Statistical testing in medicine is a controversial and commonly misunderstood topic. Despite decades of efforts by renowned associations and international experts, fallacies such as nullism, the magnitude fallacy, and dichotomania are still widespread within clinical and epidemiological research. This can lead to serious health errors (e.g., misidentification of adverse reactions). In this regard, our work sheds light on another common interpretive and cognitive error: the fallacy of high significance, understood as the mistaken tendency to prioritize findings that lead to low p-values. Indeed, there are target hypotheses (e.g., a hazard ratio of 0.10) for which a high p-value is an optimal and desirable outcome. Accordingly, we propose a novel method that goes beyond mere null hypothesis testing by assessing the statistical surprise of the experimental result compared to the prediction of several target assumptions. Additionally, we formalize the concept of interval hypotheses based on prior information about costs, risks, and benefits for the stakeholders (NORD-h protocol). The incompatibility graph (or surprisal graph) is adopted in this context. Finally, we discuss the epistemic necessity for a descriptive, (quasi) unconditional approach in statistics, which is essential to draw valid conclusions about the consistency of data with all relevant possibilities, including study limitations. Given these considerations, this new protocol has the potential to significantly impact the production of reliable evidence in public health.

Statistical testing in medicine is a controversial and commonly misunderstood topic. Despite decades of efforts by renowned associations and international experts, fallacies such as nullism, the magnitude fallacy, and dichotomania are still widespread within clinical and epidemiological research. This can lead to serious health errors (e.g., misidentification of adverse reactions). In this regard, our work sheds light on another common interpretive and cognitive error: the fallacy of high significance, understood as the mistaken tendency to prioritize findings that lead to low p-values. Indeed, there are target hypotheses (e.g., a hazard ratio of 0.10) for which a high p-value is an optimal and desirable outcome. Accordingly, we propose a novel method that goes beyond mere null hypothesis testing by assessing the statistical surprise of the experimental result compared to the prediction of several target assumptions. Additionally, we formalize the concept of interval hypotheses based on prior information about costs, risks, and benefits for the stakeholders (NORD-h protocol). The incompatibility graph (or surprisal graph) is adopted in this context. Finally, we discuss the epistemic necessity for a descriptive, (quasi) unconditional approach in statistics, which is essential to draw valid conclusions about the consistency of data with all relevant possibilities, including study limitations. Given these considerations, this new protocol has the potential to significantly impact the production of reliable evidence in public health.

Statistical testing in medicine is a controversial and commonly misunderstood topic. Despite decades of efforts by renowned associations and international experts, fallacies such as nullism, the magnitude fallacy, and dichotomania are still widespread within clinical and epidemiological research. This can lead to serious health errors (e.g., misidentification of adverse reactions). In this regard, our work sheds light on another common interpretive and cognitive error: the fallacy of high significance, understood as the mistaken tendency to prioritize findings that lead to low p-values. Indeed, there are target hypotheses (e.g., a hazard ratio of 0.10) for which a high p-value is an optimal and desirable outcome. Accordingly, we propose a novel method that goes beyond mere null hypothesis testing by assessing the statistical surprise of the experimental result compared to the prediction of several target assumptions. Additionally, we formalize the concept of interval hypotheses based on prior information about costs, risks, and benefits for the stakeholders (NORD-h protocol). The incompatibility graph (or surprisal graph) is adopted in this context. Finally, we discuss the epistemic necessity for a descriptive, (quasi) unconditional approach in statistics, which is essential to draw valid conclusions about the consistency of data with all relevant possibilities, including study limitations. Given these considerations, this new protocol has the potential to significantly impact the production of reliable evidence in public health.

OBJECTIVES: Amputation is a multifactorial complication in diabetic patients. The aim of this study was to determine the risk factors associated with amputation in patients with diabetic foot ulcers. METHODS: This matched case-control study was conducted based on new cases of amputation from March 2012 to November 2014. We selected new cases who had undergone amputation, and the control group was chosen from the cities or areas where the cases resided. Each case was matched with two controls based on the duration of diabetes and location. Conditional logistic regression was used to evaluate the associations between potential risk factors and amputation. RESULTS: A total of 131 cases were compared with 262 controls. The results of the adjusted model showed that sex (odds ratio [OR], 8.66; 95% confidence interval [CI], 2.68 to 27.91), fewer than two hemoglobin A1c (HbA1c) tests per year (OR, 13.97; 95% CI, 4.97 to 39.26), unsuitable shoes (OR, 5.50; 95% CI, 2.20 to 13.77), smoking (OR, 3.44; 95% CI, 1.45 to 8.13), and body mass index (OR, 1.20; 95% CI, 1.03 to 1.41) were associated with amputation in diabetic patients. CONCLUSIONS: The most important factors associated with amputation were females, irregular monitoring of HbA1c levels, improper footwear, and smoking. Developing educational programs and working to ensure a higher quality of care for diabetic patients are necessary steps to address these issues.
Amputation* ; Body Mass Index ; Case-Control Studies* ; Diabetes Mellitus ; Diabetic Foot* ; Female ; Humans ; Iran* ; Logistic Models ; Risk Factors* ; Shoes ; Smoke ; Smoking ; Ulcer*

OBJECTIVES: Diabetes is a major public health problem that is approaching epidemic proportions globally. Diabetes self-management can reduce complications and mortality in type 2 diabetic patients. The purpose of this study was to examine associations between diabetes self-management and microvascular complications in patients with type 2 diabetes. METHODS: In this cross-sectional study, 562 Iranian patients older than 30 years of age with type 2 diabetes who received treatment at the Diabetes Research Center of the Endocrinology and Metabolism Research Institute of the Tehran University of Medical Sciences were identified. The participants were enrolled and completed questionnaires between January and April 2014. Patients' diabetes self-management was assessed as an independent variable by using the Diabetes Self-Management Questionnaire translated into Persian. The outcomes were the microvascular complications of diabetes (retinopathy, nephropathy, and neuropathy), identified from the clinical records of each patient. A multiple logistic regression model was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) between diabetes self-management and the microvascular complications of type 2 diabetes, adjusting for potential confounders. RESULTS: After adjusting for potential confounders, a significant association was found between the diabetes self-management sum scale and neuropathy (adjusted OR, 0.64; 95% CI, 0.45 to 0.92, p=0.01). Additionally, weak evidence was found of an association between the sum scale score of diabetes self-management and nephropathy (adjusted OR, 0.71; 95% CI, 0.47 to 1.05, p=0.09). CONCLUSIONS: Among patients with type 2 diabetes, a lower diabetes self-management score was associated with higher rates of nephropathy and neuropathy.
Academies and Institutes ; Cross-Sectional Studies ; Endocrinology ; Humans ; Logistic Models ; Metabolism ; Mortality ; Odds Ratio ; Public Health ; Self Care*

OBJECTIVES: Although the effect of physical activity (PA) on the incidence of atrial fibrillation (AF) has been studied, contradictory results have been reported. Such discrepancies may reflect the different effects of various types of PA upon AF, as well as gender interactions. Therefore, we aimed to evaluate the associations of PA types (total, moderate/vigorous, and intentional), as well as walking pace, with AF risk in men and women. METHODS: Using the Multi-Ethnic Study of Atherosclerosis Typical Week Physical Activity Survey, 3 PA measures and walking pace were calculated among 6,487 men and women aged 45-84 years. The incidence of AF over approximately 11 years of follow-up was ascertained. The association of each PA measure and walking pace with AF incidence was estimated using multivariable Cox proportional hazard models. An extended Cox model with Heaviside functions (hv) of time was used to estimate the effects of time-varying covariates. RESULTS: During 11 years of follow-up (49,557 person-years), 242 new AF cases occurred. The incidence rate of AF was 48.83 per 10,000 person-years. The proportional hazard (PH) assumption for total PA among women was not met; hence, we used the hv to calculate the hazard ratio. Total PA in women in the hv2 analysis was negatively associated with AF in all 3 models, although for hv1 no significant association was observed. The PH assumption for walking pace among men was not met, and none of the hv showed a statistically significant association between walking pace and AF in men. CONCLUSIONS: These results suggest that PA is inversely associated with AF in women.
Atherosclerosis* ; Atrial Fibrillation* ; Female ; Follow-Up Studies ; Humans ; Hydrogen-Ion Concentration ; Incidence ; Male ; Motor Activity* ; Proportional Hazards Models ; Survival Analysis* ; Walking

OBJECTIVES: The lower mortality rate of obese patients with heart failure (HF) has been partly attributed to reverse causation bias due to weight loss caused by disease. Using data about weight both before and after HF, this study aimed to adjust for reverse causation and examine the association of obesity both before and after HF with mortality. METHODS: Using the Atherosclerosis Risk in Communities (ARIC) study, 308 patients with data available from before and after the incidence of HF were included. Pre-morbid and post-morbid obesity were defined based on body mass index measurements at least three months before and after incident HF. The associations of pre-morbid and post-morbid obesity and weight change with survival after HF were evaluated using a Cox proportional hazard model. RESULTS: Pre-morbid obesity was associated with higher mortality (hazard ratio [HR], 1.61; 95% confidence interval [CI], 1.04 to 2.49) but post-morbid obesity was associated with increased survival (HR, 0.57; 95% CI, 0.37 to 0.88). Adjusting for weight change due to disease as a confounder of the obesity-mortality relationship resulted in the absence of any significant associations between post-morbid obesity and mortality. CONCLUSIONS: This study demonstrated that controlling for reverse causality by adjusting for the confounder of weight change may remove or reverse the protective effect of obesity on mortality among patients with incident HF.
Atherosclerosis* ; Bias (Epidemiology) ; Body Mass Index ; Heart Failure* ; Heart* ; Humans ; Incidence ; Mortality* ; Obesity* ; Proportional Hazards Models ; Weight Loss

OBJECTIVES: We analyzed dietary patterns using reduced rank regression (RRR), and assessed how well the scores extracted by RRR predicted stroke in comparison to the scores produced by partial least squares and principal component regression models. METHODS: Dietary data at baseline were used to extract dietary patterns using the 3 methods, along with 4 response variables: body mass index, fibrinogen, interleukin-6, and low-density lipoprotein cholesterol. The analyses were based on 5,468 males and females aged 45–84 years who had no clinical cardiovascular disease, using data from the Multi-Ethnic Study of Atherosclerosis. RESULTS: The primary factor derived by RRR was positively associated with stroke incidence in both models. The first model was adjusted for sex and race and the second model was adjusted for the variables in model 1 as well as smoking, physical activity, family and sibling history of stroke, the use of any lipid-lowering medication, the use of any anti-hypertensive medication, hypertension, and history of myocardial infarction (model 1: hazard ratio [HR], 7.49; 95% confidence interval [CI], 1.66 to 33.69; p for trend=0.01; model 2: HR, 6.83; 95% CI, 1.51 to 30.87 for quintile 5 compared with the reference category; p for trend=0.02). CONCLUSIONS: Based primarily on RRR, we identified that a dietary pattern high in fats and oils, poultry, non-diet soda, processed meat, tomatoes, legumes, chicken, tuna and egg salad, and fried potatoes and low in dark-yellow and cruciferous vegetables may increase the incidence of ischemic stroke.
Atherosclerosis* ; Body Mass Index ; Cardiovascular Diseases ; Chickens ; Cholesterol ; Continental Population Groups ; Diet ; Fabaceae ; Fats ; Female ; Fibrinogen ; Humans ; Hypertension ; Incidence ; Interleukin-6 ; Least-Squares Analysis ; Lipoproteins ; Lycopersicon esculentum ; Male ; Meat ; Methods* ; Motor Activity ; Myocardial Infarction ; Oils ; Ovum ; Poultry ; Risk Factors* ; Siblings ; Smoke ; Smoking ; Solanum tuberosum ; Stroke* ; Tuna ; Vegetables

OBJECTIVES: Although the effect of physical activity (PA) on the incidence of atrial fibrillation (AF) has been studied, contradictory results have been reported. Such discrepancies may reflect the different effects of various types of PA upon AF, as well as gender interactions. Therefore, we aimed to evaluate the associations of PA types (total, moderate/vigorous, and intentional), as well as walking pace, with AF risk in men and women.METHODS: Using the Multi-Ethnic Study of Atherosclerosis Typical Week Physical Activity Survey, 3 PA measures and walking pace were calculated among 6,487 men and women aged 45-84 years. The incidence of AF over approximately 11 years of follow-up was ascertained. The association of each PA measure and walking pace with AF incidence was estimated using multivariable Cox proportional hazard models. An extended Cox model with Heaviside functions (hv) of time was used to estimate the effects of time-varying covariates.RESULTS: During 11 years of follow-up (49,557 person-years), 242 new AF cases occurred. The incidence rate of AF was 48.83 per 10,000 person-years. The proportional hazard (PH) assumption for total PA among women was not met; hence, we used the hv to calculate the hazard ratio. Total PA in women in the hv2 analysis was negatively associated with AF in all 3 models, although for hv1 no significant association was observed. The PH assumption for walking pace among men was not met, and none of the hv showed a statistically significant association between walking pace and AF in men.CONCLUSIONS: These results suggest that PA is inversely associated with AF in women.
Atherosclerosis ; Atrial Fibrillation ; Female ; Follow-Up Studies ; Humans ; Hydrogen-Ion Concentration ; Incidence ; Male ; Motor Activity ; Proportional Hazards Models ; Survival Analysis ; Walking

OBJECTIVES: We analyzed dietary patterns using reduced rank regression (RRR), and assessed how well the scores extracted by RRR predicted stroke in comparison to the scores produced by partial least squares and principal component regression models.METHODS: Dietary data at baseline were used to extract dietary patterns using the 3 methods, along with 4 response variables: body mass index, fibrinogen, interleukin-6, and low-density lipoprotein cholesterol. The analyses were based on 5,468 males and females aged 45–84 years who had no clinical cardiovascular disease, using data from the Multi-Ethnic Study of Atherosclerosis.RESULTS: The primary factor derived by RRR was positively associated with stroke incidence in both models. The first model was adjusted for sex and race and the second model was adjusted for the variables in model 1 as well as smoking, physical activity, family and sibling history of stroke, the use of any lipid-lowering medication, the use of any anti-hypertensive medication, hypertension, and history of myocardial infarction (model 1: hazard ratio [HR], 7.49; 95% confidence interval [CI], 1.66 to 33.69; p for trend=0.01; model 2: HR, 6.83; 95% CI, 1.51 to 30.87 for quintile 5 compared with the reference category; p for trend=0.02).CONCLUSIONS: Based primarily on RRR, we identified that a dietary pattern high in fats and oils, poultry, non-diet soda, processed meat, tomatoes, legumes, chicken, tuna and egg salad, and fried potatoes and low in dark-yellow and cruciferous vegetables may increase the incidence of ischemic stroke.
Atherosclerosis ; Body Mass Index ; Cardiovascular Diseases ; Chickens ; Cholesterol ; Continental Population Groups ; Diet ; Fabaceae ; Fats ; Female ; Fibrinogen ; Humans ; Hypertension ; Incidence ; Interleukin-6 ; Least-Squares Analysis ; Lipoproteins ; Lycopersicon esculentum ; Male ; Meat ; Methods ; Motor Activity ; Myocardial Infarction ; Oils ; Ovum ; Poultry ; Risk Factors ; Siblings ; Smoke ; Smoking ; Solanum tuberosum ; Stroke ; Tuna ; Vegetables