Factors predicting the severity of acute pancreatitis in elderly patients

Incidence and prognostic role of pleural effusion in patients with acute pancreatitis: a meta-analysis

BACKGROUND

Pleural effusion (PE) is reported as a common complication in acute pancreatitis (AP), while the incidence of PE in AP varies widely among studies, and the association between PE and mortality is not clear. This study aimed to comprehensively analyze the pooled incidence of PE in patients with AP and to evaluate the influence of PE on mortality through a meta-analysis.

METHOD

Six databases (PubMed, Web of Science, EMBASE, Cochrane, Scopus, and OVID) were searched thoroughly for relevant studies. Data were extracted, and Stata SE 16.0 software was applied to compute the pooled incidence of PE and assess the association between PE and mortality, taking the risk ratio (RR) as the effect size.

RESULTS

Thirty-five articles involving 7,675 patients with AP were eventually included in this meta-analysis. The pooled incidence of PE was 34% (95% CI: 28%-39%), with significant heterogeneity among studies (I2=96.7%). Further analysis revealed that the pooled incidence of unilateral and small PE occupied 49% (95% CI: 21%-77%) and 59% (95% CI: 38%-81%) of AP patients complicated by PE, respectively. The subgroup analysis revealed that "region" and "examination method" may contribute to heterogeneity. PE may be associated with increased mortality in AP patients (RR 3.99, 95% CI: 1.73-9.2).

CONCLUSION

This study suggested that PE is a common complication with high pooled incidence and that PE may be associated with increased mortality in AP patients. More studies should be performed to validate our findings.

Establishment and Validation of a Nomogram Prediction Model for the Severe Acute Pancreatitis

Background

Severe acute pancreatitis (SAP) can progress to lung and kidney dysfunction, and blood clotting within 48 hours of its onset, and is associated with a high mortality rate. The aim of this study was to establish a reliable diagnostic prediction model for the early stage of severe pancreatitis.

Methods

The clinical data of patients diagnosed with acute pancreatitis from October 2017 to June 2022 at the Shangluo Central Hospital were collected. The risk factors were screened by least absolute shrinkage and selection operator (LASSO) regression analysis. A novel nomogram model was then established by multivariable logistic regression analysis.

Results

The data of 436 patients with acute pancreatitis, 45 (10.3%) patients had progressed to SAP. Through univariate and LASSO regression analyses, the neutrophils (P <0.001), albumin (P < 0.001), blood glucose (P < 0.001), serum calcium (P < 0.001), serum creatinine (P < 0.001), blood urea nitrogen (P < 0.001) and procalcitonin (P = 0.005) were identified as independent predictive factors for SAP. The nomogram built on the basis of these factors predicted SAP with sensitivity of 0.733, specificity of 0.9, positive predictive value of 0.458 and negative predictive value of 0.967. Furthermore, the concordance index of the nomogram reached 0.889 (95% CI, 0.837-0.941), and the area under the curve (AUC) in receiver operating characteristic curve (ROC) analysis was significantly higher than that of the APACHEII and ABISAP scoring systems. The established model was validated by plotting the clinical decision curve analysis (DCA) and clinical impact curve (CIC).

Conclusion

We established a nomogram to predict the progression of early acute pancreatitis to SAP with high discrimination and accuracy.

Predicting persistent organ failure on admission in patients with acute pancreatitis: development and validation of a mobile nomogram

BACKGROUND

Early prediction of persistent organ failure (POF) is important for triage and timely treatment of patients with acute pancreatitis (AP).

METHODS

All AP patients were consecutively admitted within 48 h of symptom onset. A nomogram was developed to predict POF on admission using data from a retrospective training cohort, validated by two prospective cohorts. The clinical utility of the nomogram was defined by concordance index (C-index), decision curve analysis (DCA), and clinical impact curve (CIC), while the performance by post-test probability.

RESULTS

There were 816, 398, and 880 patients in the training, internal and external validation cohorts, respectively. Six independent predictors determined by logistic regression analysis were age, respiratory rate, albumin, lactate dehydrogenase, oxygen support, and pleural effusion and were included in the nomogram (web-based calculator: https://shina.shinyapps.io/DynNomapp/). This nomogram had reasonable predictive ability (C-indexes 0.88/0.91/0.81 for each cohort) and promising clinical utility (DCA and CIC). The nomogram had a positive likelihood ratio and post-test probability of developing POF in the training, internal and external validation cohorts of 4.26/31.7%, 7.89/39.1%, and 2.75/41%, respectively, superior or equal to other prognostic scores.

CONCLUSIONS

This nomogram can predict POF of AP patients and should be considered for clinical practice and trial allocation.

The Clinical Characteristics and Outcome of Elderly Patients With Acute Pancreatitis

OBJECTIVES

This study aimed to identify the risk factors for the progression of acute pancreatitis (AP) to severe acute pancreatitis (SAP) and death in elderly patients.

METHODS

This was a single-center retrospective study conducted in a tertiary teaching hospital. Data on patient demographics, comorbidities, duration of hospitalization, complications, interventions, and mortality rates were collected.

RESULTS

Between January 2010 and January 2021, 2084 elderly patients with AP were included in this study. The mean age of the patients was 70.0 years (standard deviation, 7.1 years). Among them, 324 (15.5%) had SAP and 105 died (5.0%). The 90-day mortality rate in the SAP group was significantly higher than that in the AP group (P < 0.0001). Multivariate regression analysis revealed that trauma, hypertension, and smoking were risk factors for SAP. After multivariate adjustment, acute respiratory distress syndrome, acute kidney injury, sepsis, organ perforation, and abdominal hemorrhage were associated with higher 90-day mortality.

CONCLUSIONS

Traumatic pancreatitis, hypertension, and smoking are independent risk factors for SAP in elderly patients. Acute respiratory distress syndrome, acute kidney injury, sepsis, organ perforation, and abdominal hemorrhage are independent risk factors for death in elderly patients with AP.

Prediction of the severity of acute pancreatitis using machine learning models

BACKGROUND

Acute pancreatitis (AP) is the most common pancreatic disease. Predicting the severity of AP is critical for making preventive decisions. However, the performance of existing scoring systems in predicting AP severity was not satisfactory. The purpose of this study was to develop predictive models for the severity of AP using machine learning (ML) algorithms and explore the important predictors that affected the prediction results.

METHODS

The data of 441 patients in the Department of Gastroenterology in our hospital were analyzed retrospectively. The demographic data, blood routine and blood biochemical indexes, and the CTSI score were collected to develop five different ML predictive models to predict the severity of AP. The performance of the models was evaluated by the area under the receiver operating characteristic curve (AUC). The important predictors were determined by ranking the feature importance of the predictive factors.

RESULTS

Compared to other ML models, the extreme gradient boosting model (XGBoost) showed better performance in predicting severe AP, with an AUC of 0.906, an accuracy of 0.902, a sensitivity of 0.700, a specificity of 0.961, and a F1socre of 0.764. Further analysis showed that the CTSI score, ALB, LDH, and NEUT were the important predictors of the severity of AP.

CONCLUSION

The results showed that the XGBoost algorithm can accurately predict the severity of AP, which can provide an assistance for the clinicians to identify severe AP at an early stage.

Pleuropulmonary pathologies in the early phase of acute pancreatitis correlate with disease severity

Background

Respiratory failure worsens the outcome of acute pancreatitis (AP) and underlying factors might be early detectable.

Aims

To evaluate the prevalence and prognostic relevance of early pleuropulmonary pathologies and pre-existing chronic lung diseases (CLD) in AP patients.

Methods

Multicentre retrospective cohort study. Caudal sections of the thorax derived from abdominal contrast enhanced computed tomography (CECT) performed in the early phase of AP were assessed. Independent predictors of severe AP were identified by binary logistic regression analysis. A one-year survival analysis using Kaplan-Meier curves and log rank test was performed.

Results

358 patients were analysed, finding pleuropulmonary pathologies in 81%. CECTs were performed with a median of 2 days (IQR 1–3) after admission. Multivariable analysis identified moderate to severe or bilateral pleural effusions (PEs) (OR = 4.16, 95%CI 2.05–8.45, p<0.001) and pre-existing CLD (OR = 2.93, 95%CI 1.17–7.32, p = 0.022) as independent predictors of severe AP. Log rank test showed a significantly worse one-year survival in patients with bilateral compared to unilateral PEs in a subgroup.

Conclusions

Increasing awareness of the prognostic impact of large and bilateral PEs and pre-existing CLD could facilitate the identification of patients at high risk for severe AP in the early phase and thus improve their prognosis.

Effects of Indwelling Pleural Catheter on Severe Acute Pancreatitis: A Retrospective Study

Background. Pleural effusion (PE) is an important predictor for severity and prognosis of severe acute pancreatitis (SAP). However, there are few studies focused on the effects and timing of indwelling pleural catheter (IPC) on SAP. Considering this, we designed a retrospective study to verify the relationship between PE and severity of SAP and observe the effects and timing of IPC in SAP. Methods. A total of 309 SAP patients were enrolled. Based on the presence or absence of PE and IPC and IPC time, the enrolled patients were divided into 6 groups. Then, baseline parameters, disease severity, critical complications, ventilator supporting time (VST), length of stay (LOS), and 60-day mortality were compared between each two groups. Results. PE was a risk factor for death of SAP, but not an independent risk factor. SAP patients with PE rather without PE had higher critical complication rates ( $p<0.001$ ), along with longer VST ( $p<0.001$ ) and LOS ( $p<0.001$ ). And the critical complication rates were lower in group 1 (IPC within 1 week of onset) than group 2 (IPC after 1 week of onset). Further, patients in group 1 also had shorter LOS ( $p=0.042$ ) and VST ( $p=0.001$ ) than those in group 2. In addition, the survival analysis showed the risk of death in the PE group was higher than the non-PE group (HR 6.6, 95% CI, 3.67–11.86, and $p<0.001$ ). And the risk of death in group 1 was lower than group 2 (HR 0.26, 95% CI, 0.08–0.84, and $p=0.025$ ). Conclusions. PE is a risk factor for death of SAP, but not an independent risk factor. IPC, especially IPC within 1 week of onset, has clinical practical value in SAP.

Usefulness of Random Forest Algorithm in Predicting Severe Acute Pancreatitis

BACKGROUND AND AIMS

This study aimed to develop an interpretable random forest model for predicting severe acute pancreatitis (SAP).

METHODS

Clinical and laboratory data of 648 patients with acute pancreatitis were retrospectively reviewed and randomly assigned to the training set and test set in a 3:1 ratio. Univariate analysis was used to select candidate predictors for the SAP. Random forest (RF) and logistic regression (LR) models were developed on the training sample. The prediction models were then applied to the test sample. The performance of the risk models was measured by calculating the area under the receiver operating characteristic (ROC) curves (AUC) and area under precision recall curve. We provide visualized interpretation by using local interpretable model-agnostic explanations (LIME).

RESULTS

The LR model was developed to predict SAP as the following function: -1.10-0.13×albumin (g/L) + 0.016 × serum creatinine (μmol/L) + 0.14 × glucose (mmol/L) + 1.63 × pleural effusion (0/1)(No/Yes). The coefficients of this formula were utilized to build a nomogram. The RF model consists of 16 variables identified by univariate analysis. It was developed and validated by a tenfold cross-validation on the training sample. Variables importance analysis suggested that blood urea nitrogen, serum creatinine, albumin, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, calcium, and glucose were the most important seven predictors of SAP. The AUCs of RF model in tenfold cross-validation of the training set and the test set was 0.89 and 0.96, respectively. Both the area under precision recall curve and the diagnostic accuracy of the RF model were higher than that of both the LR model and the BISAP score. LIME plots were used to explain individualized prediction of the RF model.

CONCLUSIONS

An interpretable RF model exhibited the highest discriminatory performance in predicting SAP. Interpretation with LIME plots could be useful for individualized prediction in a clinical setting. A nomogram consisting of albumin, serum creatinine, glucose, and pleural effusion was useful for prediction of SAP.

Pain management consultation for acute pancreatitis: impact on length of stay and opioid utilization

Aim: The purpose of the study was to understand the impact of a pain management consult for acute pancreatitis patients on their inpatient length of stay, morphine milligram equivalences (MMEs) and pancreatitis severity. Materials & methods: Adult patient data were extracted from the electronic health records from 1 October 2016 to 31 December 2018. Results & conclusion: Of 277 patients with a single acute pancreatitis hospitalization, 23 had a pain consultation (treatment group), whereas 254 did not (control group). There were statistically significant differences in median length of stay, median MME total and median MME per day between the treatment and control groups with comparable severity and pain scores (6.8 vs 3.1 days, 196.5 vs 33.8 MMEs, 30.9 vs 12.1 MMEs, respectively, p < 0.0001). This study emphasizes the complexity of pain management and the importance of further research in the field.

Assessment of the course of acute pancreatitis in the light of aetiology: a systematic review and meta-analysis

The main causes of acute pancreatitis (AP) are biliary disease, alcohol consumption, hypertriglyceridaemia (HTG) and endoscopic retrograde cholangiopancreatography (ERCP). The aim of this meta-analysis was to evaluate the effects of these aetiological factors on the severity and outcome of AP. Pubmed and Embase were searched between 01/01/2012 and 31/05/2020. Included articles involved adult alcoholic, biliary, HTG- or post-ERCP AP (PAP) patients. Primary outcome was severity, secondary outcomes were organ failures, intensive care unit admission, recurrence rate, pancreatic necrosis, mortality, length of hospital stay, pseudocyst, fluid collection and systematic inflammatory response syndrome. Data were analysed from 127 eligible studies. The risk for non-mild (moderately severe and severe) condition was the highest in HTG-induced AP (HTG-AP) followed by alcoholic AP (AAP), biliary AP (BAP) and PAP. Recurrence rate was significantly lower among BAP vs. HTG-AP or AAP patients (OR = 2.69 and 2.98, 95% CI 1.55–4.65 and 2.22–4.01, respectively). Mortality rate was significantly greater in HTG-AP vs. AAP or BAP (OR = 1.72 and 1.50, 95% CI 1.04–2.84 and 0.96–2.35, respectively), pancreatic necrosis occurred more frequently in AAP than BAP patients (OR = 1.58, 95% CI 1.08–2.30). Overall, there is a potential association between aetiology and the development and course of AP. HTG-AP is associated with the highest number of complications. Furthermore, AAP is likely to be more severe than BAP or PAP. Greater emphasis should be placed on determining aetiology on admission.