1
|
Mwenda V, Mwangi M, Gathecha G, Kibachio J, Too R, Gura Z, Temmerman M. Factors associated with late diagnosis of cervical cancer at two national referral hospitals, Kenya 2017: A case control study. Gynecol Oncol Rep 2024; 52:101355. [PMID: 38500641 PMCID: PMC10945120 DOI: 10.1016/j.gore.2024.101355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 11/01/2023] [Accepted: 02/27/2024] [Indexed: 03/20/2024] Open
Abstract
Background Cervical cancer is the leading cause of cancer mortality among women in Kenya. Two thirds of cervical cancer cases in Kenya are diagnosed in advanced stages. We aimed to identify factors associated with late diagnosis of cervical cancer, to guide policy interventions. Methods An unmatched case control study (ratio 1:2) was conducted among women aged ≥ 18 years with cervical cancer at Kenyatta National and Moi Teaching and Referral Hospitals. We defined a case as patients with International Federation of Gynecology and Obstetrics (FIGO) stage ≥ 2A and controls as those with stage ≤ 1B. A structured questionnaire was used to document exposure variables. We calculated adjusted odds ratio (aOR) to identify any associations. Results We enrolled 192 participants (64 cases, 128 controls). Mean age 39.2 (±9.3) years, 145 (76 %) were married, 77 (40 %) had primary level education, 168 (88 %) had their first pregnancy ≤ 24 years of age, 85 (44 %) were > para 3 and 150 (78 %) used contraceptives. Late diagnosis of cervical cancer was associated with cost of travel to cancer centres > USD 6.1 (aOR 6.43 95% CI [1.30, 31.72]), age > 50 years (aOR 4.71; 95% CI [1.18, 18.80]), anxiety over cost of cancer care (aOR 5.6; 95% CI [1.05, 32.72]) and ultrasound examination during evaluation of symptoms (aOR 4.89; 95% CI [1.07-22.42]). Previous treatment for gynecological infections (aOR 0.10; 95% CI [0.02, 0.47]) was protective against late diagnosis. Conclusion Cost of seeking care and the quality of the diagnostic process were important factors in this study. Decentralization of care, innovative health financing solutions and clear diagnostic and referral algorithms for women presenting with gynecological symptoms could reduce late-stage diagnosis in Kenya.
Collapse
Affiliation(s)
- Valerian Mwenda
- Department of Non-Communicable Diseases, Ministry of Health, Nairobi, Kenya
| | - Martin Mwangi
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Nairobi, Kenya
| | - Gladwell Gathecha
- Department of Non-Communicable Diseases, Ministry of Health, Nairobi, Kenya
| | - Joseph Kibachio
- Department of Non-Communicable Diseases, Ministry of Health, Nairobi, Kenya
| | - Robert Too
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Nairobi, Kenya
- School of Public Health, Moi University, Eldoret, Kenya
| | - Zeinab Gura
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Nairobi, Kenya
| | - Marleen Temmerman
- Department of Obstetrics and Gynaecology, Aga Khan University Hospital, Nairobi, Kenya
| |
Collapse
|
2
|
Mwenda V, Odeny L, Mohamed S, Gathecha G, Kendagor A, Kiptui D, Jaguga F, Mugi B, Mithi C, Okinda K, Mwai D, Njuguna D, Awuor W, Kitonyo-Devotsu R, Ong’ang’o JR. Prevalence, patterns, and factors associated with tobacco use among patients with priority tobacco related illnesses at four Kenyan national referral hospitals, 2022. PLOS Glob Public Health 2023; 3:e0002002. [PMID: 37948351 PMCID: PMC10637644 DOI: 10.1371/journal.pgph.0002002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 10/13/2023] [Indexed: 11/12/2023]
Abstract
Tobacco use is a risk factor for many chronic health conditions. Quantifying burden of tobacco use among people with tobacco-related illnesses (TRI) can strengthen cessation programs. This study estimated prevalence, patterns and correlates of tobacco use among patients with TRI at four national referral hospitals in Kenya. We conducted a cross-sectional study among patients with five TRI (cancer, cardiovascular diseases, cerebrovascular disease, chronic obstructive pulmonary disease, and pulmonary tuberculosis) during January-July 2022. Cases identified from medical records were interviewed on socio-demographic, tobacco use and cessation information. Descriptive statistics were used to characterize patterns of tobacco use. Multiple logistic regression models were used to identify associations with tobacco use. We identified 2,032 individuals with TRI; 46% (939/2,032) had age ≥60 years, and 61% (1,241/2,032) were male. About 45% (923/2,032) were ever tobacco users (6% percent current and 39% former tobacco users). Approximately half of smokers and 58% of smokeless tobacco users had attempted quitting in the last month; 42% through cessation counselling. Comorbidities were present in 28% of the participants. Most (92%) of the patients had been diagnosed with TRI within the previous five years. The most frequent TRI were oral pharyngeal cancer (36% [725/2,032]), nasopharyngeal cancer (12% [246/2.032]) and lung cancer (10% [202/2,032]). Patients >60 years (aOR 2.24, 95% CI: 1.84, 2.73) and unmarried (aOR 1.21, 95% CI: 1.03, 1.42) had higher odds of tobacco use. Female patients (aOR 0.35, 95% CI: 0.30, 0.41) and those with no history of alcohol use (aOR 0.27, 95% CI: 0.23, 0.31), had less odds of tobacco use. Our study shows high prevalence of tobacco use among patients with TRI in Kenya, especially among older, male, less educated, unmarried, and alcohol users. We recommend tobacco use screening and cessation programs among patients with TRI as part of clinical care.
Collapse
Affiliation(s)
- Valerian Mwenda
- Department of Non-communicable Diseases, Ministry of Health, Nairobi, Kenya
| | | | - Shukri Mohamed
- African Population and Health Research Center, Nairobi, Kenya
| | - Gladwell Gathecha
- Department of Non-communicable Diseases, Ministry of Health, Nairobi, Kenya
| | - Anne Kendagor
- Department of Non-communicable Diseases, Ministry of Health, Nairobi, Kenya
| | - Dorcas Kiptui
- Department of Non-communicable Diseases, Ministry of Health, Nairobi, Kenya
| | | | | | - Caroline Mithi
- Kenyatta University Teaching, Referral and Research Hospital, Nairobi, Kenya
| | - Kennedy Okinda
- Kenyatta National Hospital-Othaya Referral Hospital, Othaya, Kenya
| | | | - David Njuguna
- Department of Planning and Health Financing, Ministry of Health, Nairobi, Kenya
| | | | | | | |
Collapse
|
3
|
Nyangasi MF, McLigeyo AA, Kariuki D, Mithe S, Orwa A, Mwenda V. Decentralizing cancer care in sub-Saharan Africa through an integrated regional cancer centre model: The case of Kenya. PLOS Glob Public Health 2023; 3:e0002402. [PMID: 37738236 PMCID: PMC10516416 DOI: 10.1371/journal.pgph.0002402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 08/29/2023] [Indexed: 09/24/2023]
Abstract
For 50 years, comprehensive cancer treatment services were provided at one public hospital and a few private facilities in the capital city. In 2019, the services were decentralized to new national and regional centers to increase service accessibility using an integration model. This study aimed to analyze the status of the utilization of services at regional cancer centers. We analyzed data from the district health information system, focusing on patient demographics, visit type, cancer stage, and the type of treatment provided. For comparison, a trend analysis of new cancer cases recorded at the main national referral hospital between 2011-2021 was also conducted. We conducted a descriptive analysis of the variables of interest; the median was used to summarize continuous variables and percentages were used for categorical variables. A total of 29,321 patients visited the regional centers in 2021; the median age was 57 years (IQR 44-68) and 57.3% (16,815) were female. Visits to regional centres represented 38.8% (29,321/75,501) of all visits to public cancer centers; new visits accounted for 16.4% (4814/29321), and the rest were follow-up visits. Most patients (71%) had an advanced disease. The proportion of male patients with advanced-stage cancer was significantly higher than that of female patients (74% vs. 69%, P<0.001). Of the 15,275 patients who received treatment at regional centers, 69.1% (10,550) received chemotherapy.The increased patient visits show good service uptake at the regional centers, implying improved access. These findings can inform policies that will guide future expansion and service improvement. We recommend optimizing cancer service delivery at regional centers across the care continuum to improve patient outcomes.
Collapse
Affiliation(s)
- Mary F. Nyangasi
- National Cancer Control Program, Ministry of Health, Nairobi, Kenya
| | | | - David Kariuki
- National Cancer Control Program, Ministry of Health, Nairobi, Kenya
| | | | - Albert Orwa
- Department of Clinical Medicine and Therapeutics, University of Nairobi, Nairobi, Kenya
| | - Valerian Mwenda
- National Cancer Control Program, Ministry of Health, Nairobi, Kenya
| |
Collapse
|
4
|
Mwenda V, Jalang'o R, Miano C, Bor JP, Nyangasi M, Mecca L, Were V, Kariithi E, Pecenka C, Schuind A, Abbas K, Clark A. Impact, cost-effectiveness, and budget implications of HPV vaccination in Kenya: A modelling study. Vaccine 2023:S0264-410X(23)00546-7. [PMID: 37296015 DOI: 10.1016/j.vaccine.2023.05.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 05/03/2023] [Accepted: 05/04/2023] [Indexed: 06/12/2023]
Abstract
BACKGROUND Sub-Saharan Africa has the highest rate of cervical cancer cases and deaths worldwide. Kenya introduced a quadrivalent HPV vaccine (GARDASIL, hereafter referred to as GARDASIL-4) for ten-year-old girls in late 2019 with donor support from Gavi, the Vaccine Alliance. As Kenya may soon graduate from Gavi support, it is important to evaluate the potential cost-effectiveness and budget impact of the current HPV vaccine, and potential alternatives. METHODS We used a proportionate outcomes static cohort model to evaluate the annual budget impact and lifetime cost-effectiveness of vaccinating ten-year-old girls over the period 2020-2029. We included a catch-up campaign for girls aged 11-14 years in 2020. We estimated cervical cancer cases, deaths, disability adjusted life years (DALYs), and healthcare costs (government and societal perspective) expected to occur with and without vaccination over the lifetimes of each cohort of vaccinated girls. For each of the four products available globally (CECOLIN©, CERVARIX©, GARDASIL-4©, and GARDASIL-9 ©), we estimated the cost (2021 US$) per DALY averted compared to no vaccine and to each other. Model inputs were obtained from published sources, as well as local stakeholders. RESULTS We estimated 320,000 cases and 225,000 deaths attributed to cervical cancer over the lifetimes of the 14 evaluated birth cohorts. HPV vaccination could reduce this burden by 42-60 %. Without cross-protection, CECOLIN had the lowest net cost and most attractive cost-effectiveness. With cross-protection, CERVARIX was the most cost-effective. Under either scenario the most cost-effective vaccine had a 100 % probability of being cost-effective at a willingness-to-pay threshold of US$ 100 (5 % of Kenya's national gross domestic product per capita) compared to no vaccination. Should Kenya reach its target of 90 % coverage and graduate from Gavi support, the undiscounted annual vaccine program cost could exceed US$ 10 million per year. For all three vaccines currently supported by Gavi, a single-dose strategy would be cost-saving compared to no vaccination. CONCLUSION HPV vaccination for girls is highly cost-effective in Kenya. Compared to GARDASIL-4, alternative products could provide similar or greater health benefits at lower net costs. Substantial government funding will be required to reach and sustain coverage targets as Kenya graduates from Gavi support. A single dose strategy is likely to have similar benefits for less cost.
Collapse
Affiliation(s)
- Valerian Mwenda
- National Cancer Control Program, Ministry of Health, Nairobi, Kenya.
| | - Rose Jalang'o
- National Vaccines and Immunization Program, Ministry of Health, Nairobi, Kenya
| | - Christine Miano
- National Vaccines and Immunization Program, Ministry of Health, Nairobi, Kenya
| | - Joan-Paula Bor
- National Cancer Control Program, Ministry of Health, Nairobi, Kenya
| | - Mary Nyangasi
- National Cancer Control Program, Ministry of Health, Nairobi, Kenya
| | - Lucy Mecca
- National Vaccines and Immunization Program, Ministry of Health, Nairobi, Kenya
| | - Vincent Were
- Kenya Medical Research Institute, Nairobi, Kenya
| | | | | | | | - Kaja Abbas
- London School of Hygiene and Tropical Medicine, London, UK
| | - Andrew Clark
- London School of Hygiene and Tropical Medicine, London, UK
| |
Collapse
|
5
|
Mwenda V, Bor JP, Nyangasi M, Njeru J, Olwande S, Njiri P, Arbyn M, Weyers S, Tummers P, Temmerman M. Integrating human papillomavirus testing as a point-of care service using GeneXpert platforms: Findings and lessons from a Kenyan pilot study (2019-2020). PLoS One 2023; 18:e0286202. [PMID: 37228154 DOI: 10.1371/journal.pone.0286202] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 05/11/2023] [Indexed: 05/27/2023] Open
Abstract
BACKGROUND Globally, cervical cancer is a major public health problem, with about 604,000 new cases and over 340,000 deaths in 2020. In Kenya, it is the leading cause of cancer deaths, with over 3,000 women dying in 2020 alone. Both the Kenyan cancer screening guidelines and the World Health Organization's Global Cervical Cancer Elimination Strategy recommend human papillomavirus (HPV) testing as the primary screening test. However, HPV testing is not widely available in the public healthcare system in Kenya. We conducted a pilot study using a point of care (POC) HPV test to inform national roll-out. METHODS The pilot was implemented from October 2019 to December 2020, in nine health facilities across six counties. We utilized the GeneXpert platform (Cepheid, Sunnyvale, CA, USA), currently used for TB, Viral load testing and early infant diagnosis for HIV, for HPV screening. Visual inspection with acetic acid (VIA) was used for triage of HPV-positive women, as recommended in national guidelines. Quality assurance (QA) was performed by the National Oncology Reference Laboratory (NORL), using the COBAS 4800 platform (Roche Molecular System, Pleasanton, CF, USA). HPV testing was done using either self or clinician-collected samples. We assessed the following screening performance indicators: screening coverage, screen test positivity, triage compliance, triage positivity and treatment compliance. Test agreement between local GeneXpert and central comparator high-risk HPV (hrHPV) testing for a random set of specimens was calculated as overall concordance and kappa value. We conducted a final evaluation and applied the Nominal Group Technique (NGT) to identify implementation challenges and opportunities. KEY FINDINGS The screening coverage of target population was 27.0% (4500/16,666); 52.8% (2376/4500) were between 30-49 years of age. HPV positivity rate was 22.8% (1027/4500). Only 10% (105/1027) of HPV positive cases were triaged with VIA/VILI; 21% (22/105) tested VIA/VILI positive, and 73% (16/22) received treatment (15 received cryotherapy, 1 was referred for biopsy). The median HPV testing turnaround time (TAT) was 24 hours (IQR 2-48 hours). Invalid sample rate was 2.0% (91/4500). Concordance between the Cepheid and COBAS was 86.2% (kappa value = 0.71). Of 1042 healthcare workers, only 5.6% (58/1042) were trained in cervical cancer screening and treatment, and only 69% (40/58) of those trained were stationed at service provision areas. Testing capacity was identifed as the main challenge, while the community strategy was the main opportunity. CONCLUSION HPV testing can be performed on GeneXpert as a near point of care platform. However, triage compliance and testing TAT were major concerns. We recommend strengthening of the screening-triage-treatment cascade and expansion of testing capacity, before adoption of a GeneXpert-based HPV screening among other near point of care platforms in Kenya.
Collapse
Affiliation(s)
- Valerian Mwenda
- National Cancer Control Program, Ministry of Health, Nairobi, Kenya
| | - Joan-Paula Bor
- National Cancer Control Program, Ministry of Health, Nairobi, Kenya
| | - Mary Nyangasi
- National Cancer Control Program, Ministry of Health, Nairobi, Kenya
| | - James Njeru
- Clinton Health Access Initiative, Nairobi, Kenya
| | | | | | - Marc Arbyn
- Unit of Cancer Epidemiology, Belgian Cancer Centre, Sciensano, Brussels, Belgium
- Department of Human Structure and Repair, Gent University Hospital, Ghent, Belgium
| | - Steven Weyers
- Department of Human Structure and Repair, Gent University Hospital, Ghent, Belgium
- Department of Obstetrics and Gynaecology, University Hospital, Gent, Belgium
| | - Philippe Tummers
- Department of Human Structure and Repair, Gent University Hospital, Ghent, Belgium
- Department of Obstetrics and Gynaecology, University Hospital, Gent, Belgium
- Department of Obstetrics and Gynaecology, University Hospital, Gent, Belgium
| | - Marleen Temmerman
- Department of Obstetrics and Gynaecology, University Hospital, Gent, Belgium
- Department of Obstetrics and Gynaecology, Aga Khan University Hospital, Nairobi, Kenya
| |
Collapse
|
6
|
Mwenda V, Yellman MA, Oyugi E, Mwachaka P, Gathecha G, Gura Z. Piloting a hospital-based road traffic injury surveillance system in Nairobi County, Kenya, 2018-2019. Injury 2023; 54:S0020-1383(23)00182-1. [PMID: 36925372 PMCID: PMC10599333 DOI: 10.1016/j.injury.2023.02.051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 02/14/2023] [Accepted: 02/25/2023] [Indexed: 03/18/2023]
Abstract
BACKGROUND Kenya's estimated road traffic injury (RTI) death rate is 27.8/100,000 population, which is 1.5 times the global rate. Some RTI data are collected in Kenya; however, a systematic and integrated surveillance system does not exist. Therefore, we adopted and modified the World Health Organization's injury surveillance guidelines to pilot a hospital-based RTI surveillance system in Nairobi County, Kenya. METHODS We prospectively documented all RTI cases presenting at two public trauma hospitals in Nairobi County from October 2018-April 2019. RTI cases were defined as injuries involving ≥1 moving vehicles on public roads. Demographics, injury circumstances, and outcome information were collected using standardized case report forms. The Kampala Trauma Score (KTS) was used to assess injury severity. RTI cases were characterized with descriptive statistics. RESULTS Of the 1,840 RTI cases reported during the seven-month period, 73.2% were male. The median age was 29.8 years (range 1-89 years). Forty percent (n = 740) were taken to the hospital by bystanders. Median time for hospital arrival was 77 min. Pedestrians constituted 54.1% (n = 995) of cases. Of 400 motorcyclists, 48.0% lacked helmets. Similarly, 65.7% of bicyclists (23/35) lacked helmets. Among 386 motor vehicle occupants, 59.6% were not using seat belts (19.9% unknown). Seven percent of cases (n = 129) reported alcohol use (49.0% unknown), and 8.8% (n = 161) reported mobile phone use (59.7% unknown). Eleven percent of cases (n = 199) were severely injured (KTS <11), and 220 died. CONCLUSION We demonstrated feasibility of a hospital-based RTI surveillance system in Nairobi County. Integrating information from crash scenes and hospitals can guide prevention.
Collapse
Affiliation(s)
- Valerian Mwenda
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Nairobi, Kenya; Division of Non-communicable Diseases, Ministry of Health, Nairobi, Kenya.
| | - Merissa A Yellman
- Division of Injury Prevention, National Center for Injury Prevention and Control, U.S. Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Elvis Oyugi
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Nairobi, Kenya
| | | | - Gladwell Gathecha
- Division of Non-communicable Diseases, Ministry of Health, Nairobi, Kenya
| | - Zeinab Gura
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Nairobi, Kenya
| |
Collapse
|
7
|
Mwenda V, Bor JP, Nyangasi M, Temmerman M. Mobilizing stakeholders to drive the cervical cancer elimination agenda in Kenya: The national cervical cancer stakeholders' forum 2022. Dialogues Health 2022; 1:100066. [PMID: 38515876 PMCID: PMC10953883 DOI: 10.1016/j.dialog.2022.100066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 10/24/2022] [Accepted: 10/26/2022] [Indexed: 03/23/2024]
Abstract
Background Kenya is among the nineteen countries in Sub-Saharan Africa with the highest burden of cervical cancer globally. The high burden of cervical cancer in developing countries reflects the absence of effective cervical cancer prevention programs with limited resources invested to provide comprehensive services. Objective We aimed to engage stakeholders in a structured consultative forum, to gain insights and forge effective partnerships to drive the cervical cancer elimination agenda in Kenya. Methods The National Cervical Cancer Stakeholders Consultative Forum was organized as a part of activities to commemorate the National Cervical Cancer Awareness Month on 19th January 2022 in Nairobi, Kenya. The overall goal of the meeting was to provide a forum to sensitize stakeholders on the National Cervical Cancer Prevention and Control Program (NCCP) with a view to strengthen partnerships, increase coordination for improved service delivery and to provide a forum for resource mobilisation and alignment of key stakeholders towards elimination of cervical cancer in Kenya. Nominal group technique was adopted for structured discussions, and the findings analysed to derive key themes. Findings Key challenges to primary and secondary prevention of cervical cancer were identified as low awareness, stigma and misinformation, high unmet need for treatment of early lesions, few health care providers with capacity to screen and treat, inadequate supplies, inefficient health information systems and poor referral pathways. Championing integration of cervical cancer screening and treatment services into routine health programs, strengthening policy implementation and robust monitoring and evaluation were identified as critical interventions. Conclusion The National Cervical Cancer Stakeholders Forum 2022 provided insights for enabling Kenya to progress on the 2030 elimination targets. Such forums can be useful in bringing all actors together to evaluate achievements and identify opportunities for more effective national cervical cancer prevention and control programs.
Collapse
Affiliation(s)
- Valerian Mwenda
- National Cancer Control Program, Ministry of Health, Nairobi, Kenya
| | - Joan-Paula Bor
- National Cancer Control Program, Ministry of Health, Nairobi, Kenya
| | - Mary Nyangasi
- National Cancer Control Program, Ministry of Health, Nairobi, Kenya
| | - Marleen Temmerman
- Department of Obstetrics and Gynaecology, Aga Khan University Hospital, Nairobi, Kenya
| |
Collapse
|
8
|
Kiarie H, Temmerman M, Nyamai M, Liku N, Thuo W, Oramisi V, Nyaga L, Karimi J, Wamalwa P, Gatheca G, Mwenda V, Ombajo LA, Thumbi SM. The COVID-19 pandemic and disruptions to essential health services in Kenya: a retrospective time-series analysis. Lancet Glob Health 2022; 10:e1257-e1267. [PMID: 35961349 PMCID: PMC9363041 DOI: 10.1016/s2214-109x(22)00285-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 06/16/2022] [Accepted: 06/22/2022] [Indexed: 01/01/2023]
Abstract
BACKGROUND Public health emergencies can disrupt the provision of and access to essential health-care services, exacerbating health crises. We aimed to assess the effect of the COVID-19 pandemic on essential health-care services in Kenya. METHODS Using county-level data routinely collected from the health information system from health facilities across the country, we used a robust mixed-effect model to examine changes in 17 indicators of essential health services across four periods: the pre-pandemic period (from January, 2018 to February, 2020), two pandemic periods (from March to November 2020, and February to October, 2021), and the period during the COVID-19-associated health-care workers' strike (from December, 2020 to January, 2021). FINDINGS In the pre-pandemic period, we observed a positive trend for multiple indicators. The onset of the pandemic was associated with statistically significant decreases in multiple indicators, including outpatient visits (28·7%; 95% CI 16·0-43·5%), cervical cancer screening (49·8%; 20·6-57·9%), number of HIV tests conducted (45·3%; 23·9-63·0%), patients tested for malaria (31·9%; 16·7-46·7%), number of notified tuberculosis cases (26·6%; 14·7-45·1%), hypertension cases (10·4%; 6·0-39·4%), vitamin A supplements (8·7%; 7·9-10·5%), and three doses of the diphtheria, tetanus toxoid, and pertussis vaccine administered (0·9%; 0·5-1·3%). Pneumonia cases reduced by 50·6% (31·3-67·3%), diarrhoea by 39·7% (24·8-62·7%), and children attending welfare clinics by 39·6% (23·5-47·1%). Cases of sexual violence increased by 8·0% (4·3-25·0%). Skilled deliveries, antenatal care, people with HIV infection newly started on antiretroviral therapy, confirmed cases of malaria, and diabetes cases detected were not significantly affected negatively. Although most of the health indicators began to recover during the pandemic, the health-care workers' strike resulted in nearly all indicators falling to numbers lower than those observed at the onset or during the pre-strike pandemic period. INTERPRETATION The COVID-19 pandemic and the associated health-care workers' strike in Kenya have been associated with a substantial disruption of essential health services, with the use of outpatient visits, screening and diagnostic services, and child immunisation adversely affected. Efforts to maintain the provision of these essential health services during a health-care crisis should target the susceptible services to prevent the exacerbation of associated disease burdens during such health crises. FUNDING Bill & Melinda Gates Foundation.
Collapse
Affiliation(s)
- Helen Kiarie
- Division of Monitoring and Evaluation, Ministry of Health, Nairobi, Kenya
| | - Marleen Temmerman
- Centre of Excellence in Women and Child Health, Aga Khan University, Nairobi, Kenya
| | - Mutono Nyamai
- Centre for Epidemiological Modelling and Analysis, University of Nairobi, Nairobi, Kenya; Paul G Allen School for Global Health, Washington State University, Pullman, WA, USA
| | - Nzisa Liku
- Division of Monitoring and Evaluation, Ministry of Health, Nairobi, Kenya; Paul G Allen School for Global Health, Washington State University, Pullman, WA, USA
| | - Wangari Thuo
- Centre for Epidemiological Modelling and Analysis, University of Nairobi, Nairobi, Kenya
| | - Violet Oramisi
- National AIDS and STIs Control Programme, Ministry of Health, Nairobi, Kenya
| | - Lilly Nyaga
- Division of Monitoring and Evaluation, Ministry of Health, Nairobi, Kenya
| | - Janette Karimi
- Division of Monitoring and Evaluation, Ministry of Health, Nairobi, Kenya
| | | | - Gladwell Gatheca
- Division of Monitoring and Evaluation, Ministry of Health, Nairobi, Kenya
| | - Valerian Mwenda
- Division of Monitoring and Evaluation, Ministry of Health, Nairobi, Kenya
| | - Loice Achieng Ombajo
- Centre for Epidemiological Modelling and Analysis, University of Nairobi, Nairobi, Kenya; Department of Clinical Medicine and Therapeutics, College of Health Sciences, University of Nairobi, Nairobi, Kenya
| | - S M Thumbi
- Centre for Epidemiological Modelling and Analysis, University of Nairobi, Nairobi, Kenya; Institute of Tropical and Infectious Diseases, University of Nairobi, Nairobi, Kenya; Paul G Allen School for Global Health, Washington State University, Pullman, WA, USA; Institute of Immunology and Infection Research, School of Biological Sciences, University of Edinburgh, Edinburgh, UK.
| |
Collapse
|
9
|
Mwenda V, Mburu W, Bor JP, Nyangasi M, Arbyn M, Weyers S, Tummers P, Temmerman M. Cervical cancer programme, Kenya, 2011–2020: lessons to guide elimination as a public health problem. Ecancermedicalscience 2022; 16:1442. [PMID: 36200015 PMCID: PMC9470178 DOI: 10.3332/ecancer.2022.1442] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Indexed: 11/22/2022] Open
Abstract
Background Cervical cancer is the leading cause of cancer mortality in Kenya, with an estimated 3,200 deaths in 2020. Kenya has implemented cervical cancer interventions for more than a decade. We describe the evolution of the cervical cancer programme over the last 20 years and assess its performance. Methods We searched the Ministry of Health’s archives and website (2000–2021) for screening policy documents and assessed them using seven items: situational analysis, objectives, key result areas, implementation framework, resource considerations, monitoring and evaluation and definition of roles/responsibilities. In addition, a trend analysis was performed targeting screening and disease burden indicators in the period 2011–2020, using data from Kenya Health Information System and the Global Burden of Disease database. Findings Policy guidance improved over time, but the implementation of screening was poor. Before 2016, a clear leadership and accountability structure was lacking; improvement occurred after the establishment of the National Cancer Control Program. The main health system gaps included the lack of a trained healthcare workforce and poor data collection. Annual screening coverage varied between <1% and 36% of the target population for the year for HIV-negative women and between <1% and 7% for HIV-positive women, from 2011 to 2020. Test positivity for visual inspection with acetic acid was below 5% for most of the period. Compliance to treatment of precancerous lesions ranged between 22% and 39%. The detection rate of cervical cancer ranged between 0.5% and 1.0%. The burden of invasive cervical cancer did not change significantly: world age-standardised incidence and mortality rates of 26.3–27.4 and 16.6–18.0/100,000 women-years, respectively; disability-adjusted life years of 579–624/100,000 life years. Conclusion The Kenyan cervical cancer control programme suffered from inadequate health system strengthening and poor quality implementation. Evidence-based policy implementation and sustained health system strengthening are necessary to move towards cervical cancer elimination as a public health problem.
Collapse
Affiliation(s)
- Valerian Mwenda
- National Cancer Control Program, Ministry of Health, PO Box 30016-00100, Nairobi, Kenya
| | - Woki Mburu
- National Cancer Control Program, Ministry of Health, PO Box 30016-00100, Nairobi, Kenya
| | - Joan-Paula Bor
- National Cancer Control Program, Ministry of Health, PO Box 30016-00100, Nairobi, Kenya
| | - Mary Nyangasi
- National Cancer Control Program, Ministry of Health, PO Box 30016-00100, Nairobi, Kenya
| | - Marc Arbyn
- Unit of Cancer Epidemiology, Belgian Cancer Centre, Sciensano, Brussels 1050, Belgium
- Department of Obstetrics and Gynaecology, Ghent University Hospital, Ghent 9000, Belgium
| | - Steven Weyers
- Department of Obstetrics and Gynaecology, Ghent University Hospital, Ghent 9000, Belgium
- Cancer Research Institute Ghent (CRIG), Ghent 9000, Belgium
| | - Philippe Tummers
- Department of Obstetrics and Gynaecology, Ghent University Hospital, Ghent 9000, Belgium
- Cancer Research Institute Ghent (CRIG), Ghent 9000, Belgium
- Department of Human Structure and Repair, Ghent University Hospital, Ghent 9000, Belgium
| | - Marleen Temmerman
- Cancer Research Institute Ghent (CRIG), Ghent 9000, Belgium
- Department of Obstetrics and Gynaecology, Aga Khan University Hospital, PO Box 30270-00100, Nairobi, Kenya
| |
Collapse
|
10
|
Mwenda V, Karagu A, Githanga JN, Nyangasi M. Barriers to effective childhood cancer control in Kenya (BECK) study, 2019-2020: A mixed methods study in a national tertiary facility and 10 regional cancer treatment centers. J Clin Oncol 2022. [DOI: 10.1200/jco.2022.40.16_suppl.10018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
10018 Background: Globally, 80,000 children die from cancer annually; 80% in low- and middle-income countries (LMICs). Childhood cancer cure is possible in more than 80% of cases, in all economic settings. This study aimed to identify barriers to effective management of childhood cancers in Kenya, for program and policy intervention. Methods: We reviewed childhood cancer cases diagnosed at Kenyatta National Hospital in the period 2015-2019. We also assessed capacity of ten recently established regional cancer centres for childhood cancer diagnosis and treatment. We conducted focused group discussions among childhood cancer survivors’ caregivers and key informant interviews among childhood cancer specialists and policy makers from the Ministry of Health and the National Cancer Institute of Kenya. We estimated diagnostic delays, mapped service availability and deductively summarized the qualitative data into main themes. Results: We abstracted 1,764 cases; median age 6 years (IQR 9); 1013 (57.5%) were male. Most affected age group was 0-4 years (47.3%). Most common cancer types were retinoblastoma (23.3%), nephroblasoma (10.4%) and acute lymphoblastic leukaemia 10.3%). Cases managed at KNH decreased between 2015 and 2017, and then recovered. The median total delay (symptoms onset to treatment initiation) was 32 days (range 0-3666). Regional cancer centres lacked specialized workforce for childhood cancer care. Caregivers identified inadequate cover by National Health Insurance and disorganized care process as major challenges. At health system and policy level, low awareness, fragmented referral systems and in-effective policy implementation are major challenges to childhood cancer control. Conclusions: Increasing number of specialized personnel, creation of a differentiated financing package for childhood cancer and restructuring of referral and the care process can improve childhood cancer outcomes in Kenya.
Collapse
Affiliation(s)
- Valerian Mwenda
- National Cancer Control Program, Ministry of Health, Nairobi, Kenya
| | | | | | - Mary Nyangasi
- National Cancer Control Program, Ministry of Health, Nairobi, Kenya
| |
Collapse
|
11
|
Mwenda V, Makena I, Ogweno V, Obonyo J, Were V. Effectiveness of interactive text messaging and structured psychosocial support groups on developmental milestones of children from adolescent pregnancies in Kenya: a quasi-experimental study (Preprint). JMIR Pediatr Parent 2022; 6:e37359. [PMID: 37126373 DOI: 10.2196/37359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 07/23/2022] [Accepted: 08/23/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND In sub-Saharan Africa, one-quarter of all pregnancies occur in adolescents. Children born to adolescent mothers have poorer physical and socio-cognitive development. One reason may be inadequate knowledge on childcare and psychosocial support during pregnancy and post partum, since adolescent mothers have less antenatal care attendance and overall interaction with the health care system. Mobile health technology has been used to relay health information to special groups; however, psychosocial support commonly requires physical interaction. OBJECTIVE We aimed to assess the efficacy of an interactive mobile text messaging platform and support groups in improving adolescent mothers' knowledge and practices as well as infant growth and development. METHODS This was a quasi-experimental study, conducted among adolescent mothers with infants younger than 3 months, in Homa Bay County, Kenya. Five of the 8 subcounties in Homa Bay County were purposively selected as study clusters. Four subcounties were assigned as intervention clusters and 1 as a control cluster. Adolescent mothers from 2 intervention subcounties received interactive text messaging only (limited package), whereas those from the other 2 subcounties received text messaging and weekly support groups, moderated by a community health extension worker and a counselor (full package); the control cluster only received the end-line evaluation (posttest-only control). The follow-up period was 9 months. Key outcomes were maternal knowledge on childcare and infant development milestones assessed using the Developmental Milestones Checklist (DMC III). Knowledge and DMC III scores were compared between the intervention and control groups, as well as between the 2 intervention groups. RESULTS We recruited 791 mother-infant pairs into the intervention groups (full package: n=375; limited package: n=416) at baseline and 220 controls at end line. Attrition from the intervention groups was 15.8% (125/791). Compared with the control group, adolescent mothers receiving the full package had a higher knowledge score on infant care and development (9.02 vs 8.01; P<.001) and higher exclusive breastfeeding rates (238/375, 63.5% vs 112/220, 50.9%; P=.004), and their infants had higher average DMC III scores (53.09 vs 48.59; P=.01). The limited package group also had higher knowledge score than the control group (8.73 vs 8.01; P<.001); this group performed better than the full package group on exclusive breastfeeding (297/416, 71.4% vs 112/220, 50.9%; P<.001) and DMC III scores (58.29 vs 48.59; P<.001) when compared with the control group. We found a marginal difference in knowledge scores between full and limited package groups (9.02 vs 8.73; P=.048) but no difference in DMC III scores between the 2 groups (53.09 vs 58.29; P>.99). CONCLUSIONS An interactive text messaging platform improved adolescent mothers' knowledge on nurturing infant care and the development of their children, even without physical support groups. Such platforms offer a convenient avenue for providing reproductive health information to adolescents. TRIAL REGISTRATION Pan African Clinical Trials Registry PACTR201806003369302; https://tinyurl.com/kkxvzjse.
Collapse
Affiliation(s)
- Valerian Mwenda
- Department of Non-communicable Diseases, Ministry of Health, Nairobi, Kenya
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Nairobi, Kenya
- Field Epidemiology Society of Kenya, Nairobi, Kenya
| | - Ireen Makena
- Department of Biological Sciences, Chuka University, Chuka, Kenya
| | - Vincent Ogweno
- Department of Pediatrics, University of Nairobi, NAIROBI, Kenya
| | - James Obonyo
- County Department of Health, Homa Bay County, Homa Bay, Kenya
| | - Vincent Were
- Kenya Medical Research Institute-Wellcome trust, Nairobi, Kenya
| |
Collapse
|
12
|
Mwenda V, Bor JP, Gitungo H, Kirika L, Njoroge R, Mugi B, Ojuka D, Nyangasi M. Breast health awareness campaign and screening pilot in a Kenyan County: Findings and lessons. Cancer Rep (Hoboken) 2021; 5:e1480. [PMID: 34235881 PMCID: PMC8955074 DOI: 10.1002/cnr2.1480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 05/16/2021] [Accepted: 06/14/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND AND AIM Breast cancer is the leading cancer in terms of incidence in Kenya. We conducted a breast cancer awareness and screening pilot to assess feasibility of rolling out a national screening program in Kenya. METHODS Conducted in Nyeri County during October-November 2019, the pilot had three phases; awareness creation, screening (clinical breast examination and/or imaging) and final evaluation (post-screening exit interviews and retrospective screening data review). Descriptive statistics on awareness, screening process and outputs were derived. RESULTS During the pilot, 1813 CBE, 217 breast ultrasounds and 600 mammograms were performed. Mammography equipment utilization increased from 11% to 83%. Of 49 women with suspicious lesions on mammography, only 22 (44.9%) had been linked to care 4 months after the campaign. Of 532 exit interview respondents; 95% (505/532) were ≥35 years of age; 80% (426/532) had been reached by the awareness campaign. Majority (75% [399/532]) had received information from community health volunteers; 68% through social groups. Majority (79% [420/532]) felt the campaign had changed their behavior on breast health. Although 77% (407/532) had knowledge on self breast examination (SBE); only 13% practiced monthly SBE. More than half (58% [306/532]) had previously undertaken a CBE. Approximately 70% (375/528) were unaware of mammography before the pilot; 86% (459/532) had never previously undertaken a mammogram. Fifty-five percent (293/532) of respondents had screening waiting times of >120 min. CONCLUSION Community health workers can create breast cancer screening demand sustainably. Adequate personnel and effective follow-up are crucial before national roll-out of a breast cancer screening program.
Collapse
Affiliation(s)
- Valerian Mwenda
- National Cancer Control Program, Ministry of Health, Nairobi, Kenya
| | - Joan-Paula Bor
- National Cancer Control Program, Ministry of Health, Nairobi, Kenya
| | - Hannah Gitungo
- National Cancer Control Program, Ministry of Health, Nairobi, Kenya
| | - Lydia Kirika
- National Cancer Control Program, Ministry of Health, Nairobi, Kenya
| | - Richard Njoroge
- National Cancer Control Program, Ministry of Health, Nairobi, Kenya
| | - Beatrice Mugi
- Radiology and Diagnostic Imaging Department, Kenyatta National Hospital, Nairobi, Kenya
| | - Daniel Ojuka
- Department of Surgery, University of Nairobi, Nairobi, Kenya
| | - Mary Nyangasi
- National Cancer Control Program, Ministry of Health, Nairobi, Kenya
| |
Collapse
|
13
|
Mwangi KJ, Mwenda V, Gathecha G, Beran D, Guessous I, Ombiro O, Ndegwa Z, Masibo P. Socio-economic and demographic determinants of non-communicable diseases in Kenya: a secondary analysis of the Kenya stepwise survey. Pan Afr Med J 2020; 37:351. [PMID: 33796165 PMCID: PMC7992900 DOI: 10.11604/pamj.2020.37.351.21167] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Accepted: 12/08/2020] [Indexed: 12/04/2022] Open
Abstract
Introduction non-communicable diseases (NCDs) are projected to become the leading cause of death in Africa by 2030. Gender and socio-economic differences influence the prevalence of NCDs and their risk factors. Methods we performed a secondary analysis of the STEPS 2015 data to determine prevalence and correlation between diabetes, hypertension, harmful alcohol use, smoking, obesity and injuries across age, gender, residence and socio-economic strata. Results tobacco use prevalence was 13.5% (males 19.9%, females 0.9%, p<0.001); harmful alcohol use was 12.6% (males 18.1%, females 2.2%, p<0.001); central obesity was 27.9% (females 49.5%, males 32.9%, p=0.017); type 2 diabetes prevalence 3.1% (males 2.0%, females 2.8%, p=0.048); elevated blood pressure prevalence was 23.8% (males 25.1%, females 22.6%, p<0.001), non-use of helmets 72.8% (males 89.5%, females 56.0%, p=0.031) and seat belts non-use 67.9% (males 79.8%, females 56.0%, p=0.027). Respondents with <12 years of formal education had higher prevalence of non-use of helmets (81.7% versus 54.1%, p=0.03) and seat belts (73.0% versus 53.9%, p=0.039). Respondents in the highest wealth quintile had higher prevalence of type II diabetes compared with those in the lowest (5.2% versus 1.6%,p=0.008). Rural dwellers had 35% less odds of tobacco use (aOR 0.65, 95% CI 0.49, 0.86) compared with urban dwellers, those with ≥12 years of formal education had 89% less odds of tobacco use (aOR 0.11, 95% CI 0.07, 0.17) compared with <12 years, and those belonging to the wealthiest quintile had 64% higher odds of unhealthy diets (aOR 1.64, 95% CI 1.26, 2.14). Only 44% of respondents with type II diabetes and 16% with hypertension were aware of their diagnosis. Conclusion prevalence of NCD risk factors is high in Kenya and varies across socio-demographic attributes. Socio-demographic considerations should form part of multi-sectoral, integrated approach to reduce the NCD burden in Kenya.
Collapse
Affiliation(s)
- Kibachio Joseph Mwangi
- Faculté de Médecine, Université de Genève, Genève, Suisse.,Division of Non-communicable Disease, Ministry of Health, Nairobi, Kenya
| | - Valerian Mwenda
- Division of Non-communicable Disease, Ministry of Health, Nairobi, Kenya.,Field Epidemiology and Laboratory Training Program, Ministry of Health, Nairobi, Kenya
| | - Gladwell Gathecha
- Division of Non-communicable Disease, Ministry of Health, Nairobi, Kenya
| | - David Beran
- Division of Primary Care Medicine, Department of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Idris Guessous
- Faculté de Médecine, Université de Genève, Genève, Suisse.,Division of Tropical and Humanitarian Medicines, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Oren Ombiro
- Division of Non-communicable Disease, Ministry of Health, Nairobi, Kenya.,Improving Public Health Management for Action (IMPACT) Program, Ministry of Health, Nairobi, Kenya
| | - Zachary Ndegwa
- Division of Non-communicable Disease, Ministry of Health, Nairobi, Kenya
| | - Peninnah Masibo
- Global Programs for Research and Training, University of California, San Francisco, Nairobi, Kenya
| |
Collapse
|
14
|
Mwenda V, Niyomwungere A, Oyugi E, Githuku J, Obonyo M, Gura Z. Corrigendum to: Cholera outbreak during a scientific conference at a Nairobi hotel, Kenya 2017. J Public Health (Oxf) 2020; 42:871. [DOI: 10.1093/pubmed/fdz112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Revised: 06/14/2019] [Accepted: 06/19/2019] [Indexed: 11/13/2022] Open
Affiliation(s)
- Valerian Mwenda
- Field Epidemiology and Laboratory Training Programme, Ministry of Health, Nairobi, Kenya
| | - Alexis Niyomwungere
- Field Epidemiology and Laboratory Training Programme, Ministry of Health, Nairobi, Kenya
- Disease Surveillance and Response Unit, Ministry of Health, Nairobi, Kenya
| | - Elvis Oyugi
- Field Epidemiology and Laboratory Training Programme, Ministry of Health, Nairobi, Kenya
| | - Jane Githuku
- Field Epidemiology and Laboratory Training Programme, Ministry of Health, Nairobi, Kenya
| | - Mark Obonyo
- Field Epidemiology and Laboratory Training Programme, Ministry of Health, Nairobi, Kenya
| | - Zeinab Gura
- Field Epidemiology and Laboratory Training Programme, Ministry of Health, Nairobi, Kenya
| |
Collapse
|
15
|
Kibachio J, Mwenda V, Ombiro O, Kamano JH, Perez‐Guzman PN, Mutai KK, Guessous I, Beran D, Kasaie P, Weir B, Beecroft B, Kilonzo N, Kupfer L, Smit M. Recommendations for the use of mathematical modelling to support decision-making on integration of non-communicable diseases into HIV care. J Int AIDS Soc 2020; 23 Suppl 1:e25505. [PMID: 32562338 PMCID: PMC7305412 DOI: 10.1002/jia2.25505] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Revised: 03/03/2020] [Accepted: 03/31/2020] [Indexed: 12/20/2022] Open
Abstract
INTRODUCTION Integrating services for non-communicable diseases (NCDs) into existing primary care platforms such as HIV programmes has been recommended as a way of strengthening health systems, reducing redundancies and leveraging existing systems to rapidly scale-up underdeveloped programmes. Mathematical modelling provides a powerful tool to address questions around priorities, optimization and implementation of such programmes. In this study, we examine the case for NCD-HIV integration, use Kenya as a case-study to highlight how modelling has supported wider policy formulation and decision-making in healthcare and to collate stakeholders' recommendations on use of models for NCD-HIV integration decision-making. DISCUSSION Across Africa, NCDs are increasingly posing challenges for health systems, which historically focused on the care of acute and infectious conditions. Pilot programmes using integrated care services have generated advantages for both provider and user, been cost-effective, practical and achieve rapid coverage scale-up. The shared chronic nature of NCDs and HIV means that many operational approaches and infrastructure developed for HIV programmes apply to NCDs, suggesting this to be a cost-effective and sustainable policy option for countries with large HIV programmes and small, un-resourced NCD programmes. However, the vertical nature of current disease programmes, policy financing and operations operate as barriers to NCD-HIV integration. Modelling has successfully been used to inform health decision-making across a number of disease areas and in a number of ways. Examples from Kenya include (i) estimating current and future disease burden to set priorities for public health interventions, (ii) forecasting the requisite investments by government, (iii) comparing the impact of different integration approaches, (iv) performing cost-benefit analysis for integration and (v) evaluating health system capacity needs. CONCLUSIONS Modelling can and should play an integral part in the decision-making processes for health in general and NCD-HIV integration specifically. It is especially useful where little data is available. The successful use of modelling to inform decision-making will depend on several factors including policy makers' comfort with and understanding of models and their uncertainties, modellers understanding of national priorities, funding opportunities and building local modelling capacity to ensure sustainability.
Collapse
Affiliation(s)
- Joseph Kibachio
- Division of Non‐communicable DiseasesMinistry of HealthKenya
- Faculty of MedicineUniversity of GenevaSwitzerlandGeneva
| | - Valerian Mwenda
- Division of Non‐communicable DiseasesMinistry of HealthKenya
| | - Oren Ombiro
- Division of Non‐communicable DiseasesMinistry of HealthKenya
| | - Jamima H Kamano
- Department of MedicineMoi University School of MedicineKenyaEldoret
- AMPATHKenyaLondon
| | - Pablo N Perez‐Guzman
- MRC Centre for Global Infectious Disease AnalysisDepartment of Infectious Disease EpidemiologyImperial College LondonLondonUnited Kingdom
| | | | - Idris Guessous
- Division of Primary Care MedicineGeneva University Hospital and University of GenevaGenevaSwitzerland
| | - David Beran
- Division of Tropical and Humanitarian MedicineUniversity of Geneva and Geneva University HospitalsGenevaSwitzerland
| | - Paratsu Kasaie
- John Hopkins Bloomberg School of Public HealthBaltimoreMDUSA
| | - Brian Weir
- John Hopkins Bloomberg School of Public HealthBaltimoreMDUSA
| | - Blythe Beecroft
- Fogarty International CenterNational Institutes of HealthBethesdaMDUSA
| | | | - Linda Kupfer
- Fogarty International CenterNational Institutes of HealthBethesdaMDUSA
| | - Mikaela Smit
- MRC Centre for Global Infectious Disease AnalysisDepartment of Infectious Disease EpidemiologyImperial College LondonLondonUnited Kingdom
| |
Collapse
|
16
|
Mwenda V, Githuku J, Gathecha G, Wambugu BM, Roka ZG, Ong'or WO. Prevalence and factors associated with chronic kidney disease among medical inpatients at the Kenyatta National Hospital, Kenya, 2018: a cross-sectional study. Pan Afr Med J 2019; 33:321. [PMID: 31692795 PMCID: PMC6815467 DOI: 10.11604/pamj.2019.33.321.18114] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2019] [Accepted: 05/02/2019] [Indexed: 11/29/2022] Open
Abstract
INTRODUCTION The burden of chronic kidney disease (CKD) is increasing worldwide. Few studies in low and low-middle income countries have estimated the prevalence of CKD. We aimed to estimate prevalence and factors associated with CKD among medical inpatients at the largest referral hospital in Kenya. METHODS We conducted a cross-sectional study among medical inpatients at the Kenyatta National Hospital. We used systematic sampling and collected demographic information, behavioural risk factors, medical history, underlying conditions, laboratory and imaging workup using a structured questionnaire. We estimated glomerular filtration rate (GFR) in ml/min/1.73m2 classified into 5 stages; G1 (≥ 90), G2 (60-89), G3a (45-59), G3b (30-44), G4 (15-29) and G5 (<15, or treated by dialysis/renal transplant). Ethical approval was obtained from Kenyatta National Hospital-University of Nairobi Ethics and Research Committee (KNH-UoN ERC), approval number P510/09/2017. We estimated prevalence of CKD and used logistic regression to determine factors independently associated with CKD diagnosis. RESULTS We interviewed 306 inpatients; median age 40.0 years (IQR 24.0), 162 (52.9%) were male, 155 (50.7%) rural residents. CKD prevalence was 118 patients (38.6%, 95% CI 33.3-44.1); median age 42.5 years (IQR 28.0), 74 (62.7%) were male, 64 (54.2%) rural residents. Respondents with CKD were older than those without (difference 4.4 years, 95% CI 3.7-8.4 years, P = 0.032). Fifty-six (47.5%) of the patients had either stage G1 or G2, 17 (14.4%) had end-stage renal disease; 64 (54.2%) had haemoglobin below 10g/dl while 33 (28.0%) had sodium levels below 135 mmol/l. ). History of unexplained anaemia (aOR 1.80, 95% CI 1.02-3.19), proteinuria (aOR 5.16, 95% CI 2.09-12.74), hematuria (aOR 7.68, 95% CI 2.37-24.86); hypertension (aOR 2.71, 95% CI 1.53-4.80) and herbal medications use (aOR 1.97, 95% CI 1.07-3.64) were independently associated with CKD. CONCLUSION Burden of CKD was high among this inpatient population. Haematuria and proteinuria can aid CKD diagnosis. Public awareness on health hazards of herbal medication use is necessary.
Collapse
Affiliation(s)
- Valerian Mwenda
- Field Epidemiology and Laboratory Training Programme, Ministry of Health, Nairobi, Kenya
- Division of Non-communicable Diseases, Ministry of Health, Nairobi Kenya
| | - Jane Githuku
- Field Epidemiology and Laboratory Training Programme, Ministry of Health, Nairobi, Kenya
| | - Gladwell Gathecha
- Division of Non-communicable Diseases, Ministry of Health, Nairobi Kenya
| | | | - Zeinab Gura Roka
- Field Epidemiology and Laboratory Training Programme, Ministry of Health, Nairobi, Kenya
| | | |
Collapse
|
17
|
Mwenda V, Niyomwungere A, Oyugi E, Githuku J, Obonyo M, Gura Z. Cholera outbreak during a scientific conference at a Nairobi hotel, Kenya 2017. J Public Health (Oxf) 2019; 43:e140-e144. [DOI: 10.1093/pubmed/fdz078] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Revised: 06/14/2019] [Accepted: 06/19/2019] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
Cholera globally affects 1.3–4.0 million people and causes 21 000–143 000 deaths annually. In June 2017, a cluster of diarrhoeal illness occurred among participants of an international scientific conference at a hotel in Nairobi, Kenya. Culture confirmed Vibrio cholerae, serotype Ogawa. We investigated to assess magnitude, identify likely exposures and suggest control measures.
Methods
We carried out a retrospective cohort study utilizing a structured questionnaire administered by telephone, email and internet-based survey. We calculated food-specific attack rates, risk ratios and in a nested-case control analysis, performed logistic regression to identify exposures independently associated with the outbreak.
Results
We interviewed 249 out of 456 conference attendees (response rate=54.6%). Mean age of respondents was 37.8 years, ±8.3 years, 131 (52.6%) were male. Of all the respondents, 137 (55.0%) were cases. Median incubation time was 35 (11–59) hours. Eating chicken (adjusted OR 2.49, 95% CI, 1.22–5.06) and having eaten lunch on Tuesday (adjusted OR 2.34, 95% CI 1.09–5.05) were independently associated with illness; drinking soda was protective (adjusted OR 0.17, 95% CI 0.07–0.42).
Conclusion
Point source outbreak, associated with chicken eaten at lunch on Tuesday 20th June 2017 occurred. We recommend better collaboration between the food and health sectors in food-borne outbreak investigations.
Collapse
Affiliation(s)
- Valerian Mwenda
- Field Epidemiology and Laboratory Training Programme, Ministry of Health, Nairobi, Kenya
| | - Alexis Niyomwungere
- Field Epidemiology and Laboratory Training Programme, Ministry of Health, Nairobi, Kenya
- Disease Surveillance and Response Unit, Ministry of Health, Nairobi, Kenya
| | - Elvis Oyugi
- Field Epidemiology and Laboratory Training Programme, Ministry of Health, Nairobi, Kenya
| | - Jane Githuku
- Field Epidemiology and Laboratory Training Programme, Ministry of Health, Nairobi, Kenya
| | - Mark Obonyo
- Field Epidemiology and Laboratory Training Programme, Ministry of Health, Nairobi, Kenya
| | - Zeinab Gura
- Field Epidemiology and Laboratory Training Programme, Ministry of Health, Nairobi, Kenya
| |
Collapse
|
18
|
Mwenda V, Mwangi M, Nyanjau L, Gichu M, Kyobutungi C, Kibachio J. Dietary risk factors for non-communicable diseases in Kenya: findings of the STEPS survey, 2015. BMC Public Health 2018; 18:1218. [PMID: 30400904 PMCID: PMC6219002 DOI: 10.1186/s12889-018-6060-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Burden of non-communicable diseases (NCD) is increasing worldwide. Risk factor surveillance informs public health interventions in NCD control. This study describes the dietary risk factors for NCD found in the Kenya STEPS survey, 2015. METHODS We performed secondary analysis of the STEPS dataset to determine prevalence of dietary NCD risk factors and their determinants. New variables were created; high dietary salt, defined as addition of salt while eating or intake of processed foods high in salt and high dietary sugar, defined as intake of processed foods or drinks high in sugar in most meals or addition of sugar to beverages already with sugar, on a daily basis. We used the World Health Organization definition of minimum required intake of fruits and vegetables as consumption of less than five servings of fruits and vegetables per day. Perceptions of respondents on diet and health were also assessed. Accounting for complex survey sampling, we calculated prevalence of the various dietary modifiable determinants and adjusted odds ratios (AOR) to identify factors independently associated with dietary NCD risk factors. RESULTS Of the 4484 individuals surveyed; mean age was 40.5 years (39.9-41.1 years), 60% were female. Prevalence of high reported dietary salt intake was 18.3% (95% CI 17.2%, 19.5%) and sugar 13.7% (95% CI 11.7-15.8%). Awareness of health risk from dietary salt was 88% and 91% for dietary sugar. Approximately 56% of the respondents were implementing strategies to reduce dietary salt and 54% were doing the same for dietary sugar. Only 6.0% (95% CI 4.3-7.6%) of the respondents reported intake of a minimum of five servings of both fruits and vegetables daily. Unhealthy diet was associated with being male (AOR 1.33, 95% CI 1.04, 1.70,), age below 46 years (AOR 1.78, 95% CI 1.42, 2.12) and being a student (AOR 15.6, 95% CI 2.44, 99.39). CONCLUSION Dietary risk communication should be targeted to males and people under 45 years of age, especially students. Further research is necessary to understand the knowledge: practice mismatch on unhealthy diets.
Collapse
Affiliation(s)
- Valerian Mwenda
- Field Epidemiology and Laboratory Training Programme, Ministry of Health, Nairobi, Kenya
- Non-communicable disease division, Ministry of Health, Nairobi, Kenya
| | - Martin Mwangi
- Field Epidemiology and Laboratory Training Programme, Ministry of Health, Nairobi, Kenya
- Non-communicable disease division, Ministry of Health, Nairobi, Kenya
| | - Loise Nyanjau
- Non-communicable disease division, Ministry of Health, Nairobi, Kenya
| | - Muthoni Gichu
- Non-communicable disease division, Ministry of Health, Nairobi, Kenya
| | | | - Joseph Kibachio
- Non-communicable disease division, Ministry of Health, Nairobi, Kenya
- The Institute of Global Health, Faculty of Medicine, University of Geneva (UNIGE), Geneva, Switzerland
| |
Collapse
|
19
|
Kluyts HL, le Manach Y, Munlemvo DM, Madzimbamuto F, Basenero A, Coulibaly Y, Rakotoarison S, Gobin V, Samateh AL, Chaibou MS, Omigbodun AO, Amanor-Boadu SD, Tumukunde J, Madiba TE, Pearse RM, Biccard BM, Abbas N, Abdelatif AI, Abdoulaye T, Abd-rouf A, Abduljalil A, Abdulrahman A, Abdurazig S, Abokris A, Abozaid W, Abugassa S, Abuhdema F, Abujanah S, Abusamra R, Abushnaf A, Abusnina S, Abuzalout T, Ackermann H, Adamu Y, Addanfour A, Adeleke D, Adigun T, Adisa A, Adjignon SV, Adu-Aryee N, Afolabi B, Agaba A, Agaba P, Aghadi K, Agilla H, Ahmed B, Ahmed EZ, Ahmed AJ, Ahmed M, Ahossi R, Aji S, Akanyun S, Akhideno I, Akhter M, Akinyemi O, Akkari M, Akodjenou J, AL Samateh A, al Shams E, Alagbe-Briggs O, Alakkari E, Alalem R, Alashhab M, Alatise O, Alatresh A, Alayeb Alayeb M, Albakosh B, Albert F, Alberts A, Aldarrat A, Alfari A, Alfetore A, Algbali M, Algddar A, Algedar H, Alghafoud I, Alghazali A, Alhajj M, Alhendery Alhendery A, Alhoty F, Ali A, Ali Y, Ali A, Alioune BS, Alkassem M, Alkchr M, Alkesa T, Alkilani A, Alkobty Alkobty F, Allaye T, Alleesaib S, Alli A, Allopi K, Allorto N, Almajbery A, Almesmary R, Almisslati S, Almoraid F, Alobeidi H, Swaleh A, Swayeb E, Szpytko A, Taiwo N, Tarhuni A, Tarloff D, Tchaou B, Tchegnonsi C, Tchoupa M, Teeka M, Alomami M, Thakoor B, Theunissen M, Thomas B, Thomas M, Thotharam A, Tobiko O, Torborg A, Tshisekedi S, Tshisola S, Tshitangano R, Alphonsus CS, Tshivhula F, Tshuma H, Tumukunde J, Tun M, Udo I, Uhuebor D, Umeh K, Usenbo A, Uwiteyimbabazi J, Van der Merwe D, Alqawi O, van der Merwe F, van der Walt J, van Dyk D, Van Dyk J, van Niekerk J, van Wyk S, van Zyl H, Veerasamy B, Venter P, Vermeulen A, Alraheem A, Villarreal R, Visser J, Visser L, Voigt M, von Rahden RP, Wafa A, Wafula A, Wambugu P, Waryoba P, Waweru E, Alsabri S, Weideman M, Wise RD, Wynne E, Yahya A, Yahya A, Yahya R, Yakubu Y, Yanga J, Yangazov Y, Yousef O, Alsayed A, Yousef G, Youssouf C, Yunus A, Yusuf A, Zeiton A, Zentuti H, Zepharine H, Zerihun A, Zhou S, Zidan A, Alsellabi B, Zimogo Zié S, Zinyemba C, Zo A, Zomahoun L, Zoobei N, Zoumenou E, Zubia N, Al-Serksi M, Alshareef M, Altagazi A, Aluvale J, Alwahedi H, Alzahra E, Alzarouk M, Al-Zubaidy K, Amadou M, Amadou M, Amanor-Boadu SD, Amer AA, Amisi B, Amuthenu M, Anabah T, Anani F, Anderson P, Andriamampionona A, Andrianina L, Anele A, Angelin R, Anjar N, Antùnez O, Antwi-Kusi A, Anyanwu L, Aribi A, Arowolo O, Arrey O, Ashebir DZ, Assefa S, Assoum G, Athanse V, Athombo J, Atiku M, Atito-Narh E, Atomabe A, Attia A, Aungraheeta M, Aurélia D, Ayandipo O, Ayebale A, Azzaidey H, Babajee N, Badi H, Badianga E, Baghni R, Bahta M, Bai M, Baitchu Y, Baloyi A, Bamuza K, Bamuza M, Bangure L, Bankole O, Barongo M, Barow M, Basenero A, Bashiya L, Basson C, Bechan S, Belhaj S, Ben Mansour M, Benali D, Benamour A, Berhe A, Bertie J, Bester J, Bester M, Bezuidenhout J, Bhagwan K, Bhagwandass D, Bhat K, Bhuiyan M, Biccard BM, Bigirimana F, Bikuelo C, Bilby B, Bingidimi S, Bischof K, Bishop DG, Bitta C, Bittaye M, Biyase T, Blake C, Blignaut E, Blignaut F, BN Tanjong B, Bogoslovskiy A, Boloko P, Boodhun S, Bori I, Boufas F, Brand M, Brouckaert NT, Bruwer J, Buccimazza I, Bula Bula I, Bulamba F, Businge B, Bwambale Y, Cacala S, Cadersa M, Cairns C, Carlos F, Casey M, Castro A, Chabayanzara N, Chaibou M, Chaibva T, Chakafa N, Chalo C, Changfoot C, Chari M, Chelbi L, Chibanda J, Chifamba H, Chikh N, Chikumba E, Chimberengwa P, Chirengwa J, Chitungo F, Chiwanga M, Chokoe M, Chokwe T, Chrirangi B, Christian M, Church B, Cisekedi J, Clegg-Lamptey J, Cloete E, Coltman M, Conradie W, Constance N, Coulibaly Y, Cronje L, Da Silva M, Daddy H, Dahim L, Daliri D, Dambaki M, Dasrath A, Davids J, Davies GL, De Lange J, de Wet J, Dedekind B, Degaulle M, Dehal V, Deka P, Delinikaytis S, Desalu I, Dewanou H, Deye MM, Dhege C, Diale B, Dibwe D, Diedericks B, Dippenaar J, Dippenaar L, Diyoyo M, Djessouho E, Dlamini S, Dodiyi-Manuel A, Dokolwana B, Domoyyeri D, Drummond LW, du Plessis D, du Plessis W, du Preez L, Dube K, Dube N, Dullab K, Duvenhage R, Echem R, Edaigbini S, Egote A, Ehouni A, Ekwen G, Ekwunife N, El Hensheri M, Elfaghi I, Elfagieh M, Elfallah S, Elfiky M, Elgelany S, Elghallal A, Elghandouri M, Elghazal Z, Elghobashy A, Elharati F, Elkhogia AM, Elkhwildi R, Ellis S, Elmadani L, Elmadany H, Elmehdawi H, Elmgadmi A, Eloi H, Elrafifi D, Elsaadi G, Elsaity R, Elshikhy A, Eltaguri M, Elwerfelli A, Elyasir I, Elzoway A, Elzufri A, Enendu E, Enicker B, Enwerem E, Esayas R, Eshtiwi M, Eshwehdi A, Esterhuizen J, Esterhuizen TM, Etuk E, Eurayet O, Eyelade O, Fanjandrainy R, Fanou L, Farina Z, Fawzy M, Feituri A, Fernandes N, Ford L, Forget P, François T, Freeman T, Freeman Y, Gacii V, Gadi B, Gagara M, Gakenia A, Gallou P, Gama G, Gamal M, Gandy Y, Ganesh A, Gangaly D, Garcia M, Gatheru A, Gaya S, Gbéhadé O, Gerbel G, Ghnain A, Gigabhoy R, Giles D, Girmaye G, Gitau S, Githae B, Gitta S, Gobin V, Goga R, Gomati A, Gonzalez M, Gopall J, Gordon CS, Gorelyk O, Gova M, Govender K, Govender P, Govender S, Govindasamy V, Green-Harris J, Greenwood M, Grey-Johnson S, Grobbelaar M, Groenewald M, Grünewald K, Guegni A, Guenane M, Gueye S, Guezo M, Gunguwo T, Gweder M, Gwila M, Habimana L, Hadecon R, Hadia E, Hamadi L, Hammouda M, Hampton M, Hanta R, Hardcastle TC, Hariniaina J, Hariparsad S, Harissou A, Harrichandparsad R, Hasan S, Hashmi H, Hayes M, Hdud A, Hebli S, Heerah H, Hersi S, Hery A, Hewitt-Smith A, Hlako T, Hodges S, Hodgson RE, Hokoma M, Holder H, Holford E, Horugavye E, Houston C, Hove M, Hugo D, Human C, Hurri H, Huwidi O, Ibrahim A, Ibrahim T, Idowu O, Igaga I, Igenge J, Ihezie O, Ikandi K, Ike I, Ikuku J, Ilbarasi M, Ilunga I, Ilunga J, Imbangu N, Imessaoudene Z, Imposo D, Iraya A, Isaacs M, Isiguzo M, Issoufou A, Izquirdo P, Jaber A, Jaganath U, Jallow C, Jamabo S, Jamal Z, Janneh L, Jannetjies M, Jasim I, Jaworska MA, Jay Narain S, Jermi K, Jimoh R, Jithoo S, Johnson M, Joomye S, Judicael R, Judicaël M, Juwid A, Jwambi L, Kabango R, Kabangu J, Kabatoro D, Kabongo A, Kabongo K, Kabongo L, Kabongo M, Kady N, Kafu S, Kaggya M, Kaholongo B, Kairuki P, Kakololo S, Kakudji K, Kalisa A, Kalisa R, Kalufwelu M, Kalume S, Kamanda R, Kangili M, Kanoun H, Kapesa, Kapp P, Karanja J, Karar M, Kariuki K, Kaseke K, Kashuupulwa P, Kasongo K, Kassa S, Kateregga G, Kathrada M, Katompwa P, Katsukunya L, Kavuma K, Khalfallah, Khamajeet A, Khetrish S, Kibandwa, Kibochi W, Kilembe A, Kintu A, Kipng’etich B, Kiprop B, Kissoon V, Kisten TK, Kiwanuka J, Kluyts HL, Knox M, Koledale A, Koller V, Kolotsi M, Kongolo M, Konwuoh N, Koperski W, Koraz M, Kornilov A, Koto MZ, Kransingh S, Krick D, Kruger S, Kruse C, Kuhn W, Kuhn W, Kukembila A, Kule K, Kumar M, Kusel BS, Kusweje V, Kuteesa K, Kutor Y, Labib M, Laksari M, Lanos F, Lawal T, Le Manach Y, Lee C, Lekoloane R, Lelo S, Lerutla B, Lerutla M, Levin A, Likongo T, Limbajee M, Linyama D, Lionnet C, Liwani M, Loots E, Lopez AG, Lubamba C, Lumbala K, Lumbamba A, Lumona J, Lushima R, Luthuli L, Luweesi H, Lyimo T, Maakamedi H, Mabaso B, Mabina M, Maboya M, Macharia I, Macheka A, Machowski A, Madiba TE, Madsen A, Madzimbamuto F, Madzivhe L, Mafafo S, Maghrabi M, Mahamane DD, Maharaj A, Maharaj A, Maharaj A, Mahmud M, Mahoko M, Mahomedy N, Mahomva O, Mahureva T, Maila R, Maimane D, Maimbo M, Maina S, Maiwald DA, Maiyalagan M, Majola N, Makgofa N, Makhanya V, Makhaye W, Makhlouf N, Makhoba S, Makopa E, Makori O, Makupe AM, Makwela M, Malefo M, Malongwe S, Maluleke D, Maluleke M, Mamadou KT, Mamaleka M, Mampangula Y, Mamy R, Mananjara M, Mandarry M, Mangoo D, Manirimbere C, Manneh A, Mansour A, Mansour I, Manvinder M, Manyere D, Manzini V, Manzombi J, Mapanda P, Marais L, Maranga O, Maritz J, Mariwa F, Masela R, Mashamba M, Mashava DM, Mashile M, Mashoko E, Masia O, Masipa J, Masiyambiri A, Matenchi M, Mathangani W, Mathe R, Matola CY, Matondo P, Matos-Puig R, Matoug F, Matubatuba J, Mavesere H, Mavhungu R, Maweni S, Mawire C, Mawisa T, Mayeza S, Mbadi R, Mbayabu M, Mbewe N, Mbombo W, Mbuyi T, Mbuyi W, Mbuyisa M, Mbwele B, Mehyaoui R, Menkiti I, Mesarieki L, Metali A, Mewanou S, Mgonja L, Mgoqo N, Mhatu S, Mhlari T, Miima S, Milod I, Minani P, Mitema F, Mlotshwa A, Mmasi J, Mniki T, Mofikoya B, Mogale J, Mohamed A, Mohamed A, Mohamed A, Mohamed S, Mohamed S, Mohamed T, Mohamed A, Mohamed A, Mohamed A, Mohamed P, Mohammed I, Mohammed F, Mohammed M, Mohammed N, Mohlala M, Mokretar R, Molokoane F, Mongwe K, Montenegro L, Montwedi O, Moodie Q, Moopanar M, Morapedi M, Morulana T, Moses V, Mossy P, Mostafa H, Motilall S, Motloutsi S, Moussa K, Moutari M, Moyo O, Mphephu P, Mrara B, Msadabwe C, Mtongwe V, Mubeya F, Muchiri K, Mugambi J, Muguti G, Muhammad A, Mukama I, Mukenga M, Mukinda F, Mukuna P, Mungherera A, Munlemvo DM, Munyaradzi T, Munyika A, Muriithi J, Muroonga M, Murray R, Mushangwe V, Mushaninga M, Musiba V, Musowoya J, Mutahi S, Mutasiigwa M, Mutizira G, Muturi A, Muzenda T, Mvwala K, Mvwama N, Mwale A, Mwaluka C, Mwamba J, Mwanga H, Mwangi C, Mwansa S, Mwenda V, Mwepu I, Mwiti T, Mzezewa S, Nabela L, Nabukenya M, Nabulindo S, Naicker K, Naidoo D, Naidoo L, Naidoo L, Naidoo N, Naidoo R, Naidoo R, Naidoo S, Naidoo T, Naidu T, Najat N, Najm Y, Nakandungile F, Nakangombe P, Namata C, Namegabe E, Nansook A, Nansubuga N, Nantulu C, Nascimento R, Naude G, Nchimunya H, Ndaie M, Ndarukwa P, Ndasi H, Ndayisaba G, Ndegwa D, Ndikumana R, Ndonga AK, Ndung’u C, Neil M, Nel M, Neluheni E, Nesengani D, Nesengani N, Netshimboni L, Ngalala A, Ngari B, Ngari N, Ngatia E, Ngcobo G, Ngcobo T, Ngorora D, Ngouane D, Ngugi K, Ngumi ZW, Nibe Z, Ninise E, Niyondiko J, Njenga P, Njenga M, Njoroge M, Njoroge S, Njuguna W, Njuki P, Nkesha T, Nkuebe T, Nkuliyingoma N, Nkunjana M, Nkwabi E, Nkwine R, Nnaji C, Notoane I, Nsalamba S, Ntlhe L, Ntoto C, Ntueba B, Nyassi M, Nyatela-Akinrinmade Z, Nyawanda H, Nyokabi N, Nziene V, Obadiah S, Ochieng O, Odia P, Oduor O, Ogboli-Nwasor E, Ogendo S, Ogunbode O, Ogundiran T, Ogutu O, Ojewola R, Ojujo M, Ojuka D, Okelo O, Okiya S, Okonu N, Olang P, Omigbodun AO, Omoding S, Omoshoro-Jones J, Onyango R, Onyegbule A, Orjiako O, Osazuwa M, Oscar K, Osinaike B, Osinowo A, Othin O, Otman F, Otokwala J, Ouanes F, Oumar O, Ousseini A, Padayachee S, Pahlana S, Pansegrouw J, Paruk F, Patel M, Patel U, Patience A, Pearse RM, Pembe J, Pengemale G, Perez N, Aguilera Perez M, Peter AM, Phaff M, Pheeha R, Pienaar B, Pillay V, Pilusa K, Pochana M, Polishchuk O, Porrill OS, Post E, Prosper A, Pupyshev M, Rabemazava A, Rabiou M, Rademan L, Rademeyer M, Raherison R, Rajah F, Rajcoomar M, Rakhda Z, Rakotoarijaona A, Rakotoarisoa A, Rakotoarison SR, Rakotoarison R, Ramadan L, Ramananasoa M, Rambau M, Ramchurn T, Ramilson H, Ramjee RJ, Ramnarain H, Ramos R, Rampai T, Ramphal S, Ramsamy T, Ramuntshi R, Randolph R, Randriambololona D, Ras W, Rasolondraibe R, Rasolonjatovo J, Rautenbach R, Ray S, Rayne SR, Razanakoto F, Reddy S, Reed AR, Rian J, Rija F, Rink B, Robelie A, Roberts C, Rocher A, Rocher S, Rodseth RN, Rois I, Rois W, Rokhsi S, Roos J, Rorke NF, Roura H, Rousseau F, Rousseau N, Royas L, Roytowski D, Rungan D, Rwehumbiza S, Ryabchiy B, Ryndine V, Saaiman C, Sabwa H, Sadat S, Saed S, Salaheddin E, Salaou H, Saleh M, Salisu-Kabara H, Doles Sama H, Samateh AL, Sam-Awortwi W, Samuel N, Sanduku D, Sani CM, Sanyang L, Sarah H, Sarkin-Pawa A, Sathiram R, Saurombe T, Schutte H, Sebei M, Sedekounou M, Segooa M, Semenya E, Semo B, Sendagire C, Senoga S, Senusi F, Serdyn T, Seshibe M, Shah G, Shamamba R, Shambare C, Shangase T, Shanin S, Shefren I, Sheshe A, Shittu O, Shkirban A, Sholadoye T, Shubba A, Sigcu N, Sihope S, Sikazwe D, Sikombe B, Simaga Abdoul K, Simo W, Singata K, Singh A, Singh S, Singh U, Sinoamadi V, Sipuka N, Sithole N, Sitima S, Skinner DL, Skinner G, Smith O, Smits C, Sofia M, Sogoba G, Sohoub A, Sookun S, Sosinska O, Souhe R, Souley G, Souleymane T, Spicer J, Spijkerman S, Steinhaus H, Steyn A, Steyn G, Steyn H, Stoltenkamp HL, Stroyer S. The ASOS Surgical Risk Calculator: development and validation of a tool for identifying African surgical patients at risk of severe postoperative complications. Br J Anaesth 2018; 121:1357-1363. [PMID: 30442264 DOI: 10.1016/j.bja.2018.08.005] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Revised: 07/19/2018] [Accepted: 08/06/2018] [Indexed: 10/28/2022] Open
Abstract
BACKGROUND The African Surgical Outcomes Study (ASOS) showed that surgical patients in Africa have a mortality twice the global average. Existing risk assessment tools are not valid for use in this population because the pattern of risk for poor outcomes differs from high-income countries. The objective of this study was to derive and validate a simple, preoperative risk stratification tool to identify African surgical patients at risk for in-hospital postoperative mortality and severe complications. METHODS ASOS was a 7-day prospective cohort study of adult patients undergoing surgery in Africa. The ASOS Surgical Risk Calculator was constructed with a multivariable logistic regression model for the outcome of in-hospital mortality and severe postoperative complications. The following preoperative risk factors were entered into the model; age, sex, smoking status, ASA physical status, preoperative chronic comorbid conditions, indication for surgery, urgency, severity, and type of surgery. RESULTS The model was derived from 8799 patients from 168 African hospitals. The composite outcome of severe postoperative complications and death occurred in 423/8799 (4.8%) patients. The ASOS Surgical Risk Calculator includes the following risk factors: age, ASA physical status, indication for surgery, urgency, severity, and type of surgery. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.805 and good calibration with c-statistic corrected for optimism of 0.784. CONCLUSIONS This simple preoperative risk calculator could be used to identify high-risk surgical patients in African hospitals and facilitate increased postoperative surveillance. CLINICAL TRIAL REGISTRATION NCT03044899.
Collapse
Affiliation(s)
- H-L Kluyts
- Department of Anaesthesiology, Sefako Makgatho Health Sciences University, Pretoria, Gauteng, South Africa
| | - Y le Manach
- Department of Anesthesia, Michael DeGroote School of Medicine, Faculty of Health Sciences, McMaster University and Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Perioperative Medicine and Surgical Research Unit, Hamilton, ON, Canada; Department of Clinical Epidemiology and Biostatistics, Michael DeGroote School of Medicine, Faculty of Health Sciences, McMaster University and Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Perioperative Medicine and Surgical Research Unit, Hamilton, ON, Canada
| | - D M Munlemvo
- University Hospital of Kinshasa, Kinshasa, Democratic Republic of Congo
| | - F Madzimbamuto
- Department of Anaesthesia and Critical Care Medicine, University of Zimbabwe College of Health Sciences, Harare, Zimbabwe
| | - A Basenero
- Ministry of Health and Social Services Namibia, Windhoek, Namibia
| | - Y Coulibaly
- Department, Faculté de médicine de Bamako, Bamako, Mali
| | | | - V Gobin
- Ministry of Health and Quality of Life, Jawaharlal Nehru Hospital, Rose Belle, Grand Port, Mauritius
| | - A L Samateh
- Department of Surgery, Edward Francis Small Teaching Hospital, Banjul, Gambia
| | - M S Chaibou
- Department of Anesthesiology, Intensive Care and Emergency, National Hospital of Niamey, Niamey, Niger
| | - A O Omigbodun
- Department of Obstetrics and Gynaecology, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria
| | - S D Amanor-Boadu
- Department of Anaesthesia, University College Hospital, Ibadan, Oyo State, Nigeria
| | - J Tumukunde
- Makerere University, Makerere, Kampala, Uganda
| | - T E Madiba
- Department of Surgery, University of KwaZulu-Natal, Durban, KwaZulu-Natal, South Africa
| | - R M Pearse
- Intensive Care Medicine, Queen Mary University of London, London, UK
| | - B M Biccard
- Department of Anaesthesia and Perioperative Medicine, Groote Schuur Hospital, Faculty of Health Sciences, University of Cape Town, Observatory, Western Cape, South Africa.
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
20
|
Mwenda V, Gathecha G, Kendagor A, Kibachio J, Macharia E. Characteristics and factors associated with tobacco use: findings of Kenya Global Adult Tobacco Survey, 2014. Tob Induc Dis 2018. [DOI: 10.18332/tid/83982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
|