Medicalising diagnoses and treatment preferences: a retrospective cohort study of throat-related consultations in electronic primary care records.

BACKGROUND: Rather than first diagnosing and then deciding on treatment, GPs may intuitively decide on treatment and justify this through choice of diagnosis. AIM: To investigate the relationship between choice of a medicalising diagnosis and antibiotic treatment for throat-related consultations. DESIGN & SETTING: A retrospective cohort study in a large database of UK electronic primary care records between 1 January 2010 and 1 January 2020. METHOD: All first throat-related consultations were included, categorised as either pharyngitis/tonsillitis or sore throat. The outcome was any antibiotic prescription on the consultation date. GP-level random effects on prescribing and on diagnosis were estimated in a series of mixed-effects regression models, including age, sex, weekday, month, and clinician characteristics as fixed effects. GPs were grouped into quintiles by antibiotic prescribing propensity, and described the proportion of patients they diagnosed with pharyngitis/tonsillitis or sore throat in each quintile. RESULTS: The analysis dataset included 393 590 throat-related consultations with 6881 staff. Diagnosis of pharyngitis/tonsillitis was strongly associated with antibiotic prescribing (adjusted odds ratio = 13.41, 95% confidence interval = 12.8 to 14.04). GP random effect accounted for 18% of variation in prescribing and for 26% of variation in diagnosis. GPs in the lowest quintile of antibiotic prescribing propensity diagnosed pharyngitis/tonsillitis on 31% of occasions, compared with 55% in the highest quintile. CONCLUSION: There is substantial variation among GPs in diagnosis and treatment of throat-related problems. Preference for a medicalising diagnosis is associated with a preference for antibiotics, suggesting a common propensity to both diagnose and treat.

In simulated data and health records, latent class analysis was the optimum multimorbidity clustering algorithm.

BACKGROUND AND OBJECTIVES: To investigate the reproducibility and validity of latent class analysis (LCA) and hierarchical cluster analysis (HCA), multiple correspondence analysis followed by k-means (MCA-kmeans) and k-means (kmeans) for multimorbidity clustering. METHODS: We first investigated clustering algorithms in simulated datasets with 26 diseases of varying prevalence in predetermined clusters, comparing the derived clusters to known clusters using the adjusted Rand Index (aRI). We then them investigated the medical records of male patients, aged 65 to 84 years from 50 UK general practices, with 49 long-term health conditions. We compared within cluster morbidity profiles using the Pearson correlation coefficient and assessed cluster stability using in 400 bootstrap samples. RESULTS: In the simulated datasets, the closest agreement (largest aRI) to known clusters was with LCA and then MCA-kmeans algorithms. In the medical records dataset, all four algorithms identified one cluster of 20-25% of the dataset with about 82% of the same patients across all four algorithms. LCA and MCA-kmeans both found a second cluster of 7% of the dataset. Other clusters were found by only one algorithm. LCA and MCA-kmeans clustering gave the most similar partitioning (aRI 0.54). CONCLUSION: LCA achieved higher aRI than other clustering algorithms.

Symptoms and risk factors for long COVID in non-hospitalized adults.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection is associated with a range of persistent symptoms impacting everyday functioning, known as post-COVID-19 condition or long COVID. We undertook a retrospective matched cohort study using a UK-based primary care database, Clinical Practice Research Datalink Aurum, to determine symptoms that are associated with confirmed SARS-CoV-2 infection beyond 12 weeks in non-hospitalized adults and the risk factors associated with developing persistent symptoms. We selected 486,149 adults with confirmed SARS-CoV-2 infection and 1,944,580 propensity score-matched adults with no recorded evidence of SARS-CoV-2 infection. Outcomes included 115 individual symptoms, as well as long COVID, defined as a composite outcome of 33 symptoms by the World Health Organization clinical case definition. Cox proportional hazards models were used to estimate adjusted hazard ratios (aHRs) for the outcomes. A total of 62 symptoms were significantly associated with SARS-CoV-2 infection after 12 weeks. The largest aHRs were for anosmia (aHR 6.49, 95% CI 5.02-8.39), hair loss (3.99, 3.63-4.39), sneezing (2.77, 1.40-5.50), ejaculation difficulty (2.63, 1.61-4.28) and reduced libido (2.36, 1.61-3.47). Among the cohort of patients infected with SARS-CoV-2, risk factors for long COVID included female sex, belonging to an ethnic minority, socioeconomic deprivation, smoking, obesity and a wide range of comorbidities. The risk of developing long COVID was also found to be increased along a gradient of decreasing age. SARS-CoV-2 infection is associated with a plethora of symptoms that are associated with a range of sociodemographic and clinical risk factors.

Decreased renal function is associated with incident dementia: An IMRD-THIN retrospective cohort study in the UK.

INTRODUCTION: Decreased renal function is a potential risk factor for dementia. METHODS: This retrospective cohort study of 2.8 million adults aged ≥50 years used the IMRD-THIN database, representative of UK primary care, from January 1, 1995 to February 24, 2020. The associations between estimated glomerular filtration rate (eGFR) and urine albumin creatinine ratio (ACR) with incident all-cause dementia were analyzed using Cox regression. RESULTS: In the eGFR cohort (n = 2,797,384), worsening renal dysfunction was associated with increased hazard of all-cause dementia, with greatest hazard at eGFR 15-30 ml/min/1.73min2 (hazard ratio [HR] 1.26, 95% confidence interval [CI] 1.19-1.33). In the ACR cohort (n = 641,912), the hazard of dementia increased from ACR 3-30 mg/mmol (HR 1.13, 95% CI 1.10-1.15) to ACR > 30 mg/mmol (HR 1.25, 95% CI 1.18-1.33). DISCUSSION: Worsening eGFR and albuminuria have graded associations with the risk of dementia, which may have significant implications for the care of patients with kidney disease.

The clinical profile and associated mortality in people with and without diabetes with Coronavirus disease 2019 on admission to acute hospital services.

INTRODUCTION: To assess if in adults with COVID-19, whether those with diabetes and complications (DM+C) present with a more severe clinical profile and if that relates to increased mortality, compared to those with diabetes with no complications (DM-NC) and those without diabetes. METHODS: Service-level data was used from 996 adults with laboratory confirmed COVID-19 who presented to the Queen Elizabeth Hospital Birmingham, UK, from March to June 2020. All individuals were categorized into DM+C, DM-NC, and non-diabetes groups. Physiological and laboratory measurements in the first 5 days after admission were collated and compared among groups. Cox proportional hazards regression models were used to evaluate associations between diabetes status and the risk of mortality. RESULTS: Among the 996 individuals, 104 (10.4%) were DM+C, 295 (29.6%) DM-NC and 597 (59.9%) non-diabetes. There were 309 (31.0%) in-hospital deaths documented, 40 (4.0% of total cohort) were DM+C, 99 (9.9%) DM-NC and 170 (17.0%) non-diabetes. Individuals with DM+C were more likely to present with high anion gap/metabolic acidosis, features of renal impairment, and low albumin/lymphocyte count than those with DM-NC or those without diabetes. There was no significant difference in mortality rates among the groups: compared to individuals without diabetes, the adjusted HRs were 1.39 (95% CI 0.95-2.03, p = 0.093) and 1.18 (95% CI 0.90-1.54, p = 0.226) in DM+C and DM-C, respectively. CONCLUSIONS: Those with COVID-19 and DM+C presented with a more severe clinical and biochemical profile, but this did not associate with increased mortality in this study.

Obesity Without Metabolic Abnormality and Incident CKD: A Population-Based British Cohort Study.

RATIONALE & OBJECTIVE: Metabolically healthy obesity (obesity without any metabolic abnormality) is not considered to be associated with increased risk of morbidity and mortality. We examined and quantified the association between metabolically healthy overweight/obesity and the risk of incident chronic kidney disease (CKD) in a British primary care population. STUDY DESIGN: Retrospective population-based cohort study. SETTING & PARTICIPANTS: 4,447,955 of the 5,182,908 adults in The Health Improvement Network (THIN) database (United Kingdom, 1995-2015) with a recorded body mass index (BMI) at the time of registration date who were free of CKD and cardiovascular disease. EXPOSURE: 11 body size phenotypes were created, defined by BMI categories (underweight, normal weight, overweight, and obesity) and 3 metabolic abnormalities (diabetes, hypertension, and dyslipidemia). OUTCOME: Incident CKD defined as a recorded code for kidney replacement therapy, a recorded diagnosis of CKD, or by an estimated glomerular filtration rate of<60mL/min/1.73m2 for≥90 days, or a urinary albumin-creatinine ratio>3mg/mmol for≥90 days. RESULTS: Of the 4.5 million individuals, 1,040,921 (23.4%) and 588,909 (13.2%) had metabolically healthy overweight and metabolically healthy obesity, respectively. During a mean follow-up interval of 5.4±4.3 (SD) years, compared with individuals with a metabolically healthy normal weight (n=1,656,231), there was a higher risk of incident CKD among those who had metabolically healthy overweight (adjusted HR, 1.30 [95% CI, 1.28-1.33]) and metabolically healthy obesity (adjusted HR, 1.66 [95% CI, 1.62-1.70]). The association was stronger in those younger than 65 years of age. In all BMI categories, there was greater risk of incident CKD with a greater number of metabolic abnormalities in a graded manner. LIMITATIONS: Potential misclassification of metabolic status due to delayed diagnosis and residual confounding due to unmeasured factors. CONCLUSIONS: Overweight and obesity without metabolic abnormality are associated with a higher risk of incident CKD compared with those with normal body weight and no metabolic abnormality.

Association of Metformin with Susceptibility to COVID-19 in People with Type 2 Diabetes.

OBJECTIVE: Diabetes has emerged as an important risk factor for mortality from COVID-19. Metformin, the most commonly prescribed glucose-lowering agent, has been proposed to influence susceptibility to and outcomes of COVID-19 via multiple mechanisms. We investigated whether, in patients with diabetes, metformin is associated with susceptibility to COVID-19 and its outcomes. RESEARCH DESIGN AND METHODS: We performed a propensity score-matched cohort study with active comparators using a large UK primary care dataset. Adults with type 2 diabetes patients and a current prescription for metformin and other glucose-lowering agents (MF+) were compared to those with a current prescription for glucose-lowering agents that did not include metformin (MF-). Outcomes were confirmed COVID-19, suspected/confirmed COVID-19, and associated mortality. A negative control outcome analysis (back pain) was also performed. RESULTS: There were 29 558 and 10 271 patients in the MF+ and MF- groups, respectively, who met the inclusion criteria. In the propensity score-matched analysis, the adjusted hazard ratios for suspected/confirmed COVID-19, confirmed COVID-19, and COVID-19-related mortality were 0.85 (95% CI 0.67, 1.08), 0.80 (95% CI 0.49, 1.30), and 0.87 (95% CI 0.34, 2.20) respectively. The negative outcome control analysis did not suggest unobserved confounding. CONCLUSION: Current prescription of metformin was not associated with the risk of COVID-19 or COVID-19-related mortality. It is safe to continue prescribing metformin to improve glycemic control in patients with.

Circulating Folate Concentrations and Risk of Peripheral Neuropathy and Mortality: A Retrospective Cohort Study in the U.K.

BACKGROUND: Folate deficiency may increase the risk of peripheral neuropathy but there is a paucity of data from large prospective studies examining this association. METHODS: Longitudinal analysis of electronic health records in The Health Improvement Network (THIN), a U.K. primary care database including 594,338 patients aged 18-70 years with a folate measurement and without a history of peripheral neuropathy. RESULTS: After a mean follow-up of 3.71 (standard deviation (SD) = 3.14) years, 1949 patients were diagnosed with peripheral neuropathy and 20,679 patients died. In those <40 years, compared to patients with folate ≥13.6 nmol/L, those with folate <6.8 (deficient) and 6.8-13.5 nmol/L (insufficient) had a hazard ratio (HR) for peripheral neuropathy of 1.83 (95% confidence intervals (CI) = 1.16-2.91) and 1.48 (95% CI = 1.04-2.08), respectively. There was no significant association between folate and peripheral neuropathy among those aged 41-70 years. Compared to patients with folate ≥ 13.6 nmol/L, folate <6.8 nmol/L was associated with a greater risk of death among all ages. CONCLUSION: Folate deficiency and insufficiency was associated with a greater risk of peripheral neuropathy among younger patients. This investigation should be replicated in other large datasets and it may be important to monitor peripheral neuropathy incidence after the introduction of mandatory folic acid fortification of flour in the U.K.

Risk of Incident Obstructive Sleep Apnea Among Patients With Type 2 Diabetes.

OBJECTIVE: This study compared the incidence of obstructive sleep apnea (OSA) in patients with and without type 2 diabetes and investigated risk factors for OSA in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: A retrospective cohort study was performed to compare OSA incidence between adult patients with and without type 2 diabetes matched for age, sex, and BMI. Patients with a prevalent OSA diagnosis were excluded. The study cohort was derived from The Health Improvement Network (THIN), a U.K. primary care database, from 1 January 2005 to 31 December 2017. RESULTS: There were 3,110 (0.88%) and 5,968 (0.46%) incident OSA cases identified in the 360,250 exposed and 1,296,489 unexposed patient cohorts, respectively. Adjusted incidence rate ratio (aIRR) of OSA in patients with type 2 diabetes compared with those without was 1.48 (95% CI 1.42-1.55; P < 0.001). In a multivariate regression analysis of patients with type 2 diabetes, significant predictors of OSA were diabetes-related foot disease (1.23 [1.06-1.42]; P = 0.005), being prescribed insulin in the last 60 days (1.58 [1.42-1.75]; P < 0.001), male sex (2.27 [2.09-2.46]; P < 0.001), being overweight (2.02 [1.54-2.64]; P < 0.001) or obese (8.29 [6.42-10.69]; P < 0.001), heart failure (1.41 [1.18-1.70]; P < 0.001), ischemic heart disease (1.22 [1.11-1.34]; P < 0.001), atrial fibrillation (1.23 [1.04-1.46]; P = 0.015), hypertension (1.32 [1.23-1.43]; P < 0.001), and depression (1.75 [1.61-1.91]; P < 0.001). CONCLUSIONS: When considered alongside previous evidence, this study indicates that the association between type 2 diabetes and OSA is bidirectional. In addition to known predictors of OSA, diabetes-related foot disease and insulin treatment were identified as risk factors in patients with type 2 diabetes.

DanteR: an extensible R-based tool for quantitative analysis of -omics data.

MOTIVATION: The size and complex nature of mass spectrometry-based proteomics datasets motivate development of specialized software for statistical data analysis and exploration. We present DanteR, a graphical R package that features extensive statistical and diagnostic functions for quantitative proteomics data analysis, including normalization, imputation, hypothesis testing, interactive visualization and peptide-to-protein rollup. More importantly, users can easily extend the existing functionality by including their own algorithms under the Add-On tab. AVAILABILITY: DanteR and its associated user guide are available for download free of charge at http://omics.pnl.gov/software/. We have an updated binary source for the DanteR package up on our website together with a vignettes document. For Windows, a single click automatically installs DanteR along with the R programming environment. For Linux and Mac OS X, users must install R and then follow instructions on the DanteR website for package installation. CONTACT: rds@pnnl.gov.