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

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

The use of data in resource limited settings to improve quality of care

Quality improvement is driven by benchmarking between and within institutions over time and the collaborative improvement efforts that stem from these comparisons. Benchmarking requires systematic collection and use of standardized data. Low- and middle-income countries (LMIC) have great potential for improvements in newborn outcomes but serious obstacles to data collection, analysis, and implementation of robust improvement methodologies exist. We review the importance of data collection, internationally recommended neonatal metrics, selected methods of data collection, and reporting. The transformation from data collection to data use is illustrated by several select data system examples from LMIC. Key features include aims and measures important to neonatal team members, co-development with local providers, immediate access to data for review, and multidisciplinary team involvement. The future of neonatal care, use of data, and the trajectory to reach global neonatal improvement targets in resource-limited settings will be dependent on initiatives led by LMIC clinicians and experts

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 fifteen 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 organisational 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 improvisation 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 basis for systematically identifying and developing interventions to address barriers and enablers to IPC in low-income settings

Interventions to prevent neonatal healthcare-associated infections in low-resource settings: 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 (IPC) 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 – 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 ICROMS assessment criteria and were summarised in the final analysis. No studies were carried out in low-income countries, only one in sub-Saharan Africa and just two 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-centre studies. Of the nine studies evaluating bundles, most focused on prevention of device-associated infections and achieved significant reductions in catheter- and ventilator-associated infections. Conclusion: There is a limited evidence-base for the effectiveness of IPC interventions in LMIC neonatal units; bundled interventions targeting device-associated infections were most effective. More multi-site studies with robust study designs are needed to inform IPC intervention strategies in low-resource neonatal units

Indirect impacts of the COVID-19 pandemic at two tertiary neonatal units in Zimbabwe and Malawi: an interrupted time series analysis.

OBJECTIVES: To examine indirect impacts of the COVID-19 pandemic on neonatal care in low-income and middle-income countries. DESIGN: Interrupted time series analysis. SETTING: Two tertiary neonatal units in Harare, Zimbabwe and Lilongwe, Malawi. PARTICIPANTS: We included a total of 6800 neonates who were admitted to either neonatal unit from 1 June 2019 to 25 September 2020 (Zimbabwe: 3450; Malawi: 3350). We applied no specific exclusion criteria. INTERVENTIONS: The first cases of COVID-19 in each country (Zimbabwe: 20 March 2020; Malawi: 3 April 2020). PRIMARY OUTCOME MEASURES: Changes in the number of admissions, gestational age and birth weight, source of admission referrals, prevalence of neonatal encephalopathy, and overall mortality before and after the first cases of COVID-19. RESULTS: Admission numbers in Zimbabwe did not initially change after the first case of COVID-19 but fell by 48% during a nurses' strike (relative risk (RR) 0.52, 95% CI 0.41 to 0.66, p0.05). CONCLUSIONS: The indirect impacts of COVID-19 are context-specific. While our study provides vital evidence to inform health providers and policy-makers, national data are required to ascertain the true impacts of the pandemic on newborn health

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

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

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

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