Efficiency of red cell distribution width in predicting severity and mortality of patients with acute pancreatitis: A protocol for systematic review and meta-analysis

Nonlinear Relationship Between Serum Total Cholesterol Levels and the Severity of Hypertriglyceridemic Acute Pancreatitis: A Cohort Study in China

BACKGROUND

The relationship between total cholesterol (TC) levels and the severity of hypertriglyceridemic acute pancreatitis (HTGAP) remains unclear.

AIMS

The aim of this study was to investigate the relationship between the levels of TC at admission with the severity of HTGAP, in order to apply it as a reliable predictor at early stage in clinical practice.

METHODS

We performed a cohort study including 249 patients with AHTGP between November 2012 and April 2022 in XuanWu Hospital. Fasting TC was assayed within 24 h of admission, age, gender, body mass index, hypertension, diabetes mellitus, drinking, smoking, neutrophil-lymphocyte ratio, C-reactive protein and glucose were recorded as confounding factors. To evaluate the relationship of TC and the severity of HTGAP, we used smooth curve fitting and a segmented regression model with adjustment of confounding factors to analyze the threshold effect between TC and SAP occurrence risk.

RESULTS

249 Patients were enrolled. The incidence of SAP was 25.3% (63/249). A nonlinear relationship between TC level and the severity of HTGAP. 6.09 mmol/L was the optimal TC value associated with the lowest risk of SAP occurrence. Moreover, TC level was negatively correlated with risk of severe HTGAP occurrence for TC < 6.09 mmol/L (OR 0.45, 95% CI 0.23-0.85, P = 0.014) and positively correlated for TC > 6.09 mmol/L in HTGAP patients (OR 1.14, 95% CI 1.04-1.26, P = 0.006).

CONCLUSIONS

We found that serum TC level is nonlinearly associated with the severity of HTGAP, and it can be a reliable predictor for early intervention and intensive care.

A novel clinical prediction model of severity based on red cell distribution width, neutrophil-lymphocyte ratio and intra-abdominal pressure in acute pancreatitis in pregnancy

BACKGROUND

Acute pancreatitis in pregnancy (APIP) with a high risk of death is extremely harmful to mother and fetus. There are few models specifically designed to assess the severity of APIP. Our study aimed to establish a clinical model for early prediction of severity of APIP.

METHODS

A retrospective study in a total of 188 patients with APIP was enrolled. The hematological indicators, IAP (intra-abdominal pressure) and clinical data were obtained for statistical analysis and prediction model construction.

RESULTS

According to univariate and multivariate logistic regression analysis, we found that red cell distribution width (RDW), neutrophil-lymphocyte ratio (NLR) and Intra-abdominal pressure (IAP) are prediction indexes of the severity in APIP (p-value < 0.05). Our novel clinical prediction model was created by based on the above three risk factors and showed superior predictive power in primary cohort (AUC = 0.895) and validation cohort (AUC = 0.863). A nomogram for severe acute pancreatitis in pregnancy (SAPIP) was created based on the three indicators. The nomogram was well-calibrated.

CONCLUSION

RDW, NLR and IAP were the independent risk factors of APIP. Our clinical prediction model of severity in APIP based on RDW, NLR and IAP with predictive evaluation is accurate and effective.

Development and validation of a risk prediction score for the severity of acute hypertriglyceridemic pancreatitis in Chinese patients

BACKGROUND

The frequency of acute hypertriglyceridemic pancreatitis (AHTGP) is increasing worldwide. AHTGP may be associated with a more severe clinical course and greater mortality than pancreatitis caused by other causes. Early identification of patients with severe inclination is essential for clinical decision-making and improving prognosis. Therefore, we first developed and validated a risk prediction score for the severity of AHTGP in Chinese patients.

AIM

To develop and validate a risk prediction score for the severity of AHTGP in Chinese patients.

METHODS

We performed a retrospective study including 243 patients with AHTGP. Patients were randomly divided into a development cohort (n = 170) and a validation cohort (n = 73). Least absolute shrinkage and selection operator and logistic regression were used to screen 42 potential predictive variables to construct a risk score for the severity of AHTGP. We evaluated the performance of the nomogram and compared it with existing scoring systems. Last, we used the best cutoff value (88.16) for severe acute pancreatitis (SAP) to determine the risk stratification classification.

RESULTS

Age, the reduction in apolipoprotein A1 and the presence of pleural effusion were independent risk factors for SAP and were used to construct the nomogram (risk prediction score referred to as AAP). The concordance index of the nomogram in the development and validation groups was 0.930 and 0.928, respectively. Calibration plots demonstrate excellent agreement between the predicted and actual probabilities in SAP patients. The area under the curve of the nomogram (0.929) was better than those of the Bedside Index of Severity in AP (BISAP), Ranson, Acute Physiology and Chronic Health Evaluation (APACHE II), modified computed tomography severity index (MCTSI), and early achievable severity index scores (0.852, 0.825, 0.807, 0.831 and 0.807, respectively). In comparison with these scores, the integrated discrimination improvement and decision curve analysis showed improved accuracy in predicting SAP and better net benefits for clinical decisions. Receiver operating characteristic curve analysis was used to determine risk stratification classification for AHTGP by dividing patients into high-risk and low-risk groups according to the best cutoff value (88.16). The high-risk group (> 88.16) was closely related to the appearance of local and systemic complications, Ranson score ≥ 3, BISAP score ≥ 3, MCTSI score ≥ 4, APACHE II score ≥ 8, C-reactive protein level ≥ 190, and length of hospital stay.

CONCLUSION

The nomogram could help identify AHTGP patients who are likely to develop SAP at an early stage, which is of great value in guiding clinical decisions.