dc.description.abstract |
Tuberculosis (TB) is one of the infectious diseases of public health concern globally. In
2017, it is estimated that 10 million people developed TB globally. More than 1.3 million
of the TB cases were notified in the African region. During the same period, Kenya
reported 85,188 cases of TB. The research aimed at determining factors associated with
TB treatment outcomes among patients newly diagnosed as Mycobacterium
tuberculosis sputum smear-positive within Nairobi County. A prospective cohort study of
291 patients from 25 health facilities in Nairobi county was conducted between December
2014 and July 2015. Purposive sampling was applied to include facilities with the highest
caseloads of TB. The facilities included public, private and faith-based offering either TB
treatment only or both TB diagnosis and treatment categorized as level II, III and IV
according to Kenya Essential Package for Health classification. The allocation of the
number of study participants to the facilities was done using probability proportional to
size (PPS). All patients who consented to the study were included in the study for the six
month treatment period. Questionnaires were administered within the first three weeks of
treatment and after twelve weeks of treatment. After six months of treatment, TB registers
were reviewed to collect information on treatment outcomes. Questionnaires were
administered to the facility in-charges once during the study period. Double entry of all
the data collected was done. There was validation to check the concordance of the two
data sets. A descriptive analysis of the data was undertaken. Bivariate analysis of patientlevel factors, institutional-level factors and treatment outcomes was conducted using ChiSquare and Fisher’s exact test. Kaplan-Meier estimator was used in determining the
median time to treatment interruption. Survival was analyzed using the Kaplan-Meier
probability of failure estimate. The test for the equality of the survivor functions for the
level of education, use of alcohol, smoking,perceived availability of sufficient Health Care
Workers and nature of facility was done using the log-rank test. Cox regression hazard
analysis was undertaken to determine the predictors of treatment interruption. Statistical
significance was determined by considering a nominal p-value of less than 5% (P< 0.05)
with a 95% confidence level. The highest level of education, affliction with another
chronic disease, access to information on TB, nature of the facility, and level of the facility
according to Kenya Essential Package for Health classification, all exhibited a statistically
significant association with TB treatment outcomes (P<0.05, Fisher’s exact test). Patients
who indicated secondary level as the highest level of education posted lower treatment
success rates when compared with their counterparts who had achieved primary level
education. Cases afflicted by other chronic disease had lower treatment success rates when
compared to those who were not affected. Access to TB information showed an
association with positive treatment outcomes. Patients treated in private-for-profit and
faith-based institutions showed better treatment outcomes compared to those treated in
public facilities. Patients treated in Level II facilities (dispensaries) posted positive
treatment outcomes when compared to those in Level III facilities (Health Centers). A
total of 19 (6.5%) treatment interruptions were observed. The median time to default was
56 [95% CI, 36-105] days. Treatment in a non-public facility [AHR=0.253, 95% CI
(0.0585-1.097)] and facilities perceived to have an adequate number of health care workers to offer Directly Observed Therapy (DOT) [AHR=0.253, 95% CI (0.0919-
0.697)] showed a lower hazard for treatment interruption. Attainment of secondary level
education [AHR=3.42, 95% CI (0.99-11.815)] exhibited a higher hazard rate of treatment
interruption when compared to patients who attained a primary level education. Patientlevel and institutional-level characteristics that exhibited a significant association with
treatment outcomes in this study, should be factored into the treatment plans for new SM+
TB patients in Nairobi County to achieve higher treatment success rates. These variables
should be considered predictors of treatment outcome during TB treatment in Nairobi
County. Non-clinical aspects of health care service delivery influence patient adherence
to TB treatment. Subsequently, the health-seeking behavior of groups considered to be at
high risk for treatment interruption should be incorporated into the design and delivery of
TB treatment. |
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