Assessing the reporting of categorised quantitative variables in observational epidemiological studies

Background One aspect to consider when reporting results of observational studies in epidemiology is how quantitative risk factors are analysed. The STROBE guidelines recommend that researchers describe how they handle quantitative variables when analysing data. For categorised quantitative variables, the authors are required to provide reasons and justifications informing their practice. We investigated and assessed the practices and reporting of categorised quantitative variables in epidemiology. Methods The assessment was based on five medical journals that publish epidemiological research. Observational studies published between April and June 2015 and investigating the relationships between quantitative exposures (or risk factors) and the outcomes were considered for assessment. A standard form was used to collect the data, and the reporting patterns amongst eligible studies were quantified and described in the results section. Results Out of 61 articles assessed for eligibility, 23 observational studies were included in the assessment. Categorisation of quantitative exposures occurred in 61% of these studies and reasons informing the practice were rarely provided. Only one article explained the choice of categorisation in the analysis. Transformation of quantitative exposures into four or five groups was common and dominant amongst studies using equally spaced categories. Dichotomisation was not popular; the practice featured in one article. Overall, the majority (86%) of the studies preferred ordered or arbitrary group categories. Other criterions used to decide categorical boundaries were based on established guidelines such as consensus statements and WHO standards. Conclusion Categorisation of continuous variables remains a dominant practice in epidemiological studies. The reasons informing the practice of categorisation within published work are limited and remains unknown in most articles. The existing STROBE guidelines could provide stronger recommendations on reporting quantitative risk factors in epidemiology. Keywords Categorisation - Quantitative or continuous variables - STOBE guidelines – Observational studie

Connective tissue anomalies in patients with spontaneous cervical artery dissection.

OBJECTIVE: To investigate the prevalence of connective tissue abnormalities in patients with spontaneous cervical artery dissections (sCeAD). METHODS: We systematically assessed clinically detectable signs of connective tissue aberration in a series of consecutive patients with sCeAD and of age- and sex-matched patients with ischemic stroke unrelated to CeAD (non-CeAD IS) by a standard examination protocol including 68 items, and performed extensive molecular investigation for hereditary connective tissue disorders in all patients with sCeAD. RESULTS: The study group included 84 patients with sCeAD (mean age, 44.5 ± 7.8 years; 66.7% men) and 84 patients with non-CeAD IS. None of the patients with sCeAD met clinical or molecular diagnostic criteria for established hereditary connective tissue disorder. Connective tissue abnormalities were detected more frequently in the group of patients with sCeAD than in the group of those with non-CeAD IS (mean number of pathologic findings, 4.5 ± 3.5 vs 1.9 ± 2.3; p < 0.001). Eighty-one patients (96.4%) in the sCeAD group had at least one detectable sign compared with 55 patients (66.7%) in the group with non-CeAD IS (p < 0.001). Skeletal, ocular, and skin abnormalities, as well as craniofacial dysmorphisms, were the clinical signs more strongly associated with sCeAD. Signs suggesting connective tissue abnormality were also more frequently represented in patients with sCeAD than in patients with traumatic CeAD (28.6%, p < 0.001; mean number of pathologic findings, 1.7 ± 3.7, p = 0.045). CONCLUSIONS: Connective tissue abnormalities are frequent in patients with sCeAD. This reinforces the hypothesis that systemic aberrations of the connective tissue might be implicated in the pathogenesis of the disease

Serum magnesium and calcium levels in relation to ischemic stroke

Objective: To determine whether serum magnesium and calcium concentrations are causally associated with ischemic stroke or any of its subtypes using the mendelian randomization approach. Methods: Analyses were conducted using summary statistics data for 13 single-nucleotide polymorphisms robustly associated with serum magnesium (n = 6) or serum calcium (n = 7) concentrations. The corresponding data for ischemic stroke were obtained from the MEGASTROKE consortium (34,217 cases and 404,630 noncases). Results: In standard mendelian randomization analysis, the odds ratios for each 0.1 mmol/L (about 1 SD) increase in genetically predicted serum magnesium concentrations were 0.78 (95% confidence interval [CI] 0.69–0.89; p = 1.3 × 10−4) for all ischemic stroke, 0.63 (95% CI 0.50–0.80; p = 1.6 × 10−4) for cardioembolic stroke, and 0.60 (95% CI 0.44–0.82; p = 0.001) for large artery stroke; there was no association with small vessel stroke (odds ratio 0.90, 95% CI 0.67–1.20; p = 0.46). Only the association with cardioembolic stroke was robust in sensitivity analyses. There was no association of genetically predicted serum calcium concentrations with all ischemic stroke (per 0.5 mg/dL [about 1 SD] increase in serum calcium: odds ratio 1.03, 95% CI 0.88–1.21) or with any subtype. Conclusions: This study found that genetically higher serum magnesium concentrations are associated with a reduced risk of cardioembolic stroke but found no significant association of genetically higher serum calcium concentrations with any ischemic stroke subtype

Generic, simple risk stratification model for heart valve surgery

BACKGROUND: Heart valve surgery has an associated in-hospital mortality rate of 4% to 8%. This study aims to develop a simple risk model to predict the risk of in-hospital mortality for patients undergoing heart valve surgery to provide information to patients and clinicians and to facilitate institutional comparisons.METHODS AND RESULTS: Data on 32 839 patients were obtained from the Society of Cardiothoracic Surgeons of Great Britain and Ireland on patients who underwent heart valve surgery between April 1995 and March 2003. Data from the first 5 years (n=16 679) were used to develop the model; its performance was evaluated on the remaining data ( n=16 160). The risk model presented here is based on the combined data. The overall in-hospital mortality was 6.4%. The risk model included, in order of importance (all P < 0.01), operative priority, age, renal failure, operation sequence, ejection fraction, concomitant tricuspid valve surgery, type of valve operation, concomitant CABG surgery, body mass index, preoperative arrhythmias, diabetes, gender, and hypertension. The risk model exhibited good predictive ability (Hosmer-Lemeshow test, P=0.78) and discriminated between high- and low-risk patients reasonably well (receiver-operating characteristics curve area, 0.77). CONCLUSIONS: This is the first risk model that predicts in-hospital mortality for aortic and/or mitral heart valve patients with or without concomitant CABG. Based on a large national database of heart valve patients, this model has been evaluated successfully on patients who had valve surgery during a subsequent time period. It is simple to use, includes routinely collected variables, and provides a useful tool for patient advice and institutional comparisons

Quantification of risk factors for postherpetic neuralgia in herpes zoster patients: A cohort study.

OBJECTIVE: To investigate risk factors for postherpetic neuralgia, the neuropathic pain that commonly follows herpes zoster. METHODS: Using primary care data from the Clinical Practice Research Datalink, we fitted multivariable logistic regression models to investigate potential risk factors for postherpetic neuralgia (defined as pain ≥90 days after zoster, based on diagnostic or prescription codes), including demographic characteristics, comorbidities, and characteristics of the acute zoster episode. We also assessed whether the effects were modified by antiviral use. RESULTS: Of 119,413 zoster patients, 6,956 (5.8%) developed postherpetic neuralgia. Postherpetic neuralgia risk rose steeply with age, most sharply between 50 and 79 years (adjusted odds ratio [OR] for a 10-year increase, 1.70, 99% confidence interval 1.63-1.78). Postherpetic neuralgia risk was higher in women (6.3% vs 5.1% in men: OR 1.19, 1.10-1.27) and those with severely immunosuppressive conditions, including leukemia (13.7%: 2.07, 1.08-3.96) and lymphoma (12.7%: 2.45, 1.53-3.92); autoimmune conditions, including rheumatoid arthritis (9.1%: 1.20, 0.99-1.46); and other comorbidities, including asthma and diabetes. Current and ex-smokers, as well as underweight and obese individuals, were at increased risk of postherpetic neuralgia. Antiviral use was not associated with postherpetic neuralgia (OR 1.04, 0.97-1.11). However, the increased risk associated with severe immunosuppression appeared less pronounced in patients given antivirals. CONCLUSIONS: Postherpetic neuralgia risk was increased for a number of patient characteristics and comorbidities, notably with age and among those with severe immunosuppression. As zoster vaccination is contraindicated for patients with severe immunosuppression, strategies to prevent zoster in these patients, which could include the new subunit zoster vaccine, are an increasing priority

Modeling and analysis of disease and risk factors through learning Bayesian networks from observational data

This paper focuses on identification of the relationships between a disease and its potential risk factors using Bayesian networks in an epidemiologic study, with the emphasis on integrating medical domain knowledge and statistical data analysis. An integrated approach is developed to identify the risk factors associated with patients' occupational histories and is demonstrated using real-world data. This approach includes several steps. First, raw data are preprocessed into a format that is acceptable to the learning algorithms of Bayesian networks. Some important considerations are discussed to address the uniqueness of the data and the challenges of the learning. Second, a Bayesian network is learned from the preprocessed data set by integrating medical domain knowledge and generic learning algorithms. Third, the relationships revealed by the Bayesian network are used for risk factor analysis, including identification of a group of people who share certain common characteristics and have a relatively high probability of developing the disease, and prediction of a person's risk of developing the disease given information on his/her occupational history. Copyright © 2007 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58076/1/893_ftp.pd

Epidemiology of Epilepsy in Nigeria: A Community-Based Study From 3 Sites

BACKGROUND: We determined the prevalence, incidence, and risk factors for epilepsy in Nigeria. METHODS: We conducted a door-to-door survey to identify cases of epilepsy in 3 regions. We estimated age-standardized prevalence adjusted for nonresponse and sensitivity and the 1-year retrospective incidence for active epilepsy. To assess potential risk factors, we conducted a case-control study by collecting sociodemographic and risk factor data. We estimated odds ratios using logistic regression analysis and corresponding population attributable fractions (PAFs). RESULTS: We screened 42,427 persons (age ≥6 years), of whom 254 had confirmed active epilepsy. The pooled prevalence of active epilepsy per 1,000 was 9.8 (95% confidence interval [CI] 8.6-11.1), 17.7 (14.2-20.6) in Gwandu, 4.8 (3.4-6.6) in Afikpo, and 3.3 (2.0-5.1) in Ijebu-Jesa. The pooled incidence per 100,000 was 101.3 (95% CI 57.9-167.6), 201.2 (105.0-358.9) in Gwandu, 27.6 (3.3-128.0) in Afikpo, and 23.9 (3.2-157.0) in Ijebu-Jesa. Children's significant risk factors included febrile seizures, meningitis, poor perinatal care, open defecation, measles, and family history in first-degree relatives. In adults, head injury, poor perinatal care, febrile seizures, family history in second-degree relatives, and consanguinity were significant. Gwandu had more significant risk factors. The PAF for the important factors in children was 74.0% (71.0%-76.0%) and in adults was 79.0% (75.0%-81.0%). CONCLUSION: This work suggests varied epidemiologic numbers, which may be explained by differences in risk factors and population structure in the different regions. These variations should differentially determine and drive prevention and health care responses

Disease-Modifying Antirheumatic Drugs and Risk of Parkinson Disease Nested Case-Control Study of People With Rheumatoid Arthritis

Background and Objectives Epidemiologic studies have suggested a link between rheumatoid arthritis and Parkinson disease (PD). Disease-modifying antirheumatic drugs (DMARDs) might explain this association. The aim of this work was to evaluate the association between DMARDs and risk of PD in persons with rheumatoid arthritis. Methods This nested nationwide case-control study was conducted within the Finnish Parkinson's Disease (FINPARK) cohort, which includes 22,189 Finnish persons with clinically verified PD diagnosed in 1996 to 2015. The cases had recorded diagnosis of PD in the Special Reimbursement Register and had no exclusion diagnoses with symptoms that may be confused with PD within 2 years of PD diagnosis. This study included cases with PD diagnosed during 1999 to 2015 and rheumatoid arthritis diagnosed >3 years before PD. Rheumatoid arthritis was identified from the Finnish Care Register for Health Care and Special Reimbursement Register. Cases were matched with up to 7 controls by age, sex, duration of rheumatoid arthritis, and region. DMARDs were categorized into 5 classes, and data on purchased prescriptions were identified from the Prescription Register since 1995. Associations were studied with conditional logistic regression adjusted for confounders. Results Altogether, 315 cases with PD and 1,571 matched controls were included. The majority (>60%) were women, and the median duration of rheumatoid arthritis on matching date was 11.6 years for controls and 12.6 years for cases. Use of DMARDs was not associated with risk of PD with a 3-year lag period applied between exposure and outcome except chloroquine/hydroxychloroquine, which associated with decreased risk (adjusted odds ratio [OR] 0.74, 95% confidence interval [CI] 0.56-0.97). Other DMARDs, including sulfasalazine, methotrexate, gold preparations, and immunosuppressants, were not associated with PD. Discussion Our results suggest that the lower risk of PD in people with rheumatoid arthritis is not explained by DMARD use because these drugs in general did not modify the risk of PD among persons with rheumatoid arthritis. Association between chloroquine/hydroxychloroquine and lower risk of PD and the possible underlying mechanisms should be further investigated. Classification of Evidence This study provides Class II evidence that in individuals with rheumatoid arthritis using DMARDs, only chloroquine/ hydroxychloroquine was associated with a potentially decreased risk of developing PD (adjusted OR 0.74, 95% CI 0.56-0.97).Peer reviewe