Microbiota-Pain Association; Recent Discoveries and Research Progress

Risk of fibromyalgia following antibiotic prescriptions: A population-based case-control study

BACKGROUND

The health of the gut microbiome is now recognized to be an important component of the gut-brain axis which itself appears to be implicated in pain perception. Antibiotics are known to create dysbiosis in the microbiome, so whether fibromyalgia is more commonly diagnosed after antibiotic prescriptions provides a means of exploring the role of the microbiome in the experience of chronic pain.

METHODS

A case-control study was carried out using electronic health records collected in the UK's Clinical Practice Research Datalink (CPRD), a comprehensive database of primary care consultations. For each case of diagnosed fibromyalgia, three controls were identified and matched by age, gender and GP practice. The exposure variable was the number and timing of antibiotic prescriptions over previous years. The analysis involved adjusting for a wide range of co-variates that might be possible confounders.

RESULTS

A total of 44,674 cases of fibromyalgia were identified together with 133,513 controls. After adjusting for co-variates, it was found that both the total number of prescriptions and their timing was associated with an FM diagnosis. For example, the quartile with the highest number of prescriptions and that with the longest exposure had a greater than three-fold increase in FM diagnoses (number of prescriptions: odds ratio 3.92; 95% CIs: 3.71-4.13; exposure odds ratio 3.28; CIs: 3.13-3.43). Some antibiotics (such as tetracyclines and metronidazole) seemed to confer greater risk than others.

CONCLUSIONS

The results lend support for prior antibiotics being an important risk factor for a diagnosis of FM.

SIGNIFICANCE

This study shows an association between the volume as well as timing of prior antibiotic prescriptions and of a subsequent diagnosis of fibromyalgia in primary care.

The importance of the gut microbiome and its signals for a healthy nervous system and the multifaceted mechanisms of neuropsychiatric disorders

Increasing evidence links the gut microbiome and the nervous system in health and disease. This narrative review discusses current views on the interaction between the gut microbiota, the intestinal epithelium, and the brain, and provides an overview of the communication routes and signals of the bidirectional interactions between gut microbiota and the brain, including circulatory, immunological, neuroanatomical, and neuroendocrine pathways. Similarities and differences in healthy gut microbiota in humans and mice exist that are relevant for the translational gap between non-human model systems and patients. There is an increasing spectrum of metabolites and neurotransmitters that are released and/or modulated by the gut microbiota in both homeostatic and pathological conditions. Dysbiotic disruptions occur as consequences of critical illnesses such as cancer, cardiovascular and chronic kidney disease but also neurological, mental, and pain disorders, as well as ischemic and traumatic brain injury. Changes in the gut microbiota (dysbiosis) and a concomitant imbalance in the release of mediators may be cause or consequence of diseases of the central nervous system and are increasingly emerging as critical links to the disruption of healthy physiological function, alterations in nutrition intake, exposure to hypoxic conditions and others, observed in brain disorders. Despite the generally accepted importance of the gut microbiome, the bidirectional communication routes between brain and gut are not fully understood. Elucidating these routes and signaling pathways in more detail offers novel mechanistic insight into the pathophysiology and multifaceted aspects of brain disorders.

Evaluating ChatGPT responses to frequently asked patient questions regarding periprosthetic joint infection after total hip and knee arthroplasty

Background

Patients access relevant information concerning their orthopaedic surgery resources through multiple information channels before presenting for clinical treatment. Recently, artificial intelligence (AI)-powered chatbots have become another source of information for patients. The currently developed AI chat technology ChatGPT (OpenAI LP) is an application for such purposes and it has been rapidly gaining popularity, including for patient education. This study sought to evaluate whether ChatGPT can correctly answer frequently asked questions (FAQ) regarding periprosthetic joint infection (PJI).

Methods

Twelve FAQs about PJI after hip and knee arthroplasty were identified from the websites of fifteen international clinical expert centres. ChatGPT was confronted with these questions and its responses were analysed for their accuracy using an evidence-based approach by a multidisciplinary team. Responses were categorised in four groups: (1) Excellent response that did not require additional improvement; (2) Satisfactory responses that required a small amount of improvement; (3) Satisfactory responses that required moderate improvement; and (4) Unsatisfactory responses that required a large amount of improvement.

Results

From the analysis of the responses given by the chatbot, no reply received an 'unsatisfactory' rating; one did not require any correction; and the majority of the responses required low (7 out of 12) or moderate (4 out of 12) clarification. Although a few responses required minimal clarification, the chatbot responses were generally unbiased and evidence-based, even when asked controversial questions.

Conclusions

The AI-chatbot ChatGPT was able to effectively answer the FAQs of patients seeking information around PJI diagnosis and treatment. The given information was also written in a manner that can be assumed to be understandable by patients. The chatbot could be a valuable clinical tool for patient education and understanding around PJI treatment in the future. Further studies should evaluate its use and acceptance by patients with PJI.

Probiotics in Postoperative Pain Management

Postoperative pain is the unpleasant sensory and emotional experience after surgery, its origin being both the inflammatory reaction induced by the surgical trauma on the abdominal wall and the splanchnic pain induced by the activation of nociceptors of the viscera, which are highly sensitive to distension, ischemia, and inflammation. Nowadays, it is well recognized that there is a close relationship between the gut microbiome and pain perception, and that microbiome is highly affected by both anesthesia and surgical manipulation. Thus, efforts to restore the disturbed microbiome via supplementation with beneficial bacteria, namely probiotics, seem to be effective. In this article, the knowledge gained mainly from experimental research on this topic is analyzed, the concluding message being that each probiotic strain works in its own way towards pain relief.

Alterations of the gut microbiota in patients with postherpetic neuralgia

Postherpetic neuralgia (PHN) is a prevalent, intricate, and intractable form of neuropathic pain. The available evidence indicates that alterations in the gut microbiota are significant environmental determinants in the development of chronic neuropathic pain. Nevertheless, the correlation between the gut microbiota and PHN remains elusive. A cross-sectional study was performed on a cohort of 27 patients diagnosed with PHN and 27 matched healthy controls. Fecal samples were collected and subjected to microbiota analysis using 16S ribosomal RNA gene sequencing. Comparable levels of bacterial richness and diversity were observed in the gut microbiota of PHN patients and healthy controls. A significant difference was observed in 37 genera between the two groups. Furthermore, the LEfSe method revealed that the abundance levels of Escherichia-Shigella, Streptococcus, Ligilactobacillus, and Clostridia_UCG-014_unclassified were elevated in PHN patients, while Eubacterium_hallii_group, Butyricicoccus, Tyzzerella, Dorea, Parasutterella, Romboutsia, Megamonas, and Agathobacter genera were reduced in comparison to healthy controls. Significantly, the discriminant model utilizing the predominant microbiota exhibited efficacy in distinguishing PHN patients from healthy controls, with an area under the curve value of 0.824. Moreover, Spearman correlation analysis demonstrated noteworthy correlations between various gut microbiota and clinical symptoms, including disease course, anxiety state, sleep quality, heat pain, pain intensity, and itching intensity. Gut microbiota dysbiosis exists in PHN patients, microbiome differences could be used to distinguish PHN patients from normal healthy individuals with high sensitivity and specificity, and altered gut microbiota are related to clinical manifestations, suggesting potentially novel prevention and therapeutic directions of PHN.