Departments of Statistics

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Start date: 2023Subject: search.filters.subject.survival analysis

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    SURVIVAL ANALYSIS OF TIME TO RECOVERY OF ADIMTTED COVID-19 PATIENTS: IN HAWASSA UNVERCITY REFERAL AND COMPREHENSIV HOSPITAL TEREATMENT CENTER.
    (HAWASSA UNIVERSITY, 2023-06) AMANUEL MERDIKYOS NANA
    Corona virus is one of the major pathogens that primarily target the human respiratory system, which started in Wuhan, China in December 2019, has emerged as a global health and economic security threat with an overwhelming growing incidence worldwide. When the World Health Organization (WHO) declared the disease a global public health emergency, different stakeholders stepped up efforts to convince the world that the disease is a serious problem that needs strong containment measures. The main objective of the study is to identify the determinant risk factors for the recovery of corona virus(covid-19) patients. A study population of 826 total Covid-19 Patients that had been treated at Hawassa University Comprehensive and Referral hospital from September 20, 2013 to January 20, 2014 E.C was included in the study. Descriptive statistics and Kaplan-Meier survival curves were used to estimate and compare the recovery time of corona virus (covid-19) patients among different categorical characteristics of the patients. We used survival time model to analyze the data. The Weibull regression model better fits the recovery time of corona virus (covid-19) than the exponential, log-logistic model and log-normal model. The result showed that out of a total of 826 corona virus (covid-19) patients considered total recovery are 637(77.12%) recovered from covid-19. From the result severity (HR=0.932, p value=0.014), Co-morbidty(HR=0.89,p-value=0.038), other pains out of covid-19(HR=0.7918, P-value=0.006), shortness of breath (HR=0.83,p-value=0.025), severe headache (HR=0.843, p value=0.034) and Age (HR=0.8948, p-value=0.000) were the significant factors for the corona virus(covid-19) patients using Weibull regression model. The model showed that the major factors that affect the recovery time of corona-virus (covid-19) and see the associations factors among patients. Patient’s comorbidities have a major impact on CVID-19; So, health profession should close follow up is required for client admitted with comorbidity and create great awareness about the risk factors the corona virus (covid-19).
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    MODELING TIME TO LOSS FOLLOW-UP AMONG WOMEN UNDER BREAST CANCER PATIENTS AT HAWASSA UNIVERSITY COMPREHENSIVE SPECIALIZED HOSPITAL: APPLICATION OF COMPETING RISK MODEL
    (HAWASSA UNIVERSITY, 2025-03) TSEGISHET TEMESGEN
    Incomplete breast cancer treatment poses a significant challenge for breast cancer programs. This study aims to assess risk factors for treatment discontinuation and loss to follow-up among breast cancer patients at Hawassa University Comprehensive Specialized Hospital, considering death as a competing risk event. This study used all four year data of 463 breast cancer patients under follow up between January 2020 and December 2023. Descriptive analysis and cumulative incidence survival curve evaluations were conducted in the presence of competing risks. Univariate and Multivariate cause-specific and sub-distribution hazard analyses examined the factors associated with loss to follow-up, with death as a competing event. Out of 463 breast cancer patients recorded, 96 (20.73%) were loss to follow up, 121(26.13%) were died and 246 (53.13%) censored during the follow up. The cause-specific hazard and sub-distribution hazard models revealed that age, place of residence, types of Treatment, Stage of cancer, has non communicable disease, performance status, marital status, distance, experienced chemotherapy, experienced radiotherapy, expected adverse effect, histologic grade were the significant risk factor associated with time to loss follow up treatment. Patients with non-communicable disease had 1.846 and 2.8589 times higher risk of losing follow up compared to patients without non communicable disease comorbidities (CSHR : 1.846(0.56,2.27859))and (SDHR2.8589(0.567,4.3006)) respectively. Distance patients greater than 100km have 1.954 and 201times high risk of lost follow up compare to distance less than 100km (CSHR:2.011(0.67,2.52991) and SDHR: 1.954(0.623,6.122)). The findings showed that the estimates of the covariates effects were different for the two hazard models. This study conclude that breast cancer patients with non-communicable diseases, those residing far from the treatment center, experiencing adverse effects during follow-up, having advanced cancer stages, and being aged 60 years and older are at a higher risk of loss to follow-up. These findings highlight the critical need for Targeted interventions are essential to enhance patient retention and prevent treatment discontinuation. Finally this study recommended that the hospital authorities to give attention to patients those who are distant from Hospital, had Has NCD Comorbidities, Experienced Advert Effect at follow up and older patients.