| dc.description.abstract | The global, regional, and national burden of kidney diseases (acute kidney injury and chronic kidney disease) are attributed to impaired kidney function. The birth and death registry office in Kakamega County has recorded increased morbidity and mortality attributed to acute kidney injury (AKI) and chronic kidney disease (CKD). Most of the studies done in Kenya were on the prevalence of AKI and CKD among the population that are in Nairobi and Nyeri. The findings of this study were the first of its kind in Kenya on the survival analysis of AKI and CKD patients undergoing haemodialysis. The broad objective of this study was to determine the factors influencing survival in hemodialysis patients in Kakamega County general teaching and referral hospital (KCGT&RH). The specific objectives were to determine the demographic characteristic influencing the survival of patients undergoing hemodialysis, to establish the renal biochemical parameters as a survival predictor of patients undergoing hemodialysis, and to evaluate the prognostic factors as a survival indicator of patients undergoing hemodialysis in the renal unit, at KCGT&RH. This was hospital-based retrospective cohort study where records from the renal unit were reviewed from December 2021 to January 2015. Approval to conduct the study was obtained from the Secretary of Eastern Africa, Baraton (UEAB) Research Ethics Committee. Permit to conduct the study was also be obtained from National Commission for Science, Technology, and Innovation (NACOSTI). The clinical chemistry autoanalyzer Olympus 640 (Olympus Diagnostica GmbH, Hamburg, Germany) was used for measuring renal biochemical parameters and Huma Count 5D was used for estimating the Hb levels. The statistical package for social sciences (SPSS) version 23 was used for cleaning of data and analysis. The total number of 174 cases that had CKD and 69 cases diagnosed to have AKI were recruited and studied. Descriptive statistics were used to present frequency and proportion for the categorical variables. Inferential statistics involved the binary logistic regression analysis to establish the relationship between demographic characteristics (age and gender) and survival of both AKI and CKD patients. Whereas multinomial logistic regression was used to determine relationship between the types of comorbidities, number of comorbidities and survivals status of AKI and CKD patients. To estimate the survival functions, Kaplan Meier analysis was used, and Cox-proportional hazard regression analysis was also used to identify independent predictors and prognostic of time to death. The study was able to perform a crude and adjusted hazard ratios with a confidence interval of 95%, and p-values of less than 0.05 were used to declare the presence of statistically significant. The demographic characteristic of AKI patients showed that 33 (47.8%) were males and 36 (52.2%) Females, 36 (52.2%) were 18 – 33 years and 33 (47.8%) above 33 years whereas CKD patients showed that 99 (56.9%) were males, 75 (43.1%) Females and 33 (19%) were 18 – 33 years and 14 1(81%) above 33 years. Majority 64.03% (89) of the patients with CKD died in less than one month, 27.34% (38) died between one to six months and 8.63% (12) died > six months after the clinical diagnosis despite being on hemodialysis. The results showed statistically significant relationship between survival status and time-to-event at a p value of < 0.0001 at 1 df with a 95% CI of 0.055 – 0.218. Majority 55.56% (10) of the AKI patients died in less than one month and 44.44% (8) died > one month after clinical diagnosis despite being on hemodialysis. The results showed no statistically significant relationship between survival status and time of event at a p value of 0.923 at 1 df with a 95% CI of 0.357 – 3.112. Potassium levels were a significant (p value 0.038) parameter that acted as a survival predictor of AKI patients. Prognostic factors did not significantly influence the survival of AKI patients whereas in CKD patients it was observed that the predictors and prognostic factors significantly (p value <0.05) influenced their survival. | en_US |
