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A Pharmacoeconomics Study for Anticoagulants used for Hospitalized COVID-19 Patients in Al-Najaf Al-Ashraf city –Iraq(Conference Paper )#
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Abstract Background: The novel coronavirus 2 (SARS?CoV?2) pandemic is a pulmonary disease, which leads to cardiac, hematologic, and renal complications. Anticoagulants are used for COVID-19 infected patients because the infection increases the risk of thrombosis. The world health organization (WHO), recommend prophylaxis dose of anticoagulants: (Enoxaparin or unfractionated Heparin for hospitalized patients with COVID-19 disease. This has created an urgent need to identify effective medications for COVID-19 prevention and treatment. The value of COVID-19 treatments is affected by cost-effectiveness analysis (CEA) to inform relative value and how to best maximize social welfare through evidence-based pricing decisions. Objective: compare the clinical outcome and the costs of two anticoagulants (heparin and (enoxaparin)) used to treat hospitalized patients with COVID-19 infection. Patients and method: The study was a retrospective review of medical records of adult, non-pregnant, COVID-19 infected hospitalized patients who had baseline and last outcome measurements at Alamal Epidemiology Center, Al-Najaf city from (Augast 2020 to June 2021). The outcome measures included D-dimer, length of stay (LOS), and mortality rate. Only the cost of the medical treatment was considered in the analysis. The pharmacoeconomics analysis was done in three different cost-effectiveness analysis methods. Microsoft Excel spreadsheet and Statistical Package for the Social Sciences software (SPSS), was used to conduct statistical analysis. Kaplan Meier test was used to compare the mortality rate. T-TEST was used to compare the outcomes of the two groups. Results and discussion: two groups were compared, the first group consists of 72 patients who received heparin, and the second group consists of 72 patients who received enoxaparin. COVID-19 infected patients had a higher abnormal average D-dimer (2534.675 ng/dl). No significant differences between both genders with regards to the basal average D-dimer (males= 2649.95 ng/dl, females= 2374.1mg/dl, P-value>0.05). There was a significant difference between patient's ages 60 years and patients <60. (3177.33 ng/dl, 1763.06 ng/dl, P-value <0.05). It seems that, higher D-dimer levels were associated with a higher mortality rate (died=3166.263 ng/dl, survived= 1729.94 ng/dl, P-value <0.05). Heparin was more effective in decreasing D-dimer levels than enoxaparin which inversely increased the D-dimer levels (-24.4 ng/dl/day, +154.701 ng/dl/day, P-value <0.05). Additionally, heparin was more effective in increasing the survival rate compared to enoxaparin (55% vs, 35%, P-value<0.05). Heparin was associated with a longer duration of stay in hospital than enoxaparin but with no significant difference (13.7 days, 12.3 days, P-value >0.05). Concerning the cost, treatment with heparin cost less than enoxaparin (2.08 U.S $, 9.44 U.S $)/per patient/per day. Conclusion: Originator heparin was a more cost-effective anticoagulant therapy compared to originator enoxaparin, it was associated with a lower cost and better effect, treatment with Heparin resulted in positive INB= 11.3, where a positive result means that heparin is more cost-effective than Enoxaparin. All three methods of pharmacoeconomic analysis decide that heparin was more cost-effective than enoxaparin in treating COVID-19 infected patients.

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 The problem of missing data represents a major obstacle before researchers in the process of data analysis in different fields since , this problem is a recurrent one in all fields of study including social , medical , astronomical and clinical experiments .

The presence of such a problem within the data to be studied may influence negatively on the analysis and it may lead to misleading conclusions , together with the fact that these conclusions that result from a great bias caused by that problem in spite of the efficiency of wavelet methods but they are also affected by the missing of data , in addition to the impact of the problem of miss of accuracy estimation

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