Antidopaminergic drugs and acute pancreatitis: a population-based study

Antipsychotic drugs and risk of acute pancreatitis: A nationwide case-control study

INTRODUCTION

Use of antipsychotic drugs, especially second-generation agents, has been suggested to cause acute pancreatitis in multiple case reports; however, such an association has not been corroborated by larger studies. This study examined the association of antipsychotic drugs with risk of acute pancreatitis.

METHODS

Nationwide case-control study, based on data from several Swedish registers and including all 52,006 cases of acute pancreatitis diagnosed in Sweden between 2006 and 2019 (with up to 10 controls per case; n = 518,081). Conditional logistic regression models were used to calculate odds ratios (ORs) in current and past users of first-generation and second-generation antipsychotic drugs (dispensed prescription <91 and ≥91 days of the index date, respectively) compared with never users of such drugs.

RESULTS

In the crude model, first-generation and second-generation antipsychotic drugs were associated with increased risk of acute pancreatitis, with slightly higher ORs for past use (1.58 [95% confidence interval 1.48-1.69] and 1.39 [1.29-1.49], respectively) than for current use (1.34 [1.21-1.48] and 1.24 [1.15-1.34], respectively). The ORs were largely attenuated in the multivariable model-which included, among others, alcohol abuse and the Charlson comorbidity index-up to the point where only a statistically significant association remained for past use of first-generation agents (OR 1.18 [1.10-1.26]).

CONCLUSION

There was no clear association between use of antipsychotic drugs and risk of acute pancreatitis in this very large case-control study, indicating that previous case report data are most likely explained by confounding.

Psychiatric medications and the risk of autoimmune and immune-mediated inflammatory diseases: A systematic review and meta-analysis of observational studies

BACKGROUND

Pharmacovigilance reports have suggested that certain commonly used medications may trigger autoimmune diseases (ADs) and immune-mediated inflammatory diseases (IMIDs). We systematically reviewed the literature to evaluate whether psychiatric medication use is associated with ADs and IMIDs.

METHODS

The protocol was registered in PROSPERO (CRD42022296524) before the start of the study. We searched Medline Ovid and Scopus up to November 28th, 2021, for comparative studies, with any psychiatric medication as exposure and ADs and IMIDs as outcomes. Meta-analysis was performed using DerSimonian-Laird random-effects modeling. The PRISMA 2020 guidelines were followed in reporting. Study-level risk of bias was assessed using the Newcastle-Ottawa Scale, and the overall certainty of evidence using GRADE.

RESULTS

There were 7,265 citations from which 31 studies were eligible, all from high-income countries, covering 15 distinct immune diseases. The evidence for the association between selective serotonin reuptake inhibitor (SSRI) use and higher risk of microscopic colitis (meta-OR 2.60, 95% CI 1.05-6.39, I2 97.5%, 6 studies) was of low certainty. A subgroup analysis by the histological type of microscopic colitis showed a statistically significant association only with lymphocytic colitis (meta-OR 2.88, 95% CI 2.60-3.18, I2 00.00%, three studies). In two case-control studies, SSRI use had no significant association with psoriasis (meta-OR 0.80, 95% CI 0.58-1.10, I2 82.4%). The risk of acute pancreatitis was slightly increased with exposure to SSRIs (meta-OR 1.13, 95% CI 1.01-1.26, I2 00.0%), as was the risk of bullous pemphigoid after exposure to antipsychotics (meta-OR 1.79, 95% CI 1.17-2.73, I2 0%).

CONCLUSIONS

We reviewed the literature on whether psychiatric medications associate with the risk of ADs and IMIDs and concluded that, despite several signals, the credibility of evidence remains low at best. Prospective cohort studies would be needed as the next step to confirm the suggestions of increased risk.

The use of intelligent database systems in acute pancreatitis--a systematic review

INTRODUCTION

Acute pancreatitis (AP) is a complex disease with multiple aetiological factors, wide ranging severity, and multiple challenges to effective triage and management. Databases, data mining and machine learning algorithms (MLAs), including artificial neural networks (ANNs), may assist by storing and interpreting data from multiple sources, potentially improving clinical decision-making.

AIMS

1) Identify database technologies used to store AP data, 2) collate and categorise variables stored in AP databases, 3) identify the MLA technologies, including ANNs, used to analyse AP data, and 4) identify clinical and non-clinical benefits and obstacles in establishing a national or international AP database.

METHODS

Comprehensive systematic search of online reference databases. The predetermined inclusion criteria were all papers discussing 1) databases, 2) data mining or 3) MLAs, pertaining to AP, independently assessed by two reviewers with conflicts resolved by a third author.

RESULTS

Forty-three papers were included. Three data mining technologies and five ANN methodologies were reported in the literature. There were 187 collected variables identified. ANNs increase accuracy of severity prediction, one study showed ANNs had a sensitivity of 0.89 and specificity of 0.96 six hours after admission--compare APACHE II (cutoff score ≥8) with 0.80 and 0.85 respectively. Problems with databases were incomplete data, lack of clinical data, diagnostic reliability and missing clinical data.

CONCLUSION

This is the first systematic review examining the use of databases, MLAs and ANNs in the management of AP. The clinical benefits these technologies have over current systems and other advantages to adopting them are identified.