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Diabetes mellitus is a major public health issue globally, and type-2 diabetes mellitus is the most prevalent form of this disease. Due to multiple factors, most diabetic patients develop functional disabilities including musculoskeletal complications. To determine the frequency of musculoskeletal complications, the relationship between these complications and different potential variables, and the status of pharmacotherapy management to treat these complications among patients with type-2 diabetes mellitus. It was a cross-sectional study and data was collected through self-administered, face-validated pro forma in the English language in outpatient clinics of two tertiary care hospitals of Multan, Pakistan. Total n = 270 type-2 diabetic patients of both genders were assessed for musculoskeletal complications; n = 126 (46.7%) patients had at least one musculoskeletal complication. The most common manifestations were shoulder capsulitis or frozen shoulder (20.7%), flexor tenosynovitis (10.4%), hand stiffness syndrome (10%), and limited joint mobility (9.6%). A statistically significant association was found between frozen shoulder, limited joint mobility, and hand stiffness syndrome with the duration of diabetes (p value = 0.003, 0.0001), and overall glycemic control (p value = 0.004, 0.001) respectively. Out of 254 complaints, only 42.9% of complaints were receiving pharmacotherapy management. Main outcome measure: overall prevalence of musculoskeletal complications among patients of type-2 diabetes and level of pharmacotherapy management for them. Periarticular region of the joints in the hands and shoulders should be examined whenever diabetic patients present with uncontrolled diabetes, and pharmacotherapy management should be planned for these patients who will improve their quality of life.

Muhammad Nasir Kalam,1 Muhammad Fawad Rasool,2 Faleh Alqahtani,3 Imran Imran,4 Asim Ur Rehman,1 Naveed Ahmed1 1Department of Pharmacy, Quaid-i-Azam University, Islamabad, 45320, Pakistan; 2Department of Pharmacy Practice, Faculty of Pharmacy, Bahauddin Zakariya University, Multan, 60800, Pakistan; 3Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, 11451, Saudi Arabia; 4Department of Pharmacology, Faculty of Pharmacy, Bahauddin Zakariya University, Multan, 60800, PakistanCorrespondence: Naveed AhmedDepartment of Pharmacy, Quaid-i-Azam University, Islamabad, 45320, PakistanTel +92 (51) 90644180Email natanoli@qau.edu.pkMuhammad Fawad RasoolDepartment of Pharmacy Practice, Faculty of Pharmacy, Bahauddin Zakariya University, Multan, PakistanTel +923008639046Email fawadrasool@bzu.edu.pkAim: The study was aimed to understand the underlying causes for the differences in propranolol pharmacokinetics (PK) between healthy and cirrhosis populations by using a systematic whole-body physiologically based pharmacokinetic (PBPK) model-building approach for suggesting model informed propranolol dosing in liver cirrhosis patients with different stages of disease severity.Methods: A whole-body PBPK model was developed by using population simulator PK-Sim® by using reported physicochemical and clinical data for propranolol in healthy and liver cirrhosis populations. The model evaluation was done by visual verification and comparison of PK parameters using their observed/predicted ratios (Robs/pred).Results: The developed model has effectively described the disposition of propranolol after intravenous and oral application in healthy and liver cirrhosis populations. All the model predictions were comparable to the observed clinical data and the Robs/pred for all the PK parameters were within a 2-fold range. A significant increase in plasma concentration of propranolol and decrease in drug clearance was observed in progressive stages of liver cirrhosis. The developed model after evaluation with the reported clinical PK data was used for suggesting model informed propranolol dosing in different stages of liver cirrhosis based on systemic unbound drug concentration.Conclusion: The developed PBPK model has successfully described propranolol PK in healthy and cirrhosis populations after IV and oral administration. The evaluated PBPK propranolol-cirrhosis model can have many implications in predicting propranolol dosing in liver cirrhosis patients with different stages of disease severity.Keywords: PBPK, propranolol, cirrhosis, dose adjustments, drug therapy

Background:Nobel laureate Sir James Black’s molecule, propranolol, still has broad potential in cardiovascular diseases, infantile haemangiomas and anxiety. A comprehensive and systematic review of the literature for the summarization of pharmacokinetic parameters would be effective to explore the new safe uses of propranolol in different scenarios, without exposing humans and using virtual-human modeling approaches.Objective:This review encompasses physicochemical properties, pharmacokinetics and drug-drug interaction data of propranolol collected from various studies.Methods:Clinical pharmacokinetic studies on propranolol were screened using Medline and Google Scholar databases. Eighty-three clinical trials, in which pharmacokinetic profiles and plasma time concentration were available after oral or IV administration, were included in the review.Results:The study depicts that propranolol is well absorbed after oral administration. It has dose-dependent bioavailability, and a 2-fold increase in dose results in a 2.5-fold increase in the area under the curve, a 1.3-fold increase in the time to reach maximum plasma concentration and finally, 2.2 and 1.8-fold increase in maximum plasma concentration in both immediate and long-acting formulations, respectively. Propranolol is a substrate of CYP2D6, CYP1A2 and CYP2C19, retaining potential pharmacokinetic interactions with co-administered drugs. Age, gender, race and ethnicity do not alter its pharmacokinetics. However, in renal and hepatic impairment, it needs a dose adjustment.Conclusion:Physiochemical and pooled pharmacokinetic parameters of propranolol are beneficial to establish physiologically based pharmacokinetic modeling among the diseased population.