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Huxford, Charly; Nguyen, Vuong; Trawin, Jessica; Johnson, Teresa; Kissoon, Niranjan; Wiens, Matthew; Ogilvie, Gina; Murthy, Srinivas; Dhugga, Gurm; Kinshella, Maggie Woo; Ansermino, J Mark — 2023-04-18 <strong>Objective(s):</strong> Momentum for open access to research is growing. Funding agencies and publishers are increasingly requiring researchers make their data and research outputs open and publicly available. However, this introduces many challenges, especially when managing confidential clinical data.<br /> <br />The aim of this 1 hr virtual workshop is to provide participants with knowledge about what synthetic data is, methods to create synthetic data, and the 2023 Pediatric Sepsis Data Challenge.<br /> <br />Workshop Agenda:<br /> <br />1. Introduction - Speaker: Mark Ansermino, Director, Centre for International Child Health <br /> <br />2. "Leveraging Synthetic Data for an International Data Challenge" - Speaker: Charly Huxford, Research Assistant, Centre for International Child Health <br /> <br />3. "Methods in Synthetic Data Generation." - Speaker: Vuong Nguyen, Biostatistician, Centre for International Child Health and The HIPpy Lab <br /> <br />This workshop draws on work supported by the Digital Research Alliance of Canada.<br /> <br /><strong>Data Description:</strong> Presentation slides, Workshop Video, and Workshop Communication<br /> <br />Charly Huxford: Leveraging Synthetic Data for an International Data Challenge presentation and accompanying PowerPoint slides.<br /> <br />Vuong Nguyen: Methods in Synthetic Data Generation presentation and accompanying Powerpoint slides.<br /> <br />This workshop was developed as part of Dr. Ansermino's Data Champions Pilot Project supported by the <a href = "https://alliancecan.ca/en">Digital Research Alliance of Canada</a>.<br /> <br /><strong>NOTE for restricted files:</strong> If you are not yet a CoLab member, please complete our <a href = "https://rc.bcchr.ca/redcap/surveys/?s=EDCYL7AC79">membership application survey</a> to gain access to restricted files within 2 business days. <br />Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator on <a href = "https://www.bcchr.ca/pediatric-sepsis-data-colab">this page</a> under "collaborate with the pediatric sepsis colab."

Wiens, Matthew O; Bone, Jeffrey N; Kumbakumba, Elias; Businge, Stephen; Tagoola, Abner; Sherine, Sheila Oyella; Byaruhanga, Emmanuel; Ssemwanga, Edward; Barigye, Celestine; Nsungwa, Jesca; Olaro, Charles; Ansermino, J Mark; Kissoon, Niranjan; Singer, Joel; Larson, Charles P; Lavoie, Pascal M; Dunsmuir, Dustin; Moschovis, Peter P; Novakowski, Stefanie; Komugisha, Clare; Tayebwa, Mellon; Mwesignwa, Douglas; Knappett, Martina; West, Nicholas; Nguyen, Vuong; Mugisha, Nathan-Kenya; Kabakyenga, Jerome — 2022-12-06 <br /><strong>Background:</strong> Substantial mortality occurs after hospital discharge in children younger than 5 years with suspected sepsis, especially in low-income countries. A better understanding of its epidemiology is needed for effective interventions to reduce child mortality in these countries. We evaluated risk factors for death after discharge in children admitted to hospital for suspected sepsis in Uganda, and assessed how these differed by age, time of death, and location of death. <br /> <br /><strong>Methods:</strong> In this prospective observational cohort study, we recruited 0-60-month-old children admitted with suspected sepsis from the community to the paediatric wards of six Ugandan hospitals. The primary outcome was six-month post-discharge mortality among those discharged alive. We evaluated the interactive impact of age, time of death, and location of death on risk factors for mortality.<br /> <br /><strong>Findings:</strong> 6,545 children were enrolled, with 6,191 discharged alive. The median (interquartile range) time from discharge to death was 28 (9-74) days, with a six-month post-discharge mortality rate of 5·5%, constituting 51% of total mortality. Deaths occurred at home (45%), in-transit to care (18%), or in hospital (37%) during a subsequent readmission. Post-discharge death was strongly associated with weight-for-age z-scores < -3 (adjusted risk ratio [aRR] 4·7, 95% CI 3·7–5·8 vs a Z score of >–2), referral for further care (7·3, 5·6–9·5), and unplanned discharge (3·2, 2·5–4·0). The hazard ratio of those with severe anaemia increased with time since discharge, while the hazard ratios of discharge vulnerabilities (unplanned, poor feeding) decreased with time. Age influenced the effect of several variables, including anthropometric indices (less impact with increasing age), anaemia (greater impact), and admission temperature (greater impact).<br /> <br /><strong>Data Collection Methods:</strong> All data were collected at the point of care using encrypted study tablets and these data were then uploaded to a Research Electronic Data Capture (REDCap) database hosted at the BC Children’s Hospital Research Institute (Vancouver, Canada). At admission, trained study nurses systematically collected data on clinical, social and demographic variables. Following discharge, field officers contacted caregivers at 2 and 4 months by phone, and in-person at 6 months, to determine vital status, post-discharge health-seeking, and readmission details. Verbal autopsies were conducted for children who had died following discharge.<br /> <br /><strong>Data Processing Methods:</strong> For this analysis, data from both cohorts (0-6 months and 6-60 months) were combined and analysed as a single dataset. We used periods of overlapping enrolment (72% of total enrolment months) between the two cohorts to determine site-specific proportions of children who were 0-6 and 6-60 months of age. These proportions were used to weight the cohorts for the calculation of overall mortality rate. Z-scores were calculated using height and weight. Hematocrit was converted to hemoglobin. Distance to hospital was calculated using latitude and longitude. Extra symptom and diagnosis categories were created based on text field in these two variables. BCS score was created by summing all individual components.<br /> <br /><strong>Abbreviations:</strong><br /> MUAC -mid upper arm circumference<br /> wfa – weight for age<br /> wfl – weight for length<br /> bmi – body mass index<br /> lfa – length for age<br /> abx - antibiotics<br /> hr – heart rate<br /> rr – respiratory rate<br /> antimal - antimalarial<br /> sysbp – systolic blood pressure<br /> diasbp – diastolic blood pressure<br /> resp – respiratory<br /> cap - capillary<br /> BCS - Blantyre Coma Scale<br /> dist- distance<br /> hos - hospital<br /> ed - education<br /> disch - discharge<br /> dis -discharge<br /> fu – follow-up<br /> pd – post-discharge<br /> loc - location<br /> materl - maternal<br /> <br /><strong>Ethics Declaration:</strong> This study was approved by the Mbarara University of Science and Technology Research Ethics Committee (No. 15/10-16), the Uganda National Institute of Science and Technology (HS 2207), and the University of British Columbia / Children & Women’s Health Centre of British Columbia Research Ethics Board (H16-02679). This manuscript adheres to the guidelines for STrengthening the Reporting of OBservational studies in Epidemiology (STROBE).<br /> <br /><strong>Study Protocol & Supplementary Materials:</strong> <br /> <a href = "https://borealisdata.ca/dataset.xhtml?persistentId=doi%3A10.5683%2FSP3%2FQRUMNQ&version=1.0">Smart Discharges to improve post-discharge health outcomes in children: A prospective before-after study with staggered implementation </a><br /> <br /><strong>NOTE for restricted files:</strong> If you are not yet a CoLab member, please complete our <a href = "https://rc.bcchr.ca/redcap/surveys/?s=EDCYL7AC79">membership application survey</a> to gain access to restricted files within 2 business days. <br />Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at <a href = mailto:sepsiscolab@bccchr.ca>sepsiscolab@bcchr.ca</a> or visit our <a href = "https://wfpiccs.org/pediatric-sepsis-colab/">website</a>.

Umuhoza, Christian; Zhang, Cherri; Hooft, Anneka; Trawin, Jessica; Uwiragiye, Emmanuel; Mfuranziza, Cynthia Grace; Nguyen, Vuong; Lewis, Peter; Kornblith, Aaron E; Kenya-Mughisha, Nathan; Wiens, Matthew O — 2024-04-18 <br/><strong>Background:</strong>In Sub-Saharan Africa, pediatric post-discharge death is increasingly recognized as an important contributor to mortality. To address morbidity and mortality during this period, it is critical to generate a representative evidence base throughout sub-Saharan Africa to inform resource prioritization, as well as policy and guideline development. To date, no studies have been conducted in Rwanda, limiting the understanding of the epidemiology of post-discharge mortality in this region. This study aims to describe the epidemiology of post-discharge mortality in a group of children admitted for suspected sepsis in Rwanda.<br /> <br /><strong>Methods:</strong> We prospectively recruited children aged 0-60 months admitted for suspected sepsis at two sites in Rwanda: Ruhengeri Referral Hospital in Musanze, Rwanda (rural) and University Hospital of Kigali in Kigali, Rwanda (urban) from May 2022 - February 2023. Clinical, laboratory and social variables were collected at admission. Following discharge, participants were followed up to 6 months to determine vital status and health-seeking. We analyzed data in two age-specific cohorts, defined a priori: 0-6m and 6-60m. Multivariate logistic regression was used to identify risk factors. Age-stratified Kaplan-Meier curves were used to estimate the cumulative hazard of 6-month post-discharge mortality.<br /> <br /><strong>Findings:</strong>Of 1218 children enrolled, 115 died (11%): 50% in-hospital (n=57) and 50% after discharge (n=58). Post-discharge mortality was higher in 0-6m cohort (n=28/274, 10%) than in those 6-60m (30/850, 4%), and in Kigali (n=37/413, 9%) vs Ruhengeri (n=21/805, 3%). Median time to post-discharge death was ~1 month (38d in 0-6m; 33d in 6-60m). In both cohorts, increased odds of post-discharge death were associated with weight-for-age z-score <-3 (OR=3.16 (1.26-7.93), 0-6m; OR=7.44 (2.93-18.89), 6-60m) while higher maternal education was protective (OR=0.15 (0.03-0.85), 0-6m; OR=0.09 (0.02-0.75), 6-60m). Abnormal coma scale (OR=3.29 (1.47-7.38)), travel time of >2h (OR=4.63 (1.40-15.22)) and being referred for higher level of care (OR=4.09 (1.04-16.12)) were significant in 6-60 months. Younger children were at highest risk of cumulative mortality.<br /> <br /><strong>Ethics Declaration:</strong> Ethical approval was obtained from the University of Rwanda College of Medicine and Health Sciences (No 411/CMHS IRB/2021); University Teaching Hospital of Kigali (EC/CHUK/005/2022), University of California San Francisco (381688) and the University of British Columbia (H21-02795).<br />

Wiens, Matthew O; Tagoola, Abner; Kissoon, Niranjan; Ansermino, J Mark; Oyella Sherine, Sheila; Byaruhanga, Emmanuel; Ssemwanga, Edwards; Zhang, Cherri; Nguyen, Vuong; Bone, Jeffery N; Kenya Mugisha, Nathan; Kumbakumba, Elias; Kabakyenga, Jerome — 2024-07-22 <br/><strong>Background:</strong> In Sub-Saharan Africa, pediatric post-discharge death is increasingly recognized as an important contributor to mortality. Current studies evaluating interventional approaches for post-discharge mortality focus on pharmacologic therapy, though only malaria prophylaxis post-discharge appears effective. Approaches to reduce vulnerability through health system strengthening approaches may further help to improve outcomes. This study aimed to evaluate the impact of a risk-differentiated approach to improved peri-discharge care on post-discharge mortality among children under 60 months.<br /> <br /><strong>Methods:</strong> We conducted a prospective parallel cluster crossover trial at 6 hospitals in Uganda. Children <60 months admitted due to suspected infectious illness were eligible for enrollment. Phase 1 was a comparative control. During phase 2, enrolled children were screened for post-discharge mortality risk at admission using a multivariable risk algorithm. All children received counselling on post-discharge care practices during admission and at discharge. High-risk children received referrals and automated SMS engagement at 2, 7 and 14 days at a clinic of their choice, or by a community health worker. Survival analysis, adjusting for age, sex, site, period time and predicted risk of mortality was used to estimate the effect of the intervention on 6-month all-cause post-discharge mortality.<br /> <br /><strong>Findings:</strong> 13,050 patients were enrolled (phase 1: n=6954; phase 2: n=6096) and had complete 6-month follow-up. Baseline characteristics were similar between groups. The median age was 0.8 months (IQR: 0.2-1.7), with 56% of participants male. The multivariable risk algorithm gave a mean predicted risk of post-discharge mortality of 6.1% in phase 1 and 5.9% in phase 2. The rate of post-discharge mortality was 6.0% during phase 1 and 4.9% during phase 2, with an adjusted hazard ratio of 0.77 (95% CI – 0.90), favoring the intervention. Additional sensitivity analysis using different sets of covariates in the model showed similar results. <br /> <br /><strong>Ethics Declaration:</strong> These studies were approved by the Mbarara University of Science and Technology (No. 15/10-16), the Uganda National Council for Science and Technology (HS 2207), and the University of British Columbia (H16-02679).<br /> <br /><strong>NOTE for restricted files:</strong> If you are not yet a CoLab member, please complete our <a href = "https://rc.bcchr.ca/redcap/surveys/?s=EDCYL7AC79">membership application survey</a> to gain access to restricted files within 2 business days. <br />Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at <a href = mailto:sepsiscolab@bccchr.ca>sepsiscolab@bcchr.ca</a> or visit our <a href = "https://wfpiccs.org/pediatric-sepsis-colab/">website</a>.

Knappett, Martina; Nguyen, Vuong; Chaudhry, Maryum; Trawin, Jessica; Kabakyenga, Jerome; Kumbakumba, Elias; Jacob, Shevin T; Ansermino, J Mark; Kissoon, Niranjan; Kenya-Mugisha, Nathan; Wiens, Matthew O — 2024-02-02 <br /><strong>NOTE for restricted files:</strong> If you are not yet a CoLab member, please complete our <a href = "https://rc.bcchr.ca/redcap/surveys/?s=EDCYL7AC79">membership application survey</a> to gain access to restricted files within 2 business days. <br />Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at <a href = mailto:sepsiscolab@bccchr.ca>sepsiscolab@bcchr.ca</a> or visit our <a href = "https://wfpiccs.org/pediatric-sepsis-colab/">website</a>. <br/><strong>Background:</strong> Under-five mortality remains concentrated in resource-poor countries. Post-discharge mortality is becoming increasingly recognized as a significant contributor to overall child mortality. With a substantial recent expansion of research and novel data synthesis methods, this study aims to update the current evidence base by providing a more nuanced understanding of the burden and associated risk factors of pediatric post-discharge mortality after acute illness.<br /> <br /><strong>Methods:</strong> Eligible studies published between January 1, 2017 and January 31, 2023, were retrieved using MEDLINE, Embase, and CINAHL databases. Studies published before 2017 were identified in a previous review and added to the total pool of studies. Only studies from countries with low or low-middle Socio-Demographic Index with a post-discharge observation period greater than seven days were included. Risk of bias was assessed using a modified version of the Joanna Briggs Institute critical appraisal tool for prevalence studies. Studies were grouped by patient population, and 6-month post-discharge mortality rates were quantified by random-effects meta-analysis. Secondary outcomes included post-discharge mortality relative to in-hospital mortality, pooled risk factor estimates, and pooled post-discharge Kaplan–Meier survival curves. PROSPERO study registration: #CRD42022350975.<br /> <br /><strong>Findings:</strong> Of 1963 articles screened, 42 eligible articles were identified and combined with 22 articles identified in the previous review, resulting in 64 total articles. These articles represented 46 unique patient cohorts and included a total of 105,560 children. For children admitted with a general acute illness, the pooled risk of mortality six months post-discharge was 4.4% (95% CI: 3.5%–5.4%, I2 = 94.2%, n = 11 studies, 34,457 children), and the pooled in-hospital mortality rate was 5.9% (95% CI: 4.2%–7.7%, I2 = 98.7%, n = 12 studies, 63,307 children). Among disease subgroups, severe malnutrition (12.2%, 95% CI: 6.2%–19.7%, I2 = 98.2%, n = 10 studies, 7760 children) and severe anemia (6.4%, 95% CI: 4.2%–9.1%, I2 = 93.3%, n = 9 studies, 7806 children) demonstrated the highest 6-month post-discharge mortality estimates. Diarrhea demonstrated the shortest median time to death (3.3 weeks) and anemia the longest (8.9 weeks). Most significant risk factors for post-discharge mortality included unplanned discharges, severe malnutrition, and HIV seropositivity.<br /> <br /><strong>Interpretation:</strong> Pediatric post-discharge mortality rates remain high in resource-poor settings, especially among children admitted with malnutrition or anemia. Global health strategies must prioritize this health issue by dedicating resources to research and policy innovation.<br /> <br /><strong>Data Processing Methods:</strong> Data were extracted using a standard data extraction form developed by the review authors. Kaplan–Meier survival curves, where provided, were extracted using a plot digitizer. The data extraction file, “PDMSR2024_DataExtraction_Dataset_SD” was generated as described above and analyzed as is. <br /> <br />Co-ordinates were extracted from the survival curves in their original, published form, using a plot digitizer (https://automeris.io/WebPlotDigitizer/). The co-ordinates for each survival curve were then cleaned up to: <br /> <br />1. Re-scale the time points to weeks<br /> 2. Curves which reported % mortality were converted to % survival (1 – mortality)<br /> 3. First co-ordinate was set to (0, 1), i.e., survival is 100% at time-point 0<br /> 4. Include the numbers at risk (if reported), primary reference, and subgroup information<br /> <br />Using these cleaned co-ordinates, individual-level patient data were extracted (see Guyot et al, 2012, <a href = "https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/1471-2288-12-9">doi.org/10.1186/1471-2288-12-9</a>) and the survival curves re-constructed to obtain the survival and number at risk at specified time-points (0-52 weeks). Where possible, disease and age subgroups were combined to create all admissions curves by combining the individual-level patient data from multiple curves in the same study. <br /> <br />Additional data from the survival curves were extracted to produce the “PDMSR2024_AdditionalDataSurvivalCurves6M_Dataset_SD” and “PDMSR2024_AdditionalDataSurvivalCurves12M_Dataset_SD” files by extracting the survival rate at 6 and 12 months. <br /> <br />Previously unpublished hazards ratios were extracted from the dataset used in the Wiens et al (2015) study on post-discharge mortality (<a href = "https://doi.org/10.1136%2Fbmjopen-2015-009449">doi:10.1136/bmjopen-2015-009449</a>) to produce the “PDMSR2024_Wiens2015HazardsRatios_Dataset_SD.xlsx” file. These original data are published on Dataverse at: <a href = "https://doi.org/10.5683/SP2/VBPLRM">doi.org/10.5683/SP2/VBPLRM</a> <br /> <br />Analyses were in R version 4.3.0 (R Foundation for Statistical Computing, Vienna, Austria), and RStudio version 2023.6.1 (RStudio, Boston, MA). <br /> <br /><strong>Additional Files:</strong> Survival curves in their original, published form, as well as survival curve coordinates files can be made available by request.

Pillay, Yashodani; Ngonzi, Joseph; Nguyen, Vuong; Payne, Beth A.; Komugisha, Clare; Twinomujuni, Annet H.; Vidler, Marianne; Lavoie, Pascal M.; Bebell, Lisa M.; Christoffersen-Deb, Astrid; Kenya-Mugisha, Nathan; Kissoon, Niranjan; Ansermino, J Mark; Wiens, Matthew O — 2023-11-09 <br/><strong>Background:</strong> The first six weeks following delivery bear the most significant and persistent burden of under-5 and maternal death, and severe neonatal and maternal morbidity. Efforts are currently underway to improve outcomes immediately following births at health facilities for both mothers and newborns. However, care following facility discharge presents significant challenges and accounts for a high proportion of maternal and neonatal death and morbidity. The objective of this study is to develop a clinical risk prediction model using maternal and infant characteristics collected at the time of hospital discharge following a facility delivery to predict maternal or neonatal death or major morbidity within six weeks of birth. A secondary objective is to characterize the epidemiology of post-discharge mortality and morbidity for women and their infants after facility delivery. <br/> <br /><strong>Methods:</strong> We will recruit a cohort of 3200 maternal and infant pairs after delivery at Mbarara Regional Referral Hospital to develop the risk model. This study involves prospective recruitment and data collection prior to discharge and final follow-up at six weeks postpartum for both mom and baby. Initial data collection will be completed by study research nurses as a prospective chart review and time of discharge patient assessment. Data collection will include maternal socio-demographics variables, clinical condition during admission, details of delivery and co-morbid conditions and maternal and infant vital signs at hospital discharge. Six-week follow up will be completed in person at the facility or through telephone follow-up to capture any maternal or infant adverse outcomes, including details of any re-admission to hospital, occurring after the initial discharge.<br /> <br /><strong>Ethics Declaration:</strong> Institutional review boards at the University of British Columbia (H18-02523), the Mbarara University of Science and Technology (14/09-18), and the Uganda National Council for Science and Technology (SS 4853) approved the study.<br /> <br /><strong>NOTE for restricted files:</strong> If you are not yet a CoLab member, please complete our <a href = "https://rc.bcchr.ca/redcap/surveys/?s=EDCYL7AC79">membership application survey</a> to gain access to restricted files within 2 business days. <br />Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at <a href = mailto:sepsiscolab@bccchr.ca>sepsiscolab@bcchr.ca</a> or visit our <a href = "https://wfpiccs.org/pediatric-sepsis-colab/">website</a>.

Nguyen, Vuong; Huxford, Charly; Rafiei, Alireza; Wiens, Matthew; Ansermino, J Mark; Kissoon, Niranjan; Kamaleswaran, Rishikesan — 2023-06-21 <p><br /><strong>Objective(s):</strong> The 2024 Pediatric Sepsis Data Challenge provides an opportunity to address the lack of appropriate mortality prediction models for LMICs. For this challenge, we are asking participants to develop a working, open-source algorithm to predict in-hospital mortality and length of stay using only the provided synthetic dataset. <br> <br> The original data used to generate the real-world data (RWD) informed synthetic training set available to participants was obtained from a prospective, multisite, observational cohort study of children with suspected sepsis aged 6 months to 60 months at the time of admission to hospitals in Uganda. For this challenge, we have created a RWD-informed synthetically generated training data set to reduce the risk of re-identification in this highly vulnerable population. The synthetic training set was generated from a random subset of the original data (full dataset A) of 2686 records (70% of the total dataset - training dataset B). All challenge solutions will be evaluated against the remaining 1235 records (30% of the total dataset - test dataset C). <br> <br /><strong>Data Description:</strong> Report describing the comparison of univariate and bivariate distributions between the Synthetic Dataset and Test Dataset C. Additionally, a report showing the maximum mean discrepancy (MMD) and Kullback–Leibler (KL) divergence statistics. Data dictionary for the synthetic training dataset containing 148 variables. <br /><strong>NOTE for restricted files:</strong> If you are not yet a CoLab member, please complete our <a href = "https://rc.bcchr.ca/redcap/surveys/?s=EDCYL7AC79">membership application survey</a> to gain access to restricted files within 2 business days. <br />Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at <a href = mailto:sepsiscolab@bccchr.ca>sepsiscolab@bcchr.ca</a> or visit our <a href = "https://wfpiccs.org/pediatric-sepsis-colab/">website</a>.

Pillay,Yashodani; Ngonzi, Joseph; Nguyen, Vuong; Payne, Beth A; Komugisha, Clare; Twinomujuni, Annet H.; Vidler, Marianne; Lavoie, Pascal M.; Bebell, Lisa M.; Christoffersen-Deb, Astrid; Kenya-Mugisha, Nathan; Kissoon, Niranjan; Ansermino, J Mark; Wiens, Matthew O — 2024-08-14 <br/><strong>Background:</strong> Sub-Saharan Africa accounts for two-thirds of the global burden of maternal and newborn deaths. Adverse outcomes among postpartum women and newborns occurring in the first six weeks of life are often related, though data co-examining patients are limited. This study is an exploratory analysis describing the epidemiology of postnatal complications among postpartum women and newborns following facility birth and discharge in Mbarara, Uganda.<br/> <br /><strong>Methods: </strong> This single-site prospective cohort observational study enrolled postpartum women following facility-based delivery. To capture health information about both the postpartum women and newborns, data was collected and categorized according to domains within the continuum of care including (1) social and demographic, (2) pregnancy history and antenatal care, (3) delivery, (4) maternal discharge, and (5) newborn discharge. The primary outcomes were readmission and mortality within the six-week postnatal period as defined by the WHO. Multivariable logistic regression was used to identify risk factors. <br /> <br /><strong>Findings: </strong> Among 2930 discharged dyads, 2.8% and 9.0% of women and newborns received three or more postnatal visits respectively. Readmission and deaths occurred among 108(3.6%) and 25(0.8%) newborns and in 80(2.7%) and 0(0%) women, respectively. Readmissions were related to sepsis/infection in 70(88%) women and 68(63%) newborns. Adjusted analysis found that caesarean delivery (OR:2.91; 95%CI:1.5–6.04), longer travel time to the facility (OR:1.54; 95%CI:1.24–1.91) and higher maternal heart rate at discharge (OR:1.02; 95%CI:1.00–1.01) were significantly associated with maternal readmission. Discharge taken on all patients including maternal haemoglobin (per g/dL) (OR:0.90; 95%CI:0.82–0.99), maternal symptoms (OR:1.76; 95%CI:1.02–2.91), newborn temperature (OR:1.66; 95%CI:1.28–2.13) and newborn heart rate at (OR:1.94; 95%CI:1.19–3.09) were risk factors among newborns. Readmission and death following delivery and discharge from healthcare facilities is still a problem in settings with low rates of postnatal care visits for both women and newborns. Strategies to identify vulnerable dyads and provide better access to follow-up care, are urgently required. <br /> <br /><strong>Data Collection Methods:</strong> This prospective cohort study aimed to enroll women presenting in labor at >28 weeks’ gestation who delivered liveborn infants and were routinely discharged together home with their infants. Following delivery, we obtained written consent to complete a structured questionnaire in-person and a follow-up questionnaire over the phone six weeks later. Specifically, following enrolment, research nurses prospectively collected study variables previously identified through two systematic reviews on risk factors for re-admission and mortality among postpartum women and infants, as well as through discussion with colleagues and other experts. Given the interactive health relationship between postpartum women and infants, variables were collected and categorized according to relevant time points across the continuum of care. A total of 86 variables were collected and broadly categorized into five domains: (1) social and demographic, (2) pregnancy history and antenatal care, (3) delivery, (4) maternal discharge, and (5) neonatal discharge (Table 4A-E). Apart from discharge measurements, we prioritized gathering data from the hospital medical record, followed by interviews with the postpartum women and finally confirmation with the medical team if there were discrepancies, missing information, or questions the postpartum woman was unable to answer. With respect to discharge measurements, we obtained and recorded clinical data for both mother and their newborns on every dyad discharged together from the hospital. Blood pressure was measured using a Welch Allyn Vital Signs Monitor 300 Series (Welch Allyn, New York, USA). Oxygen saturation (SpO2) and heart rate was measured using the Masimo iSpO2® (Masimo Corporation, California, USA) and respiratory rates were measured using the RRate Application. Maternal hematocrit was quantified using a microhematocrit centrifuge. Random blood glucose was measured on mother and newborn using the FreeStyle Optimum Xceed (Abbott Healthcare, Massachusetts, USA). Anthropometric data of infants (length, weight, mid-upper arm circumference (MUAC), head circumference) were also measured and recorded. All dyads received routine care during admission and were discharged at the discretion of their medical teams. Six weeks following discharge, women who were discharged with their newborns were contacted by phone to determine the status of the mother and newborn and timing and frequency of postnatal care visits. For children who died, the cause of death was collected, as reported by the caregiver (mother or other family member). In addition to vital status, details surrounding the timing, frequency and length of stay pertaining to readmissions and health seeking were also recorded. Data were collected and managed using Research Electronic Data Capture (REDCap) tools hosted at the BC Children’s Hospital Research Institute in Vancouver, Canada.<br /> <br /><strong>Data Processing Methods:</strong>The initial cleaned data file was created using R version 4.2.1 (R Foundation for Statistical Computing, Vienna, Austria). Further processing to obtain the final dataset used for analysis including creating new columns, removing redundant columns, and removing duplicate data were also performed in R in the R scripts titled “MBEPI2024_DataManipulations_Code_SD.R” and “MBEPI2024_CombinedDatasetforOR_Code_SD.R” . All analyses were conducted using R version 4.2.1 (R Foundation for Statistical Computing, Vienna, Austria)<br/> <br /><strong>Ethics Declaration:</strong> Institutional review boards at the University of British Columbia (H18-02523), the Mbarara University of Science and Technology (14/09-18), and the Uganda National Council for Science and Technology (SS 4853) approved the study.<br />

Wiens, Matthew O; Nguyen, Vuong; Bone, Jeffrey N; Kumbakumba, Elias; Businge, Stephen; Tagoola, Abner; Sherine, Sheila Oyella; Byaruhanga, Emmanuel; Ssemwanga, Edward; Barigye, Celestine; Nsungwa, Jesca; Olaro,Charles; Ansermino, J Mark; Kissoon, Niranjan; Singer, Joel; Larson, Charles P; Lavoie, Pascal M; Dunsmuir, Dustin; Moschovis, Peter P; Novakowski, Stefanie; Komugisha, Clare; Tayebwa, Mellon; Mwesigwa, Douglas; Knappett, Martina; West, Nicholas; Kenya-Mugisha, Nathan; Kabakyenga, Jerome — 2024-07-16 <br/><strong>Background:</strong> In many low-income countries, over five percent of hospitalized children die following hospital discharge. The lack of available tools to identify those at risk of post-discharge mortality has limited the ability to make progress towards improving outcomes. We aimed to develop algorithms designed to predict post-discharge mortality among children admitted with suspected sepsis.<br /> <br /><strong>Methods:</strong> Four prospective cohort studies of children in two age groups (0–6 and 6–60 months) were conducted between 2012–2021 in six Ugandan hospitals. Prediction models were derived for six-months post-discharge mortality, based on candidate predictors collected at admission, each with a maximum of eight variables, and internally validated using 10-fold cross-validation.<br /> <br /><strong>Findings:</strong> 8,810 children were enrolled: 470 (5.3%) died in hospital; 257 (7.7%) and 233 (4.8%) post-discharge deaths occurred in the 0-6-month and 6-60-month age groups, respectively. The primary models had an area under the receiver operating characteristic curve (AUROC) of 0.77 (95%CI 0.74–0.80) for 0-6-month-olds and 0.75 (95%CI 0.72–0.79) for 6-60-month-olds; mean AUROCs among the 10 cross-validation folds were 0.75 and 0.73, respectively. Calibration across risk strata was good: Brier scores were 0.07 and 0.04, respectively. The most important variables included anthropometry and oxygen saturation. Additional variables included: illness duration, jaundice-age interaction, and a bulging fontanelle among 0-6-month-olds; and prior admissions, coma score, temperature, age-respiratory rate interaction, and HIV status among 6-60-month-olds.<br /> <br /><strong>Data Processing Methods:</strong> The post-processed data files were created using R version 4.2.2. (R Foundation for Statistical Computing, Vienna, Austria) and briefly involved renaming columns from the different datasets so that they are consistent, converting categories coded as “unknown”, “don’t know”, or “missing” to NA, creating new columns, calculating z-scored variables, and converting relevant columns to factors or dates. <br /> <br /><strong>Ethics Declaration:</strong> These studies were approved by the Mbarara University of Science and Technology (No. 15/10-16), the Uganda National Council for Science and Technology (HS 2207), and the University of British Columbia (H16-02679).<br />

Hooft, Anneka; Kornblith, Aaron E; Umhoza, Christian; Trawin, Jessica; Mfuranziza, Cynthia Grace; Uwiragiye, Emmanuel; Zhang, Cherri; Nguyen, Vuong; Lewis, Peter; Wiens, Matthew O — 2024-04-11 <br /><strong>NOTE for restricted files:</strong> If you are not yet a CoLab member, please complete our <a href = "https://rc.bcchr.ca/redcap/surveys/?s=EDCYL7AC79">membership application survey</a> to gain access to restricted files within 2 business days. <br />Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at <a href = mailto:sepsiscolab@bccchr.ca>sepsiscolab@bcchr.ca</a> or visit our <a href = "https://wfpiccs.org/pediatric-sepsis-colab/">website</a>. <br/><strong>Background:</strong>Mortality following hospital discharge remains a significant threat to child health, particularly in resource-limited settings. In Uganda, the Smart Discharges risk-prediction models have demonstrated success in their ability to predict those at highest risk of death after discharge and use this to guide a risk-based approach to post-discharge care in children admitted with suspected sepsis. Respective prediction models for post-discharge mortality in ages 0-6 months and ages 6-60 months were developed in this cohort but have not yet been validated outside of Uganda. This study aimed to externally validate existing risk prediction models for pediatric post-discharge mortality within the Rwandan context.<br /> <br /><strong>Methods:</strong> Prospective cohort of children 0d-60 mos admitted with suspected sepsis at two hospitals in Rwanda: Ruhengeri Referral Hospital in Musanze (rural) and University Hospital of Kigali in Kigali (urban) from May 2022 to February 2023. Vital status follow up was conducted at 2-, 4- and 6-months post-discharge.<br /> <br />Five existing models from Smart Discharges Uganda were validated in this cohort: two models for children 0-6 months, and three for children 6-60 months. Models were applied to each participant in the Rwanda cohort to obtain a risk score which was then used to calculate predicted probability of post-discharge death. Model performance was evaluated by comparing to observed outcomes and to determine sensitivity, specificity, and AUROC. Threshold was set at 80% sensitivity. .<br /> <br /><strong>Findings:</strong>In a cohort of 1218 children, 1123 children (96.7%) completed follow up. The overall rate of post-discharge mortality was 4.8% (n=58). The highest performing models had an AUROC of 0.75 (0-6 mos) and 0.74 (6-60mos), respectively. All five prediction models tested achieved an AUROC greater than 0.7 (range 0.706 - 0.738). Model degradation (determined by the percent reduction in AUC between the original model and the derived model) was relatively low, ranging from from 1.1% to 7.7%. Calibration plots showed good calibration for all models at predicted probabilities below 10%. There were too few outcomes to assess calibration among those at higher levels of predicted risk. <br /> <br /><strong>Data Processing Methods:</strong> <br /> <br /><strong>Ethics Declaration:</strong> Ethical approval was obtained from the University of Rwanda College of Medicine and Health Sciences (No 411/CMHS IRB/2021); University Teaching Hospital of Kigali (EC/CHUK/005/2022), University of California San Francisco (381688) and the University of British Columbia (H21-02795).<br />

Wiens, Matthew O; Toliva,Opar Bernard; Nsungwa-Sabiiti, Jesca; Mwaka, Savio; Komugisha, Clare; Nyalwal, Beatrice Lydiah Adhiambo; Bone, Jeffrey; Nguyen, Vuong; Kenya-Mugisha, Nathan — 2024-07-22 <br /><strong>Background:</strong> In many African countries, pediatric post-discharge mortality following in-hospital treatment for severe infectious illness is higher than in-hospital mortality (5-8%). Risk algorithms can be used to help health workers identify those most vulnerable to poor post-discharge outcomes. They can also assist health workers in providing personalized discharge counselling and recommending effective follow-up care. This can improve overall system efficiency. While this approach has shown promise among general pediatric populations, no research has addressed issues of post-discharge morbidity and mortality within the refugee context, where unique vulnerabilities exist. This study aims to validate the Smart Discharges approach to improve outcomes among children in refugee settings, and ultimately to build a generalizable and inclusive solution to improving pediatric post-discharge outcomes.<br /> <br /><strong>Methods:</strong> This study is a prospective observational cohort study that will be conducted at 3 health facilities in Lamwo District, northern Uganda between April 2023 and September 2024. We will enroll 1,500 children under 13 years of age between the three study sites of Padibe HCIV, Paluda HCIII, and Palabek Kal HCIII. The primary objective is to validate, calibrate, and refine the Smart Discharges risk-prediction algorithm in a representative cohort of refugee children. Secondary objectives include: i) to describe the epidemiology of, and risk factors for, post-discharge mortality of children in the context of refugee settings; ii) to describe the post-discharge health seeking patterns of children in the context of refugee settings; and iii) to evaluate the pediatric discharge process at 3 health facilities providing discharge care to children living in refugee settings. Following enrollment a research nurse will obtain and record clinical and demographic variables required for model validation including vital signs, oxygen saturation, anthropometric data, prior care seeking, co-morbidities and diagnoses. A rapid diagnostic test using blood, which will require a finger prick to collect < 0.5ml of blood, will be conducted to assess the patient's HIV status, malaria parasitemia, and hemoglobin (hemocue). All enrolled children will receive phone follow-up from study staff at 2-, 4- and 6 months following hospital discharge for research purposes. Verbal autopsies, often used in this context to determine cause of death, will be conducted for all children who die following discharge. All study sites will also undergo the discharge module of a 5-survey Facility Scan developed by the Pediatric Sepsis Data CoLaboratory’s (Sepsis CoLab) to support health facilities in identifying and assessing quality improvement priorities and initiatives.This will be done at both baseline (conclusion of clinical study activities) and 4 months following the completion of study activities to measure the facility readiness to implement improved discharge care, and its persistence over time.<br /> <br /><strong>Ethics Declaration:</strong> Ethical approval has been obtained from the University of British Columbia Children’s & Women’s Research Ethics Board in Canada (H23-00012) and the Makerere School of Public Health Research Ethics Board in Uganda (SPH-2023-369). <br /> <br /><strong>NOTE for restricted files:</strong> If you are not yet a CoLab member, please complete our <a href = "https://rc.bcchr.ca/redcap/surveys/?s=EDCYL7AC79">membership application survey</a> to gain access to restricted files within 2 business days. <br />Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at <a href = mailto:sepsiscolab@bccchr.ca>sepsiscolab@bcchr.ca</a> or visit our <a href = "https://wfpiccs.org/pediatric-sepsis-colab/">website</a>.

Zhang, Cherri; Akter, Tanjila; Nguyen, Vuong; Bone, Jeff; Wiens, Matthew — 2024-10-22 This data is a subset of the Smart Discharges Uganda Under 5 years parent study and is specific to the Phase I observation cohort of children aged 0-6 months collected during the Covid-19 pandemic in 2020. <br> <br/><strong>Objective(s):</strong> Used as part of the Smart Discharge prediction modelling for adverse outcomes such as post-discharge death and readmission. <br> <br /><strong>Data Description:</strong> All data were collected at the point of care using encrypted study tablets and these data were then uploaded to a Research Electronic Data Capture (REDCap) database hosted at the BC Children’s Hospital Research Institute (Vancouver, Canada). At admission, trained study nurses systematically collected data on clinical, social and demographic variables. Following discharge, field officers contacted caregivers at 2 and 4 months by phone, and in-person at 6 months, to determine vital status, post-discharge health-seeking, and readmission details. Verbal autopsies were conducted for children who had died following discharge. . <br> <br /><strong>Data Processing:</strong> Created z-scores for anthropometry variables using height and weight according to WHO cutoff. Distance to hospital was calculated using latitude and longitude. Extra symptom and diagnosis categories were created based on text field in these two variables. BCS score was created by summing all individual components.<br> <br /><strong>Limitations:</strong> There are missing dates and the admission, discharge, and readmission dates are not in order. <br> <br /><strong>Ethics Declaration:</strong> This study was approved by the Mbarara University of Science and Technology Research Ethics Committee (No. 15/10-16), the Uganda National Institute of Science and Technology (HS 2207), and the University of British Columbia / Children & Women’s Health Centre of British Columbia Research Ethics Board (H16-02679). This manuscript adheres to the guidelines for STrengthening the Reporting of OBservational studies in Epidemiology (STROBE). <br /><strong>NOTE for restricted files:</strong> If you are not yet a CoLab member, please complete our <a href = "https://rc.bcchr.ca/redcap/surveys/?s=EDCYL7AC79">membership application survey</a> to gain access to restricted files within 2 business days. <br />Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at <a href = mailto:sepsiscolab@bccchr.ca>sepsiscolab@bcchr.ca</a> or visit our <a href = "https://wfpiccs.org/pediatric-sepsis-colab/">website</a>.