-day prognosis of the patients; a patient scoring formula is formed by combining correlation coefficients obtained by multi-factor Logistic regression; and the prognosis of the infected patients is evaluated according to the scores of the patients. The method provided by the invention is simple in calculation method, relatively good in sensitivity and specificity, and relatively high in diagnosis efficiency, and the area under the curve is 0.887. High-risk early warning can be made for infected patients as soon as possible, clinical doctors can pay attention to the illness state in time, and prognosis is improved.

Description

Technical field [0001] The present invention relates to a method for infecting a prognostic assessment of a patient and a multi-cytokine detection kit, belonging to the technical field of medical test. Background technique [0002] Previous research suggests that certain cytokines can have a certain role in the prognosis of infected patients. Cell factors such as GM-CSF and M-CSF can be used for sepsis, which can significantly reduce the incidence of sepsis and improve sepicity. Although the research on the progression of cytokines and infection patients and prognosis in recent years, there is different studies between different research, and there are differences in the study, and the results of the results are not the same, and there is no uniform. in conclusion. In the art, there is an urgent need to combine methods of detecting different cytokines, better predicting prognosis of infected patients, to identify high-risk patients, facilitating clinical response. Inventive cont...

Claims

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Application Information

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IPC IPC(8): G01N33/68
CPCG01N33/6863
Inventor 张静左依慧
Owner ZHONGSHAN HOSPITAL FUDAN UNIV
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