-Purpose: Concomitant use of some non-Aspirin nonsteroidal anti-inflammatory drugs (NANSAIDs) reduces the extent of platelet aggregation of Aspirin (acetylsalicylic acid). This is while many observational studies and clinical trials suggest that Aspirin reduces cardiovascular (CV) risk attributed to the use of NANSAIDs. Thus, the therapeutic outcome of the interaction needs to be assessed. Methods: We searched various databases up to October 2017 for molecular interaction studies between the drugs and long-term clinical outcomes based on randomized clinical trials and epidemiological observations that reported the effect estimates of CV risks (OR, RR or HR; 95% CI) of the interacting drugs alone or in combinations. Comparisons were made between outcomes after Aspirin alone, NANSAIDs alone and Aspirin with naproxen, ibuprofen, celecoxib, meloxicam, diclofenac or rofecoxib. Results: In total, 32 eligible studies (20 molecular interactions studies and 12 observational trials) were found. Conflicting in vitro/in vivo/ex vivo platelet aggregation data were found for ibuprofen, naproxen and celecoxib. Nevertheless, for naproxen, the interaction at the aggregation level did not amount to a loss of cardioprotective effects of Aspirin. Similarly, for ibuprofen, the results overwhelmingly suggest no negative clinical CV outcomes following the combination therapy. Meloxicam and rofecoxib neither interacted with Aspirin at the level of platelet aggregation nor altered clinical outcomes. The clinical outcomes data for celecoxib and diclofenac are in conflict. Conclusion: Aspirin appears to maintain its cardioprotective effect in the presence of naproxen, ibuprofen, meloxicam and rofecoxib. The limited available data suggest that the effect of interaction at the platelet aggregation level may dissipate shortly, or the reduced platelet aggregation yielded by the interaction may be sufficient for cardioprotection; i.e., no need for near complete aggregation. In addition, cardioprotective effect of Aspirin, despite reduced platelet aggregation caused by NANSAIDs, may be through its involvement in other mechanisms such as the renin-angiotensin system and/or metabolism of arachidonic acid to biologically active compounds mediated by cytochrome P450.
Enterprises rely more and more on well-qualified and highly specialized IT professionals. Although the increasing availability of IT jobs is a good indicator for IT graduates, they nonetheless may find themselves confused about the most appropriate career for their future. In this paper, a recommendation system called CareerRec is proposed, which uses machine learning algorithms to help IT graduates select a career path based on their skills. CareerRec was trained and tested using a dataset of 2255 employees in the IT sector in Saudi Arabia. We conducted a performance comparison between five machine learning algorithms to assess their accuracy for predicting the best-suited career path among 3 classes. Our experiments demonstrate that the XGBoost algorithm outperforms other models and gives the highest accuracy (70.47%).
Background Potassium balance in heart failure is affected by many factors including neurohormonal mechanisms and drugs used in its management. Renin–angiotensin–aldosterone system inhibitor therapies are part of heart failure therapy and have been associated with increase the risk of hyperkalemia. Currently, there are limited data on the prevalence and risk factors of hyperkalemia in heart failure patients who received spironolactone as an add-on to standard therapy which include Angiotensin-Converting Enzyme Inhibitors (ACEIs) or Angiotensin II receptor blockers (ARBs). The objective of this study is to identify Incidence and determine of hyperkalemia risk factors among heart failure patients who have been using spironolactone. Methods This is a retrospective chart review, from March 1, 2016 to March 31, 2019 conducted at King Abdulaziz Medical City-Riyadh. All heart failure patients with age more than 18 year who are using spironolactone were included and we excluded if they had any of the following criteria: (1) end stage renal disease on dialysis; (2) cancer; (3) history of hyperkalemia. A data collection sheet was used to collect demographics (e.g., age, gender, weight, ejection fraction, and baseline potassium), comorbidities (e.g., chronic kidney disease, and diabetes), visit history (dose of spironolactone, hyperkalemia incidence, time to the event, medication that was patient on include (ACEI, ARB, digoxin, furosemide, beta-blockers, and potassium supplements), average potassium level, average creatinine, and average BNP). An Excel-based tool (Microsoft® Excel; Version 2018) was used for systematic data sampling and analysis. The study was approved by Institutional Review Board. Results A total of 349 patients met the inclusion criteria. 43% of patients were men while 57% were women. The mean age of patients was 64.87 ± 14.02 years. The mean baseline of potassium before start spironolactone were 4.34 ± 3.45 mmol/L. Hyperkalemia were assessed with different dose of spironolactone (12.5 mg, 25 mg, 50 mg). 161 patients were received 12.5 mg spironolactone, 40% of those patients who had incidence of hyperkalemia. 62% of those who developed hyperkalemia were on ACEI, 28% on ARB, 14% on potassium supplements. 263 patients were received 25 mg spironolactone, 47% of patients had incidence of hyperkalemia. 49% of those who developed hyperkalemia were on ACEI, 31% on ARB, and 22% on potassium supplements. 17 patients were received 50 mg spironolactone, 53% of patients had incidence of hyperkalemia. 44% of those who developed hyperkalemia were on ACEI, 22% on ARB, and 22% on potassium supplements. Conclusion Our study showed that half of heart failure patients who used spironolactone developed hyperkalemia. The majority of patients who developed hyperkalemia were either on ACEIs or ARBs. Spironolactone dosing of 50 mg was associated with highest incidence of hyperkalemia. Further study with a larger sample size is required to clarify and confirm our study findings.
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