Comorbidities in Privately Insured South Africans With Systemic Lupus Erythematosus

Introduction Comorbidities in systemic lupus erythematosus (SLE) impact negatively on health-related quality of life (HRQoL) and life expectancy. We investigated the frequency and spectrum of comorbidities in privately insured South Africans with SLE. Methods The data of SLE patients based on International Classification of Diseases, Tenth Revision (ICD-10) codes and insured with Discovery Health Medical Scheme (DHMS), South Africa, aged ≥16 years at diagnosis and with ≥6 months of follow-up were reviewed. Demographics, comorbidities listed in the Charlson comorbidity index (CCI), other common comorbidities, intercurrent illnesses, and drug therapy were documented. Results Of the 520 patients coded as SLE, 207 met the inclusion criteria. Most were females (90.8%), with a median (interquartile range {IQR}) age and follow-up duration of 39 (30.3-53.0) and 6.1 (3.7-8.1) years, respectively. All patients had at least one comorbidity; the most frequent CCI comorbidities were pulmonary disease (30.9%), congestive heart failure (CHF, 15%), and renal disease (14.0%). Other common comorbidities were hypertension (53.1%) and mood and anxiety disorders (46.9%). Urinary tract infections (UTIs, 37.7%) and pneumonia (33.8%) were common intercurrent illnesses. The independent predictors of CHF were renal disease (odds ratio {OR}=855), dyslipidemia (OR=15.3), and male gender (OR=43.0); the independent predictors of hypertension were age at diagnosis (OR=1.03), type 2 diabetes (OR=4.45), and renal disease (OR=4.34); and the independent predictors of mood and anxiety disorders were female gender (OR=3.98), stroke (OR=3.18), UTI (OR=2.39), and chloroquine use (OR=1.94). Conclusion In this study of privately insured South Africans with SLE, comorbidities were common, and all patients had at least one comorbidity. Hypertension, infections, and mood and anxiety disorders were the leading comorbidities overall, and pulmonary disease was the most common CCI comorbidity. There is an obvious need to formally study the burden of mental health disorders in South African SLE patients.

Pancreatic cancer mortality in South Africa: A case-control study

BACKGROUND

There are variations in the numbers of pancreatic cancer deaths reported annually in South Africa (SA). Since pancreatic cancer deaths in SA from 1997 to 2016, the number of cases has hugely increased, and reached 23 581 in both sexes. Sex differences are likely to contribute to the variations in the strength of associations between the risk factors and pancreatic cancer mortality.

OBJECTIVE

To identify factors associated with an increased risk of pancreatic cancer mortality in SA.

METHODS

A matched case-control study with 1:1 matching was conducted using data collected by Statistics SA from 1997 to 2016. Controls were randomly selected to be as similar as possible to the cases, and matched by age, sex and year of death. Conditional logistic regression was used to identify factors associated with pancreatic cancer mortality.

RESULTS

This case-control study comprised a final selection of 23 581 cases (12 171 males and 11 410 females) and 23 581 controls (12 171 males and 11 410 females). A significantly increased risk of pancreatic cancer mortality was observed among males who were managers (odds ratio (OR) 2.99; 95% confidence interval (CI) 1.36 - 6.60; p=0.006) and craft and related trade workers (OR 1.89; 95% CI 1.14 - 3.14; p=0.013). Elevated risks of pancreatic cancer mortality were also found among females who were managers (OR 6.13; 95% CI 1.32 - 28.52; p=0.021), professionals (OR 2.12; 95% CI 1.24 - 3.63; p=0.006), clerical support workers (OR 3.78; 95% CI 1.79 - 7.98; p=0.001) and elementary occupation workers (OR 1.41; 95% CI 0.99 - 2.00; p=0.059). Smoking was significantly associated with pancreatic cancer mortality in females (OR 1.36; 95% CI 1.02 - 1.82; p=0.039). Working in several occupations was associated with an increased risk of pancreatic cancer mortality in males (OR 1.31; 95% CI 1.01 - 1.71; p=0.045) and females (OR 1.66; 95% CI 1.30 - 2.12; p<0.001).

CONCLUSION

Smoking and certain occupations increased the risk of pancreatic cancer mortality. Further research is needed to evaluate the associations between other extrinsic and intrinsic factors and pancreatic cancer mortality.

Spatial heterogeneity in relationship between district patterns of HIV incidence and covariates in Zimbabwe: a multi-scale geographically weighted regression analysis

A study was conducted to investigate the district-level patterns of incidence of the human immunodeficiency virus (HIV) in Zimbabwe in the period 2005-2015 and explore variations in the relationship between covariates and HIV incidence across different districts. Demographic health survey data were analysed using hotspot analysis, spatial autocorrelation, and multi-scale geographically weighted regression (MGWR) techniques. The analysis revealed hotspots of the HIV epidemic in the southern and western regions of Zimbabwe in contrast to the eastern and northern regions. Specific districts in Matabeleland South and Matabeleland North provinces showed clusters of HIV incidence in 2005-2006, 2010-2011 and 2015. Variables studied were multiple sex partners and sexually transmitted infections (STI) condom use and being married. Recommendations include implementing targeted HIV prevention programmes in identified hotspots, prioritising interventions addressing the factors mentioned above as well as enhancing access to HIV testing and treatment services in high-risk areas, strengthening surveillance systems, and conducting further research to tailor interventions based on contextual factors. The study also emphasizes the need for regular monitoring and evaluation at the district level to inform effective responses to the HIV epidemic over time. By addressing the unique challenges and risk factors in different districts, significant progress can be made in reducing HIV transmission and improving health outcomes in Zimbabwe. These findings should be valuable for policymakers in resource allocation and designing evidence-based interventions.

Predicting the drop out from the maternal, newborn and child healthcare continuum in three East African Community countries: application of machine learning models

BACKGROUND

For optimal health, the maternal, newborn, and child healthcare (MNCH) continuum necessitates that the mother/child receive the full package of antenatal, intrapartum, and postnatal care. In sub-Saharan Africa, dropping out from the MNCH continuum remains a challenge. Using machine learning, the study sought to forecast the MNCH continuum drop out and determine important predictors in three East African Community (EAC) countries.

METHODS

The study utilised Demographic Health Surveys data from the Democratic Republic of Congo (DRC) (2013/14), Kenya (2014) and Tanzania (2015/16). STATA 17 was used to perform the multivariate logistic regression. Python 3.0 was used to build five machine learning classification models namely the Logistic Regression, Random Forest, Decision Tree, Support Vector Machine and Artificial Neural Network. Performance of the models was assessed using Accuracy, Precision, Recall, Specificity, F1 score and area under the Receiver Operating Characteristics (AUROC).

RESULTS

The prevalence of the drop out from the MNCH continuum was 91.0% in the DRC, 72.4% in Kenya and 93.6% in Tanzania. Living in the rural areas significantly increased the odds of dropping out from the MNCH continuum in the DRC (AOR:1.76;95%CI:1.30-2.38), Kenya (AOR:1.23;95%CI:1.03-1.47) and Tanzania (AOR:1.41;95%CI:1.01-1.97). Lower maternal education also conferred a significant increase in the DRC (AOR:2.16;95%CI:1.67-2.79), Kenya (AOR:1.56;95%CI:1.30-1.84) and Tanzania (AOR:1.70;95%CI:1.24-2.34). Non exposure to mass media also conferred a significant positive influence in the DRC (AOR:1.49;95%CI:1.15-1.95), Kenya (AOR:1.46;95%CI:1.19-1.80) and Tanzania (AOR:1.65;95%CI:1.13-2.40). The Random Forest exhibited superior predictive accuracy (Accuracy = 75.7%, Precision = 79.1%, Recall = 92.1%, Specificity = 51.6%, F1 score = 85.1%, AUROC = 70%). The top four predictors with the greatest influence were household wealth, place of residence, maternal education and exposure to mass media.

CONCLUSIONS

The MNCH continuum dropout rate is very high in the EAC countries. Maternal education, place of residence, and mass media exposure were common contributing factors to the drop out from MNCH continuum. The Random Forest had the highest predictive accuracy. Household wealth, place of residence, maternal education and exposure to mass media were ranked among the top four features with significant influence. The findings of this study can be used to support evidence-based decisions in MNCH interventions and to develop web-based services to improve continuity of care retention.

Estimating HIV incidence over a decade in Zimbabwe: A comparison of the catalytic and Farrington models

Over the years, numerous modelling studies have been proposed to estimate HIV incidence. As a result, this study aimed to evaluate two alternative methods for predicting HIV incidence in Zimbabwe between 2005 and 2015. We estimated HIV incidence from seroprevalence data using the catalytic and Farrington-2-parameter models. Data were obtained from 2005-06, 2010-11, and 2015 Zimbabwe Demographic Health Survey (ZDHS). These models were validated at the micro and macro-level using community-based cohort incidence and empirical estimates from UNAIDS EPP/SPECTRUM, respectively. The HIV incidence for the catalytic model was 0.32% (CI: 0.28%, 0.36%), 0.36% (CI: 0.33%, 0.39%), and 0.28% (CI: 0.26%, 0.30%), for the years 2005-06, 2010-11, and 2015, respectively. The HIV incidence for the Farrington model was 0.21% (CI: 0.16%, 0.26%), 0.22% (CI: 0.20%, 0.25%), and 0.19% (CI: 0.16%, 0.22%), for the years 2005-06, 2010-11, and 2015, respectively. According to these findings, the catalytic model estimated a higher HIV incidence rate than the Farrington model. Compared to cohort estimates, the estimates were within the observed 95% confidence interval, with 88% and 75% agreement for the catalytic and Farrington models, respectively. The limits of agreement observed in the Bland-Altman plot were narrow for all plots, indicating that our model estimates were comparable to cohort estimates. Compared to UNAIDS estimates, the catalytic model predicted a progressive increase in HIV incidence for males throughout all survey years. Without a doubt, HIV incidence declined with each subsequent survey year for all models. To improve programmatic and policy decisions in the national HIV response, we recommend the triangulation of multiple methods for incidence estimation and interpretation of results. Multiple estimating approaches should be considered to reduce uncertainty in the estimations from various models.

RETRACTED

BACKGROUND

Upon the addition of the numbers corresponding to various cancer anatomical locations in the report published by Statistics South Africa (StatsSA), the absolute number and proportion of deaths due to all cancers increased from 36 726 (8.0%) in 2013 to 40 460 (8.5%) in 2015. These high figures suggest that malignant neoplasms were in fact the second-most frequent cause of death in South Africa (SA) in 2013, and moved to the first rank in 2015.

OBJECTIVES

To support the initiative aimed at reducing cancer mortality in SA. To this purpose, we assessed trends in cancer mortality rates among males and females in SA from 1997 to 2016 to better understand the increasing threat of cancer mortality in SA.

METHODS

The general mortality data for the period 1997 - 2016, as captured from death certificates in SA, was retrieved from StatsSA. Agestandardised mortality rates (ASMR) for each year were computed using the world standard population structure proposed by Segi as the reference population. The adjusted rates were reported per 100 000 population per year. The years of potential productive life lost (YPPLL) due to cancer deaths were calculated for each age group and gender.

RESULTS

There were 681  689 total cancer deaths from 1997 to 2016, with 51.1% males and 48.9% females. Males had higher mortality rates than females. The ASMR ranged from 105.0 to 129.2 and 67.9 to 88.3 per 100 000 population per year among males and females, respectively. In 2004, the cancer mortality rate increased significantly among males (129.2 per 100 000 population), which was 1.5 times higher than in females (88.3 per 100 000 population). Among males, cancer of the lung had the highest YPPLL (394 779.3), followed by oesophageal (253 989.4) and liver (207 911.0). The YPPLL for cancer of the cervix (647 855.5) ranked first, followed by breast (483 863.6) and lung (146 304.6) in females.

CONCLUSION

Cancer mortality rates have increased since 1997, regardless of gender. Overall, there was a decline in YPPLL for cancer in the young population, while it increased in the adult population. A significant reduction in cancer deaths could be achieved by broadly applying effective interventions.

Cancer mortality distribution in South Africa, 1997-2016

Introduction

The mortality data in South Africa (SA) have not been widely used to estimate the patterns of deaths attributed to cancer over a spectrum of relevant subgroups. There is no research in SA providing patterns and atlases of cancer deaths in age and sex groups per district per year. This study presents age-sex-specific geographical patterns of cancer mortality at the district level in SA and their temporal evolutions from 1997 to 2016.

Methods

Individual mortality level data provided by Statistics South Africa were grouped by three age groups (0-14, 15-64, and 65+), sex (male and female), and aggregated at each of the 52 districts. The proportionate mortality ratios (PMRs) for cancer were calculated per 100 residents. The atlases showing the distribution of cancer mortality were plotted using ArcGIS. Spatial analyses were conducted through Moran's I test.

Results

There was an increase in PMRs for cancer in the age groups 15-64 and 65+ years from 2006 to 2016. Ranges were 2.83 (95% CI: 2.77-2.89) -4.16 (95% CI: 4.08-4.24) among men aged 15-64 years and 2.99 (95% CI: 2.93-3.06) -5.19 (95% CI: 5.09-5.28) among women in this age group. The PMRs in men and women aged 65+ years were 2.47 (95% CI: 2.42-2.53) -4.06 (95% CI: 3.98-4.14), and 2.33 (95% CI: 2.27-2.38) -4.19 (95% CI: 4.11-4.28). There were considerable geographical variations and similarities in the patterns of cancer mortality. For the age group 15-64 years, the ranges were 1.18 (95% CI: 0.78-1.71) -8.71 (95% CI: 7.18-10.47), p < 0.0001 in men and 1.35 (95% CI: 0.92-1.92) -10.83 (95% CI: 8.84-13.14), p < 0.0001 in women in 2016. There were higher PMRs among women in the Western Cape, Northern Cape, North West, and Gauteng compared to other areas. Similar patterns were also observed among men in these provinces, except in North West and Gauteng.

Conclusion

The identification of geographical and temporal distributions of cancer mortality provided evidence of periods and districts with similar and divergent patterns. This will contribute to understanding the past, present, future trends and formulating interventions at a local level.

Predicting HIV infection in the decade (2005-2015) pre-COVID-19 in Zimbabwe: A supervised classification-based machine learning approach

The burden of HIV and related diseases have been areas of great concern pre and post the emergence of COVID-19 in Zimbabwe. Machine learning models have been used to predict the risk of diseases, including HIV accurately. Therefore, this paper aimed to determine common risk factors of HIV positivity in Zimbabwe between the decade 2005 to 2015. The data were from three two staged population five-yearly surveys conducted between 2005 and 2015. The outcome variable was HIV status. The prediction model was fit by adopting 80% of the data for learning/training and 20% for testing/prediction. Resampling was done using the stratified 5-fold cross-validation procedure repeatedly. Feature selection was done using Lasso regression, and the best combination of selected features was determined using Sequential Forward Floating Selection. We compared six algorithms in both sexes based on the F1 score, which is the harmonic mean of precision and recall. The overall HIV prevalence for the combined dataset was 22.5% and 15.3% for females and males, respectively. The best-performing algorithm to identify individuals with a higher likelihood of HIV infection was XGBoost, with a high F1 score of 91.4% for males and 90.1% for females based on the combined surveys. The results from the prediction model identified six common features associated with HIV, with total number of lifetime sexual partners and cohabitation duration being the most influential variables for females and males, respectively. In addition to other risk reduction techniques, machine learning may aid in identifying those who might require Pre-exposure prophylaxis, particularly women who experience intimate partner violence. Furthermore, compared to traditional statistical approaches, machine learning uncovered patterns in predicting HIV infection with comparatively reduced uncertainty and, therefore, crucial for effective decision-making.

Population-based temporal trends and ethnic disparity in breast cancer mortality in South Africa (1999-2018): Joinpoint and age-period-cohort regression analyses

Globally, breast cancer is the leading cause of cancer deaths, accounting for 15.5% of female cancer deaths in 2020. Breast cancer is also the leading cause of female cancers in South Africa. The rapid epidemiological transition in South Africa may have an impact on the trends in breast cancer mortality in the country. We therefore evaluated the trends in the breast cancer mortality in SA over 20 years (1999-2020).

Methods

Joinpoint regression analyses of the trends in crude and age-standardized mortality rates (ASMR) of breast cancer among South African women were conducted from 1999 to 2018 using mortality data from Statistics South Africa. Age-period-cohort regression analysis was then conducted to evaluate the independent effect of age, period, and cohort on breast cancer mortality, and analysis was stratified by ethnicity.

Results

The mortality rate of breast cancer (from 9.82 to 13.27 per 100,000 women) increased at around 1.4% per annum (Average Annual Percent Change (AAPC): 1.4%, 95% CI:0.8-2.0, P-value< 0.001). Young women aged 30-49 years (1.1%-1.8%, P-value< 0.001) had increased breast cancer mortality. The risk of breast cancer mortality increased among successive birth cohorts from 1924 to 1928 but decreased among recent cohorts born from 1989 to 1993. In 2018, the breast cancer mortality rate among Blacks (9.49/100,000 women) was around half of the rates among the non-Blacks. (Coloreds: 18.11 per 100,000 women; Whites: 17.77/100,000 women; Indian/Asian: 13.24 per 100,000 women).

Conclusions

Contrary to the trends in high- and middle-income countries, breast cancer mortality increased in South Africa especially among young women. Breast cancer prevention programs should be intensified and should also target young women. The marked disparity in ethnic burden of breast cancer should be considered during planning and implementation of interventions.

Small area analysis of HIV viral load suppression patterns in a high priority district (2012-2016), South Africa

Globally, high viral load (VL) suppression rates are indicators of successful HIV treatment programs. Evaluation of these programmes at lower levels is likely to highlight variations that are masked at the provincial or national levels. This ecological study used routinely collected clinical and surveillance data on the HIV programme from 88 sampled Ekurhuleni wards. Between January 2012 and December 2016, 26 222 HIV VL tests for 2817 patients were conducted. We conducted a secondary analysis to determine the predictors of high VL suppression accounting for space and time random effects and estimate the impact of the national universal test-and-treat roll-out in 2016 and forecast VL suppression rates for five years post-2016.The proportion of VL suppression increased over the years: 2012 (47.8%: 95% confidence interval (CI): 36.7%-67.4%); 2013 (58.2%: 95%CI: 41.4%-79.6%); 2014 (62.7%: 95%CI: 45.2%-84.7%); 2015 (67.2%: 95%CI: 49.0%-89.9%) and 2016 (61.2%: 95%CI: 43.9%-83.0%). For every percentage increase in ART initiation, high VL suppression rates increased by 35% (RR: 1.345; 95% credible interval (Crl) 1.221-1.492) and for every percentage increase in women in the ward, high VL suppression increased by 44% (RR: 1.442; 95%CrI: 1.056-1.962). There was evidence of high and low clusters of viral load suppression observed at ward-level. The VL suppression rates in Ekurhuleni were lower than the 90% UNAIDS target. There was heterogeneity of high VL suppression across wards and study period. Targeted interventions strengthening ART initiation and retention in care are critical to achieving optimal VL suppression in Ekurhuleni and districts with similar profiles.

Digital delivery of behavioural activation therapy to overcome depression and facilitate social and economic transitions of adolescents in South Africa (the DoBAt study): protocol for a pilot randomised controlled trial

INTRODUCTION

Scalable psychological treatments to address depression among adolescents are urgently needed. This is particularly relevant to low-income and middle-income countries where 90% of the world's adolescents live. While digital delivery of behavioural activation (BA) presents a promising solution, its feasibility, acceptability and effectiveness among adolescents in an African context remain to be shown.

METHODS AND ANALYSIS

This study is a two-arm single-blind individual-level randomised controlled pilot trial to assess the feasibility, acceptability and initial efficacy of digitally delivered BA therapy among adolescents with depression. The intervention has been coproduced with adolescents at the study site. The study is based in the rural northeast of South Africa in the Bushbuckridge subdistrict of Mpumalanga province. A total of 200 adolescents with symptoms of mild to moderately severe depression on the Patient Health Questionnaire Adolescent Version will be recruited (1:1 allocation ratio). The treatment group will receive BA therapy via a smartphone application (the Kuamsha app) supported by trained peer mentors. The control group will receive an enhanced standard of care. The feasibility and acceptability of the intervention will be evaluated using a mixed methods design, and signals of the initial efficacy of the intervention in reducing symptoms of depression will be determined on an intention-to-treat basis. Secondary objectives are to pilot a range of cognitive, mental health, risky behaviour and socioeconomic measures; and to collect descriptive data on the feasibility of trial procedures to inform the development of a further larger trial.

ETHICS AND DISSEMINATION

This study has been approved by the University of the Witwatersrand Human Research Ethics Committee (MED20-05-011) and the Oxford Tropical Research Ethics Committee (OxTREC 34-20). Study findings will be published in scientific open access peer-reviewed journals, presented at scientific conferences and communicated to participants, their caregivers, public sector officials and other relevant stakeholders.

TRIAL REGISTRATION NUMBERS

This trial was registered on 19 November 2020 with the South African National Clinical Trials Registry (DOH-27-112020-5741) and the Pan African Clinical Trials Registry (PACTR202206574814636).

Estimating age specific prevalence and force of infection in Zimbabwe using combined cross-sectional surveys from 2005 to 2015

Objective

Age structured sexual mixing patterns have been noted to be associated with HIV prevalence and force of infection. Therefore, this study aimed to estimate the age dependent HIV force of infection using survey cross-sectional data from Zimbabwe.

Methods

We fit generalized additive models namely; linear, semi-parametric, non-parametric and non-proportional hazards models. Using the 2005-06, 2010-11 and 2015 Zimbabwe Demographic Health Surveys data. The Akaike Information Criteria was used to select the best model. The best model was then used to estimate the age dependent HIV prevalence and force-of-infection.

Results

Based on birth year cohort-specific prevalence, the female HIV prevalence reaches the highest peak at around 29 years of age, then declines thereafter. Males have a lower cohort specific prevalence between 15 and 30 years than females. Male cohort-specific prevalence slightly decreases between the ages of 33 and 39, then peaks around the age of 40. The cohort-specific FOI is greater in females than in males throughout all age categories. In addition, the cohort-specific HIV FOI peaked at ages 22 and 40 for females and males, respectively. The observed 18-year age difference between the HIV FOI peaks of males and females.

Conclusion

Our model was appealing because we did not assume that the FOI is stationary over time; however, we used serological survey data to distinguish the FOI's age-and-time effect. The cohort-specific FOI peaked 18 years earlier in females than males, indicative of age-mixing patterns. We recommend interventions that target younger females so as to reduce HIV transmission rates.

Malaria attributable fractions with changing transmission intensity: Bayesian latent class vs logistic models

Background

Asymptomatic carriage of malaria parasites is common in high transmission intensity areas and confounds clinical case definitions for research studies. This is important for investigations that aim to identify immune correlates of protection from clinical malaria. The proportion of fevers attributable to malaria parasites is widely used to define different thresholds of parasite density associated with febrile episodes. The varying intensity of malaria transmission was investigated to check whether it had a significant impact on the parasite density thresholds. The same dataset was used to explore an alternative statistical approach, using the probability of developing fevers as a choice over threshold cut-offs. The former has been reported to increase predictive power.

Methods

Data from children monitored longitudinally between 2005 and 2017 from Junju and Chonyi in Kilifi, Kenya were used. Performance comparison of Bayesian-latent class and logistic power models in estimating malaria attributable fractions and probabilities of having fever given a parasite density with changing malaria transmission intensity was done using Junju cohort. Zero-inflated beta regressions were used to assess the impact of using probabilities to evaluate anti-merozoite antibodies as correlates of protection, compared with multilevel binary regression using data from Chonyi and Junju.

Results

Malaria transmission intensity declined from over 49% to 5% between 2006 and 2017, respectively. During this period, malaria attributable fraction varied between 27–59% using logistic regression compared to 10–36% with the Bayesian latent class approach. Both models estimated similar patterns of fevers attributable to malaria with changing transmission intensities. The Bayesian latent class model performed well in estimating the probabilities of having fever, while the latter was efficient in determining the parasite density threshold. However, compared to the logistic power model, the Bayesian algorithm yielded lower estimates for both attributable fractions and probabilities of fever. In modelling the association of merozoite antibodies and clinical malaria, both approaches resulted in comparable estimates, but the utilization of probabilities had a better statistical fit.

Conclusions

Malaria attributable fractions, varied with an overall decline in the malaria transmission intensity in this setting but did not significantly impact the outcomes of analyses aimed at identifying immune correlates of protection. These data confirm the statistical advantage of using probabilities over binary data.

Performance evaluation of machine learning and Computer Coded Verbal Autopsy (CCVA) algorithms for cause of death determination: A comparative analysis of data from rural South Africa

Computer Coded Verbal Autopsy (CCVA) algorithms are commonly used to determine the cause of death (CoD) from questionnaire responses extracted from verbal autopsies (VAs). However, they can only operate on structured data and cannot effectively harness information from unstructured VA narratives. Machine Learning (ML) algorithms have also been applied successfully in determining the CoD from VA narratives, allowing the use of auxiliary information that CCVA algorithms cannot directly utilize. However, most ML-based studies only use responses from the structured questionnaire, and the results lack generalisability and comparability across studies. We present a comparative performance evaluation of ML methods and CCVA algorithms on South African VA narratives data, using data from Agincourt Health and Demographic Surveillance Site (HDSS) with physicians' classifications as the gold standard. The data were collected from 1993 to 2015 and have 16,338 cases. The random forest and extreme gradient boosting classifiers outperformed the other classifiers on the combined dataset, attaining accuracy of 96% respectively, with significant statistical differences in algorithmic performance (p < 0.0001). All our models attained Area Under Receiver Operating Characteristics (AUROC) of greater than 0.884. The InterVA CCVA attained 83% Cause Specific Mortality Fraction accuracy and an Overall Chance-Corrected Concordance of 0.36. We demonstrate that ML models could accurately determine the cause of death from VA narratives. Additionally, through mortality trends and pattern analysis, we discovered that in the first decade of the civil registration system in South Africa, the average life expectancy was approximately 50 years. However, in the second decade, life expectancy significantly dropped, and the population was dying at a much younger average age of 40 years, mostly from the leading HIV related causes. Interestingly, in the third decade, we see a gradual improvement in life expectancy, possibly attributed to effective health intervention programmes. Through a structure and semantic analysis of narratives where experts disagree, we also demonstrate the most frequent terms of traditional healer consultations and visits. The comparative approach also makes this study a baseline that can be used for future research enforcing generalization and comparability. Future study will entail exploring deep learning models for CoD classification.

Loss to Follow-Up Risk among HIV Patients on ART in Zimbabwe, 2009-2016: Hierarchical Bayesian Spatio-Temporal Modeling

Loss to follow-up (LTFU) is a risk factor for poor outcomes in HIV patients. The spatio-temporal risk of LTFU is useful to identify hotspots and guide policy. Secondary data on adult HIV patients attending a clinic in provinces of Zimbabwe between 2009 and 2016 were used to estimate the LTFU risk in each of the 10 provinces. A hierarchical Bayesian spatio-temporal Poisson regression model was fitted using the Integrated Nested Laplace Approximation (INLA) package with LTFU as counts adjusting for age, gender, WHO clinical stage, tuberculosis coinfection and duration on ART. The structured random effects were modelled using the conditional autoregression technique and the temporal random effects were modelled using first-order random walk Gaussian priors. The overall rate of LTFU was 22.7% (95%CI: 22.6/22.8) with Harare (50.28%) and Bulawayo (31.11%) having the highest rates. A one-year increase in the average number of years on ART reduced the risk of LTFU by 35% (relative risk (RR) = 0.651; 95%CI: 0.592-0.712). In general, the provinces with the highest exceedance LTFU risk were Matabeleland South and Matabeleland North. LTFU is one of the drawbacks of HIV prevention. Interventions targeting high-risk regions in the southern and northern regions of Zimbabwe are a priority. Community-based interventions and programmes which mitigate LTFU risk remain essential in the global HIV prevention campaign.

Assessing spatial patterns of HIV prevalence and interventions in semi-urban settings in South Africa. Implications for spatially targeted interventions

Equitable allocation of resources targeting the human immunodeficiency virus (HIV) at the local level requires focusing interventions in areas of the greatest need. Understanding the geographical variation in the HIV epidemic and uptake of selected HIV prevention and treatment programmes are necessary to identify such areas. Individual-level HIV data were obtained from a 2012 national HIV survey in South Africa. Spatial regression models on each outcome measure (HIV infection, sub-optimal condom use or non-anti-retroviral treatment (ART) adjusted for spatial random effects at the ward level were fitted using WINBUGS software. In addition, ward-level data was utilized to estimate condom use coverage and ART initiation rates which were obtained from routinely collected data in 2012. Ordinary Kriging was used to produce smoothed maps of HIV infection, condom use coverage and ART initiation rates. HIV infection was associated with individuals undertaking tertiary education [posterior odds ratio (POR): 19.53; 95% credible intervals (CrI): 3.22- 84.93]. Sub-optimal condom use increased with age (POR: 1.09; 95%CrI: 1.06-1.11) and was associated with being married (POR: 4.14; 95%CrI: 1.23-4.28). Non-ART use was associated with being married (POR: 6.79; 95%CrI: 1.43-22.43). There were clusters with high HIV infection, sub-optimal condom use, and non- ART use in Ekurhuleni, an urban and semi-urban district in Gauteng province, South Africa. Findings show the need for expanding condom programmes and/or strengthening other HIV prevention programmes such as pre-exposure prophylaxis and encouraging sustained engagement in HIV care and treatment in the identified areas with the greatest need in Ekurhuleni Metropolitan Municipality.

Measurement of kidney function in Malawi, South Africa, and Uganda: a multicentre cohort study

BACKGROUND

The burden of kidney disease in many African countries is unknown. Equations used to estimate kidney function from serum creatinine have limited regional validation. We sought to determine the most accurate way to measure kidney function and thus estimate the prevalence of impaired kidney function in African populations.

METHODS

We measured serum creatinine, cystatin C, and glomerular filtration rate (GFR) using the slope-intercept method for iohexol plasma clearance (mGFR) in population cohorts from Malawi, Uganda, and South Africa. We compared performance of creatinine and cystatin C-based estimating equations to mGFR, modelled and validated a new creatinine-based equation, and developed a multiple imputation model trained on the mGFR sample using age, sex, and creatinine as the variables to predict the population prevalence of impaired kidney function in west, east, and southern Africa.

FINDINGS

Of 3025 people who underwent measured GFR testing (Malawi n=1020, South Africa n=986, and Uganda n=1019), we analysed data for 2578 participants who had complete data and adequate quality measurements. Among 2578 included participants, creatinine-based equations overestimated kidney function compared with mGFR, worsened by use of ethnicity coefficients. The greatest bias occurred at low kidney function, such that the proportion with GFR of less than 60 mL/min per 1·73 m² either directly measured or estimated by cystatin C was more than double that estimated from creatinine. A new creatinine-based equation did not outperform existing equations, and no equation, including the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2021 race-neutral equation, estimated GFR within plus or minus 30% of mGFR for 75% or more of the participants. Using a model to impute kidney function based on mGFR, the estimated prevalence of impaired kidney function was more than two-times higher than creatinine-based estimates in populations across six countries in Africa.

INTERPRETATION

Estimating GFR using serum creatinine substantially underestimates the individual and population-level burden of impaired kidney function in Africa with implications for understanding disease progression and complications, clinical care, and service provision. Scalable and affordable ways to accurately identify impaired kidney function in Africa are urgently needed.

FUNDING

The GSK Africa Non-Communicable Disease Open Lab.

TRANSLATIONS

For the Luganda, Chichewa and Xitsonga translations of the abstract see Supplementary Materials section.

Comorbidities in Black South Africans with established rheumatoid arthritis

Objective

Comorbidities contribute both to morbidity and mortality in rheumatoid arthritis (RA). The aim of the current study was to investigate the prevalence and spectrum of comorbidities in South Africans with established RA.

Methods

A retrospective, consecutive case record review of 500 Black South African patients with established disease of ≥5 years attending a tertiary rheumatology service was performed. Common comorbidities including those listed in the Charlson Comorbidity Score (CCS) were documented.

Results

Most patients, 463 known alive (AG) and 37 known deceased (DG), were female (87%). Mean (SD) age and disease duration were 60 (11.1) and 10.7 (5.0) years respectively, and 98% had ≥1 comorbidities. Median CCS was 2, significantly higher in DG than AG (4 vs 2, P < .0001). Despite hypertension (70%) and hypercholesterolemia (47%) being the commonest comorbidities overall and type 2 diabetes (T2D) occurring in 15.4%, clinical cardiovascular events were rare (0.6%). Peptic ulcer disease (odds ratio [OR] = 8.67), congestive cardiac failure (OR = 7.09), serious infections (OR = 7.02) and tuberculosis (OR = 2.56) were significantly more common in DG than AG. Multivariate analysis showed that American College of Rheumatology functional class 3/4 was associated with increased risk for serious infections (OR = 3.84) and tuberculosis (OR = 2.10).

Conclusion

Despite the high burden of cardiometabolic comorbidities in South Africans with established RA, cardiovascular events were rare. Serious infections and tuberculosis, both associated with severe functional disability, are a major cause of morbidity and mortality.

Trends and determinants of late antenatal care initiation in three East African countries, 2007-2016: A population based cross-sectional analysis

Early antenatal care is critical for the mother and newborn's health. Antenatal care is often delayed in Sub-Saharan Africa. The study aims to examine the trends and determinants of late antenatal care initiation in the Democratic Republic of Congo, Kenya, and Tanzania from 2007-2016. The study employed Demographic Health Surveys data of reproductive-age women seeking antenatal care in the Democratic Republic of Congo (2007-2013/14), Kenya (2008-2014), and Tanzania (2010-2015/16). Bivariate and multivariate analysis was conducted per survey, taking sampling weights into account. The determinants of late antenatal care initiation were measured using multivariate logistic regression models and the trends were assessed using prediction scores. Late antenatal care initiation declined in Tanzania (60.9%-49.8%) and Kenya (67.8%-60.5%) but increased in the Democratic Republic of Congo (56.8%-61.0%) between surveys. In the Democratic Republic of Congo, higher birth order was associated with antenatal care initiation delays from 2007-2014, whilst rural residency (AOR:1.28;95%CI:1.09-1.52), lower maternal education (AOR:1.29;95%CI:1.13-1.47) and lower-income households (AOR:1.30;95%CI:1.08-1.55) were linked to antenatal care initiation delays in 2014. In Kenya, lower maternal education and lower-income households were associated with antenatal care initiation delays from 2008-2014, whilst rural residency (AOR:1.24;95%CI:1.11-1.38) and increased birth order (AOR:1.12; 95%CI:1.01-1.28) were linked to antenatal care initiation delays in 2014. In Tanzania, higher birth order and larger households were linked to antenatal care initiation delays from 2010-2016, whilst antenatal care initiation delays were associated with lower maternal education (OR:1.51;95%CI:1.16-1.97) in 2010 and lower-income households (OR:1.45;95%CI:1.20-1.72) in 2016. Except for the Democratic Republic of Congo, the sub-region is making progress in reducing antenatal care delays. Women from various geographic, educational, parity, and economic groups exhibited varying levels of delayed antenatal care uptake. Increasing women's access to information platforms and strengthening initiatives that enhance female education, household incomes, and localise services may enhance early antenatal care utilisation.

Understanding factors influencing utilization of HIV prevention and treatment services among patients and providers in a heterogeneous setting: A qualitative study from South Africa

Despite advances made in HIV prevention and treatment interventions in South Africa, barriers to their utilization continue to exist. Understanding perspectives from patients and providers of healthcare can shed light on the necessary strategies to enhance uptake of HIV services. A cross-sectional qualitative study was conducted in July 2020 in Ekurhuleni District. Based on HIV prevalence estimates from a national survey, male condom use coverage and antiretroviral treatment (ART) initiation rates from routinely collected clinical data for 2012, we selected facilities from geographical areas with varying HIV prevalence and uptake of HIV services. In-depth interviews were conducted with adult (≥18 years) patients and healthcare workers in selected primary healthcare facilities. Thematic analysis was performed following a framework built around the social cognitive theory to describe behavioural, personal, and social/environmental factors influencing utilization of HIV services. Behavioural factors facilitating uptake of HIV services included awareness of the protective value of condoms, and the benefits of ART in suppressing viral load and preventing mother-to-child HIV transmission which was evident across geographical areas. Barriers in high prevalence areas included suboptimal condom use, fears of a positive HIV result, and anticipated HIV-related stigma while seeking healthcare services. Across the geographical areas, personal factors included ability to correctly use available services enhanced by knowledge acquired during counselling sessions and community-based health promotion activities. Further, social support from family reinforced engagement in care. Compared to low uptake areas, clinics in high uptake areas used care-facilitators, outreach teams and decanting programs to address the environmental barriers including staff shortages and long queues. Barriers at multiple levels prevent optimal utilization of HIV services, calling for strategies that target and address the different levels and tailored to needs of specific settings. Overall, improved delivery of HIV prevention or treatment interventions can be achieved through strengthening training of healthcare providers in facilities and communities and addressing negative sequelae from utilising services in low uptake areas.

Use of Machine Learning and Statistical Algorithms to Predict Hospital Length of Stay Following Colorectal Cancer Resection: A South African Pilot Study

The aim of this pilot study was to develop logistic regression (LR) and support vector machine (SVM) models that differentiate low from high risk for prolonged hospital length of stay (LOS) in a South African cohort of 383 colorectal cancer patients who underwent surgical resection with curative intent. Additionally, the impact of 10-fold cross-validation (CV), Monte Carlo CV, and bootstrap internal validation methods on the performance of the two models was evaluated. The median LOS was 9 days, and prolonged LOS was defined as greater than 9 days post-operation. Preoperative factors associated with prolonged LOS were a prior history of hypertension and an Eastern Cooperative Oncology Group score between 2 and 4. Postoperative factors related to prolonged LOS were the need for a stoma as part of the surgical procedure and the development of post-surgical complications. The risk of prolonged LOS was higher in male patients and in any patient with lower preoperative hemoglobin. The highest area under the receiving operating characteristics (AU-ROC) was achieved using LR of 0.823 (CI = 0.798–0.849) and SVM of 0.821 (CI = 0.776–0.825), with each model using the Monte Carlo CV method for internal validation. However, bootstrapping resulted in models with slightly lower variability. We found no significant difference between the models across the three internal validation methods. The LR and SVM algorithms used in this study required incorporating important features for optimal hospital LOS predictions. The factors identified in this study, especially postoperative complications, can be employed as a simple and quick test clinicians may flag a patient at risk of prolonged LOS.

Markov modelling of viral load adjusting for CD4 orthogonal variable and multivariate conditional autoregressive mapping of the HIV immunological outcomes among ART patients in Zimbabwe

BACKGROUND

This study aimed to jointly model HIV disease progression patterns based on viral load (VL) among adult ART patients adjusting for the time-varying "incremental transients states" variable, and the CD4 cell counts orthogonal variable in a single 5-stage time-homogenous multistate Markov model. We further jointly mapped the relative risks of HIV disease progression outcomes (detectable VL (VL ≥ 50copies/uL) and immune deterioration (CD4 < 350cells/uL) at the last observed visit) conditional not to have died or become loss to follow-up (LTFU).

METHODS

Secondary data analysis of individual-level patients on ART was performed. Adjusted transition intensities, hazard ratios (HR) and regression coefficients were estimated from the joint multistate model of VL and CD4 cell counts. The mortality and LTFU transition rates defined the extent of patients' retention in care. Joint mapping of HIV disease progression outcomes after ART initiation was done using the Bayesian intrinsic Multivariate Conditional Autoregressive prior model.

RESULTS

The viral rebound from the undetectable state was 1.78times more likely compared to viral suppression among patients with VL ranging from 50-1000copies/uL. Patients with CD4 cell counts lower than expected had a higher risk of viral increase above 1000copies/uL and death if their VL was above 1000copies/uL (state 2 to 3 (λ₂₃): HR = 1.83 and (λ₃₄): HR = 1.42 respectively). Regarding the time-varying effects of CD4 cell counts on the VL transition rates, as the VL increased, (λ₁₂ and λ₂₃) the transition rates increased with a decrease in the CD4 cell counts over time. Regardless of the individual's VL, the transition rates to become LTFU decreased with a decrease in CD4 cell counts. We observed a strong shared geographical pattern of 66% spatial correlation between the relative risks of detectable VL and immune deterioration after ART initiation, mainly in Matabeleland North.

CONCLUSION

With high rates of viral rebound, interventions which encourage ART adherence and continual educational support on the barriers to ART uptake are crucial to achieve and sustain viral suppression to undetectable levels. Area-specific interventions which focus on early ART screening through self-testing, behavioural change campaigns and social support strategies should be strengthened in heavily burdened regions to sustain the undetectable VL. Sustaining undetectable VL lowers HIV transmission in the general population and this is a step towards achieving zero HIV incidences by 2030.

Predicting Colorectal Cancer Recurrence and Patient Survival Using Supervised Machine Learning Approach: A South African Population-Based Study

Background: South Africa (SA) has the highest incidence of colorectal cancer (CRC) in Sub-Saharan Africa (SSA). However, there is limited research on CRC recurrence and survival in SA. CRC recurrence and overall survival are highly variable across studies. Accurate prediction of patients at risk can enhance clinical expectations and decisions within the South African CRC patients population. We explored the feasibility of integrating statistical and machine learning (ML) algorithms to achieve higher predictive performance and interpretability in findings.

Methods: We selected and compared six algorithms:- logistic regression (LR), naïve Bayes (NB), C5.0, random forest (RF), support vector machine (SVM) and artificial neural network (ANN). Commonly selected features based on OneR and information gain, within 10-fold cross-validation, were used for model development. The validity and stability of the predictive models were further assessed using simulated datasets.

Results: The six algorithms achieved high discriminative accuracies (AUC-ROC). ANN achieved the highest AUC-ROC for recurrence (87.0%) and survival (82.0%), and other models showed comparable performance with ANN. We observed no statistical difference in the performance of the models. Features including radiological stage and patient's age, histology, and race are risk factors of CRC recurrence and patient survival, respectively.

Conclusions: Based on other studies and what is known in the field, we have affirmed important predictive factors for recurrence and survival using rigorous procedures. Outcomes of this study can be generalised to CRC patient population elsewhere in SA and other SSA countries with similar patient profiles.

protGear: A protein microarray data pre-processing suite

Protein microarrays are versatile tools for high throughput study of the human proteome, but systematic and non-systematic sources of bias constrain optimal interpretation and the ultimate utility of the data. Published guidelines to limit technical variability whilst maintaining important biological variation favour DNA-based microarrays that often differ fundamentally in their experimental design. Rigorous tools to guide background correction, the quantification of within-sample variation, normalisation, and batch correction specifically for protein microarrays are limited, require extensive investigation and are not centrally accessible.

Here, we develop a generic one-stop-shop pre-processing suite for protein microarrays that is compatible with data from the major protein microarray scanners. Our graphical and tabular interfaces facilitate a detailed inspection of data and are coupled with supporting guidelines that enable users to select the most appropriate algorithms to systematically address bias arising in customized experiments. The localization and distribution of background signal intensities determine the optimal correction strategy. A novel function overcomes the limitations in the interpretation of the coefficient of variation when signal intensities are at the lower end of the detection threshold. We demonstrate essential considerations in the experimental design and their impact on a range of algorithms for normalization and minimization of batch effects.

Our user-friendly interactive web-based platform eliminates the need for prowess in programming. The open-source R interface includes illustrative examples, generates an auditable record, enables reproducibility, and can incorporate additional custom scripts through its online repository. This versatility will enhance its broad uptake in the infectious disease and vaccine development community.

A review of multistate modelling approaches in monitoring disease progression: Bayesian estimation using the Kolmogorov-Chapman forward equations

There are numerous fields of science in which multistate models are used, including biomedical research and health economics. In biomedical studies, these stochastic continuous-time models are used to describe the time-to-event life history of an individual through a flexible framework for longitudinal data. The multistate framework can describe more than one possible time-to-event outcome for a single individual. The standard estimation quantities in multistate models are transition probabilities and transition rates which can be mapped through the Kolmogorov-Chapman forward equations from the Bayesian estimation perspective. Most multistate models assume the Markov property and time homogeneity; however, if these assumptions are violated, an extension to non-Markovian and time-varying transition rates is possible. This manuscript extends reviews in various types of multistate models, assumptions, methods of estimation and data features compatible with fitting multistate models. We highlight the contrast between the frequentist (maximum likelihood estimation) and the Bayesian estimation approaches in the multistate modeling framework and point out where the latter is advantageous. A partially observed and aggregated dataset from the Zimbabwe national ART program was used to illustrate the use of Kolmogorov-Chapman forward equations. The transition rates from a three-stage reversible multistate model based on viral load measurements in WinBUGS were reported.

Developing excellence in biostatistics leadership, training and science in Africa: How the Sub-Saharan Africa Consortium for Advanced Biostatistics (SSACAB) training unites expertise to deliver excellence

The increase in health research in sub-Saharan Africa (SSA) has led to a high demand for biostatisticians to develop study designs, contribute and apply statistical methods in data analyses. Initiatives exist to address the dearth in statistical capacity and lack of local biostatisticians in SSA health projects. The Sub-Saharan African Consortium for Advanced Biostatistics (SSACAB) led by African institutions was initiated to improve biostatistical capacity according to the needs identified by African institutions, through collaborative masters and doctoral training in biostatistics. SACCAB has created a critical mass of biostatisticians and a network of institutions over the last five years and has strengthened biostatistics resources and capacity for health research studies in SSA.  SSACAB comprises 11 universities and four research institutions which are supported by four European universities.  In 2015, only four universities had established Masters programmes in biostatistics and SSACAB supported the remaining seven to develop Masters programmes. In 2019 the University of the Witwatersrand became the first African institution to gain Royal Statistical Society accreditation for a Biostatistics Masters programme. A total of 150 fellows have been awarded scholarships to date of which 123 are Masters fellowships (41 female) of whom 58 have already graduated. Graduates have been employed in African academic (19) and research (15) institutions and 10 have enrolled for PhD studies. A total of 27 (10 female) PhD fellowships have been awarded; 4 of them are due to graduate by 2020. To date, SSACAB Masters and PhD students have published 17 and 31 peer-reviewed articles, respectively. SSACAB has also facilitated well-attended conferences, face-to-face and online short courses. Pooling of limited biostatistics resources in SSA combined with co-funding from external partners has shown to be an effective strategy for the development and teaching of advanced biostatistics methods, supervision and mentoring of PhD candidates.

Effect of Neural Mobilization on Nerve-Related Neck and Arm Pain: A Randomized Controlled Trial

Purpose: Neural mobilization (NM) is often used to treat nerve-related conditions, and its use is reasonable with nerve-related neck and arm pain (NNAP). The aims of this study were to establish the effect of NM on the pain, function, and quality of life (QOL) of patients with NNAP and to establish whether high catastrophizing and neuropathic pain influence treatment outcomes. Method: A randomized controlled trial compared a usual-care (UC; n = 26) group, who received cervical and thoracic mobilization, exercises, and advice, with an intervention (UCNM; n = 60) group, who received the same treatment but with the addition of NM. Soft tissue mobilization along the tract of the nerve was used as the NM technique. The primary outcomes were pain intensity (rated on the Numerical Pain Rating Scale), function (Patient-Specific Functional Scale), and QOL (EuroQol-5D) at 3 weeks, 6 weeks, 6 months, and 12 months. The secondary outcomes were the presence of neuropathic pain (using the Neuropathic Diagnostic Questionnaire) and catastrophizing (Pain Catastrophising Scale). Results: Both groups improved in terms of pain, function, and QOL over the 12-month period (p < 0.05). No between-groups differences were found at 12 months, but the UCNM group had significantly less pain at 6 months (p = 0.03). Patients who still presented with neuropathic pain (p < 0.001) and high pain catastrophizing (p = 0.02) at 6- and 12-mo follow-ups had more pain. Conclusions: Both groups had similar improvements in function and QOL at 12-month follow-up. The UCNM group had significantly less pain at 6-month follow-up and a lower mean pain rating at 12-month follow-up, although the difference between groups was not significant. Neuropathic pain is common among this population and, where it persisted, patients had more pain and functional limitations at 12-mo follow-up.

Biodex© training post-stroke for postural stability in the upper trunk: A pilot study

Background

Stroke affects upper trunk postural stability and upper limb function in approximately 85% of stroke survivors. Upper trunk postural stability is essential for functioning of the upper limb and is a prerequisite for hand function. The rehabilitation of the upper limb and upper trunk post-stroke remains a challenge because of poor recovery of motor and sensory function.

Objectives

To determine the effect of Biodex© upper limb weight-bearing training on upper trunk postural stability in patients post-stroke.

Method

A longitudinal randomised control pilot trial with single blinding was undertaken to assess postural stability on the Biodex© at baseline and 1-month post-baseline. In addition to standard rehabilitative care, upper limb weight-bearing training on the Biodex© was added for participants in the experimental group. Descriptive data analysis and the Mann–Whitney test for group comparisons were done using STATA (p < 0.05).

Results

Fifteen participants took part, seven in the control and eight in the experimental group, with an overall median age of 55 years. At baseline there were statistically significant lower scores in the experimental group on overall (p = 0.02) and anterior/posterior (p = 0.009) stability level 6 (moderately unstable base of support) in the upper trunk postural stability scores. No statistically significant improvements were noted between groups on any of the Biodex© stability levels at 1-month post-baseline testing (p > 0.05).

Conclusion

Upper limb weight-bearing training with the addition of Biodex© training did not result in improvements in upper trunk postural stability.

Clinical implications

The findings suggest that exercising on a moderately unstable base of support may improve upper trunk postural stability in patients post-stroke. The addition of Biodex© training to standard rehabilitative care for retraining and exercising upper trunk postural control in a weight-bearing position does not lead to better outcomes than standard care.

Competing risk of mortality on loss to follow-up outcome among patients with HIV on ART: a retrospective cohort study from the Zimbabwe national ART programme

OBJECTIVE

To determine the loss to follow-up (LTFU) rates at different healthcare levels after antiretroviral therapy (ART) services decentralisation among ART patients who initiated ART between 2004 and 2017 using the competing risk model in addition to the Kaplan-Meier and Cox regressions analysis.

DESIGN

A retrospective cohort study.

SETTING

The study was done in Zimbabwe using a nationwide routinely collected HIV patient-level data from various health levels of care facilities compiled through the electronic patient management system (ePMS).

PARTICIPANTS

We analysed 390 771 participants aged 15 years and above from 538 health facilities.

OUTCOMES

The primary endpoint was LTFU defined as a failure of a patient to report for drug refill for at least 90 days from last appointment date or if the patient missed the next scheduled visit date and never showed up again. Mortality was considered a secondary outcome if a patient was reported to have died.

RESULTS

The total exposure time contributed was 1 544 468 person-years. LTFU rate was 5.75 (95% CI 5.71 to 5.78) per 100 person-years. Adjustment for the competing event independently increased LTFU rate ratio in provincial and referral (adjusted sub-HRs (AsHR) 1.22; 95% CI 1.18 to 1.26) and district and mission (AsHR 1.47; 95% CI 1.45 to 1.50) hospitals (reference: primary healthcare); in urban sites (AsHR 1.61; 95% CI 1.59 to 1.63) (reference: rural); and among adolescence and young adults (15-24 years) group (AsHR 1.19; 95% CI 1.16 to 1.21) (reference: 35-44 years). We also detected overwhelming association between LTFU and tuberculosis-infected patients (AsHR 1.53; 95% CI 1.45 to 1.62) (reference: no tuberculosis).

CONCLUSIONS

We have observed considerable findings that 'leakages' (LTFU) within the ART treatment cascade persist even after the decentralisation of health services. Risk factors for LTFU reflect those found in sub-Saharan African studies. Interventions that retain patients in care by minimising any 'leakages' along the treatment cascade are essential in attaining the 90-90-90 UNAIDS fast-track targets.

Developing excellence in biostatistics leadership, training and science in Africa: How the Sub-Saharan Africa Consortium for Advanced Biostatistics (SSACAB) training unites expertise to deliver excellence

The increase in health research in sub-Saharan Africa (SSA) has generated large amounts of data and led to a high demand for biostatisticians to analyse these data locally and quickly.  Donor-funded initiatives exist to address the dearth in statistical capacity, but few initiatives have been led by African institutions. The Sub-Saharan African Consortium for Advanced Biostatistics (SSACAB) aims to improve biostatistical capacity in Africa according to the needs identified by African institutions, through (collaborative) masters and doctoral training in biostatistics. We describe the SSACAB Consortium, which comprises 11 universities and four research institutions- supported by four European universities. SSACAB builds on existing resources to strengthen biostatistics for health research with a focus on supporting biostatisticians to become research leaders; building a critical mass of biostatisticians, and networking institutions and biostatisticians across SSA.  In 2015 only four institutions had established Masters programmes in biostatistics and SSACAB supported the remaining institutions to develop Masters programmes. In 2019 the University of the Witwatersrand became the first African institution to gain Royal Statistical Society accreditation for a Biostatistics MSc programme. A total of 150 fellows have been awarded scholarships to date of which 123 are Masters fellowships (41 female) of which with 58 have already graduated. Graduates have been employed in African academic (19) and research (15) institutions and 10 have enrolled for PhD studies. A total of 27 (10 female) PhD fellowships have been awarded; 4 of them are due to graduate by 2020. To date, SSACAB Masters and PhD students have published 17 and 31 peer-reviewed articles, respectively. SSACAB has also facilitated well-attended conferences, face-to-face and online short courses. Pooling the limited biostatistics resources in SSA, and combining with co-funding from external partners is an effective strategy for the development and teaching of advanced biostatistics methods, supervision and mentoring of PhD candidates.

The relationship between childhood trauma and schizophrenia in the Genomics of Schizophrenia in the Xhosa people (SAX) study in South Africa

BACKGROUND

Evidence from high-income countries suggests that childhood trauma is associated with schizophrenia. Studies of childhood trauma and schizophrenia in low and middle income (LMIC) countries are limited. This study examined the prevalence of childhood traumatic experiences among cases and controls and the relationship between specific and cumulative childhood traumatic experiences and schizophrenia in a sample in South Africa.

METHODS

Data were from the Genomics of Schizophrenia in the South African Xhosa people study. Cases with schizophrenia and matched controls were recruited from provincial hospitals and clinics in the Western and Eastern Cape regions in South Africa. Childhood traumatic experiences were measured using the Childhood Trauma Questionnaire (CTQ). Adjusted logistic regression models estimated associations between individual and cumulative childhood traumatic experiences and schizophrenia.

RESULTS

Traumatic experiences were more prevalent among cases than controls. The odds of schizophrenia were 2.44 times higher among those who experienced any trauma than those who reported no traumatic experiences (95% CI 1.77-3.37). The odds of schizophrenia were elevated among those who experienced physical/emotional abuse (OR 1.59, CI 1.28-1.97), neglect (OR 1.39, CI 1.16-1.68), and sexual abuse (OR 1.22, CI 1.03-1.45) compared to those who did not. Cumulative physical/emotional abuse and neglect experiences increased the odds of schizophrenia as a dose-response relationship.

CONCLUSION

Childhood trauma is common in this population. Among many other benefits, interventions to prevent childhood trauma may contribute to a decreasing occurrence of schizophrenia.

A space-time analysis of recurrent malnutrition-related hospitalisations in Kilifi, Kenya for children under-5 years

Background

Globally, malnutrition underlies 45% of under-5 s mortality, mainly from potentiating common infections such as diarrhoea and pneumonia. Malnutrition as a public health problem is not evenly disbursed because of disparities in food insecurity and health, and children commonly suffer recurrent episodes of opportunistic infections. We aimed to understand better the spatial and temporal structure of multiple paediatric hospital admissions associated with malnutrition-related illnesses. This paper aimed to investigate the spatial-temporal variations in malnutrition-related recurrent morbidity of children under-5 years from the Kilifi County in Kenya between 2002 and 2015.

Methods

The study included data from children under-5 years old who had more than one admission to a rural district hospital in Kenya within the Kilifi Health and Demographic Surveillance System (KHDSS). The primary outcome was a malnutrition-related admission, based on wasting (WHZ < -2) or nutritional oedema. Individual, household and environmental level covariates were examined as exposures. We first fitted a SARIMA model for the temporality, and the Moran’s Index affirmed spatial clustering in malnutrition admissions. Kulldorf Statistics using SaTScan were applied to detect hotspots. Then, bivariate analysis was done using repeated values tabulation and analysis of covariance (ANCOVA). Inferential analysis was done using a mixed effect multivariable negative-binomial regression model, adjusting for spatiotemporal random effects.

Results

A total of 2821 children were admitted more than once, giving a total of 6375 admissions. Of these 6375 admissions, 1866 were malnutrition-related, and 3.9% (109/2821) of the children with repeat admissions died. There was a seasonal pattern of re-admissions, peaking from May to July over the years. Hotspots were found in both the Northern and Southern areas of the KHDSS, while the areas near Kilifi Town were least affected. We found that disease severity was most likely associated with a malnutrition re-admission to the hospital.

Conclusion

Disease severity was strongly associated with admission with malnutrition but its effect reduced after adjusting for the spatial and temporal random effects. Adjusting for clustering in space and in time (spatial-temporal) in models helps to improve the understanding of recurrent hospitalisations involving malnutrition.

Electronic supplementary material

The online version of this article (10.1186/s40795-019-0296-5) contains supplementary material, which is available to authorized users.

HIV Disease Progression Among Antiretroviral Therapy Patients in Zimbabwe: A Multistate Markov Model

Background: Antiretroviral therapy (ART) impact has prolonged survival of people living with HIV. We evaluated HIV disease progression among ART patients using routinely collected patient-level data between 2004 and 2017 in Zimbabwe. Methods: We partitioned HIV disease progression into four transient CD4 cell counts states: state 1 (CD4 ≥ 500 cells/μl), state 2 (350 cells/μl ≤ CD4 < 500 cells/μl), state 3 (200 cells/μl ≤ CD4 < 350 cells/μl), state 4 (CD4 < 200 cells/μl), and the absorbing state death (state 5). We proposed a semiparametric time-homogenous multistate Markov model to estimate bidirectional transition rates. Covariate effects (age, gender, ART initiation period, and health facility level) on the transition rates were assessed. Results: We analyzed 204,289 clinic visits by 63,422 patients. There were 24,325 (38.4%) patients in state 4 (CD4 < 200) at ART initiation, and 7,995 (12.6%) deaths occurred by December 2017. The overall mortality rate was 3.9 per 100 person-years. The highest mortality rate of 5.7 per 100 person-years (4,541 deaths) was from state 4 (CD4 < 200) compared to other states. Mortality rates decreased with increase in time since ART initiation. Health facility type was the strongest predictor for immune recovery. Provincial or central hospital patients showed a diminishing dose-response effect on immune recovery by state from a hazard ratio (HR) of 8.30 [95% confidence interval (95% CI), 6.64-10.36] (state 4 to 3) to HR of 3.12 (95% CI, 2.54-4.36) (state 2 to 1) compared to primary healthcare facilities. Immune system for male patients was more likely to deteriorate, and they had a 32% increased mortality risk (HR, 1.32; 95% CI, 1.23-1.42) compared to female patients. Elderly patients (45+ years) were more likely to immune deteriorate compared to 25-34 years age group: HR, 1.35; 95% CI, 1.18-1.54; HR, 1.56; 95% CI, 1.34-1.81 and HR, 1.53; 95% CI, 1.32-1.79 for states 1 to 2, state 2 to 3, and states 3 to 4, respectively. Conclusion: Immune recovery was pronounced among provincial or central hospitals. Male patients with lower CD4 cell counts were at a higher risk of immune deterioration and mortality, while elderly patients were more likely to immune deteriorate. Early therapeutic interventions when the immune system is relatively stable across gender and age may contain mortality and increase survival outcomes. Interventions which strengthen ART services in primary healthcare facilities are essential.

The effect of a home exercise intervention on persons with lower limb amputations: a randomized controlled trial

OBJECTIVE

To establish if a home-based exercise and education programme is more effective than usual treatment in improving function, mobility and quality of life in people with lower limb amputation due to peripheral vascular disease.

METHOD

A blocked randomized single-blinded controlled trial (RCT) with 154 participants (54 female; mean age 58) compared a home-based exercise and education programme (n = 77) with usual care (control) (n = 77). Participants were measured at baseline, immediately post intervention at three months, and after a further three months without any intervention. The outcome measures were the Barthel Index, Participation Scale, EuroQuol 5D, Modified Locomotor Capability Index and Timed Up and Go Test. Changes over time were established using generalized estimating equations and analysis of covariance, (P < 0.05).

RESULTS

The Participation Scale (18.73 ± 14.91 against 26.67 ± 19.14; P = 0.011), the EuroQuol5D visual analogue scale (69.10 ± 20.31 against 55.37 ± 27.67; P = 0.003), EuroQuol5D utility index (0.672 ± 0.300 against 0.532 ± 0.358; P = 0.25) and the Modified Capability Index (21.03 ± 15.79 against 15.91 ± 13.67; P = 0.034) improved in the intervention group compared with the control group at three months. At six months, there was no difference between the groups in any of the measures except for the EuroQuol5D visual analogue scale (74.52 ± 16.14 against 66.34 ± 22.91; P = 0.033). Although there were no differences between the Timed Up and Go test at 3 (35.39 ± 32.48 against 45.08 ± 41.52; P = 0.192) and six months (28.22 ± 20.96 against 36.08 ± 36.19; P = 0.189) between the groups the intervention group was more mobile.

CONCLUSION

This intervention improved function, mobility and quality of life in persons following lower limb amputation in the first three months post amputation.

Effect of a Mentor Mother Programme on retention of mother-baby pairs in HIV care: A secondary analysis of programme data in Uganda

Background

Community healthcare workers (CHWs) play an important role in promoting HIV-care retention. Notwithstanding inconsistencies in the outcomes of CHW programmes, these programmes are known to have a positive effect on retention of mother-baby pairs in HIV-care in sub-Saharan Africa.

Aim

The aim of this analysis was to assess the effect of mothers2mothers (m2m) Ugandan Mentor Mother (MM) programme on the retention of mother-baby pairs in HIV-care.

Methods

We conducted a secondary analysis of data obtained from the m2m Uganda MM programme in nine East Central districts. The primary data was generated through a quasi-experimental study of women attending prevention of mother to child transmission of HIV (PMTCT) clinics in Uganda between January 2011 and March 2014; where those who were enrolled at PMTCT sites with the MM intervention (n = 1161) were compared with those who received standard PMCTCT services without the MM intervention (n = 1143). Frequencies and descriptive statistics were calculated for categorical and continuous measures respectively. Risk factors for retention in care were determined by clustered generalised estimating equations and reported as adjusted odds ratios (AOR) with 95% confidence intervals (95% CI).

Results

Retention in the PMTCT cascade was significantly higher for mother-baby pairs in the intervention arm compared to those in the control arm across all measured time points (96.7% vs 65.8% at 6 weeks after birth, p<0.001; 81.5% vs 42% at 6 weeks after cessation of breastfeeding, p<0.001; and 71.2% vs 20.6% at 18 months after birth, p<0.001). Relative to the control group, women in the intervention group were less likely to be lost to follow up following treatment initiation (AOR 0.05, 95% CI: 0.02, 0.15). There was no difference in the proportion of the retained mother-baby pairs who received prescribed PMTCT interventions at different time points but a significantly higher number of mother-baby pairs in the intervention arm were retained at different time points.

Conclusion

HIV positive mothers and their HIV exposed children in the mothers2mothers Ugandan Mentor Mother programme had higher retention in HIV care at every step along the PMTCT cascade. We therefore recommend adoption of this peer-to-peer model in sub-Saharan Africa to complement retention in care strategies and health system interventions especially among priority and key populations.

The effects of a physiotherapist-led exercise intervention on peripheral neuropathy among people living with HIV on antiretroviral therapy in Kigali, Rwanda

Background

HIV-associated peripheral neuropathy (PN) is common in people living with HIV. Its management is mostly symptomatic utilising pharmacological approaches.

Objectives

This study determined the effects of an exercise intervention on PN among Rwandan people living with HIV receiving antiretroviral therapy (ART).

Methods

A 12-week single-blinded randomised controlled trial using the Brief Peripheral Neuropathy Screen (BPNS) as the assessment tool tested the effects of an exercise intervention on PN, followed by a 12-week non-intervention period. A total of 120 people with HIV- associated PN on ART were randomised to an exercise or no exercise group. Both groups continued receiving routine care. A bivariate analysis using Pearson’s chi-square test for significant differences in PN symptoms and signs, between groups, at baseline, after the 12 weeks intervention and 12 weeks post-intervention using generalised linear regression models to determine predictors of treatment outcomes was undertaken, utilising an intention-to-treat analysis (alpha p ≤ 0.05).

Results

At 12 weeks, the intervention group compared to the control: neuropathic pain 70% versus 94% (p < 0.005), PN symptoms severity – mild and/or none in 85% versus 60% (p < 0.001) and radiation of PN symptoms reduced, 80% versus 37% (p < 0.001). There were no differences in PN signs at 12 weeks intervention and at 12 weeks post-intervention. Having changed the antiretroviral (ARV) and having developed PN symptoms after the start on ARVs predicted treatment improvement, while demographic factors did not predict any treatment outcome.

Conclusion

A physiotherapist-led exercise intervention improved PN symptoms, but with non-significant improvement in PN signs. Factors related to early diagnosis and treatment of PN were facilitators for the improvement of PN symptoms.

Clinical implications

Physiotherapist-led exercises should be integrated into the routine management of people living with HIV on ART with PN symptoms.

Factors Associated With HIV Infection in Zimbabwe Over a Decade From 2005 to 2015: An Interval-Censoring Survival Analysis Approach

Objectives: The main objective of this study was to compare results from two approaches for estimating the effect of different factors on the risk of HIV infection and determine the best fitting model.

Study design: We performed secondary data analysis on cross-sectional data which was collected from the Zimbabwe Demographic Health Survey (ZDHS) from 2005 to 2015.

Methods: Survey and cluster adjusted logistic regression was used to determine variables for use in survival analysis with HIV status as the outcome variable. Covariates found significant in the logistic regression were used in survival analysis to determine the factors associated with HIV infection over the 10 years. The data for the survival analysis were modeled assuming age at survey imputation (Model 1) and interval-censoring (Model 2).

Results: Model goodness of fit test based on the Cox-Snell residuals against the cumulative hazard indicated that Model 1 was the best model. On the contrary, the Akaike Information Criterion (AIC) indicated that Model 2 was the best model. Factors associated with a high risk of HIV infection were being female, number of sexual partners, and having had an STI in the past year prior to the survey.

Conclusion: The difference between the results from the Cox-Snell residuals graphical method and the model estimates and AIC value maybe due to the lack of adequate methods to test the goodness-of -fit of interval-censored data. We concluded that Model 2 with interval-censoring gave better estimates due to its consistency with the published results from literature. Even though we consider the interval-censoring model as the superior model with regards to our specific data, the method had its own set of limitations.

Modeling Long-Term Graft Survival With Time-Varying Covariate Effects: An Application to a Single Kidney Transplant Centre in Johannesburg, South Africa

Objectives: Patients' characteristics that could influence graft survival may also exhibit non-constant effects over time; therefore, violating the important assumption of the Cox proportional hazard (PH) model. We describe the effects of covariates on the hazard of graft failure in the presence of long follow-ups.

Study Design and Settings: We studied 915 adult patients that received kidney transplant between 1984 and 2000, using Cox PH, a variation of the Aalen additive hazard and Accelerated failure time (AFT) models. Selection of important predictors was based on the purposeful method of variable selection.

Results: Out of 915 patients under study, 43% had graft failure by the end of the study. The graft survival rate is 81, 66, and 50% at 1, 5, and 10 years, respectively. Our models indicate that donor type, recipient age, donor-recipient gender match, delayed graft function, diabetes and recipient ethnicity are significant predictors of graft survival. However, only the recipient age and donor-recipient gender match exhibit constant effects in the models.

Conclusion: Conclusion made about predictors of graft survival in the Cox PH model without adequate assessment of the model fit could over-estimate significant effects. The additive hazard and AFT models offer more flexibility in understanding covariates with non-constant effects on graft survival. Our results suggest that the period of follow-up in this study is long to support the proportionality assumption. Modeling graft survival at different time points may restrain the possibility of important covariates showing time-variant effects in the Cox PH model.

PO 8313 PREDICTORS OF HEALTH INSTITUTIONAL READINESS FOR EBOLA EPIDEMIC CONTAINMENT IN NIGERIA: A STRUCTURAL EQUATION MODELLING (SEM) APPROACH

Background

There is paucity of literature on organisational readiness in the health space. Previous studies focus on epidemic preparedness and often depict readiness as a minor element in the implementation space. This study investigated the predictors of health institutional readiness to implement innovations for combating an Ebola epidemic outbreak in Nigeria.

Methods

The cross-sectional, mixed methods design was employed. The study population was 785 health care workers and non-health workers working at University of Port-Harcourt Teaching Hospital (Nigeria). The purposive sampling was used for qualitative study while the stratified random sampling technique was utilised for the quantitative study. Qualitative data were collected from fifteen respondents while a total of 511 questionnaires were administered at the study site. The qualitative data was analysed using inductive thematic analysis. The quantitative data was analysed using structural equation modelling (SEM).

Results

The qualitative study suggested that quality improvement was perceived as most useful in influencing all the tree sub-components of readiness. Training is perceived as most useful in building readiness while it is perceived to be moderately useful in influencing the sub-component of readiness. The OLS estimates indicates that QI/QA exert a positive and significant effect on motivation (β=0.004, p<0.05) and general capacity score (β=0.28 p<0.05) while it inversely but significantly exerts influence on innovation specific capacity (β=−0.21×10–3, p<0.05). The SEM/pathway analysis shows the direct and indirect routes of interactions among predictors of readiness after adjusting for confounders. All the explanatory variables have significant effect on readiness except gender which was dropped from the final model.

Conclusion

The strength of evidence of how an evidence-based system for innovation support can influence readiness was established. Though readiness is a rate-determining step in ensuring robust and effective implementation outcomes for epidemic containment, exploring innovation outcomes and their amplification through explicitly target readiness dynamics requires further investigation.

Spatial and socio-economic correlates of effective contraception among women seeking post-abortion care in healthcare facilities in Kenya

Introduction

Information, counseling, availability of contraceptives, and their adoption by post-abortion care (PAC) patients are central to the quality of PAC in healthcare facilities. Effective contraceptive adoption by these patients reduces the risks of unintended pregnancy and repeat abortion.

Methods

This study uses data from the Incidence and Magnitude of Unsafe Abortion Study of 2012 to assess the level and determinants of highly effective contraception among patients treated with complications from an unsafe abortion in healthcare facilities in Kenya. Highly effective contraception was defined as any method adopted by a PAC patient that reduces pregnancy rate by over 99%.

Results

Generally, contraceptive counseling was high among all PAC patients (90%). However, only 54% of them received a modern family planning method—45% a short-acting method and 9% a long-acting and permanent method. Adoption of highly effective contraception was determined by patient’s previous exposure to unintended pregnancies, induced abortion and modern family planning (FP). Facility level factors associated with the uptake of highly effective contraceptives included: facility ownership, availability of evacuation procedure room, whether the facility had a specialized obstetric-gynecologist, a facility that also had maternity services and the number of FP methods available for PAC patients.

Discussion and conclusion

For better adoption of highly effective FP, counseling of PAC patients requires an understanding of the patient’s past experience with contraception and their future fertility intentions and desires in order to meet their reproductive needs more specifically. Family planning integration with PAC can increase contraceptive uptake and improve the reproductive health of post-abortion care patients.

Policy, law and post-abortion care services in Kenya

BACKGROUND

Unsafe abortion is still a leading cause of maternal death in most Sub-Saharan African countries. Post-abortion care (PAC) aims to minimize morbidity and mortality following unsafe abortion, addressing incomplete abortion by treating complications, and reducing possible future unwanted pregnancies by providing contraceptive advice. In this article, we draw on data from PAC service providers and patients in Kenya to illustrate how the quality of PAC in healthcare facilities is impacted by law and government policy.

METHODS

A cross-sectional design was used for this study, with in-depth interviews conducted to collect qualitative data from PAC service providers and seekers in healthcare facilities. Data were analyzed both deductively and inductively, with diverse sub-themes related to specific components of PAC quality.

RESULTS

The provision of quality PAC in healthcare facilities in Kenya is still low, with access hindered by restrictions on abortion. Negative attitudes towards abortion result in the continued undirected self-administration of abortifacients. Intermittent service interruptions through industrial strikes and inequitable access to care also drive unsafe terminations. Poor PAC service availability and lack of capacity to manage complications in primary care facilities result in multiple referrals and delays in care following abortion, leading to further complications. Inefficient infection control exposes patients and caregivers to unrelated infections within facilities, and the adequate provision of contraception is a continued challenge.

DISCUSSION

Legal, policy and cultural restrictions to access PAC increase the level of complications. In Kenya, there is limited policy focus on PAC, especially at primary care level, and no guidelines for health providers to provide legal, safe abortion. Discrimination at the point of care discourages women from presenting for care, and discourages providers from freely offering post-abortion contraceptive guidance and services. Poor communication between facilities and communities continues to result in delayed care and access-related discrimination.

CONCLUSION

Greater emphasis should be placed on the prevention of unsafe abortion and improved access to post-abortion care services in healthcare facilities. There is a definite need for service guidelines for this to occur.

Effects of shoulder strapping in patients with stroke: A randomised control trial

Background

Disability post stroke remains a global problem, with upper limb involvement playing a key role. Shoulder strapping is one of the techniques used clinically to address this.

Objectives

To compare the effect of two shoulder strapping techniques in patients with stroke.

Method

A longitudinal randomised controlled trial included baseline, weeks one, two and six assessments of 56 participants with upper limb hemiplegia. The participants were assessed for shoulder subluxation, shoulder pain, upper limb motor function and muscle tone. They were randomised into control, longitudinal strapping or circumferential strapping groups.

Results

Longitudinal strapping had a non-significant decrease in shoulder subluxation and pain (p > 0.05). Circumferential strapping had no significant effect on any outcomes; however, it prevented the shoulder pain from worsening as much as in the control group (p > 0.05). General improvement in upper limb motor function was observed for all three groups.

Conclusion

Trends in improvement showed that longitudinal strapping could be recommended because it positively influenced shoulder subluxation and pain. Even without significant changes, strapping creates awareness of the limb in patients and caregivers and could be of clinical benefit.

Clinical implication

Longitudinal strapping of the shoulder in patients with stroke seems to positively influence shoulder subluxation and pain.

Four decades of pulmonary tuberculosis in deceased South African miners: trends and determinants

OBJECTIVE

We investigated trends and determinants of pulmonary tuberculosis (PTB) in deceased South African miners.

METHODS

Statutory autopsies are performed on miners for occupational lung disease compensation, irrespective of cause of death. Data were extracted from the PATHAUT (Pathology Automation System) autopsy database. PTB trends were analysed and explanatory variables (year of autopsy, age at death, gold employment duration, silicosis and HIV) were evaluated using binary logistic regression modelling. Analyses were stratified by population group because of racial differences in socioeconomic status, employment patterns and access to facilities for autopsies. The analyses were segmented to represent the pre-HIV (1975-1989), rapid HIV spread (1990-2004) and antiretroviral therapy (2005-2014) periods.

RESULTS

The proportions of men with PTB at autopsy increased from 4.62% in 1975 to 27.18% in 2014 in black miners, and from 2.07% to 5.19% in white miners, with peaks in 2007 (43.12% and 9.51%, respectively). The magnitude and significance of adjusted ORs of determinants differed by population group and calendar period. PTB was largely associated with silicosis, increasing gold employment duration and year of autopsy (a surrogate for unmeasured confounders, such as unknown HIV status and tuberculosis transmission).

CONCLUSIONS

Changes in PTB time trends and determinants reflect the complex social and political environment in which mining occurs. Silica dust reduction remains a key intervention for tuberculosis reduction, together with tuberculosis and HIV treatment and management. The autopsy data provide reliable information to monitor progress towards the achievement of industry and national targets to reduce tuberculosis.