ABSTRACT
Objective:To analyze the prognostic risk factors of patients with traumatic pancreatitis (TP) and establish an early combined prediction of multiple indicators model for TP.Methods:Patients admitted to the ICU of the First Affiliated Hospital of Zhengzhou University from June 2017 to June 2022 were collected retrospectively. Based on their prognosis, the patients were divided into two groups: the good prognosis group and the poor prognosis group. The general data such as sex, age, underlying diseases, Glasgow Coma Scale (GCS), acute physiology and chronic health evaluationⅡ (APACHEⅡ), injury severity score (ISS), bedside index for severity in acute pancreatitis (BISAP), and clinical test indices such as blood routine, blood coagulation, blood gas analysis, and liver and kidney function at admission were compared between the two groups. Univariate analysis and multivariate logistic regression analysis were used to screen the early independent predictors of poor prognosis of TP, and the prediction model of TP was established by combining all of the independent indicators. The receiver operating characteristic (ROC) curve of each independent predictor and prediction model was drawn, and the area under the curve (AUC), sensitivity, specificity, and optimal cut-off value were calculated to examine the diagnostic impact of each independent predictor and the combined prediction model.Results:There were statistically significant differences in the complication rate of mental disorders, GCS, APACHE II, combined craniocerebral injury, combined chest injury, activated partial thromboplastin time, fibrin(pro)degradation products, lactate, aspartate aminotransferase, glomerular filtration rate, amylase, lipase, NT-proBNP, myoglobin, procalcitonin, ISS, and BISAP between the good and poor prognosis groups (all P<0.05). Multivariate logistic regression analysis showed that lactate ( OR=1.636, 95% CI: 1.046-2.559), lipase ( OR=1.005, 95% CI: 1.001-1.008), and ISS ( OR=1.161, 95% CI: 1.064-1.266) were independent risk factors influencing the prognosis of patients with TP. Based on the risk factors listed above, a prediction model was created: Logit P=-9.260+0.492×lactate+0.005×lipase+0.149×ISS, and the ROC curve was plotted. The AUC curve of the prediction model was 0.96 (95% CI: 0.91-1.00). Conclusions:Lactate, lipase, and ISS are early independent risk factors associated with the prognosis of TP. Their combined multi-indicator prediction model has an excellent clinical prediction effect, which can provide a clinical reference for early prediction and treatment of TP.
ABSTRACT
OBJECTIVE@#To investigate the predictive value of pancreatitis activity scoring system (PASS) combined with Neutrophil to lymphocyte ratio (NLR) and C-reactive protein (CRP) for infected pancreatic necrosis (IPN) in patients with severe acute pancreatitis (SAP).@*METHODS@#Clinical data of SAP patients admitted to the First Affiliated Hospital of Zhengzhou University from January 2020 to January 2023 were retrospectively collected, including basic information, vital signs at admission, first laboratory indexes within 48 hours of admission. The PASS scores at admission and 24, 48 and 72 hours after admission were calculated. According to the diagnostic criteria of IPN, the patients were divided into the non-IPN group and the IPN group, and the independent risk factors of SAP complicating IPN were determined by using univariate analysis and multifactorial Logistic regression. The receiver operator characteristic curve (ROC curve) was drawn to evaluate the predictive value of NLR, CRP, and PASS score, alone and in combination for IPN in patients with SAP.@*RESULTS@#A total of 149 SAP patients were enrolled, including 102 in the non-IPN group and 47 in the IPN group. The differences in PASS score at each time point, NLR, CRP, procalcitonin (PCT), blood urea nitrogen, blood chloride, and days of hospitalization between the two groups were statistically significant. Multifactorial Logistic regression analysis showed that 72 hours admission PASS score [odds ratio (OR) = 1.034, 95% confidence interval (95%CI) was 1.005-1.065, P = 0.022], NLR (OR = 1.284, 95%CI was 1.139-1.447, P = 0.000), and CRP (OR = 1.015, 95%CI was 1.006-1.023, P = 0.001) were independent risk factors for IPN in patients with SAP. ROC curve analysis showed that the area under the ROC curve (AUC) of the PASS score at 72 hours of admission, NLR, and CRP alone in predicting IPN in SAP patients were 0.828, 0.771, and 0.701, respectively. The AUC of NLR combined with CRP, PASS combined with NLR, and PASS combined with CRP were 0.818, 0.895, and 0.874, respectively. The combination of PASS score at 72 hours after admission, NLR, and CRP had a better predictive ability for IPN in patients with SAP (AUC = 0.922, 95%CI was 0.877-0.967), and the sensitivity was 72.3% when the cut-off value was 0.539.@*CONCLUSIONS@#The predictive value of the PASS score at 72 hours after admission, NLR and CRP in combination for IPN in SAP patients is better than that of the combination of each two and individual detection and has better test efficacy.
Subject(s)
Humans , Pancreatitis, Acute Necrotizing/diagnosis , C-Reactive Protein/metabolism , Acute Disease , Neutrophils/metabolism , Retrospective Studies , ROC Curve , Lymphocytes , PrognosisABSTRACT
Objective:To explore the predictive value of combined detection of serum interleukin-6 (IL-6), chloride (Cl -), D-dimer and fibrin degradation products (FDP) for severity of acute pancreatitis (AP). Methods:From December 2020 to March 2022, 132 AP patients who met the criteria for inclusion were screened for retrospective analysis from 292 AP patients admitted in emergency surgery at the First Affiliated Hospital of Zhengzhou University and they were divided into severe acute pancreatitis (SAP) group and non-SAP group, with 63 in SAP group and 69 in non-SAP group, according to classification criteria. The data including lab results, abdominal doppler ultrasound and chest and abdominal CT, etc. The bedside index for severity in acute pancreatitis (BISAP) score was calculated. Multivariate Logistic regression analysis was carried out to find the risk factors for the severity of AP patients. The receiver operator characteristic curve (ROC) was drawn to judge the clinical predictive value of each factor.Results:A total of 132 AP patients were enrolled. The serum IL-6, D-dimer, FDP levels and the BISAP score in SAP group were significantly higher than those in non-SAP group [serum IL-6 (ng/L): 62.73 (21.54, 187.47) vs. 8.22 (4.13, 14.70), D-dimer (mg/L): 5.36 (2.94, 8.25) vs. 0.94 (0.42, 2.21), FDP (mg/L): 13.54 (6.76, 22.45) vs. 3.20 (2.50, 6.10), BISAP score: 2.00 (1.00, 3.00) vs. 1.00 (0, 2.00), all P < 0.05], while the serum Cl - level was significantly lower than that of non-SAP group (mmol/L: 97.90±4.86 vs. 101.73±4.32, P < 0.05). Multivariate Logistic regression analysis showed that increased levels of IL-6 [odds ratio ( OR) = 1.02, 95% confidence interval (95% CI) was 1.01-1.04], D-dimer ( OR = 1.21, 95% CI was 1.05-1.40) and decreased Cl - level ( OR = 0.88, 95% CI was 0.79-0.98) were risk factors for SAP (all P < 0.05). The ROC curve analysis showed that the area under the ROC curve (AUC) of IL-6, Cl -, D-dimer and FDP combined to predict the severity of AP patients was larger (0.89), and the sensitivity (82.50%) and specificity (85.50%) were higher. Conclusion:Compared with single index, the combined detection of serum IL-6, Cl -, D-dimer and FDP is more precise in determining the condition of AP.