IntroductionAntimicrobial resistance (AMR) is a growing problem globally especially in Sub-Saharan Africa including Kenya. Without any intervention, lower/middle-income countries (LMICs) will be most affected due to already higher AMR levels compared with higher income countries and due to the far higher burden of diseases in the LMICs. Studies have consistently shown that inappropriate use of antimicrobials is the major driver of AMR. To address this challenge, hospitals are now implementing antibiotic stewardship programmes (ASPs), which have been shown to achieve reduced antibiotic usage, to decrease the prevalence of resistance and lead to significant economic benefits. However, the implementation of the guideline is highly dependent on the settings in which they are rolled out. This study, employing an implementation science approach, aims to address the knowledge gap in this area and provide critical data as well as practical experiences when using antibiotic guidelines and stewardship programmes in the public health sector. This will provide evidence of ASP performance and potentially contribute to the county, national and regional policies on antibiotics use.Methods and analysisThe study will be conducted in three geographically diverse regions, each represented by two hospitals. A baseline study on antibiotic usage, resistance and de-escalation, duration of hospital stay, rates of readmission and costs will be carried out in the preimplementation phase. The intervention, that is, the use of antibiotic guidelines and ASPs will be instituted for 18 months using a stepwise implementation strategy that will facilitate learning and continuous improvement of stewardship activities and updating of guidelines to reflect the evolving antibiotic needs.Ethics and disseminationApprovals to carry out the study have been obtained from the National Commission for Science, Technology and Innovation and the Mount Kenya University Ethics Review Committee. The approvals from the two institutions were used to obtain permission to conduct the study at each of the participating hospitals. Study findings will be presented to policy stakeholders and published in peer-reviewed scientific journals. It is anticipated that the findings will inform the appropriate antibiotic use guidelines within our local context.
Background Few studies have investigated risk factor heterogeneity by molecular subtypes in indigenous African populations where prevalence of traditional breast cancer (BC) risk factors, genetic background, and environmental exposures show marked differences compared to European ancestry populations. Methods We conducted a case-only analysis of 838 pathologically confirmed BC cases recruited from 5 groups of public, faith-based, and private institutions across Kenya between March 2012 to May 2015. Centralized pathology review and immunohistochemistry (IHC) for key markers (ER, PR, HER2, EGFR, CK5-6, and Ki67) was performed to define subtypes. Risk factor data was collected at time of diagnosis through a questionnaire. Multivariable polytomous logistic regression models were used to determine associations between BC risk factors and tumor molecular subtypes, adjusted for clinical characteristics and risk factors. Results The median age at menarche and first pregnancy were 14 and 21 years, median number of children was 3, and breastfeeding duration was 62 months per child. Distribution of molecular subtypes for luminal A, luminal B, HER2-enriched, and triple negative (TN) breast cancers was 34.8%, 35.8%, 10.7%, and 18.6%, respectively. After adjusting for covariates, compared to patients with ER-positive tumors, ER-negative patients were more likely to have higher parity (OR = 2.03, 95% CI = (1.11, 3.72), p = 0.021, comparing ≥ 5 to ≤ 2 children). Compared to patients with luminal A tumors, luminal B patients were more likely to have lower parity (OR = 0.45, 95% CI = 0.23, 0.87, p = 0.018, comparing ≥ 5 to ≤ 2 children); HER2-enriched patients were less likely to be obese (OR = 0.36, 95% CI = 0.16, 0.81, p = 0.013) or older age at menopause (OR = 0.38, 95% CI = 0.15, 0.997, p = 0.049). Body mass index (BMI), either overall or by menopausal status, did not vary significantly by ER status. Overall, cumulative or average breastfeeding duration did not vary significantly across subtypes. Conclusions In Kenya, we found associations between parity-related risk factors and ER status consistent with observations in European ancestry populations, but differing associations with BMI and breastfeeding. Inclusion of diverse populations in cancer etiology studies is needed to develop population and subtype-specific risk prediction/prevention strategies.
Background Since the outbreak of the COVID-19 pandemic in Wuhan, China, which has now spread globally, the health systems continue to face challenges in the provision of health care, there is a risk of exposure for both the physicians and the patients. While there is significant progress in the adoption of technology in health care. This study sought to examine the adverse effects of the measures put in place by the government to curb the spread of COVID-19 and come up with an intervention to prevent worse outcomes for chronic conditions. Methods Booking registers for four specialty clinics in Machakos Level 5 Hospital were reviewed to identify patients who missed clinic appointments for follow-up. An automated data collection tool (ODK-collect) was used for data collection. COVID-19 Machakos App was developed to facilitate follow-up and referral of patients to the nearest facilities, capturing and posting of information in real-time to a central database. The mobile App also facilitated the tracking of patients and aided doctors to give feedback on whether the patients reported to the referred facilities. The doctors were also able to capture doctors’ notes on the patients' status while ensuring the confidentiality and privacy of the patients. An interactive dashboard was developed to generate analytics reports and summaries to monitor clinic attendance and trends in the provision of health care during the pandemic period. Results Register data showed 977 (81.5%) out of a total of 1199 patients had missed their scheduled appointments. Among the 977, 746 (76%) were residents of Machakos County and qualified for follow-up. Missed appointments varied by clinic: Cancer Clinic 12 (1.6) %), Diabetes Clinic 212 (28.4%), Hypertension 293 (39.3%), and Paediatrics Clinic 229 (30.7%). Contact was made and follow-up was attempted for 746 patients, of which 453 patients (60.7%) were successful. The follow-up distribution of the 453 patients varied by the clinic as follows: Cancer Clinic 10, Diabetes Clinic 146, Hypertension 185, and Paediatrics Clinic 112. During the follow-up process, 331 patients from diabetes and hypertension clinics were requested to choose a preferred or nearby facility to be referred to. 191 (58%) patients chose Machakos Level 5 Hospital as their preferred facility and 137 (41%) patients chose to be referred to level 3 or 4 hospitals within the County. Three deaths were reported from the medical (Hypertension) clinic. Through the developed App, a total, 82 (60%) patients out of the 137 were reviewed at the referral facilities jointly with a specialist at Machakos Level 5 Hospital. For the duration of the study, some patients reported worse conditions by the time of review after missing scheduled appointments. Conclusions This intervention demonstrated that mobile phone technology could be leveraged to provide specialty treatment services remotely to mitigate against worse patient outcomes. The study...
BackgroundFew studies have investigated risk factor heterogeneity by molecular subtypes in indigenous African populations where prevalence of traditional breast cancer (BC) risk factors, genetic background, and environmental exposures show marked differences compared to European ancestry populations. MethodsWe conducted a case-only analysis of 838 pathologically confirmed BC cases recruited from 5 groups of public, faith-based and private institutions across Kenya between March 2012 to May 2015. Centralized pathology review and immunohistochemistry (IHC) for key markers (ER, PR, HER2, EGFR, CK5-6, and Ki67) was performed to define subtypes. Risk factor data was collected at time of diagnosis through a questionnaire. Multivariable polytomous logistic regression models were used to determine associations between BC risk factors and tumor molecular subtypes, adjusted for clinical characteristics and risk factors.ResultsThe median age at menarche and first pregnancy were 14 and 21 years, median number of children was 3 and breastfeeding duration was 62 months per child. Distribution of molecular subtypes for luminal A, luminal B, HER2-enriched, and Triple Negative (TN) breast cancers was 34.8%, 35.8%, 10.7%, and 18.6%, respectively. After adjusting for covariates, compared to patients with ER positive tumors, ER negative patients were more likely to have higher parity (OR=2.03, 95% CI= (1.11, 3.72), p=0.021, comparing ≥5 to <2 children) and younger age at first pregnancy (ORtrend=0.77, 95% CItrend=0.61, 0.98, Ptrend=0.032, comparing older to younger age). Compared to patients with luminal A tumors, luminal B patients were more likely to have lower parity (OR=0.45, 95% CI= 0.23, 0.87, p=0.018, comparing ≥5 to <2 children); HER2-enriched patients were less likely to be obese (OR=0.36, 95% CI=0.16, 0.81, p=0.013) or older age at menopause (OR=0.38, 95% CI=0.15, 0.997, p=0.049). Body mass index (BMI), either overall or by menopausal status, did not vary significantly by ER status. Overall, cumulative or average breastfeeding duration did not vary significantly across subtypes. Conclusions In Kenya, we found associations between parity-related risk factors and ER status consistent with observations in European ancestry populations, but differing associations with BMI and breastfeeding. Inclusion of diverse populations in cancer etiology studies are needed to develop population and subtype specific risk prediction/prevention strategies.
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