The Role of Antidiabetic Medications on Osteoporosis

Purpose:

Osteoporosis is a condition that causes diminishment of bone density, increasing fracture risk.1 Data has shown that patients with Type I and II diabetes may have an increased risk for comorbid conditions like osteoporosis.2 Bone remodeling and turnover is compromised in diabetic patients, with longer duration, poor glycemic control, and thiazolidinone use for glycemic index control as risk factors for fracture.3,4,5 The purpose of this study was to assess the risk of osteoporosis secondary to the use of three antidiabetic medications: insulin, metformin, or sulfonylureas.

Methods:

The study was a retrospective cross-sectional survey study of 4,910 participants using NHANES data. Exposure was defined as patients taking one of three defined drugs, concomitant osteoporosis identified through self-report or total bone mineral density (BMD) 2.5 standard deviations below average. Inclusion criteria: participants over age 25 reporting a HbA1C, osteoporosis, gender, total BMD, alcohol use or smoking. Outcome assessment defined as incidence of osteoporosis. Covariates for the data included age, gender, alcohol use, smoking, and HbA1C level (%). Multivariate logistic regression was used in determination of the results.

Results:

Utilizing a Chi-square test, results showed that all three of the prespecified medications were not statistically significant for the increase in osteoporosis risk as all carried a p-value greater than 0.05. Additionally, the multivariate logistic regression yielded results of age, smokers, alcohol users, and men as statistically significant. An odds ratio of 1.338 was identified for alcohol users, indicative of osteoporosis risk.

Conclusions:

After survey data was assessed, the majority of patients with osteoporosis had no relationship to diabetes. These results do not align with current data regarding risk factors for osteoporosis. Limitations include, temporality, limited diabetes diagnosis data, recall bias, incomplete medication lists, age, quantified alcohol consumption and smoking quantity. Future studies should include duration of treatment for the medications of interest.

Impact of Arthritis Diagnosis on Serum Creatinine Levels

Purpose:

Arthritis remains one of the leading causes of disability among elderly females in the United States1. Serum creatinine (Scr) can be obtained to assess kidney function. Normal SCr range for men is 0.7-1.3 mg/dL and women is 0.6-1.1 mg/dL2 . Previous literature demonstrated that arthritis can be associated with an increased Scr3,4,5 . The study objective was to assess the impact of arthritis on kidney function by comparing Scr between patients with and without arthritis.

Methods:

We performed a Wilcoxon rank-sum and chi-square test to analyze the covariates and Scr along with a multiple linear regression to assess correlation using the NHANES 2017-2018 data. The primary outcome was Scr, and risk factors included age, gender, race, kidney failure status and recent increase in exercise. Exclusion criteria eliminated patients <20 and ≥80 years-old, not answering for arthritis status, and without data for primary outcome.

Results:

The population consisted of 4,482 patients with a median age of 62 (arthritis) and 44 (without arthritis). At baseline, 6.7% patients with arthritis and 1.9% patients without arthritis had been told they had weak or failing kidneys. The raw comparison showed significant increase in Scr level for patients with arthritis (p=<0.001). However, the multivariable linear regression showed this was not significant when accounting for covariates (p=0.098).

Conclusion:

The study findings suggest that the difference in median Scr between patients with and without arthritis was not significant. Since there are other factors that have effects on Scr and there was a disproportionate patient population between those with arthritis and those without, this data is not applicable to practice. Due to the retrospective analysis, there is no assessment on causality between the exposure, covariates and outcome over time which further limits the relativity of the data.

The Association between Oral Contraceptive Use and Cardiovascular Events in Females with Hypertension

Purpose:

It is known that hypertension and oral hormonal contraceptive use in women are both risk factors for cardiovascular events including stroke and myocardial infarction. The study objective is to assess if there is an association between taking birth control and the frequency of cardiovascular events in the population of females with hypertension, and if it should affect the prescribing of hormonal contraceptives in this population.

Methods:

Data included in this study was collected from 2017-2018 Continuous NHANES Questionnaire Data. A data analysis was run using SPSS to investigate the incidence of cardiovascular events. The study population from the survey data included all females who were ever told that they had high blood pressure. The incidence of cardiovascular events was compared between subjects who answered yes to ever taking birth control and those who answered no. A chi-square analysis was conducted using a P-value significance level of 0.05 to determine if there is statistical significance in the cumulative incidence of the primary outcome.

Results:

The relative risk when comparing cumulative incidence of cardiovascular events between subjects exposed versus not exposed to hormonal contraception is increased by 3.8% with a Pvalue of 0.839, indicating that the results were not statistically significant. Therefore, we accept the null-hypothesis that there is no association between cardiovascular events and hormonal contraceptives in this population.

Conclusions:

The retrospective cohort study findings demonstrate a correlation between use of hormonal contraception and cardiovascular events, although the results were not statistically significant. Therefore, these results should not make an impact on clinical-decision making of prescribing hormonal contraception for females with hypertension. Limitations include a lack of information on the sequence of events including when subjects were told they had hypertension, when they took birth control and when they experienced a cardiovascular event.

Effects of Myocardial Infarction on Glycohemoglobin in Patients with Type II Diabetes

Jason Cambra Pharm.D. Candidate, Katelyn Choiniere Pharm.D. Candidate, Gillian DiIorio Pharm.D. Candidate, Rocco Riccitelli Pharm.D. Candidate, Allegra Sette Pharm.D. Candidate

Purpose:

Type II diabetes mellitus increases the risk of cardiovascular disease as well as morbidity and mortality. This study assesses the effect of a previous myocardial infarction (MI) on current glycemic control in patients with type II diabetes based on current glycohemoglobin values.

Methods:

The NHANES data used in this study was obtained from a cross sectional survey of participants between 2017 and 2018. Patients 50 years or older with type II diabetes mellitus who had a previous MI (n=91) and who have no history of MI (n=537) were included in this study. The exposure of interest was a prior MI, and the outcome of interest was lab-reported glycohemoglobin dichotomized as controlled (≤ 7%) or uncontrolled (>7%). Using logistic regression, an odds ratio was generated to evaluate our exposure of interest. Non-parametric independent t-tests and chi-square tests were used for continuous and categorical variables respectively with a significance level of 0.05.

Results:

A total of 628 patients meeting inclusion criteria were compared. In the group with a prior MI, 54 patients had controlled HbA1c while 37 had uncontrolled HbA1c. The group with no prior MI consisted of 275 patients with controlled and 262 patients with uncontrolled HbA1c. Based on raw data, the difference in glycohemoglobin control for patients with or without a previous MI was not statistically significant with a p-value of 0.151. Logistic regression analysis also showed no statistical significance between prior MI and HbA1c control while accounting for multiple confounders (age, gender, total cholesterol, smoking, and systolic blood pressure) (OR 1.28 [0.782, 1.984] p = 0.356).

Conclusions:

This study found that in patients with type II diabetes older than 50 years, there was no significant difference in glycemic control based on myocardial infarction exposure.

Statin Efficacy Between Dyslipidemic Patients Based on History of Inhaled Substance Use

Ashley Chiarello, Pharm.D. Candidate, Victoria Gugliotti, Pharm.D. Candidate, Kimberly Khan, Pharm.D. Candidate, Krystle Sclafani, Pharm.D. Candidate, Christine Wu, Pharm.D. Candidate

Purpose

Dyslipidemia is an imbalance of cholesterol, low-density lipoprotein (LDL), triglycerides, and high-density lipoprotein in the blood.1 Statins, the first-line therapy for treating dyslipidemia, lower LDL by slowing down cholesterol production.2 Although cigarette smoking is an established risk factor for dyslipidemia, there is no conclusive data regarding the association of statins with smoking e-cigarettes and marijuana.3 This study aimed to assess the efficacy of statin therapy on LDL in patients with the composite outcome of inhaled substance use consisting of smoking tobacco, e-cigarettes, and marijuana.

Methods

The cross-sectional National Health and Nutrition Examination Survey data from 2017-2018 was used to assess the primary outcome of LDL dichotomized as “high” (> 100 mg/dL) or “not high” (≤ 100 mg/dL).4 Patients included in the study had a prescription for rosuvastatin, atorvastatin, lovastatin, pravastatin, or simvastatin for their dyslipidemia. A logistic regression analysis adjusted for multiple covariates (age, gender, BMI, race, current alcohol use, and statin intensity) to generate an odds ratio comparing the exposures of interest, with 95% confidence intervals.

Results

There were 130 participants in the sample size comparing dyslipidemic patients with a history of inhaled substance use (n = 23) and without (n = 107). Patients with a history of inhaled substance use had 0.417 times the risk of high LDL compared to the unexposed group (p = 0.139).

Conclusion

The results suggest that there is no statistically significant difference in statin efficacy on LDL values between the two groups. Causation between the exposure and outcome cannot be determined due to the lack of power in the study and use of cross-sectional design.5 More robust studies must be conducted to conclude whether a history of inhaled substance use affects LDL levels before treatment guidelines are amended.

Comparison of A1C Values Associated with Neuropathy Medications in Patients with Diabetes

Alyssa Christopulos, Pharm.D. Candidate, Henry Karshis Jr. Pharm.D. Candidate, Astrid Kugener Pharm.D. Candidate, Madison Savidge Pharm.D. Candidate, Rebecca Schein PharmD Candidate

Purpose:

Diabetic peripheral neuropathy (DPN) is a common complication in patients with diabetes (70%)1, serving as the leading cause of amputation amongst these individuals.2 First line pharmacotherapy includes anticonvulsants and antidepressants.3 Anticonvulsants inhibit calcium channels, decreasing excitatory neurotransmission.4 Antidepressants inhibit reuptake of serotonin and norepinephrine, enhancing analgesic effects.5 Studies assessing neuropathy medication use in patients with diabetes with a low A1C compared to a high A1C are limited in literature.6 The objective of the study was to determine whether an association exists between A1C levels and use of neuropathy medications in patients with diabetes.

Methods:

A cross-sectional study was designed based on data collected from the 2017-18 National Health and Nutrition Examination Survey. We included participants with a confirmed diabetes diagnosis and an obtained A1C value. The exposure was an A1C > 8% (compared to A1C < 8%), and the primary outcome was whether participants reported taking neuropathy medications. Pearson's Chisquared, independent T-test, and logistic regression were used for analysis.

Results:

The sample size for the analysis included 734 participants, 335 of which had a high A1C. There were no significant differences between the exposure groups in terms of neuropathy prescription treatment. Approximately 8% of patients in each group were on neuropathy medications. Duloxetine (4.9%) gabapentin (2.2%), and amitriptyline (1.5%) were the medications reported. Patients with a low A1C were found to have a positive, yet nonsignificant association with being on neuropathy medications (OR = 1.075, P value = 0.859).

Conclusions:

Findings do not support the causal relationship between A1C levels and increased likeliness of neuropathy treatment. Future research utilizing a cohort study design is indicated to determine whether a stronger causal relationship exists. Study limitations include the inability to determine causation, small sample size, unknown confounders, and recall bias.