Publications by authors named "Eyasu Habte Tesfamariam"

3 Publications

  • Page 1 of 1

Nurses' attitude towards oral care and their practicing level for hospitalized patients in Orotta National Referral Hospital, Asmara-Eritrea: a cross-sectional study.

BMC Nurs 2020 10;19:63. Epub 2020 Jul 10.

Department of Dialysis, Orotta National Referral Hospital, Asmara, Eritrea.

Background: Effective and routine mouth care is necessary for hospitalized patients as it helps to maintain the health of oral cavity and overall health. However, oral care is often overlooked and not prioritized in daily activity plan of nurses even when oral problems are apparent. Therefore, the aim of this study was to assess nurses' attitude towards oral care and their practicing level for hospitalized patients.

Methods: A cross-sectional study design was conducted in adult medical-surgical department of Orotta hospital from December 2017 to January 2018. Data was collected from all ( = 73) diploma and associate nurses through face to face interview using a pretested and structured questionnaire. Kruskal-Wallis, Mann-Whitney U tests and spearman rank correlation coefficient tools were performed to analyze the data using SPSS (Version 22).

Results: Out of the 79 participants, 73 completed the interview successfully with a response rate of 92.4%. Of the total, 56.2% were diploma nurses and 43.9% were associate nurses. The median attitude score was 68.89/100 (IQR = 48.89). The majority (94.5%) of the nurses agreed that oral cavity assessment is nurse's responsibility and 94.5% reported adequate training is needed to provide quality oral care. On the other hand, the median practice score was 50.00/100 (IQR = 17.86). Majority of the participants (76.7%) did not perform routine oral health assessment. Almost all (98.4%) used gauze and normal saline for oral care. Practice score was significantly different across the various wards ( < 0.001), however, it was not significantly correlated with attitude ( = 0.646).

Conclusions: The participants had poor level of oral care practice to hospitalized patients, nevertheless, they had favourable attitude. Therefore, Orotta National Referral Hospital needs to give further effort to train the nursing staff, ensure the availability of adequate oral care equipment and provide clear guidelines regarding oral care of hospitalized patients.
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July 2020

Maternal Satisfaction and Its Associated Factors towards Spinal Anesthesia for Caesarean Section: A Cross-Sectional Study in Two Eritrean Hospitals.

Anesthesiol Res Pract 2020 21;2020:5025309. Epub 2020 Mar 21.

Department of Epidemiology and Biostatistics, School of Public Health, Asmara College of Health Sciences, Asmara, Eritrea.

Objective: Satisfaction of mothers during caesarean section is an important indicator for measuring quality of obstetric anesthesia. This study aimed to determine mothers' level of satisfaction and the predicting factors of dissatisfaction towards spinal anesthesia during caesarean section.

Methods: Cross-sectional study design was utilized in Orotta Maternity Hospital (OMH) and Sembel Hospital from December 2017 to February 2018, in Asmara, Eritrea. Satisfaction of the mothers was measured using a pretested questionnaire. Bivariate and multivariate logistic regression were utilized to identify predictors of dissatisfaction using SPSS (Version 22.0).

Results: Involvement of mothers in the choice of anesthesia (3.3%) and explanation about the stay at operating theater (10%) were the two least reported items. As per the subscale analysis, the lowest satisfaction was observed for the preoperative assessment (16.7%). Overall, 87.9% of the mothers were satisfied with the spinal anesthetic service. Hospital at which anesthesia was administered ( < 0.001), marital status ( < 0.001), and intraoperative pain ( < 0.001) were significant predictors of dissatisfaction towards spinal anesthesia. Moreover, the rate of refusal to have spinal anesthesia in the future was 12.5%.

Conclusion: Though overall satisfaction can be considered as fair, preoperative assessment is considerably low. Hence, explaining the benefits and risks of the anesthetic techniques as well as considering patient's opinion is very important while deciding the type of anesthesia.
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March 2020

Malaria Risk Stratification and Modeling the Effect of Rainfall on Malaria Incidence in Eritrea.

J Environ Public Health 2019 1;2019:7314129. Epub 2019 Apr 1.

Asmara College of Health Sciences, School of Public Health, Department of Epidemiology and Biostatistics, Asmara, Eritrea.

Background: Malaria risk stratification is essential to differentiate areas with distinct malaria intensity and seasonality patterns. The development of a simple prediction model to forecast malaria incidence by rainfall offers an opportunity for early detection of malaria epidemics.

Objectives: To construct a national malaria stratification map, develop prediction models and forecast monthly malaria incidences based on rainfall data.

Methods: Using monthly malaria incidence data from 2012 to 2016, the district level malaria stratification was constructed by nonhierarchical clustering. Cluster validity was examined by the maximum absolute coordinate change and analysis of variance (ANOVA) with a conservative post hoc test (Bonferroni) as the multiple comparison test. Autocorrelation and cross-correlation analyses were performed to detect the autocorrelation of malaria incidence and the lagged effect of rainfall on malaria incidence. The effect of rainfall on malaria incidence was assessed using seasonal autoregressive integrated moving average (SARIMA) models. Ljung-Box statistics for model diagnosis and stationary -squared and Normalized Bayesian Information Criteria for model fit were used. Model validity was assessed by analyzing the observed and predicted incidences using the spearman correlation coefficient and paired samples -test.

Results: A four cluster map (high risk, moderate risk, low risk, and very low risk) was the most valid stratification system for the reported malaria incidence in Eritrea. Monthly incidences were influenced by incidence rates in the previous months. Monthly incidence of malaria in the constructed clusters was associated with 1, 2, 3, and 4 lagged months of rainfall. The constructed models had acceptable accuracy as 73.1%, 46.3%, 53.4%, and 50.7% of the variance in malaria transmission were explained by rainfall in the high-risk, moderate-risk, low-risk, and very low-risk clusters, respectively.

Conclusion: Change in rainfall patterns affect malaria incidence in Eritrea. Using routine malaria case reports and rainfall data, malaria incidences can be forecasted with acceptable accuracy. Further research should consider a village or health facility level modeling of malaria incidence by including other climatic factors like temperature and relative humidity.
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April 2020