Mechanisms of Food-Induced Symptom Induction and Dietary Management in Functional Dyspepsia

Functional dyspepsia (FD) is a common disorder of gut-brain interaction, characterised by upper gastrointestinal symptom profiles that differentiate FD from the irritable bowel syndrome (IBS), although the two conditions often co-exist. Despite food and eating being implicated in FD symptom induction, evidence-based guidance for dietetic management of FD is limited. The aim of this narrative review is to collate the possible mechanisms for eating-induced and food-related symptoms of FD for stratification of dietetic management. Specific carbohydrates, proteins and fats, or foods high in these macronutrients have all been reported as influencing FD symptom induction, with removal of ‘trigger’ foods or nutrients shown to alleviate symptoms. Food additives and natural food chemicals have also been implicated, but there is a lack of convincing evidence. Emerging evidence suggests the gastrointestinal microbiota is the primary interface between food and symptom induction in FD, and is therefore a research direction that warrants substantial attention. Objective markers of FD, along with more sensitive and specific dietary assessment tools will contribute to progressing towards evidence-based dietetic management of FD.     

Precision Nutrition for Alzheimer’s Prevention in ApoE4 Carriers

The ApoE4 allele is the most well-studied genetic risk factor for Alzheimer’s disease, a condition that is increasing in prevalence and remains without a cure. Precision nutrition targeting metabolic pathways altered by ApoE4 provides a tool for the potential prevention of disease. However, no long-term human studies have been conducted to determine effective nutritional protocols for the prevention of Alzheimer’s disease in ApoE4 carriers. This may be because relatively little is yet known about the precise mechanisms by which the genetic variant confers an increased risk of dementia. Fortunately, recent research is beginning to shine a spotlight on these mechanisms. These new data open up the opportunity for speculation as to how carriers might ameliorate risk through lifestyle and nutrition. Herein, we review recent discoveries about how ApoE4 differentially impacts microglia and inflammatory pathways, astrocytes and lipid metabolism, pericytes and blood–brain barrier integrity, and insulin resistance and glucose metabolism. We use these data as a basis to speculate a precision nutrition approach for ApoE4 carriers, including a low-glycemic index diet with a ketogenic option, specific Mediterranean-style food choices, and a panel of seven nutritional supplements. Where possible, we integrate basic scientific mechanisms with human observational studies to create a more complete and convincing rationale for this precision nutrition approach. Until recent research discoveries can be translated into long-term human studies, a mechanism-informed practical clinical approach may be useful for clinicians and patients with ApoE4 to adopt a lifestyle and nutrition plan geared towards Alzheimer’s risk reduction.     

The effect of various media and probe angles on the power output of the Cyclo G6 Glaucoma Laser System

Lasers in Medical Science - To evaluate the effect of various media and Iridex MicroPulse P3 (MP3) probe angles on the power output from the Cyclo G6 Glaucoma Laser (G6) System. A laser power meter...     

What is the Level of Evidence Substantiating Commercial Payers’ Coverage Policies for Total Joint Arthroplasty?

BackgroundThe prevalence of total joint arthroplasty (TJA) in the United States has drawn the attention of health care stakeholders. The payers have also used a variety of strategies to regulate the medical necessity of these procedures. The purpose of this study was to examine the level of evidence of the coverage policies being used by commercial payers in the United States.MethodsThe references of the coverage policies of four commercial insurance companies were reviewed for type of document, level of evidence, applicability to a TJA population, and success of nonoperative treatment in patients with severe degenerative joint disease.Results282 documents were reviewed. 45.8% were primary journal articles, 14.2% were level I or II, 41.2% were applicable to patients who were candidates for TJA, and 9.9% discussed the success of nonoperative treatment in patients who would be candidates for TJA.ConclusionMost of the references cited by commercial payers are of a lower level of scientific evidence and not applicable to patients considered to be candidates for TJA. This is relatively uniform across the reviewed payers. The dearth of high-quality literature cited by commercial payers reflects the lack of evidence and difficulty in conducting high level studies on the outcomes of nonoperative versus operative treatment for patients with severe, symptomatic osteoarthritis. Patients, surgeons, and payers would all benefit from such studies and we encourage professional societies to strive toward that end through multicenter collaboration.     

Can Machine Learning Methods Produce Accurate and Easy-to-Use Preoperative Prediction Models of One-Year Improvements in Pain and Functioning After Knee Arthroplasty?

BackgroundApproximately 15%-20% of total knee arthroplasty (TKA) patients do not experience clinically meaningful improvements. We sought to compare the accuracy and parsimony of several machine learning strategies for developing predictive models of failing to experience minimal clinically important differences in patient-reported outcome measures (PROMs) 1 year after TKA.MethodsPatients (N = 587) in 3 large Veteran Health Administration facilities completed PROMs before and 1 year after TKA (92% follow-up). Preoperative PROMs and electronic health record data were used to develop and validate models to predict failing to experience at least a minimal clinically important difference in Knee Injury and Osteoarthritis Outcome Score (KOOS) Total, KOOS JR, and KOOS subscales (Pain, Symptoms, Activities of Daily Living, Quality of Life, and recreation). Several machine learning strategies were used for model development. Ten-fold cross-validation and bootstrapping were used to produce measures of overall accuracy (C-statistic, Brier Score). The sensitivity and specificity of various predicted probability cut-points were examined.ResultsThe most accurate models produced were for the Activities of Daily Living, Pain, Symptoms, and Quality of Life subscales of the KOOS (C-statistics 0.76, 0.72, 0.72, and 0.71, respectively). Strategies varied substantially in terms of the numbers of inputs required to achieve similar accuracy, with none being superior for all outcomes.ConclusionModels produced in this project provide estimates of patient-specific improvements in major outcomes 1 year after TKA. Integrating these models into clinical decision support, informed consent and shared decision making could improve patient selection, education, and satisfaction.Level of EvidenceLevel III, diagnostic study.     

Selected conditions associated with an increased incidence of incisional hernia: A review of molecular biology

BackgroundIncisional hernias (IH) following a laparotomy, on average, occur in 10–20% of patients, however, little is known about its molecular basis. Thus, a better understanding of the molecular mechanisms could lead to the identification of key target(s) to intervene pre-and post-operatively.MethodsWe examined the current literature describing the molecular mechanisms of IH and overlap these factors with smoking, abdominal aortic aneurysm, obesity, diabetes mellitus, and diverticulitis.ResultsThe expression levels of collagen I and III, matrix metalloproteinases, and tissue inhibitors of metalloproteases are abnormal in the extracellular matrix (ECM) of IH patients and ECM disorganization has an overlap with these comorbid conditions.ConclusionUnderstanding the pathophysiology of IH development and associated risk factors will allow physicians to identify patients that may be at increased risk for IH and to possibly act preemptively to decrease the incidence of IH.     

Patience is a virtue: Multiple preoperative visits are associated with decreased recurrence in pediatric pilonidal disease

Background/PurposeThis study aimed to compare preoperative management strategies for patients undergoing trephination for pilonidal disease and evaluate risk factors for recurrence.MethodsA retrospective review was performed of children undergoing index surgical treatment with trephination for pilonidal disease between September 2017 and April 2019. Intraoperative and postoperative management were standardized. Demographic and perioperative data were collected and analyzed.ResultsOne-hundred twenty patients were identified with a median follow-up time of 7.5 months (interquartile range 4.1–13.2 months). Overall, 24 (20%) patients had a postoperative recurrence of pilonidal disease. Patients with multiple preoperative surgery clinic visits were less likely to have recurrent disease compared to those seen only once preoperatively (11% vs 26%, p = 0.040). Compared to patients without recurrence, those who recurred went to the operating room sooner from the time of initial surgical consultation (32 days vs 54 days, p < 0.001). Perioperative antibiotics, history of acute infection, and prior drainage procedures were not risk factors for recurrence.ConclusionsMultiple preoperative clinic visits are associated with a lower recurrence rate in children undergoing trephination for pilonidal disease. An increased duration of preoperative medical management may be responsible for this finding. Prospective study is needed to confirm these findings and identify additional factors that influence recurrence.Type of StudyTreatment Study.Level of EvidenceIII (Retrospective Comparative).