A Comparative Study on the Quality of Life of Leprosy Patients in Kilifi and Kwale Counties in Kenya

Background:Kenya at present is in the post-elimination phase of leprosy having achieved a prevalence of <1 case per 10,000 persons in 1989. In 2019 Kenya notified 163 leprosy patients, highest being in Kilifi and Kwale counties. About a quarter (26%) of the notified leprosy patients had grade 2 disability at the time of diagnosis, this being the most severe form of disability that may indicate a late diagnosis. This study aimed at assessing the quality of life of leprosy patients to guide policies and programs intended to enhance the health and well-being of leprosy patients.Materials and Methods:This was a case-control study conducted in Kilifi and Kwale Counties. For every leprosy index patient enrolled, two controls were identified within the same village to match the case. Descriptive statistics were used to summarise demographic and clinical variables. The World Health Organisation (WHOQOL-BREF) tool was used to measure the quality of life. The tool derived four (4) domains of physical health, psychological status, social relationship, and environmental profile. These were transformed into a scale between 0 to 100 for analysis. The F-test was used to compare mean scores in the four domains between cases and controls. The quality of life among the index cases against their controls was further analysed using conditional logistic regression models.Results: A total of 98 leprosy patients and 167 controls were evaluated for quality of life. On the perception of quality of life, leprosy patients had significantly lower mean transformed scores of 39 (SD 25) versus 49 (SD 25) p= <0.0001 compared to controls. Similarly, index cases had lower health satisfaction scores of 42 (SD 26) compared to controls scoring 61(SD 27) p=<0.001. Overall leprosy patients had statistically significant poorer scores on physical health, psychological health, social relationships and environmental QoL domains. Differences were most remarkable in the psychological domain, with a mean transformed score of 53 (SD 20) versus 68 (SD 16) p= < 0.0001 for controls. The overall quality of life model revealed that leprosy patients who were found to have either diabetes or hypertension enjoyed a better overall quality of life with OR of 10.98 and 1.22 respectively with a p-value <0.00001. Patients with tuberculosis and HIV presented the poorest quality of life with ORs of 0.49 and 0.14 respectively.Conclusion: The quality of life of the leprosy patients was significantly lower than that of the community controls in all the domains. Governments and communities need to prioritize rehabilitation measures such as the provision of artificial limbs, cataract surgery, and social protection disbursements to help leprosy victims improve their quality of life

Accuracy of computer-aided chest X-ray in community-based tuberculosis screening: Lessons from the 2016 Kenya National Tuberculosis Prevalence Survey

Community-based screening for tuberculosis (TB) could improve detection but is resource intensive. We set out to evaluate the accuracy of computer-aided TB screening using digital chest X-ray (CXR) to determine if this approach met target product profiles (TPP) for community-based screening. CXR images from participants in the 2016 Kenya National TB Prevalence Survey were evaluated using CAD4TBv6 (Delft Imaging), giving a probabilistic score for pulmonary TB ranging from 0 (low probability) to 99 (high probability). We constructed a Bayesian latent class model to estimate the accuracy of CAD4TBv6 screening compared to bacteriologically-confirmed TB across CAD4TBv6 threshold cut-offs, incorporating data on Clinical Officer CXR interpretation, participant demographics (age, sex, TB symptoms, previous TB history), and sputum results. We compared model-estimated sensitivity and specificity of CAD4TBv6 to optimum and minimum TPPs. Of 63,050 prevalence survey participants, 61,848 (98%) had analysable CXR images, and 8,966 (14.5%) underwent sputum bacteriological testing; 298 had bacteriologically-confirmed pulmonary TB. Median CAD4TBv6 scores for participants with bacteriologically-confirmed TB were significantly higher (72, IQR: 58–82.75) compared to participants with bacteriologically-negative sputum results (49, IQR: 44–57, p<0.0001). CAD4TBv6 met the optimum TPP; with the threshold set to achieve a mean sensitivity of 95% (optimum TPP), specificity was 83.3%, (95% credible interval [CrI]: 83.0%—83.7%, CAD4TBv6 threshold: 55). There was considerable variation in accuracy by participant characteristics, with older individuals and those with previous TB having lowest specificity. CAD4TBv6 met the optimal TPP for TB community screening. To optimise screening accuracy and efficiency of confirmatory sputum testing, we recommend that an adaptive approach to threshold setting is adopted based on participant characteristics

'If not TB, what could it be?' Chest X-ray findings from the 2016 Kenya Tuberculosis Prevalence Survey

Background: The prevalence of diseases other than tuberculosis (TB) detected during chest X-ray (CXR) screening is unknown in sub-Saharan Africa. This represents a missed opportunity for identification and treatment of potentially significant disease. Our aim was to describe and quantify non-TB abnormalities identified by TB-focused CXR screening during the 2016 Kenya National TB prevalence survey. Methods: We reviewed a random sample of 1140 adult (≥15 years) CXRs classified as “abnormal, suggestive of TB” or “abnormal other” during field interpretation from the TB Prevalence Survey. Each image was read (blinded to field classification and study radiologist read) by two expert radiologists, with images classified into one of four major anatomical categories and primary radiological findings. A third reader resolved discrepancies. Prevalence and 95% confidence intervals of abnormalities diagnosis were estimated. Findings: Cardiomegaly was the most common non-TB abnormality at 259/1123 (23∙1%, 95% CI 20∙6%-25∙6%), while cardiomegaly with features of cardiac failure occurred in 17/1123 (1∙5 %, 95% CI 0.9%-2∙4%). We also identified chronic pulmonary pathology including suspected chronic obstructive pulmonary disease in 3∙2% (95% CI 2∙3%- 4∙4%) and non-specific patterns in 4∙6% (95% CI 3∙5%-6∙0%). Prevalence of active-TB and severe post-TB lung changes was 3∙6% (95% CI 2∙6%- 4∙8%) and 1∙4% (95% CI 0∙8%- 2∙3%) respectively. Interpretation: Based on radiological findings, we identified a wide variety of non-TB abnormalities during population-based TB screening. TB prevalence surveys and active case finding activities using mass CXR offer an opportunity to integrate disease screening efforts

Kenya tuberculosis prevalence survey 2016: Challenges and opportunities of ending TB in Kenya.

BackgroundWe aimed to determine the prevalence of pulmonary TB amongst the adult population (≥15 years) in 2016 in Kenya.MethodA nationwide cross-sectional survey where participants first underwent TB symptom screening and chest x-ray. Subsequently, participants who reported cough >2weeks and/or had a chest x-ray suggestive of TB, submitted sputum specimen for laboratory examination by smear microscopy, culture and Xpert MTB/RIF.ResultThe survey identified 305 prevalent TB cases translating to a prevalence of 558 [95%CI 455-662] per 100,000 adult population. The highest disease burden was reported among people aged 25-34 years (716 [95% CI 526-906]), males (809 [(95% CI 656-962]) and those who live in urban areas (760 [95% CI 539-981]). Compared to the reported TB notification rate for Kenya in 2016, the prevalence to notification ratio was 2.5:1. The gap between the survey prevalence and notification rates was highest among males, age groups 25-34, and the older age group of 65 years and above. Only 48% of the of the survey prevalent cases reported cough >2weeks. In addition, only 59% of the identified cases had the four cardinal symptoms for TB (cough ≥2 weeks, fever, night sweat and weight loss. However, 88.2% had an abnormal chest x-ray suggestive of TB. The use of Xpert MTB/RIF identified 77.7% of the cases compared to smear microscopy's 46%. Twenty-one percent of the survey participants with respiratory symptoms reported to have sought prior health care at private clinics and chemists. Among the survey prevalent cases who reported TB related symptoms, 64.9% had not sought any health care prior to the survey.ConclusionThis survey established that TB prevalence in Kenya is higher than had been estimated, and about half of the those who fall ill with the disease each year are missed