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Background: Smoking is common in patients of depression and is known to affect response to antidepressants. This study was undertaken to evaluate the effect of smoking on the antidepressant effect of sertraline. Method: Patients with depression were divided into smoker and nonsmoker cohorts and followed up for 8 weeks. Serum sertraline levels were estimated using the high-performance liquid chromatography system. Response to treatment was evaluated with the Hamilton Depression Rating Scale (HAM-D). Results: Serum sertraline levels did not differ between smokers and nonsmokers at 4 and 8 weeks. Nonsmokers responded better to sertraline than smokers after 8 weeks. Adverse drug reaction profile did not vary between the two groups and was not impacted by serum sertraline levels. Nonsmokers showed a greater fall in the HAM-D score than smokers. Conclusion: This study found depression among smokers to be less responsive to sertraline. This was not explained by serum sertraline levels. Treatment of depression in smokers with sertraline might require higher doses and duration, with more frequent reviews.
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Background: Statins are the mainstay for the treatment of dyslipidemia. Recently, rosuvastatin has also been demonstrated to possess analgesic properties in animal studies. The present study has been planned to further confirm the analgesic activity of rosuvastatin, etoricoxib, tramadol, amlodipine, and amitriptyline and study the interaction of rosuvastatin with the above-mentioned analgesics. The objective of the study was to confirm the analgesic activity of rosuvastatin and determine the minimum analgesic dose of rosuvastatin, etoricoxib, tramadol, amlodipine and amitriptyline and to study the analgesic effect of combination of subanalgesic doses of rosuvastatin with sub-analgesic doses of etoricoxib, tramadol, amlodipine, and amitriptyline. Method: After IAEC approval, the study was carried out in albino mice in two phases. In phase I, the analgesic effect of rosuvastatin, etoricoxib, tramadol, amlodipine, and amitriptyline was confirmed by using tail-flick and writhing methods. In phase II, analgesic effect of combinations of subanalgesic dose of rosuvastatin with subanalgesic dose of etoricoxib, tramadol, amlodipine, and amitriptyline was studied. Results: Minimal analgesic dose of rosuvastatin, etoricoxib, tramadol, amlodipine, and amitriptyline was observed as 5, 20, 10, 5, and 10 mg/kg, respectively. In phase II, combination of subanalgesic dose of rosuvastatin 2.5 mg/kg with subanalgesic doses of etoricoxib (10 mg/kg), tramadol (5 mg/kg), amlodipine (2.5 mg/kg), and amitriptyline (5 mg/kg), demonstrated synergistic analgesic activity. Conclusion: Rosuvastatin exerts dose-dependent analgesic activity that is synergistic to that of etoricoxib, tramadol, amlodipine, and amitriptyline. If established in clinical studies as well, this finding can lead to the reduction of analgesic dosing in patients already on statins.
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Background: Ensuring quality, safety and efficacy of all pharmaceuticals is the responsibility of drug regulators. However, healthcare workers should be aware of the legal/regulatory provisions involved. This study was planned to assess and compare the knowledge of various drugs schedules under the Drugs and Cosmetics Act, 1940 amongst medical students, post graduate residents and pharmacists. Methods: A questionnaire was designed based on review of literature and was validated. After obtaining ethical clearance and consent from participants, questionnaire was administered to students undergoing internship/6 th semester/4 th semester, post graduate residents and pharmacy students. Participants' knowledge was assessed based on the percentage of correct responses and the intergroup comparison was done by applying ANOVA test. Results: Overall, nearly half of the participants had poor knowledge about schedule H1. Sixth semester MBBS students had maximum knowledge followed by interns whereas pharmacy students, 4 th semester MBBS students and PG residents had poor knowledge about drug schedules. Conclusion: The study clearly highlights the need for further knowledge dissemination about drug schedules. We recommend that a capsule course be developed especially for post graduate residents and final year pharmacy students.
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Precision medicine is the new age medicine and refers to tailoring treatments to a subpopulation who have a common susceptibility to a particular disease or similar response to a particular drug. Although the concept existed even during the times of Sir William Osler, it was given a shot in the arm with the Precision Medicine Initiative launched by Barack Obama in 2015. The main tools of precision medicine are Big data, artificial intelligence, the various omics, pharmaco-omics, environmental and social factors and the integration of these with preventive and population medicine. Big data can be acquired from electronic health records of patients and includes various biomarkers (clinical and omics based), laboratory and radiological investigations and these can be analysed through machine learning by various complex flowcharts setting up an algorithm for the management of specific subpopulations. So, there is a move away from the traditional "one size fits all" treatment to precision-based medicine. Research in "omics" has increased in leaps and bounds and advancements have included the fields of genomics, epigenomics, proteomics, transcriptomics, metabolomics and microbiomics. Pharmaco-omics has also come to the forefront with development of new drugs and suiting a particular drug to a particular subpopulation, thus avoiding their prescription to non-responders, preventing unwanted adverse effects and proving economical in the long run. Environmental, social and behavioural factors are as important or in fact more important than genetic factors in most complex diseases and managing these factors form an important part of precision medicine. Finally integrating precision with preventive and public health makes "precision medicine" a complete final product which will change the way medicine will be practised in future.
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Precision medicine has brought in many changes to the practise of medicine. The omics-based development of biomarkers and pharmaco-omics-based drug development programmes are evidences for the advancement. However, the field where it has proved to be most useful is in the development of various modalities of treatment in oncology. Various drugs targeting vascular endothelial growth factor, epidermal growth factor, tyrosine kinase receptor and rat sarcoma mutations have come to the forefront proving to be beneficial in many cancers. Some of the classic drugs developed using this concept include trastuzumab, bevacizumab, cetuximab and panitumumab among others. Precision medicine has been put to best use in the COVID-19 pandemic through use of various biomarkers such as IL-6 and c-reactive protein in assessing severity of disease, for development of various therapies and also to judge efficacy of vaccines. Precision medicine is also finding its place in management of infectious diseases, chronic diseases such as asthma, connective tissue diseases, cardiovascular diseases, diabetes and obesity. India has also made its presence felt in the field by launching various initiatives such as the Indian genome project and Indian cancer genome atlas. Numerous challenges still exist to the future of precision medicine such as cost involved, ethics, security of the Big data, merger of various platforms to integrate data and also availability of trained manpower to manage the data and algorithms. This new age medicine is a big step forward for mankind and hopefully it will bring more benefits for both patients and the caregivers in the near future.
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Smoking markedly increases the risk of asbestos-related lung cancer. We conducted a randomized pilot trial of a telephone-based smoking cessation intervention in asbestos workers. Fifty-nine smokers were assigned to either a control or telephone-based smoking cessation treatment group and were followed-up at 6 months. Intent-to-treat analysis revealed a 16.7% quit rate at 6 months for the intervention group compared to 6.9% for the control group (P = 0.25). Treatment-received quit-rates were 33% for the intervention group and 6.9% for the control group (P = 0.05). The intervention group was twice as likely to use smoking cessation medicines and progressed further along the stage of change continuum compared with the control group. Incorporating telephone-based smoking cessation treatment into medical screening activities for asbestos workers is feasible and the intervention is effective in increasing quit rates at 6 months.
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Amianto , Neoplasias Pulmonares/etiología , Enfermedades Profesionales/etiología , Cese del Hábito de Fumar , Fumar/efectos adversos , Adulto , Anciano , Recolección de Datos , Femenino , Humanos , Masculino , Persona de Mediana Edad , Proyectos Piloto , Prevención del Hábito de Fumar , TeléfonoRESUMEN
BACKGROUND: Smoking restrictions provide opportunities to modify smoking behavior. A large insurance company implemented a smoke-free grounds policy at two of their office complexes in January, 2000. METHODS: This cohort study evaluated the impact of the smoke-free grounds policy on abstinence among 128 employees who participated in a tobacco dependence treatment program. RESULTS: The overall quit rate at 6 months was 44.5%. The larger complex showed a trend for higher quit rates compared to the smaller complex (46.5 vs. 28.6%). Post-ban participants had higher quit rates than pre-ban participants (52.4 vs. 43.0%). The probability of abstinence at 6 months follow-up was higher for post-ban compared to pre-ban participants (P = 0.03). Post-ban participants were 80% less likely to relapse than pre-ban participants. Non-quitters decreased their consumption by 6.6 cigarettes/day (39.1% decrease). CONCLUSIONS: A "smoke-free grounds" policy encourages abstinence and may play a significant role in harm reduction among continuing tobacco users.