A novel weighting method to remove bias from within-subject exposure dependency in case-crossover studies

Background Case-crossover studies have been widely used in various fields including pharmacoepidemiology. Vines and Farrington indicated in 2001 that when within-subject exposure dependency exists, conditional logistic regression can be biased. However, this bias has not been well studied. Methods We have extended findings by Vines and Farrington to develop a weighting method for the case-crossover study which removes bias from within-subject exposure dependency. Our method calculates the exposure probability at the case period in the case-crossover study which is used to weight the likelihood formulae presented by Greenland in 1999. We simulated data for the population with a disease where most patients receive a cyclic treatment pattern with within-subject exposure dependency but no time trends while some patients stop and start treatment. Finally, the method was applied to real-world data from Japan to study the association between celecoxib and peripheral edema and to study the association between selective serotonin reuptake inhibitor (SSRI) and hip fracture in Australia. Results When the simulated rate ratio of the outcome was 4.0 in a case-crossover study with no time-varying confounder, the proposed weighting method and the Mantel-Haenszel odds ratio reproduced the true rate ratio. When a time-varying confounder existed, the Mantel-Haenszel method was biased but the weighting method was not. When more than one control period was used, standard conditional logistic regression was biased either with or without time-varying confounding and the bias increased (up to 8.7) when the study period was extended. In real-world analysis with a binary exposure variable in Japan and Australia, the point estimate of the odds ratio (around 2.5 for the association between celecoxib and peripheral edema and around 1.6 between SSRI and hip fracture) by our weighting method was equal to the Mantel-Haenszel odds ratio and stable compared with standard conditional logistic regression. Conclusion Case-crossover studies may be biased from within-subject exposure dependency, even without exposure time trends. This bias can be identified by comparing the odds ratio by the Mantel-Haenszel method and that by standard conditional logistic regression. We recommend using our proposed method which removes bias from within-subject exposure dependency and can account for time-varying confounders.

Accuracy of Flash Glucose Monitoring During Postprandial Rest and Different Walking Conditions in Overweight or Obese Young Adults

Aims: To investigate the accuracy of FreeStyle LibreTM flash glucose monitoring (FGM) relevant to plasma glucose (PG) measurements during postprandial rest and different walking conditions in overweight/obese young adults.Methods: Data of 40 overweight/obese participants from two randomized crossover studies were pooled into four trials: (1) sitting (SIT, n = 40); (2) walking continuously for 30 min initiated 20 min before individual postprandial glucose peak (PPGP) (20iP + CONT, n = 40); (3) walking continuously for 30 min initiated at PPGP (iP + CONT, n = 20); and (4) accumulated walking for 30 min initiated 20 min before PPGP (20iP + ACCU, n = 20). Paired FGM and PG were measured 4 h following breakfast.Results: The overall mean absolute relative difference (MARD) between PG and FGM readings was 16.4 ± 8.6% for SIT, 16.2 ± 4.7% for 20iP + CONT, 16.7 ± 12.2% for iP + CONT, and 19.1 ± 6.8% for 20iP + ACCU. The Bland–Altman analysis showed a bias of −1.03 mmol⋅L–1 in SIT, −0.89 mmol⋅L–1 in 20iP + CONT, −0.82 mmol⋅L–1 in iP + CONT, and −1.23 mmol⋅L–1 in 20iP + ACCU. The Clarke error grid analysis showed that 99.6–100% of the values in all trials fell within zones A and B.Conclusion: Although FGM readings underestimated PG, the FGM accuracy was overall clinically acceptable during postprandial rest and walking in overweight/obese young adults.

Control of Weekly Time Trend in Time-Stratified Case-Crossover Design

Case-crossover designs have become widespread in biomedical investigations of transient associations. However, the most popular reference-selection strategy - the time-stratified scheme - may not be an optimum solution to control systematic bias in case-crossover studies. To prove this, we conducted a time series decomposition for daily ozone records and examined the capability of the time-stratified scheme to control for yearly, monthly, and weekly time trends; and observed its failure on the control for the weekly time trend. To solve this issue, we proposed a new logistic regression approach in which we suggest the adjustment for the weekly time trend. We compared the performance of the proposed with that of the traditional method by simulation. We further conducted an empirical study to explore the performance of the new logistic regression approach in examining potential associations between ambient air pollutants and acute myocardial infarction hospitalizations. The time-stratified scheme provides effective control for yearly and monthly time trends but not of the weekly time trend. Uncontrolled weekly time trends could be the dominant source of systematic bias in time-stratified case-crossover studies. In contrast, the proposed logistic regression approach can effectively minimize systematic bias in a case-crossover study.

The Efficacy of Manual Therapy in Patients with Knee Osteoarthritis: A Systematic Review

Background and objectives: Osteoarthritis (OA) is among the most common degenerative diseases that induce pain, stiffness and reduced functionality. Various physiotherapy techniques and methods have been used for the treatment of OA, including soft tissue techniques, therapeutic exercises, and manual techniques. The primary aim of this systemic review was to evaluate the short-and long-term efficacy of manual therapy (MT) in patients with knee OA in terms of decreasing pain and improving knee range of motion (ROM) and functionality. Materials and Methods: A computerised search on the PubMed, PEDro and CENTRAL databases was performed to identify controlled randomised clinical trials (RCTs) that focused on MT applications in patients with knee OA. The keywords used were ‘knee OA’, ‘knee arthritis’, ‘MT’, ‘mobilisation’, ‘ROM’ and ‘WOMAC’. Results: Six RCTs and randomised crossover studies met the inclusion criteria and were included in the final analysis. The available studies indicated that MT can induce a short-term reduction in pain and an increase in knee ROM and functionality in patients with knee OA. Conclusions: MT techniques can contribute positively to the treatment of patients with knee OA by reducing pain and increasing functionality. Further research is needed to strengthen these findings by comparing the efficacy of MT with those of other therapeutic techniques and methods, both in the short and long terms.

A Novel Weighting Method to Remove Bias from Within-subject Exposure Dependency in Case-crossover Studies

Background:Case-crossover studies have been widely used in various fields including pharmacoepidemiology. Vines and Farrington indicated in 2001 that when within-subject exposure dependency exists, conditional logistic regression can be biased. However, this bias has not been well studied.Methods:We have extended findings by Vines and Farrington to develop a weighting method for the case-crossover study which removes bias from within-subject exposure dependency. Our method calculates the exposure probability at the case period in the case-crossover study which is used to weight the likelihood formulae presented by Greenland in 1999. We simulated data for the population with a disease where most patients receive a cyclic treatment pattern with within-subject exposure dependency but no time trends while some patients stop and start treatment. Finally, the method was applied to real-world data from Japan to study the association between celecoxib and peripheral edema and to study the association between selective serotonin reuptake inhibitor (SSRI) and hip fracture in Australia.Results:When the simulated rate ratio of the outcome was 4.0 in a case-crossover study with no time-varying confounder, the proposed weighting method and the Mantel-Haenszel odds ratio reproduced the true rate ratio. When a time-varying confounder existed, the Mantel-Haenszel method was biased but the weighting method was not. When more than one control period was used, standard conditional logistic regression was biased either with or without time-varying confounding and the bias increased (up to 9.4) when the study period was extended. In real-world analysis with a binary exposure variable in Japan and Australia, the point estimate of the odds ratio (around 2.5 for the association between celecoxib and peripheral edema and around 1.6 between SSRI and hip fracture) by our weighting method was equal to the Mantel-Haenszel odds ratio and stable compared with standard conditional logistic regression. Conclusion:Case-crossover studies may be biased from within-subject exposure, even without exposure time trends. This bias can be identified by comparing the odds ratio calculated by the Mantel-Haenszel method and that by standard conditional logistic regression. Our proposed method will remove bias from within-subject exposure dependency and can account for time-varying confounders.

Accentuated Eccentric Loading is Superior to Traditional Loading for Improving Acute Countermovement Jump Performance in Adult, Resistance-Trained Males

Clinical Scenario: Traditional loading (TL) is a common technique to employ when engaging in countermovement jumps (CMJ). Accentuated eccentric loading (AEL) is a newer modality that is being explored for acute CMJ performance. Focused Clinical Question: In adult, resistance-trained males, will AEL have a superior impact on acute CMJ performance compared to TL? Summary of Key Findings: The literature was searched for studies that examined the influence of AEL on acute CMJ performance compared to a TL protocol. TL was defined as any loading condition that utilized an equivalent resistance during both the eccentric and concentric contractions. Three studies met the inclusion and exclusion criteria, and were identified and included in the critically appraised topic. Each of the 3 studies found that various AEL conditions were either equal to or better than TL when examining subsequent CMJ performance. In no specific CMJ outcome measure was TL deemed to have a greater impact than AEL. Clinical Bottom Line: AEL provides more favorable acute CMJ performance than TL in adult, resistance-trained males. Strength of Recommendation: Consistent findings from 2 randomized crossover studies and one repeated-measured design investigation suggest level 2b evidence to support AEL as an ideal protocol for acute CMJ performance.

High-Protein or Low Glycemic Index Diet—Which Energy-Restricted Diet Is Better to Start a Weight Loss Program?

Background: To date, no crossover studies have compared the effects of high-protein (HP) and low glycemic index (LGI) diets applied as starting energy-restricted diets. Methods: Thirty-five overweight or obese volunteers with sedentary lifestyles aged 41.4 ± 11.0 years, with body mass index (BMI) of 33.6 ± 4.2 kg/m2, without diabetes, completed an 8-week randomized crossover study of an energy-restricted diet (reduction of 30%; approximately 600 kcal/day). The anthropometric parameters, body composition, 24 h blood pressure, and basic metabolic profile were measured at baseline and after completing the two 4-week diets; i.e., the HP (protein at 30% of the daily energy intake) or LGI diet, followed by the opposite diet. All subjects maintained food diaries and attended six counselling sessions with a clinical dietitian. Results: The final weight loss was not significantly different when the HP diet was used first but was associated with a greater loss of fat mass: 4.6 kg (5.8; 3.0 kg) vs. 2.2 (4.5; 0.8); p < 0.025, preserved muscle mass, and reduced LDL-cholesterol. Conclusions: A short-term HP diet applied as a jump-start diet appeared to be more beneficial than an LGI diet, as indicated by the greater fat mass loss, preservation of muscle mass, and better effects on the lipid profile.

Serum Level of Uromodulin as an Early Predictor Marker of Kidney Disorders

BACKGROUND: Metabolic diseases are known to be risk factors of kidney injury. The glycoprotein Uromodulin Tamm-Horsfall protein is a biochemical marker specifically synthesized and secreted by kidney tubular epithelial cells. AIM: The study aimed to use novel biochemical parameters to predict early changes in renal functions and to use natural food supplements to help in the prevention and management of such conditions. METHODS: Crossover studies comparing two interventions trials. Subjects: Seventy obese females were included in this study. They were divided in two groups, first group (34 women) with mean age 45.82 ± 1.51 and mean body mass index (BMI) 35.65 ± 0.68 kg/m2, and second group (36 women) with mean age 49.80 ± 2.27, and mean BMI 37.67 ± 1.59. Intervention: All participants have followed a low caloric balanced regimen (1000–1200 Kcal/day) of the each groups consumed a different specific nutritional supplement composed mainly of whole grains and herbs. All patients were monitored clinically, anthropometrically, dietary 24 h recall and biochemically. RESULTS: After intervention all the recorded anthropometric parameters showed significant decreases at p ≤ 0.05–0.01. The serum uromodulin (sUMOD) increased significantly after intervention in both groups the increments were 15.56 and 9.37%. Numerically creatinine and urea decreased, while creatinine clearance increased. CONCLUSION: Data revealed the importance of using dietary therapy composed of hypocaloric diet with supplements made from whole grains and special herbs in management of obesity and its metabolic disorders. sUMOD proved to be an accurate biochemical marker that showed the kidneys’ response to the management in comparison to using usual diagnostic markers.

A data visualisation method for assessing exposure misclassification in case-crossover studies: the example of tricyclic antidepressants and the risk of hip fracture in older people

Background The case-crossover design is suited to medication safety studies but is vulnerable to exposure misclassification. Using the example of tricyclic antidepressants and the risk of hip fracture, we present a data visualisation tool for observing exposure misclassification in case-crossover studies. Methods A case-crossover study was conducted using Australian Government Department of Veterans’ Affairs claims data. Beneficiaries aged over 65 years who were hospitalised for hip fracture between 2009 and 2012 were included. The case window was defined as 1–50 days pre fracture. Control window one and control window two were defined as 101–150 and 151–200 days pre fracture, respectively. Patients were stratified by whether exposure status changed when control window two was specified instead of control window one. To visualise potential misclassification, each subject’s tricyclic antidepressant dispensings were plotted over the 200 days pre fracture. Results The study population comprised 8828 patients with a median age of 88 years. Of these subjects, 348 contributed data to the analyses with either control window. The data visualisation suggested that 14% of subjects were potentially misclassified with control window one while 45% were misclassified with control window two. The odds ratio for the association between tricyclic antidepressants and hip fracture was 1.18 (95% confidence interval = 0.91–1.52) using control window one, whereas risk was significantly increased (odds ratio = 1.43, 95% confidence interval = 1.11–1.83) using control window two. Conclusions Exposure misclassification was less likely to be present with control window one than with an earlier control window, control window two. When specifying different control windows in a case-crossover study, data visualisation can help to assess the extent to which exposure misclassification may contribute to variable results.