Time to Recovery from COVID-19 and Its Predictors in Patients Hospitalized at Tibebe Ghion Specialized Hospital Care and Treatment Center, A Retrospective Follow-Up Study, North West Ethiopia.

Background: Since the end of 2019, the world has been facing a new coronavirus disease 19 (COVID-19), which is considered a global pandemic. COVID-19 is considered a major public health burden due to the uncontrolled morbidity and mortality of the global community. The World Health Organization estimates the recovery time as 2 weeks for patients with mild infection and 3 to 6 weeks for those with serious illnesses. The recovery time and its predictors are not well studied in Ethiopia yet. Therefore, the aim of this study was to estimate time to recovery from COVID-19 and its predictors among COVID-19 patients admitted to Tibebe Ghion Specialized Hospital care and treatment center, North West Ethiopia. Methods: An institution-based retrospective follow-up study was conducted among 452 COVID-19 patients admitted to Tibebe Ghion Specialized Hospital from March 2020 to September 2021. Simple random sampling using a table of random number generators was used to select study units. Data entry and analysis were performed using EpiData 3.1 and Stata version 14, respectively. Bivariable and multivariable Cox proportional hazard analyses were used to identify predictors of recovery time. An AHR at a 5% level of significance was used to identify significant predictors. Results: : Among 452 COVID-19 patients, 437 (88%) were recovered, with a median recovery time of 9 days. Recovery time was significantly related to age (AHR = 0.98; 95% CI = 0.97, 0.99), oxygen saturation (AHR = 0.42; 95% CI = 0.31, 0.56), shortness of breath (AHR = 0.65; 95% CI = 0.47, 0.85), disease severity (moderate (AHR = 0.63; 95% CI = 0.47, 0.85) and severe (AHR = 0.32; 95% CI = 0.22, 0.47)), and comorbidities (AHR = 0.67; 95% CI = 0.53, 0.84). Conclusions and recommendations: The overall median recovery time was 9 days. Older age, low oxygen saturation, shortness of breath, disease severity (moderate and severe), history of comorbidities, and high-level of WBC were predictors of delayed recovery time. On the other hand, corticosteroid use significantly shortens the median recovery time of COVID-19 patients. Thus, patients presented with older age, low oxygen saturation, shortness of breath, moderate and severe COVID-19 disease, comorbidities, and increased WBC need to be closely monitoring and followed up by healthcare providers. In addition, there should be special attention during the administration of corticosteroid.

Time to development of surgical site infection and its predictors among general surgery patients admitted at specialized hospitals in Amhara region, northwest Ethiopia: a prospective follow-up study.

BACKGROUND: Surgical site infection is an infection occurring within 30 days after surgery. It is recently reported that evidence-based information on the specific time when the majority of surgical site infections would develop is a key to early detect the infection as well as to preventing and early intervene against their pressing and fatal complications. Therefore, the current study aimed to determine the incidence, predictors, and time to development of surgical site infection among general surgery patients at specialized hospitals in the Amhara region. METHOD: An institution-based prospective follow-up study was conducted. The two-stage cluster sampling procedure was used. A systematic sampling technique with a K interval of 2 was applied to prospectively recruit 454 surgical patients. Patients were followed up for 30 days. Data were collected using Epicollect5 v 3.0.5 software. Post-discharge follow-up and diagnosis were done by telephone call follow-up. Data were analyzed using STATA™ version 14.0. Kaplan-Meier curve was used to estimate survival time. Cox proportional regression model was used to determine significant predictors. Variables with a P-value less than 0.05 in the multiple Cox regression models were independent predictors. RESULT: The incidence density was 17.59 per 1000 person-day-observation. The incidence of post-discharge Surgical site infection was 70.3%. The majority of surgical site infections were discovered after discharge between postoperative days 9 to 16. Being male (AHR: 1.98, 95% CI: 1.201 - 3.277, diabetes Mellitus (AHR: 1.819, 95% CI: 1.097 - 3.016), surgical history (AHR: 2.078, 95% CI: 1.345, 3.211), early antimicrobial prophylaxis (AHR: 2.60, 95% CI: 1.676, 4.039), American Society of Anesthesiologists score ≥ III AHR: 6.710, 95% CI: 4.108, 10.960), duration of the surgery (AHR: 1.035 95% CI: 1.001, 1.070), Age (AHR: 1.022 95% CI: 1.000, 1.043), and the number of professionals in the Operation Room (AHR: 1.085 95% CI: 1.037, 1.134) were found to be the predictors of time to development of Surgical site infection. CONCLUSION: The incidence of surgical site infection was higher than the acceptable international range. The majority of infections were detected after hospital discharge between 9 to 16 postoperative days. The main predictors of Surgical site infection were Age, Sex, Diabetes Mellitus, previous surgical history, the timing of Antimicrobial prophylaxis, American Society of Anesthesiologists score, pre-operative hospital stay, duration of surgery, and the number of professionals in the operation room. Hence, hospitals should give great emphasis on pre-operative preparation, post-discharge surveillance, modifiable predictors, and high-risk patients, as they found in this study.

Validation of risk prediction for outcomes of severe community-acquired pneumonia among under-five children in Amhara region, Northwest Ethiopia.

BACKGROUND: Globally there are over 1,400 cases of pneumonia per 100,000 children every year, where children in South Asia and Sub-Saharan Africa are disproportionately affected. Some of the cases develop poor treatment outcome (treatment failure or antibiotic change or staying longer in the hospital or death), while others develop good outcome during interventions. Although clinical decision-making is a key aspect of the interventions, there are limited tools such as risk scores to assist the clinical judgment in low-income settings. This study aimed to validate a prediction model and develop risk scores for poor outcomes of severe community-acquired pneumonia (SCAP). METHODS: A cohort study was conducted among 539 under-five children hospitalized with SCAP. Data analysis was done using R version 4.0.5 software. A multivariable analysis was done. We developed a simplified risk score to facilitate clinical utility. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and calibration plot. Bootstrapping was used to validate all accuracy measures. A decision curve analysis was used to evaluate the clinical and public health utility of our model. RESULTS: The incidence of poor outcomes of pneumonia was 151(28%) (95%CI: 24.2%-31.8%). Vaccination status, fever, pallor, unable to breastfeed, impaired consciousness, CBC abnormal, entered ICU, and vomiting remained in the reduced model. The AUC of the original model was 0.927, 95% (CI (0.90, 0.96), whereas the risk score model produced prediction accuracy of an AUC of 0.89 (95%CI: 0.853-0.922. Our decision curve analysis for the model provides a higher net benefit across ranges of threshold probabilities. CONCLUSIONS: Our model has excellent discrimination and calibration performance. Similarly, the risk score model has excellent discrimination and calibration ability with an insignificant loss of accuracy from the original. The models can have the potential to improve care and treatment outcomes in the clinical settings.

Case-control study of determinants of corrective upper eyelid surgery refusals among trachomatous trichiasis patients in Ethiopia.

Background: Repeated infection with Chlamydia trachomatis causes trachomatous trichiasis (TT). Surgery is the main and preferred method of treatment. However, many people decline surgery despite the availability of free services in nearby health facilities. Aimz: To identify the determinants of surgery refusal among TT patients in Ethiopia. Methods: This community-based, case-control study was conducted among 338 cases and 338 controls from 5 October to 17 December 2018. Using systematic random sampling, we selected people who had been operated on (controls) and those who refused surgery (cases) from registration documents and used a pre-tested, interviewer-administered, structured questionnaire for data collection. We used SPSS version 23 to analyse the data and used multivariate logistic regression to identify the determinants. Results: Having witnessed a poor surgical outcome [adjusted odds ratio (aOR): 3.51, 95% CI: 1.94-6.35] and lack of knowledge about TT (aOR: 1.77, 95% CI: 1.18-2.65) increased the refusal rate for surgery. Having trust in the surgeon (aOR: 0.26, 95% CI: 0.15-0.45), knowledge about eyelid surgery (aOR: 0.32, 95% CI: 0.16-0.64), long duration of trichiasis (aOR: 0.50, 95% CI: 0.31-0.79), decision-making via discussion with the family (aOR: 0.29, 95% CI: 0.13-0.64), frequent epilation (aOR: 0.31, 95% CI: 0.17-0.60), and receiving personal advice (aOR: 0.11, 95% CI: 0.04-0.28) reduced refusal rates. Conclusion: Refusing to have TT surgery was significantly related to knowledge about upper eyelid surgery, past surgical outcomes, decision-making capacity, and personal influences. Improved systems for upper eyelid surgery should be established in Ethiopia to better manage, and reduce unfavourable, surgical outcomes, and reduce surgery refusal.