Study on the diagnostic accuracy of elderly patients with early sepsis screening model based on non-invasive physiological parameters
10.3760/cma.j.issn.0254-9026.2024.05.009
- VernacularTitle:基于无创生理参数的脓毒症早期筛查模型对老年患者诊断准确性的研究
- Author:
Taotao LIU
1
;
Yang LIU
;
He WANG
;
Hong SHI
Author Information
1. 北京医院重症医学科 国家老年医学中心 中国医学科学院老年医学研究院，北京 100730
- Keywords:
Sepsis;
Systemic Inflammatory Response Syndrome;
Logistic model
- From:
Chinese Journal of Geriatrics
2024;43(5):597-602
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To evaluate the diagnostic accuracy of a noninvasive physiological parameter-based early sepsis screening model for elderly patients in comparison to the systemic inflammatory response syndrome(SIRS)and quick sequential organ failure assessment(qSOFA)scores.Methods:A retrospective study was conducted using data from the Medical Information Mart for Intensive Care Ⅳ(MIMIC-Ⅳ)database.The study focused on patients who were admitted to the intensive care unit(ICU)within 24 hours and were categorized into septic and non-septic groups based on the presence or absence of sepsis.Baseline data and patient outcomes were recorded.Additionally, the SIRS score and qSOFA scores within 24 hours of ICU admission were calculated.Physiological parameters that showed statistical significance in the univariate analysis included respiratory rate, heart rate, level of consciousness, body temperature, systolic blood pressure, and urine output.These parameters were then included in Logistic regression models.The specificity and sensitivity of the regression model for sepsis screening were calculated, and receiver operating characteristic(ROC)curves were plotted.The areas under the ROC curves(AUCs)of the screening model, SIRS, and qSOFA scoring systems were compared.Results:A total of 53 150 ICU hospitalization records were screened, and 23 681 patients with infection or suspected infection within 24 hours were included.Among them, 18 277 patients had sepsis.The 28-day mortality rate for septic patients was higher compared to non-septic patients(13.5% vs.5.1%, χ2=285.131, P<0.001).The baseline data within 24 hours showed significant differences between the two groups in terms of heart rate, respiratory rate, body temperature, state of consciousness, 24-hour urine output, and systolic blood pressure(all P<0.001).These variables were included in the regression equation: ∑β iX i=2.055+ 0.285(temperature: 0/1)+ 0.172(respiratory rate: 0/1)+ 0.073(heart rate: 0/1)+ 1.204(mental status: 0/1)-0.022(systolic blood pressure)+ 0.227(classification of urine output: 0/1/2), P=1/[1+ EXP(-∑β iX i)].The regression model diagnosed sepsis ROC area in young and middle-aged patients as 0.726(95% CI: 0.718 to 0.735), which was significantly higher than the SIRS score(0.585, 95% CI: 0.576 to 0.595)and the qSOFA score(0.676, 95% CI: 0.667 to 0.685)(both P<0.001).In elderly patients, the regression model diagnosed sepsis ROC area as 0.671(95% CI: 0.663 to 0.679), which was also significantly higher than the SIRS score(0.572, 95% CI: 0.563 to 0.580)and the qSOFA score(0.631, 95% CI: 0.623 to 0.639)(both P<0.001). Conclusions:The early sepsis diagnosis model, which utilizes noninvasive physiological parameters, has shown higher accuracy when compared to the SIRS and qSOFA scores.However, it is important to note that its accuracy is lower in elderly patients as compared to young and middle-aged patients.This indicates the necessity for further optimization of the model in order to improve its performance in diagnosing sepsis in the elderly.
