Overview of the Global and US Burden of Preterm Birth

Preterm birth (PTB) is the leading cause of morbidity and mortality in children globally, yet its prevalence has been difficult to accurately estimate due to unreliable methods of gestational age dating, heterogeneity in counting, and insufficient data. The estimated global PTB rate in 2020 was 9.9% (95% confidence interval: 9.1, 11.2), which reflects no significant change from 2010, and 81% of prematurity-related deaths occurred in Africa and Asia. PTB prevalence in the United States in 2021 was 10.5%, yet with concerning racial disparities. Few effective solutions for prematurity prevention have been identified, highlighting the importance of further research.

Postnatal care and acceptability of emollient therapy in very low birthweight infants in Harare, Zimbabwe: a qualitative analysis

BACKGROUND

Preterm birth (birth before 37 completed weeks of pregnancy) is the leading cause of neonatal and child under-five mortality globally, both of which are highest regionally in sub-Saharan Africa. The skin barrier plays a critical role in neonatal health and increasing evidence supports the use of topical emollient therapy to promote postnatal growth and reduce hospital-acquired infections in preterm infants. The World Health Organization (WHO) currently recommends emollient therapy in preterm or low birthweight infants globally but calls for further research on impacts of emollient use, especially in Africa. Little is known about postnatal skincare practices and the tradition of oil massage across sub-Saharan Africa. Further documentation is necessary to understand the context for future emollient intervention trials.

METHODS

61 semi-structured interviews with mothers who just delivered preterm or term infants and 4 focus group discussions (32 participants) with physician and nurse providers of newborn care were conducted at Sally Mugabe Central Hospital (SMCH), in Harare, Zimbabwe. SMCH is the principal public-sector tertiary care hospital for newborn infants in the northern part of the country. Mothers and healthcare professionals were questioned about newborn care at the hospital, current neonatal skincare and bathing practices, and the community's receptivity to a future emollient therapy clinical trial.

RESULTS

Postnatal skincare is centrally important to Zimbabwean communities and petroleum jelly application is nearly universal. The use of cooking oil and other natural oils on infants is also part of traditional customs. The primary needs and desires of mothers who have just given birth to preterm infants are having greater agency in their children's care and financial support in purchasing prescribed medications while at the hospital. Community receptivity to emollient therapy as a cost-effective treatment is high, particularly if mothers are trained to assist with the intervention.

CONCLUSION

Emollient therapy will likely be well-received by communities in and around Harare because of its accordance with current skincare practices and perceptions; however, cultural norms and the experiences of new mothers who have given birth at a facility highlight challenges and considerations for future clinical trial execution.

TRIAL REGISTRATION

Clinicaltrials.gov NCT05461404.

Development and Implementation of Digital Diagnostic Algorithms for Neonatal Units in Zimbabwe and Malawi: Development and Usability Study

BACKGROUND

Despite an increase in hospital-based deliveries, neonatal mortality remains high in low-resource settings. Due to limited laboratory diagnostics, there is significant reliance on clinical findings to inform diagnoses. Accurate, evidence-based identification and management of neonatal conditions could improve outcomes by standardizing care. This could be achieved through digital clinical decision support (CDS) tools. Neotree is a digital, quality improvement platform that incorporates CDS, aiming to improve neonatal care in low-resource health care facilities. Before this study, first-phase CDS development included developing and implementing neonatal resuscitation algorithms, creating initial versions of CDS to address a range of neonatal conditions, and a Delphi study to review key algorithms.

OBJECTIVE

This second-phase study aims to codevelop and implement neonatal digital CDS algorithms in Malawi and Zimbabwe.

METHODS

Overall, 11 diagnosis-specific web-based workshops with Zimbabwean, Malawian, and UK neonatal experts were conducted (August 2021 to April 2022) encompassing the following: (1) review of available evidence, (2) review of country-specific guidelines (Essential Medicines List and Standard Treatment Guidelinesfor Zimbabwe and Care of the Infant and Newborn, Malawi), and (3) identification of uncertainties within the literature for future studies. After agreement of clinical content, the algorithms were programmed into a test script, tested with the respective hospital's health care professionals (HCPs), and refined according to their feedback. Once finalized, the algorithms were programmed into the Neotree software and implemented at the tertiary-level implementation sites: Sally Mugabe Central Hospital in Zimbabwe and Kamuzu Central Hospital in Malawi, in December 2021 and May 2022, respectively. In Zimbabwe, usability was evaluated through 2 usability workshops and usability questionnaires: Post-Study System Usability Questionnaire (PSSUQ) and System Usability Scale (SUS).

RESULTS

Overall, 11 evidence-based diagnostic and management algorithms were tailored to local resource availability. These refined algorithms were then integrated into Neotree. Where national management guidelines differed, country-specific guidelines were created. In total, 9 HCPs attended the usability workshops and completed the SUS, among whom 8 (89%) completed the PSSUQ. Both usability scores (SUS mean score 75.8 out of 100 [higher score is better]; PSSUQ overall score 2.28 out of 7 [lower score is better]) demonstrated high usability of the CDS function but highlighted issues around technical complexity, which continue to be addressed iteratively.

CONCLUSIONS

This study describes the successful development and implementation of the only known neonatal CDS system, incorporated within a bedside data capture system with the ability to deliver up-to-date management guidelines, tailored to local resource availability. This study highlighted the importance of collaborative participatory design. Further implementation evaluation is planned to guide and inform the development of health system and program strategies to support newborn HCPs, with the ultimate goal of reducing preventable neonatal morbidity and mortality in low-resource settings.

Development and Pilot Implementation of Neotree, a Digital Quality Improvement Tool Designed to Improve Newborn Care and Survival in 3 Hospitals in Malawi and Zimbabwe: Cost Analysis Study

Background

Two-thirds of the 2.4 million newborn deaths that occurred in 2020 within the first 28 days of life might have been avoided by implementing existing low-cost evidence-based interventions for all sick and small newborns. An open-source digital quality improvement tool (Neotree) combining data capture with education and clinical decision support is a promising solution for this implementation gap.

Objective

We present results from a cost analysis of a pilot implementation of Neotree in 3 hospitals in Malawi and Zimbabwe.

Methods

We combined activity-based costing and expenditure approaches to estimate the development and implementation cost of a Neotree pilot in 1 hospital in Malawi, Kamuzu Central Hospital (KCH), and 2 hospitals in Zimbabwe, Sally Mugabe Central Hospital (SMCH) and Chinhoyi Provincial Hospital (CPH). We estimated the costs from a provider perspective over 12 months. Data were collected through expenditure reports, monthly staff time-use surveys, and project staff interviews. Sensitivity and scenario analyses were conducted to assess the impact of uncertainties on the results or estimate potential costs at scale. A pilot time-motion survey was conducted at KCH and a comparable hospital where Neotree was not implemented.

Results

Total cost of pilot implementation of Neotree at KCH, SMCH, and CPH was US $37,748, US $52,331, and US $41,764, respectively. Average monthly cost per admitted child was US $15, US $15, and US $58, respectively. Staff costs were the main cost component (average 73% of total costs, ranging from 63% to 79%). The results from the sensitivity analysis showed that uncertainty around the number of admissions had a significant impact on the costs in all hospitals. In Malawi, replacing monthly web hosting with a server also had a significant impact on the costs. Under routine (nonresearch) conditions and at scale, total costs are estimated to fall substantially, up to 76%, reducing cost per admitted child to as low as US $5 in KCH, US $4 in SMCH, and US $14 in CPH. Median time to admit a baby was 27 (IQR 20-40) minutes using Neotree (n=250) compared to 26 (IQR 21-30) minutes using paper-based systems (n=34), and the median time to discharge a baby was 9 (IQR 7-13) minutes for Neotree (n=246) compared to 3 (IQR 2-4) minutes for paper-based systems (n=50).

Conclusions

Neotree is a time- and cost-efficient tool, comparable with the results from limited similar mHealth decision-support tools in low- and middle-income countries. Implementation costs of Neotree varied substantially between the hospitals, mainly due to hospital size. The implementation costs could be substantially reduced at scale due to economies of scale because of integration to the health systems and reductions in cost items such as staff and overhead. More studies assessing the impact and cost-effectiveness of large-scale mHealth decision-support tools are needed.

Diagnosing early-onset neonatal sepsis in low-resource settings: development of a multivariable prediction model

OBJECTIVE

To develop a clinical prediction model to diagnose neonatal sepsis in low-resource settings.

DESIGN

Secondary analysis of data collected by the Neotree digital health system from 1 February 2019 to 31 March 2020. We used multivariable logistic regression with candidate predictors identified from expert opinion and literature review. Missing data were imputed using multivariate imputation and model performance was evaluated in the derivation cohort.

SETTING

A tertiary neonatal unit at Sally Mugabe Central Hospital, Zimbabwe.

PATIENTS

We included 2628 neonates aged <72 hours, gestation ≥32+0 weeks and birth weight ≥1500 g.

INTERVENTIONS

Participants received standard care as no specific interventions were dictated by the study protocol.

MAIN OUTCOME MEASURES

Clinical early-onset neonatal sepsis (within the first 72 hours of life), defined by the treating consultant neonatologist.

RESULTS

Clinical early-onset sepsis was diagnosed in 297 neonates (11%). The optimal model included eight predictors: maternal fever, offensive liquor, prolonged rupture of membranes, neonatal temperature, respiratory rate, activity, chest retractions and grunting. Receiver operating characteristic analysis gave an area under the curve of 0.74 (95% CI 0.70-0.77). For a sensitivity of 95% (92%-97%), corresponding specificity was 11% (10%-13%), positive predictive value 12% (11%-13%), negative predictive value 95% (92%-97%), positive likelihood ratio 1.1 (95% CI 1.0-1.1) and negative likelihood ratio 0.4 (95% CI 0.3-0.6).

CONCLUSIONS

Our clinical prediction model achieved high sensitivity with low specificity, suggesting it may be suited to excluding early-onset sepsis. Future work will validate and update this model before considering implementation within the Neotree.

Development and implementation experience of a learning healthcare system for facility based newborn care in low resource settings: The Neotree

Introduction

Improving peri- and postnatal facility-based care in low-resource settings (LRS) could save over 6000 babies' lives per day. Most of the annual 2.4 million neonatal deaths and 2 million stillbirths occur in healthcare facilities in LRS and are preventable through the implementation of cost-effective, simple, evidence-based interventions. However, their implementation is challenging in healthcare systems where one in four babies admitted to neonatal units die. In high-resource settings healthcare systems strengthening is increasingly delivered via learning healthcare systems to optimise care quality, but this approach is rare in LRS.

Methods

Since 2014 we have worked in Bangladesh, Malawi, Zimbabwe, and the UK to co-develop and pilot the Neotree system: an android application with accompanying data visualisation, linkage, and export. Its low-cost hardware and state-of-the-art software are used to support healthcare professionals to improve postnatal care at the bedside and to provide insights into population health trends. Here we summarise the formative conceptualisation, development, and preliminary implementation experience of the Neotree.

Results

Data thus far from ~18 000 babies, 400 healthcare professionals in four hospitals (two in Zimbabwe, two in Malawi) show high acceptability, feasibility, usability, and improvements in healthcare professionals' ability to deliver newborn care. The data also highlight gaps in knowledge in newborn care and quality improvement. Implementation has been resilient and informative during external crises, for example, coronavirus disease 2019 (COVID-19) pandemic. We have demonstrated evidence of improvements in clinical care and use of data for Quality Improvement (QI) projects.

Conclusion

Human-centred digital development of a QI system for newborn care has demonstrated the potential of a sustainable learning healthcare system to improve newborn care and outcomes in LRS. Pilot implementation evaluation is ongoing in three of the four aforementioned hospitals (two in Zimbabwe and one in Malawi) and a larger scale clinical cost effectiveness trial is planned.

Risk factors of mortality in neonates with neonatal encephalopathy in a tertiary newborn care unit in Zimbabwe over a 12-month period

Neonatal encephalopathy (NE) accounts for ~23% of the 2.4 million annual global neonatal deaths. Approximately 99% of global neonatal deaths occur in low-resource settings, however, accurate data from these low-resource settings are scarce. We reviewed risk factors of neonatal mortality in neonates admitted with neonatal encephalopathy from a tertiary neonatal unit in Zimbabwe. A retrospective review of risk factors of short-term neonatal encephalopathy mortality was conducted at Sally Mugabe Central Hospital (SMCH) (November 2018 -October 2019). Data were gathered using a tablet-based data capture and quality improvement newborn care application (Neotree). Analyses were performed on data from all admitted neonates with a diagnosis of neonatal encephalopathy, incorporating maternal, intrapartum, and neonatal risk predictors of the primary outcome: mortality. 494/2894 neonates had neonatal encephalopathy on admission and were included. Of these, 94 died giving a neonatal encephalopathy-case fatality rate (CFR) of 190 per 1000 admitted neonates. Caesarean section (odds ratio (OR) 2.95(95% confidence interval (CI) 1.39-6.25), convulsions (OR 7.13 (1.41-36.1)), lethargy (OR 3.13 (1.24-7.91)), Thompson score "11-14" (OR 2.98 (1.08-8.22)) or "15-22" (OR 17.61 (1.74-178.0)) were significantly associated with neonatal death. No maternal risk factors were associated with mortality. Nearly 1 in 5 neonates diagnosed with neonatal encephalopathy died before discharge, similar to other low-resource settings but more than in typical high-resource centres. The Thompson score, a validated, sensitive and specific tool for diagnosing neonates with neonatal encephalopathy was an appropriate predictive clinical scoring system to identify at risk neonates in this setting. On univariable analysis time-period, specifically a period of staff shortages due to industrial action, had a significant impact on neonatal encephalopathy mortality. Emergency caesarean section was associated with increased mortality, suggesting perinatal care is likely to be a key moment for future interventions.

Protocol for an intervention development and pilot implementation evaluation study of an e-health solution to improve newborn care quality and survival in two low-resource settings, Malawi and Zimbabwe: Neotree

INTRODUCTION

Every year 2.4 million deaths occur worldwide in babies younger than 28 days. Approximately 70% of these deaths occur in low-resource settings because of failure to implement evidence-based interventions. Digital health technologies may offer an implementation solution. Since 2014, we have worked in Bangladesh, Malawi, Zimbabwe and the UK to develop and pilot Neotree: an android app with accompanying data visualisation, linkage and export. Its low-cost hardware and state-of-the-art software are used to improve bedside postnatal care and to provide insights into population health trends, to impact wider policy and practice.

METHODS AND ANALYSIS

This is a mixed methods (1) intervention codevelopment and optimisation and (2) pilot implementation evaluation (including economic evaluation) study. Neotree will be implemented in two hospitals in Zimbabwe, and one in Malawi. Over the 2-year study period clinical and demographic newborn data will be collected via Neotree, in addition to behavioural science informed qualitative and quantitative implementation evaluation and measures of cost, newborn care quality and usability. Neotree clinical decision support algorithms will be optimised according to best available evidence and clinical validation studies.

ETHICS AND DISSEMINATION

This is a Wellcome Trust funded project (215742_Z_19_Z). Research ethics approvals have been obtained: Malawi College of Medicine Research and Ethics Committee (P.01/20/2909; P.02/19/2613); UCL (17123/001, 6681/001, 5019/004); Medical Research Council Zimbabwe (MRCZ/A/2570), BRTI and JREC institutional review boards (AP155/2020; JREC/327/19), Sally Mugabe Hospital Ethics Committee (071119/64; 250418/48). Results will be disseminated via academic publications and public and policy engagement activities. In this study, the care for an estimated 15 000 babies across three sites will be impacted.

TRIAL REGISTRATION NUMBER

NCT0512707; Pre-results.

The Impact of Interventions to Prevent Neonatal Healthcare-associated Infections in Low- and Middle-income Countries: A Systematic Review

BACKGROUND

Clinically suspected and laboratory-confirmed bloodstream infections are frequent causes of morbidity and mortality during neonatal care. The most effective infection prevention and control interventions for neonates in low- and middle-income countries (LMIC) are unknown.

AIM

To identify effective interventions in the prevention of hospital-acquired bloodstream infections in LMIC neonatal units.

METHODS

Medline, PUBMED, the Cochrane Database of Systematic Reviews, EMBASE and PsychInfo (January 2003 to October 2020) were searched to identify studies reporting single or bundled interventions for prevention of bloodstream infections in LMIC neonatal units.

RESULTS

Our initial search identified 5206 articles; following application of filters, 27 publications met the inclusion and Integrated Quality Criteria for the Review of Multiple Study Designs assessment criteria and were summarized in the final analysis. No studies were carried out in low-income countries, only 1 in Sub-Saharan Africa and just 2 in multiple countries. Of the 18 single-intervention studies, most targeted skin (n = 4) and gastrointestinal mucosal integrity (n = 5). Whereas emollient therapy and lactoferrin achieved significant reductions in proven neonatal infection, glutamine and mixed probiotics showed no benefit. Chlorhexidine gluconate for cord care and kangaroo mother care reduced infection in individual single-center studies. Of the 9 studies evaluating bundles, most focused on prevention of device-associated infections and achieved significant reductions in catheter- and ventilator-associated infections.

CONCLUSIONS

There is a limited evidence base for the effectiveness of infection prevention and control interventions in LMIC neonatal units; bundled interventions targeting device-associated infections were most effective. More multisite studies with robust study designs are needed to inform infection prevention and control intervention strategies in low-resource neonatal units.

Evaluation of a Novel Culture System for Rapid Pathogen Identification and Detection of Cephalosporin Resistance in Neonatal Gram-negative Sepsis at a Tertiary Referral Unit in Harare, Zimbabwe

BACKGROUND

Neonatal sepsis accounts for a large proportion of neonatal deaths in sub-Saharan Africa. The lack of access to diagnostic testing and excessively long turnaround times to result contributes to delays in sepsis identification and initiation of appropriate treatment. This study aims to evaluate the novel InTrays COLOREX Screen and extended-spectrum beta-lactamase for rapid identification of bacterial pathogens causing sepsis and detection of resistance.

METHODS

Neonates with suspected sepsis admitted to the Harare Central Hospital were prospectively enrolled. One blood culture was collected and incubated using the BacT/ALERT automated system. Positive blood cultures with potential pathogens identified by Gram stain were inoculated on the InTray COLOREX Screen and extended-spectrum beta-lactamase culture plates.

RESULTS

A total of 216 neonates with suspected sepsis were recruited. Pathogens were isolated from blood cultures in 56 (25.9%) neonates of which 54 were Klebsiella pneumoniae. All K. pneumoniae were resistant to ceftriaxone and 53 (98%) were resistant to gentamicin. Sensitivity and specificity for ceftriaxone-resistant K. pneumoniae detection using InTrays were 100%. InTrays results were interpretable as early as 5-10 hours (median 7 hours, interquartile range 7-7) post blood culture positivity enabling rapid identification and notification of result and leading to a 60% reduction in time to result from blood culture collection.

CONCLUSIONS

This study shows that the implementation of a novel culture method was feasible and reduced turnaround times for results by 60% compared with standard microbiologic techniques. An impact on patient outcomes and cost-effectiveness of this method needs to be demonstrated.

Metabolic gestational age assessment in low resource settings: a validation protocol

Preterm birth is the leading global cause of neonatal morbidity and mortality. Reliable gestational age estimates are useful for quantifying population burdens of preterm birth and informing allocation of resources to address the problem. However, evaluating gestational age in low-resource settings can be challenging, particularly in places where access to ultrasound is limited. Our group has developed an algorithm using newborn screening analyte values derived from dried blood spots from newborns born in Ontario, Canada for estimating gestational age within one to two weeks. The primary objective of this study is to validate a program that derives gestational age estimates from dried blood spot samples (heel-prick or cord blood) collected from health and demographic surveillance sites and population representative health facilities in low-resource settings in Zambia, Kenya, Bangladesh and Zimbabwe. We will also pilot the use of an algorithm to identify birth percentiles based on gestational age estimates and weight to identify small for gestational age infants. Once collected from local sites, samples will be tested by the Newborn Screening Ontario laboratory at the Children's Hospital of Eastern Ontario (CHEO) in Ottawa, Canada. Analyte values will be obtained through laboratory analysis for estimation of gestational age as well as screening for other diseases routinely conducted at Ontario's newborn screening program. For select conditions, abnormal screening results will be reported back to the sites in real time to facilitate counseling and future clinical management. We will determine the accuracy of our existing algorithm for estimation of gestational age in these newborn samples. Results from this research hold the potential to create a feasible method to assess gestational age at birth in low- and middle-income countries where reliable estimation may be otherwise unavailable.

Electronic application to improve management of infections in low-income neonatal units: pilot implementation of the NeoTree beta app in a public sector hospital in Zimbabwe

There are 2. 4 million annual neonatal deaths worldwide. Simple, evidence-based interventions such as temperature control could prevent approximately two-thirds of these deaths. However, key problems in implementing these interventions are a lack of newborn-trained healthcare workers and a lack of data collection systems. NeoTree is a digital platform aiming to improve newborn care in low-resource settings through real-time data capture and feedback alongside education and data linkage. This project demonstrates proof of concept of the NeoTree as a real-time data capture tool replacing handwritten clinical paper notes over a 9-month period in a tertiary neonatal unit at Harare Central Hospital, Zimbabwe. We aimed to deliver robust data for monthly mortality and morbidity meetings and to improve turnaround time for blood culture results among other quality improvement indicators. There were 3222 admissions and discharges entered using the NeoTree software with 41 junior doctors and 9 laboratory staff trained over the 9-month period. The NeoTree app was fully integrated into the department for all admission and discharge documentation and the monthly presentations became routine, informing local practice. An essential factor for this success was local buy-in and ownership at each stage of the project development, as was monthly data analysis and presentations allowing us to rapidly troubleshoot emerging issues. However, the laboratory arm of the project was negatively affected by nationwide economic upheaval. Our successes and challenges piloting this digital tool have provided key insights for effective future roll-out in Zimbabwe and other low-income healthcare settings.

Barriers and facilitators to infection prevention and control in a neonatal unit in Zimbabwe - a theory-driven qualitative study to inform design of a behaviour change intervention

BACKGROUND

Hospital-acquired infection (HAI) is an increasing cause of neonatal morbidity/mortality in low-income settings. Hospital staff behaviours (e.g., hand hygiene) are key contributors to HAI. Understanding the drivers of these can inform interventions to improve infection prevention and control (IPC).

AIM

To explore barriers/facilitators to IPC in a neonatal unit in Harare, Zimbabwe.

METHODS

Interviews were conducted with 15 staff members of neonatal and maternity units alongside ethnographic observations. The interview guide and data analysis were informed by the COM-B (Capability, Opportunity, Motivation-Behaviour) model and explored individual, socio-cultural, and organizational barriers/facilitators to IPC. Potential interventions were identified using the Behaviour-Change Wheel.

FINDINGS

Enablers within Capability included awareness of IPC, and within Motivation beliefs that IPC was crucial to one's role, and concerns about consequences of poor IPC. Staff were optimistic that IPC could improve, contingent upon resource availability (Opportunity). Barriers included: limited knowledge of guidelines, no formal feedback on performance (Capability), lack of resources (Opportunity), often leading to improvization and poor habit formation. Further barriers included the unit's hierarchy, e.g., low engagement of cleaners and mothers in IPC, and staff witnessing implementation of poor practices by other team members (Opportunity). Potential interventions could include role-modelling, engaging mothers and staff across cadres, audit and feedback and flexible protocols (adaptable to water/handrub availability).

CONCLUSIONS

Most barriers to IPC fell within Opportunity, whilst most enablers fell under Capability and Motivation. Theory-based investigation provides the basis for systematically identifying and developing interventions to address barriers and enablers to IPC in low-income settings.

Metabolic gestational age assessment in low resource settings: a validation protocol

Preterm birth is the leading global cause of neonatal morbidity and mortality. Reliable gestational age estimates are useful for quantifying population burdens of preterm birth and informing allocation of resources to address the problem. However, evaluating gestational age in low-resource settings can be challenging, particularly in places where access to ultrasound is limited. Our group has developed an algorithm using newborn screening analyte values derived from dried blood spots from newborns born in Ontario, Canada for estimating gestational age within one to two weeks. The primary objective of this study is to validate a program that derives gestational age estimates from dried blood spot samples (heel-prick or cord blood) collected from health and demographic surveillance sites and population representative health facilities in low-resource settings in Zambia, Kenya, Bangladesh and Zimbabwe. We will also pilot the use of an algorithm to identify birth percentiles based on gestational age estimates and weight to identify small for gestational age infants. Once collected from local sites, samples will be tested by the Newborn Screening Ontario laboratory at the Children’s Hospital of Eastern Ontario (CHEO) in Ottawa, Canada. Analyte values will be obtained through laboratory analysis for estimation of gestational age as well as screening for other diseases routinely conducted at Ontario’s newborn screening program. For select conditions, abnormal screening results will be reported back to the sites in real time to facilitate counseling and future clinical management. We will determine the accuracy of our existing algorithm for estimation of gestational age in these newborn samples. Results from this research hold the potential to create a feasible method to assess gestational age at birth in low- and middle-income countries where reliable estimation may be otherwise unavailable.

Auditing use of antibiotics in Zimbabwean neonates

BACKGROUND

Neonatal sepsis is a major cause of morbidity and mortality in low-income settings. As signs of sepsis are non-specific and deterioration precipitous, antibiotics are often used profusely in these settings where diagnostics may not be readily available. Harare Central Hospital, Zimbabwe, delivers 12000 babies per annum admitting ∼4800 to the neonatal unit. Overcrowding, understaffing and rapid staff turnover are consistent problems. Suspected sepsis is highly prevalent, and antibiotics widely used. We audited the impact of training and benchmarking intervention on rationalizing antibiotic prescription using local, World Health Organization-derived, guidelines as the standard.

METHODS

An initial audit of admission diagnosis and antibiotic use was performed between 8th May - 6th June 2018 as per the audit cycle. An intern training programme, focusing on antimicrobial stewardship and differentiating between babies 'at risk of' versus 'with' clinically-suspected sepsis was instituted post-primary audit. Re-audit was conducted after 5 months.

RESULTS

Sepsis was the most common admitting diagnosis by interns at both time points but reduced at repeat audit (81% versus 59%, P<0.0001). Re-audit after 5 months demonstrated a decrease in antibiotic prescribing at admission and discharge. Babies prescribed antibiotics at admission decreased from 449 (98%) to 96 (51%), P<0.0001. Inpatient days of therapy (DOT) reduced from 1243 to 1110/1000 patient-days. Oral amoxicillin prescription at discharge reduced from 349/354 (99%) to 1% 1/161 (P<0.0001).

CONCLUSION

A substantial decrease in antibiotic use was achieved by performance feedback, training and leadership, although ongoing performance review will be key to ensuring safety and sustainability.

Childhood Cancers in Zimbabwe: A 10 year review of the Zimbabwe National Cancer Registry data

OBJECTIVE

To document the pattern of cancer in children (0-14 years) registered in the Zimbabwe National Cancer Registry from 2000-2009.

DESIGN

Retrospective descriptive analysis.

METHODS

Analysis of data from the Zimbabwe National Cancer Registry for the period 2000-2009.

SETTING

The Zimbabwe National Cancer Registry.

RESULTS

Childhood Cancer constituted 3.8% of all malignancies recorded at the cancer registry during the study period. The common cancers were: Wilm's Tumour 286 (16.2%), Kaposi Sarcoma 277 (15.7%), Retinoblastoma 231 (13.1%), Non- Hodgkins lymphoma 182 (10.3%), leukemia 158 (8.9%), brain and nervous tissue 107 (6.1%), connective tissue 105 (5.9%), bone 97 (5.5%), Hodgkins lymphoma 57 (3.2%), Non-melanoma skin 33 (1.9%). All the other remaining cancers were 233 (13.2%). Burkits lymphoma constituted only 2% of all cancers. The noted pattern of cancers in this study were compared to patterns from other countries and similarities and differences are discussed.

CONCLUSION

This study showed high incidence rates of Nephroblastoma, Retinoblastoma and Kaposi sarcoma. In contrast to high income countries leukemia and brain tumours are more prevalent in older age group. Compared to other countries in Africa, Burkits lymphoma was rare. Further research is required to identify factors that influence relative frequencies in childhood cancers in Zimbabwe. Findings from this study provide baseline data for future studies.

Determinants of premature births in two central hospital Harare, Zimbabwe, 2011

INTRODUCTION

Prematurity is a major determinant of neonatal morbidity and mortality in Zimbabwe. Although 8-10% of deliveries are premature , prematurity contributes 33% of neonatal deaths. Identifying local risk factors for prematurity could help incoming up with local intervention and prevention strategies.

DESIGN

1:1 unmatched case control study.

SETTING

Harare and Parirenyatwa central hospitals maternity units.

SUBJECTS

All mothers who delivered in the units June to July 2011. Acase was a mother who had delivered a premature baby and control was a mother who delivered a term baby.

RESULTS

We interviewed 188 cases and 188 controls. Independent risk factors for premature delivery were -A previous premature delivery [AOR 3.15 95% CI 1.17 8.49, 4.61] being admitted with a medical complication in pregnancy[AOR 2.15 95% CI 1.18-3.92]. Birth interval > 24 months [AOR 0.26 95% CI 0.12 0.59] being well nourished evidenced by BMI ≥20kg/m [ AOR 0.926 95% CI 0.88 0.97] and MUAC ≥23cm [AOR 0.95 95% CI 0.91 0.95] reduced the risk of premature delivery. HIV test was done on 87% of participants, 12% were positive (66% controls, 33% cases) (p≤0.001).

CONCLUSION

Birth interval < 24 months, previous premature delivery, only one ANC attendance, maternal under nutrition and being hospitalized with complications in pregnancy were associated with premature delivery. There was no association with HIV infection. Efforts should be made to give food supplements to pregnant undernourished women.