Abstract-Stroke is a neurological disease that occurs when a brain cells die as a result of oxygen and nutrient deficiency. Stroke detection within the first few hours improves the chances to prevent complications and improve health care and management of patients. In addition, significant effect of medications that were used as treatment for stroke would appear only if they were given within the first three hours since the beginning of stroke. A framework has been designed based on data mining techniques on Stroke data set that is obtained from Ministry of National Guards Health Affairs hospitals, Kingdom of Saudi Arabia. A data mining model was built with 95% accuracy. Furthermore, this study showed that patient with the following medical conditions, such as heart diseases (hypertension mainly), immunity diseases, diabetes militias, kidney diseases, hyperlipidemia, epilepsy, or blood (platelets) disorders has a higher probability to develop stroke.
Background Previous studies have suggested that drug pricing could contribute to drug shortages; however, there is limited quantitative assessment of this potential causal association. This retrospective database analysis aimed to investigate the association between drug prices and drug shortage incidents in Saudi Arabia. Methods This was a retrospective database analysis study. Drugs with shortage notifications sent to the Saudi Food and Drug Authority (SFDA) between January 2017 and December 2020 were included. Each drug's foreign-to-Saudi price ratio (FTSPR) was calculated by dividing the mean international price by the Saudi price. Drugs were categorized into three groups based on their FTSPR: Group 1 (FTSPR > 1), Group 2 (FTSPR = 1), and Group 3 (FTSPR < 1). The primary outcome was the ratio of mean counts (mCR) between the three groups, with Group 3 serving as the control group. The analysis was adjusted for the measured confounders using a negative binomial regression model. Results A total of 900 drugs were included in the study, with 348 in Group 1, 345 in Group 2, and 209 in Group 3. The mean count in Group 1 was higher compared to Group 3 (mCR: 1.88; 95% confidence interval [CI] 1.24 to 2.83), while the mean counts between Group 2 and Group 3 were comparable (mCR: 1.39; 95% CI 0.92 to 2.09). Conclusions Our findings indicate an association between drug shortage incidents and higher prices of drugs outside Saudi Arabia. Further studies are needed to explore this causal relationship in different contexts.
Aims: Studies suggested that drug pricing might be a risk factor for drug shortage; however, a few provided a quantitative assessment of this possible causal association. This study aimed to assess whether drug prices are associated with drug shortage incidents. Methods: This was a retrospective database analysis study. Drugs with shortage notifications (one drug per notification) that were sent to the Saudi Food and Drug Authority (SFDA) from Jan/2017 to Dec/2020 by different stakeholders were included in the study. For each drug, the foreign-to-Saudi-price ratio (FTSPR) was calculated (FTSPR= mean international price/Saudi price). Accordingly, drugs were split into three groups: Group 1 (FTSPR >1]), Group 2 (FTSPR =1]), and Group 3 (FTSPR <1]). The primary outcomes were the ratio of mean counts (mCR) between the three groups with Group 3 chosen as a control group. The study outcomes were analyzed using a negative binomial regression model adjusting for the measured confounders. All study analyses were conducted using RSudio Version 1.2.5033. Results: A total of 900 drugs were included (Group 1=348, Group 2=345, Group 3=209). The mean count of Group 1 higher was higher than Group 3 (mCR: 1.88; 95% confidence interval [CI] 1.24 to 2.83), while and mean counts of Group 2 vs. Group 3 were comparable (mCR: 1.39; 95%CI 0.92 to 2.09). Discussion: The results of our study showed that shortage was associated with drugs that are more expensive outside Saudi Arabia. Additional international studies are needed to explore this causal association.
Purpose: Optimal adherence to antidiabetics among patients with type 2 diabetes mellitus has been associated with positive health outcomes; however, studies to assess this adherence in Saudi Arabia are scarce. We aimed to evaluate adherence to antidiabetics using a Saudi population. Methods: This was a multicenter, retrospective cohort study of patients (≥ 18 years old) with type 2 diabetes mellitus who received ≥ 1 antidiabetic between 2015 and 2020. Adherence was estimated using the continuous multiple-interval measure of medication availability (CMA7). A CMA7 cutoff point of ≥ 80% was chosen to define optimal adherence, and the odds of not achieving therapeutic annual HbA1c levels (i.e. ≥ 7%) in the optimal vs. suboptimal adherence groups was assessed using a logistic regression model adjusting for the measured confounders. Results: A total of 36,789 patients were included in the study. The most commonly prescribed regimens were metformin single treatment (n=15,025 [41.6%]) and gliclazide-metformin combination treatment (n=5,667 [15.7%]). The median CMA7 was 70.4%, and only 13,552 (36.9%) patients were adherent to their antidiabetics (CMA7 ≥ 80%). The odds of not achieving therapeutic HbA1c levels one year after the index date were comparable in the optimal vs. suboptimal adherence groups (odds ratio = 0.99, 95% confidence interval 0.92 to 1.05). Conclusions: This study showed that a large proportion of a Saudi population with type 2 diabetes mellitus were non-adherent to their antidiabetic treatments. Future Saudi and regional studies are needed to assess the impact of adherence on HbA1c levels and on cardiovascular outcomes.
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