Patients with decompensated cirrhosis have typically prescribed a combination of therapeutic and prophylactic medications. Polypharmacy increases the probability of medication errors and drug related problems. Clinical pharmacists are highly effective at identifying, resolving, and preventing clinically important drug-related problems in their patients' care. The objectives of the study were the identification and classification of drug-related problems, as well as the discussion of these problems with health care providers (physicians, pharmacists, and nurses) and patients. Reduce their incidence as effectively as possible and educate all research participants on the significance of following their prescribed drug regimen. Prospective, interventional, clinical study for 80 hospitalized decompensated liver cirrhosis patients was designed in two phases, an observational phase to identify drug related problems and classify them according to the Pharmaceutical Care Network Europe classification version 9.1, and an interventional phase to increase the awareness of patients and the health care providers about those problems and to propose a proper solution for each one. The majority of drug-related problems were attributable to the Effect of drug treatment not optimal in 41.5%, Adverse drug events (possibly) occurring in 41.5 %, and Untreated symptoms or indications in 17%. Causes were Drug dose too high in 30.2%, Patient unintentionally using the drug in the wrong way in 22.6%, and Prescribed drug not available in 13.2%. Omeprazole and lactulose were the most common medications causing problems. Acceptance and full implementation were high and observed in 71.7% of pharmacist interventions while 15.1% of the intervention have no agreement. Significant numbers of Iraqi patients with decompensated liver cirrhosis have drug-related problems, and the use of proton pump inhibitors in too high dose was accountable for a large number of problems. Physicians and clinical pharmacists collaborated exceptionally well
Background: Soft Laser has been advantageous in medical applications and is widely used in clinical practice. It is applied because it doesn’t cause the significant thermal effects or tissue hurt when irradiated. The blood response to low power laser radiation provides information about processes of laser radiation interaction with live creatures. Objective: The aim of the current work was to evaluate the laser-induced changes of in vitro erythrocyte sedimentation rate (ESR), mean corpuscular volume (MCV), and mean corpuscular hemoglobin concentration (MCHC) in patients with breast cancer by irradiating a human blood sample using a green laser and comparing its effects before and after irradiation with the same power density (100mW/c
... Show MoreAsthma is a chronic inflammatory disease of respiratory airways characterized by distinctive history of respiratory symptoms due to variable airflow obstruction which reverses either spontaneously or in response to certain medications. Acetylcholine is a parasympathetic neurotransmitter which plays fundamental roles in the development of persistent asthma. Treatment guidelines recommend using medium doses of inhaled corticosteroids in addition to another controller bronchodilator instead of using high doses inhaled steroid alone for treatment of moderate to severe persistent asthma. The inhaled long acting muscarinic antagonist, tiotropium, was approved recently to control unresponsive asthma to inhaled corticosteroid with or without a long
... Show MoreKE Sharquie, JR Al-Rawi, AA Noaimi, MM Jabir, Iraqi Postgraduate Medical Journal, 2009
S Khalifa E, AR Jamal R, N Adil A, J Munqithe M…, 2009
Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al
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