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AIM: This study aimed to: (1) assess the level of moral sensitivity of nurses and the quality of nursing care for patients with COVID-19 in Iran; and (2) identify the relationship between the moral sensitivity of nurses and the quality of nursing care for patients with COVID-19 in Iran. DESIGN: This study was designed as a descriptive, cross-sectional, and correlational research. METHOD: A total of 211 nurses working in four hospitals affiliated with the Hamadan University of Medical Sciences in Iran from December 2021 to April 2022 were selected via the stratified proportional random sampling method. Demographic information, a moral sensitivity questionnaire, and the Good Nursing Care Scale were used for data collection. The data were analysed by SPSS 24 based on descriptive and inferential statistics (Pearson correlation coefficient and multiple regression). RESULTS: Results revealed that 188 of the nurses (89.1%) had a moderate level of moral sensitivity. Furthermore, 160 of the participants (75.8%) reported a relatively low level of the quality of nursing care. The results of the Pearson correlation coefficient test indicated that there was an inverse and significant relationship between the moral sensitivity of nurses and the quality of nursing care (r = -0.528, p < 0.001). The results of multiple regression indicated that the model of moral sensitivity components explained 27.9% of the variance in the quality of nursing care. The components of moral sensitivity, including relation (ß = -0.246, p < 0.001), meaning (ß = -0.188, p = 0.003), conflict (ß = -0.170, p = 0.008), benevolence (ß = -0.153, p = 0.012), and rules (ß = -0.144, p = 0.019) had inverse and significant effects on the quality of nursing care. CONCLUSION: Since higher mean scores of moral sensitivity reflect lower moral sensitivity, it can be stated that with the increase in moral sensitivity of nurses, the quality of nursing care for patients with COVID-19 grows.
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COVID-19 , Nurses , Nursing Care , Humans , Cross-Sectional Studies , Stress, Psychological , Attitude of Health Personnel , MoralsABSTRACT
BACKGROUND: Accurate information on the cost determinants in the COVID-19 patients could provide policymakers a valuable planning tool for dealing with the future COVID-19 crises especially in the health systems with limited resources. OBJECTIVES: This study aimed to determine the factors affecting direct medical cost of COVID-19 patients in Hamadan, the west of Iran. METHODS: This study considered 909 confirmed COVID-19 patients with positive real-time reverse-transcriptase polymerase-chain-reaction test which were hospitalized from 1 March to 31 January 2021 in Farshchian (Sina) hospital in Hamadan, Iran. A checklist was utilized to assess the relationship of demographic characteristics, clinical presentation, medical laboratory findings and the length of hospitalization to the direct hospitalization costs in two groups of patients (patients with hospitalization ≤ 9 days and > 9 days). Statistical analysis was performed using chi-square, median test and multivariable quantile regression model at 0.05 significance levels with Stata 14 software program. RESULTS: The median cost of hospitalization in patients was totally 134.48 dollars (Range: 19.19-2397.54) and respectively 95.87 (Range: 19.19-856.63) and 507.30 dollars (Range: 68.94-2397.54) in patients with hospitalization ≤ 9 days and > 9 days. The adjusted estimates presented that in patients with 9 or less hospitalization days history of cardiovascular disease, wheezing pulmonary lung, SPO2 lower than 90%, positive CRP, LDH higher than 942 U/L, NA lower than 136 mEq/L, lymphosite lower than 20% and patients with ICU experience had significantly positive relationship to the median of cost. Moreover, in patients with more than 9 hospitalization days, history of cardiovascular disease and ICU experience was statistically positive association and age older than 60 years and WBC lower than 4.5 mg/dL had statistically negative relationship to the median of hospitalization cost. CONCLUSION: As the length of hospital stay, which can be associated with the severity of the disease, increases, health systems become more vulnerable in terms of resource utilization, which in turn can challenge their responsiveness and readiness to meet the specialized treatment needs of individuals.
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PURPOSE: Coronavirus increases mortality rate in people with underlying disease. The purpose of the present research was to compare the clinical outcomes in Covid-19 patients with and without underlying diabetes disease using propensity score matching. METHODS: A matched case-control study was conducted on 459 diabetic patients with Covid-19 (case group) and 459 non-diabetic patients with Covid-19 (control group). Matching in two groups was performed using propensity score matching method. The effect of covariates on the clinical outcome of the patients (recovery-death) was assessed using logistic regression and the associations of factors with the patients' survival were determined using Cox proportional hazards regression model. Data were analyzed using R software. RESULTS: The mean (standard deviation) age of patients in the case and control groups were 65.77 (12.2) and 65.8 (12.24), respectively. 196 patients (43%) in the case group, and 249 patients (54%) in the control group were male (with P-value < 0.05). The logistic regression model showed that the variables of age, level of blood oxygen (SpO2), ICU admission, length of hospitalization, cancer and diabetes affected patients' death. Furthermore, the resuts of the Cox regression showed that the variables of age, level of blood oxygen (SpO2), ICU admission,cancer and diabetes were related to survival of the patients. It was found that diabetes was significantly associated with mortality from COVID-19 with odds ratio of 2.88 (95% CI: 1.80-4.69; P < 0.01) and hazard ratio of 1.45 (95% CI: 1.01-2.03; P = 0.05). CONCLUSION: The underlying diabetes significantly increases the mortality among patients with Covid-19, so special care should be taken for this high risk group if they develop Covid-19.
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Purpose Coronavirus increases mortality rate in people with underlying disease. The purpose of the present research was to compare the clinical outcomes in Covid-19 patients with and without underlying diabetes disease using propensity score matching. Methods A matched case–control study was conducted on 459 diabetic patients with Covid-19 (case group) and 459 non-diabetic patients with Covid-19 (control group). Matching in two groups was performed using propensity score matching method. The effect of covariates on the clinical outcome of the patients (recovery-death) was assessed using logistic regression and the associations of factors with the patients' survival were determined using Cox proportional hazards regression model. Data were analyzed using R software. Results The mean (standard deviation) age of patients in the case and control groups were 65.77 (12.2) and 65.8 (12.24), respectively. 196 patients (43%) in the case group, and 249 patients (54%) in the control group were male (with P-value < 0.05). The logistic regression model showed that the variables of age, level of blood oxygen (SpO2), ICU admission, length of hospitalization, cancer and diabetes affected patients' death. Furthermore, the resuts of the Cox regression showed that the variables of age, level of blood oxygen (SpO2), ICU admission,cancer and diabetes were related to survival of the patients. It was found that diabetes was significantly associated with mortality from COVID-19 with odds ratio of 2.88 (95% CI: 1.80–4.69;P < 0.01) and hazard ratio of 1.45 (95% CI: 1.01–2.03;P = 0.05). Conclusion The underlying diabetes significantly increases the mortality among patients with Covid-19, so special care should be taken for this high risk group if they develop Covid-19.