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A Step Towards a Better Understanding of Pain Phenotypes: Latent Class Analysis in Chronic Pain Patients Receiving Multimodal Inpatient Treatment.

ABSTRACT: Purpose:The number of non-responders to treatment among patients with chronic pain (CP) is high, although intensive multimodal treatment is broadly accessible. One reason is the large variability in manifestations of CP. To facilitate the development of tailored treatment approaches, phenotypes of CP must be identified. In this study, we aim to identify subgroups in patients with CP based on several aspects of self-reported health. Patients and Methods:A latent class analysis (LCA) was carried out in retrospective data from 411 patients with CP of different origins. All patients experienced severe physical and psychosocial consequences and were therefore undergoing multimodal inpatient pain treatment. Self-reported measures of pain (?visual analogue scales for pain intensity, frequency, and impairment; Pain Perception Scale), emotional distress (Patient Health Questionnaire, PHQ-9; Generalized Anxiety Disorder Scale, GAD-7) and physical health (Short Form Health Survey; SF-8) were collected immediately after admission and before discharge. Instruments assessed at admission were used as input to the LCA. Resulting classes were compared in terms of patient characteristics and treatment outcome. Results:A model with four latent classes demonstrated the best model fit and interpretability. Classes 1 to 4 included patients with high (54.7%), extreme (17.0%), moderate (15.6%), and low (12.7%) pain burden, respectively. Patients in class 4 showed high levels of emotional distress, whereas emotional distress in the other classes corresponded to the levels of pain burden. While pain as well as physical and mental health improved in class 1, only the levels of depression and anxiety improved in patients in the other groups during multimodal treatment. Conclusion:The specific needs of these subgroups should be taken into account when developing individualized treatment programs. However, the retrospective design limits the significance of the results and replication in prospective studies is desirable.

SUBMITTER: Obbarius A

PROVIDER: S-EPMC7234963 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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A Step Towards a Better Understanding of Pain Phenotypes: Latent Class Analysis in Chronic Pain Patients Receiving Multimodal Inpatient Treatment.

Obbarius Alexander A Fischer Felix F Liegl Gregor G Obbarius Nina N van Bebber Jan J Hofmann Tobias T Rose Matthias M

Journal of pain research 20200514

<h4>Purpose</h4>The number of non-responders to treatment among patients with chronic pain (CP) is high, although intensive multimodal treatment is broadly accessible. One reason is the large variability in manifestations of CP. To facilitate the development of tailored treatment approaches, phenotypes of CP must be identified. In this study, we aim to identify subgroups in patients with CP based on several aspects of self-reported health.<h4>Patients and methods</h4>A latent class analysis (LCA ...[more]

PMID: 32523372

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Project description:Introduction: Although pharmacogenetics and pharmacogenomics have been at the forefront of research aimed at finding novel personalized therapies, the focus of research has recently extended to the potential of intestinal microbiota to affect drug efficacy. Complex interplay of gut microbiota with bile acids may have significant repercussions on drug pharmacokinetics. However, far too little attention has been paid to the potential implication of gut microbiota and bile acids in simvastatin response which is characterized by large interindividual variations. The Aim: In order to gain more insight into the underlying mechanism and its contribution in assessing the clinical outcome, the aim of our study was to examine simvastatin bioaccumulation and biotransformation in probiotic bacteria and the effect of bile acids on simvastatin bioaccumulation in in vitro conditions. Materials and methods: Samples with simvastatin, probiotic bacteria and three different bile acids were incubated at anaerobic conditions at 37°C for 24 h. Extracellular and intracellular medium samples were collected and prepared for the LC-MS analysis at predetermined time points (0 min, 15 min, 1 h, 2 h, 4 h, 6 h, 24 h). The concentrations of simvastatin were analyzed by LC-MS/MS. Potential biotransformation pathways were analyzed using a bioinformatics approach in correlation with experimental assay. Results: During the incubation, simvastatin was transported into bacteria cells leading to a drug bioaccumulation over the time, which was augmented upon addition of bile acids after 24 h. A decrease of total drug level during the incubation indicates that the drug is partly biotransformed by bacterial enzymes. According to the results of bioinformatics analysis, the lactone ring is the most susceptible to metabolic changes and the most likely reactions include ester hydrolysis followed by hydroxylation. Conclusion: Results of our study reveal that bioaccumulation and biotransformation of simvastatin by intestinal bacteria might be the underlying mechanisms of altered simvastatin bioavailability and therapeutic effect. Since this study is based only on selected bacterial strains in vitro, further more in-depth research is needed in order to elicit completely the contribution of complex drug-microbiota-bile acids interactions to overall clinical response of simvastatin which could ultimately lead to novel approaches for the personalized lipid-lowering therapy.

Project description:BackgroundGiven the relatively high rates of suicidal ideation and attempt among people with chronic pain, there is a need to understand the underlying factors to target suicide prevention efforts. To date, no study has examined the association between pain phenotypes and suicide related behaviors among those with mild traumatic brain injuries.ObjectiveTo determine if pain phenotypes were independently associated with suicidal ideation / attempt or if comorbidities within the pain phenotypes account for the association between pain phenotypes and suicide related behaviors.MethodsThis is a longitudinal retrospective cohort study of suicide ideation/attempts among pain phenotypes previously derived using general mixture latent variable models of the joint distribution of repeated measures of pain scores and pain medications/treatment. We used national VA inpatient, outpatient, and pharmacy data files for Post-9/11 Veterans with mild traumatic injury who entered VA care between fiscal years (FY) 2007 and 2009. We considered a counterfactual causal modeling framework to assess the extent that the pain phenotypes during years 1-5 of VA care were predictive of suicide ideation/attempt during years 6-8 of VA care conditioned on covariates being balanced between pain phenotypes.ResultsWithout adjustment, pain phenotypes were significant predictors of suicide related behaviors. When we used propensity scores to balance the comorbidities present in the pain phenotypes, the pain phenotypes were no longer significantly associated with suicide related behaviors.ConclusionThese findings suggest that suicide ideation/attempt is associated with pain trajectories primarily through latent multimorbidity. Therefore, it is critical to identify and manage comorbidities (e.g., depression, post-traumatic stress disorder) to prevent tragic outcomes associated with suicide related behaviors throughout the course of chronic pain and mild traumatic brain injury management.

Dataset Information

A Step Towards a Better Understanding of Pain Phenotypes: Latent Class Analysis in Chronic Pain Patients Receiving Multimodal Inpatient Treatment.

Publications

A Step Towards a Better Understanding of Pain Phenotypes: Latent Class Analysis in Chronic Pain Patients Receiving Multimodal Inpatient Treatment.

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