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BACKGROUND: Medical school curricula strive to train community-engaged and culturally competent physicians, and many use service learning to instill these values in students. The current standards for medical service learning frameworks have opportunities for improvement, such as encouraging students to have more sustainable and reciprocal impact and to ingrain service learning as a value to carry throughout their careers rather than a one-time experience. PEDS 220: A COVID-19 Elective is a Stanford University course on the frontlines of this shift; it provides timely education on the COVID-19 pandemic, integrating community-oriented public health work to help mitigate its impact. METHODS: To analyze our medical service learning curriculum, we combined qualitative and quantitative methods to understand our students' experiences. Participants completed the Course Experience Questionnaire via Qualtrics, and were invited to complete an additional interview via Zoom. Interview transcripts were analyzed using an interactive, inductive, and team-based codebook development process, where recurring themes were identified across participant interviews. RESULTS: We demonstrate through self-determination theory that our novel curriculum gives students valuable leadership and project management experience, awards strong academic and community-based connections, and motivates them to pursue future community-engaged work. CONCLUSIONS: This educational framework, revolving around students, communities, and diversity, can be used beyond the COVID-19 pandemic at other educational institutions to teach students how to solve other emergent global health problems. Using proven strategies that empower future physicians to view interdisciplinary, community-engaged work as a core pillar of their responsibility to their patients and communities ensures long-term, sustainable positive impact. TRIAL REGISTRATION: N/A.
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COVID-19 , Currículo , Humanos , COVID-19/epidemiologia , SARS-CoV-2 , Estudantes de Medicina/psicologia , Educação de Graduação em Medicina/métodos , Pandemias , Competência Cultural/educação , Feminino , MasculinoRESUMO
BACKGROUND: Early warning scores for neonatal mortality have not been designed for low income countries. We developed and validated a score to predict mortality upon admission to a NICU in Ethiopia. METHODS: We conducted a retrospective case-control study at the University of Gondar Hospital, Gondar, Ethiopia. Neonates hospitalized in the NICU between January 1, 2016 to June 31, 2017. Cases were neonates who died and controls were neonates who survived. RESULTS: Univariate logistic regression identified variables associated with mortality. The final model was developed with stepwise logistic regression. We created the Neonatal Mortality Score, which ranged from 0 to 52, from the model's coefficients. Bootstrap analysis internally validated the model. The discrimination and calibration were calculated. In the derivation dataset, there were 207 cases and 605 controls. Variables associated with mortality were admission level of consciousness, admission respiratory distress, gestational age, and birthweight. The AUC for neonatal mortality using these variables in aggregate was 0.88 (95% CI 0.85-0.91). The model achieved excellent discrimination (bias-corrected AUC) under internal validation. Using a cut-off of 12, the sensitivity and specificity of the Neonatal Mortality Score was 81 and 80%, respectively. The AUC for the Neonatal Mortality Score was 0.88 (95% CI 0.85-0.91), with similar bias-corrected AUC. In the validation dataset, there were 124 cases and 122 controls, the final model and the Neonatal Mortality Score had similar discrimination and calibration. CONCLUSIONS: We developed, internally validated, and externally validated a score that predicts neonatal mortality upon NICU admission with excellent discrimination and calibration.
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Mortalidade Infantil , Estudos de Casos e Controles , Etiópia/epidemiologia , Feminino , Humanos , Lactente , Recém-Nascido , Masculino , Gravidez , Prognóstico , Estudos RetrospectivosRESUMO
BACKGROUND AND OBJECTIVES: Pediatric fellows across all subspecialties are interested in global health (GH). Little is known about how GH is incorporated into Pediatric Hospital Medicine (PHM) fellowships. Our objective was to examine the current landscape of GH education in PHM fellowships. METHODS: In 2022, we conducted a cross-sectional electronic survey of PHM fellowship directors (FDs), current fellows, and recently graduated fellows (alumni) via e-mail and listservs. Surveys asked about GH education (curriculum, electives, and research) in PHM fellowships, barriers to GH training, and fellow interest in GH. RESULTS: Response rates were 56% (34/61) among PHM FDs, 57% (102/178) among fellows, and 29% (59/206) among alumni. Most fellows (73%) and alumni (59%) were interested in GH electives. Although 53% of FDs reported offering GH electives, a minority of fellows (21%) and alumni (19%) reported being offered GH electives (P <.001). Few FDs reported offering a GH curriculum (9%), although most fellows (63%) and alumni (50%) expressed interest. Of the 16 FDs without GH electives, 81% planned to offer them. Cited barriers included a lack of GH curricula, insufficient funding, competing educational demands, and a lack of international partnerships. More FDs (82%) than fellows (64%) and alumni (45%) agreed that GH education improves overall fellow education (P = .01). Similarly, more FDs (75%) than fellows (56%) and alumni (38%) agreed that offering GH education improves recruitment (P = .002). CONCLUSIONS: There is an unmet demand for GH education in PHM fellowships, and fellows may not be aware of GH opportunities.
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Bolsas de Estudo , Saúde Global , Medicina Hospitalar , Pediatria , Humanos , Estudos Transversais , Estados Unidos , Pediatria/educação , Saúde Global/educação , Medicina Hospitalar/educação , Hospitais Pediátricos , Currículo , Educação de Pós-Graduação em Medicina , Inquéritos e QuestionáriosRESUMO
INTRODUCTION: To improve healthcare provider knowledge of Tanzanian newborn care guidelines, we developed adaptive Essential and Sick Newborn Care (aESNC), an adaptive e-learning environment. The objectives of this study were to (1) assess implementation success with use of in-person support and nudging strategy and (2) describe baseline provider knowledge and metacognition. METHODS: 6-month observational study at one zonal hospital and three health centres in Mwanza, Tanzania. To assess implementation success, we used the Reach, Efficacy, Adoption, Implementation and Maintenance framework and to describe baseline provider knowledge and metacognition we used Howell's conscious-competence model. Additionally, we explored provider characteristics associated with initial learning completion or persistent activity. RESULTS: aESNC reached 85% (195/231) of providers: 75 medical, 53 nursing and 21 clinical officers; 110 (56%) were at the zonal hospital and 85 (44%) at health centres. Median clinical experience was 4 years (IQR 1-9) and 45 (23%) had previous in-service training for both newborn essential and sick newborn care. Efficacy was 42% (SD ±17%). Providers averaged 78% (SD ±31%) completion of initial learning and 7% (SD ±11%) of refresher assignments. 130 (67%) providers had ≥1 episode of inactivity >30 day, no episodes were due to lack of internet access. Baseline conscious-competence was 53% (IQR: 38%-63%), unconscious-incompetence 32% (IQR: 23%-42%), conscious-incompetence 7% (IQR: 2%-15%), and unconscious-competence 2% (IQR: 0%-3%). Higher baseline conscious-competence (OR 31.6 (95% CI 5.8 to 183.5)) and being a nursing officer (aOR: 5.6 (95% CI 1.8 to 18.1)), compared with medical officer, were associated with initial learning completion or persistent activity. CONCLUSION: aESNC reach was high in a population of frontline providers across diverse levels of care in Tanzania. Use of in-person support and nudging increased reach, initial learning and refresher assignment completion, but refresher assignment completion remains low. Providers were often unaware of knowledge gaps, and lower baseline knowledge may decrease initial learning completion or activity. Further study to identify barriers to adaptive e-learning normalisation is needed.
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Instrução por Computador , Recém-Nascido , Humanos , Tanzânia , Aprendizagem , Competência ClínicaRESUMO
Background: In low- and -middle-income countries (LMICs) like Tanzania, the competency of healthcare providers critically influences the quality of pediatric care. To address this, we introduced PACE (Pediatric Acute Care Education), an adaptive e-learning program tailored to enhance provider competency in line with Tanzania's national guidelines for managing seriously ill children. Adaptive e-learning presents a promising alternative to traditional in-service education, yet optimal strategies for its implementation in LMIC settings remain to be fully elucidated. Objectives: This study aimed to (1) evaluate the initial implementation of PACE in Mwanza, Tanzania, using the constructs of Normalization Process Theory (NPT), and (2) provide insights into its feasibility, acceptability, and scalability potential. Methods: A mixed-methods approach was employed across three healthcare settings in Mwanza: a zonal hospital and two health centers. NPT was utilized to navigate the complexities of implementing PACE. Data collection involved a customized NoMAD survey, focus groups and in-depth interviews with healthcare providers. Results: The study engaged 82 healthcare providers through the NoMAD survey and 79 in focus groups and interviews. Findings indicated high levels of coherence and cognitive participation, demonstrating that PACE is well-understood and resonates with existing healthcare goals. Providers expressed a willingness to integrate PACE into their practice, distinguishing it from existing educational methods. However, challenges related to resources and infrastructure, particularly affecting collective action, were noted. The short duration of the study limited the assessment of reflexive monitoring, though early indicators point towards the potential for PACE's long-term sustainability. Conclusion: This study offers vital insights into the feasibility and acceptability of implementing PACE in a Tanzanian context. While PACE aligns well with healthcare objectives, addressing resource and infrastructure challenges is crucial for its successful and sustainable implementation. Furthermore, the study underscores the value of NPT as a framework in guiding implementation processes, with broader implications for implementation science and pediatric acute care in LMICs.
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CONTEXT: Clinical sign algorithms are a key strategy to identify young infants at risk of mortality. OBJECTIVE: Synthesize the evidence on the accuracy of clinical sign algorithms to predict all-cause mortality in young infants 0-59 days. DATA SOURCES: MEDLINE, Embase, CINAHL, Global Index Medicus, and Cochrane CENTRAL Registry of Trials. STUDY SELECTION: Studies evaluating the accuracy of infant clinical sign algorithms to predict mortality. DATA EXTRACTION: We used Cochrane methods for study screening, data extraction, and risk of bias assessment. We determined certainty of evidence using Grading of Recommendations Assessment Development and Evaluation. RESULTS: We included 11 studies examining 26 algorithms. Three studies from non-hospital/community settings examined sign-based checklists (n = 13). Eight hospital-based studies validated regression models (n = 13), which were administered as weighted scores (n = 8), regression formulas (n = 4), and a nomogram (n = 1). One checklist from India had a sensitivity of 98% (95% CI: 88%-100%) and specificity of 94% (93%-95%) for predicting sepsis-related deaths. However, external validation in Bangladesh showed very low sensitivity of 3% (0%-10%) with specificity of 99% (99%-99%) for all-cause mortality (ages 0-9 days). For hospital-based prediction models, area under the curve (AUC) ranged from 0.76-0.93 (n = 13). The Score for Essential Neonatal Symptoms and Signs had an AUC of 0.89 (0.84-0.93) in the derivation cohort for mortality, and external validation showed an AUC of 0.83 (0.83-0.84). LIMITATIONS: Heterogeneity of algorithms and lack of external validation limited the evidence. CONCLUSIONS: Clinical sign algorithms may help identify at-risk young infants, particularly in hospital settings; however, overall certainty of evidence is low with limited external validation.
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Algoritmos , Mortalidade Infantil , Humanos , Lactente , Recém-Nascido , Mortalidade Infantil/tendências , Lista de Checagem , Medição de Risco/métodosRESUMO
CONTEXT: Accurate identification of possible sepsis in young infants is needed to effectively manage and reduce sepsis-related morbidity and mortality. OBJECTIVE: Synthesize evidence on the diagnostic accuracy of clinical sign algorithms to identify young infants (aged 0-59 days) with suspected sepsis. DATA SOURCES: MEDLINE, Embase, CINAHL, Global Index Medicus, and Cochrane CENTRAL Registry of Trials. STUDY SELECTION: Studies reporting diagnostic accuracy measures of algorithms including infant clinical signs to identify young infants with suspected sepsis. DATA EXTRACTION: We used Cochrane methods for study screening, data extraction, risk of bias assessment, and determining certainty of evidence using Grading of Recommendations Assessment Development and Evaluation. RESULTS: We included 19 studies (12 Integrated Management of Childhood Illness [IMCI] and 7 non-IMCI studies). The current World Health Organization (WHO) 7-sign IMCI algorithm had a sensitivity of 79% (95% CI 77%-82%) and specificity of 77% (95% CI 76%-78%) for identifying sick infants aged 0-59 days requiring hospitalization/antibiotics (1 study, N = 8889). Any IMCI algorithm had a pooled sensitivity of 84% (95% CI 75%-90%) and specificity of 80% (95% CI 64%-90%) for identifying suspected sepsis (11 studies, N = 15523). When restricting the reference standard to laboratory-supported sepsis, any IMCI algorithm had a pooled sensitivity of 86% (95% CI 82%-90%) and lower specificity of 61% (95% CI 49%-72%) (6 studies, N = 14278). LIMITATIONS: Heterogeneity of algorithms and reference standards limited the evidence. CONCLUSIONS: IMCI algorithms had acceptable sensitivity for identifying young infants with suspected sepsis. Specificity was lower using a reference standard of laboratory-supported sepsis diagnosis.
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Algoritmos , Sepse , Humanos , Lactente , Recém-Nascido , Sepse/diagnóstico , Sensibilidade e EspecificidadeRESUMO
In 2019, 80% of the 7.4 million global child deaths occurred in low- and middle-income countries (LMICs). Global and regional estimates of cause of hospital death and admission in LMIC children are needed to guide global and local priority setting and resource allocation but are currently lacking. The study objective was to estimate global and regional prevalence for common causes of pediatric hospital mortality and admission in LMICs. We performed a systematic review and meta-analysis to identify LMIC observational studies published January 1, 2005-February 26, 2021. Eligible studies included: a general pediatric admission population, a cause of admission or death, and total admissions. We excluded studies with data before 2,000 or without a full text. Two authors independently screened and extracted data. We performed methodological assessment using domains adapted from the Quality in Prognosis Studies tool. Data were pooled using random-effects models where possible. We reported prevalence as a proportion of cause of death or admission per 1,000 admissions with 95% confidence intervals (95% CI). Our search identified 29,637 texts. After duplicate removal and screening, we analyzed 253 studies representing 21.8 million pediatric hospitalizations in 59 LMICs. All-cause pediatric hospital mortality was 4.1% [95% CI 3.4%-4.7%]. The most common causes of mortality (deaths/1,000 admissions) were infectious [12 (95% CI 9-14)]; respiratory [9 (95% CI 5-13)]; and gastrointestinal [9 (95% CI 6-11)]. Common causes of admission (cases/1,000 admissions) were respiratory [255 (95% CI 231-280)]; infectious [214 (95% CI 193-234)]; and gastrointestinal [166 (95% CI 143-190)]. We observed regional variation in estimates. Pediatric hospital mortality remains high in LMICs. Global child health efforts must include measures to reduce hospital mortality including basic emergency and critical care services tailored to the local disease burden. Resources are urgently needed to promote equity in child health research, support researchers, and collect high-quality data in LMICs to further guide priority setting and resource allocation.
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The goal of a diagnostic test is to provide information on the probability of disease. In this article, we review the principles of diagnostic test characteristics, including sensitivity, specificity, positive and negative predictive value, receiver operating characteristics curves, likelihood ratios, and interval likelihood ratios. We illustrate how interval likelihood ratios optimize the information that can be obtained from test results that can take on >2 values, how they are reflected in the slope of the receiver operating characteristics curve, and how they can be easily calculated from published data.
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Testes Diagnósticos de Rotina , Humanos , Sensibilidade e Especificidade , Curva ROC , Valor Preditivo dos Testes , Testes Diagnósticos de Rotina/métodosRESUMO
Introduction: To improve healthcare provider knowledge of Tanzanian newborn care guidelines, we developed adaptive Essential and Sick Newborn Care (aESNC), an adaptive e-learning environment (AEE). The objectives of this study were to 1) assess implementation success with use of in-person support and nudging strategy and 2) describe baseline provider knowledge and metacognition. Methods: 6-month observational study at 1 zonal hospital and 3 health centers in Mwanza, Tanzania. To assess implementation success, we used the RE-AIM framework and to describe baseline provider knowledge and metacognition we used Howell's conscious-competence model. Additionally, we explored provider characteristics associated with initial learning completion or persistent activity. Results: aESNC reached 85% (195/231) of providers: 75 medical, 53 nursing, and 21 clinical officers; 110 (56%) were at the zonal hospital and 85 (44%) at health centers. Median clinical experience was 4 years [IQR 1,9] and 45 (23%) had previous in-service training for both newborn essential and sick newborn care. Efficacy was 42% (SD±17%). Providers averaged 78% (SD±31%) completion of initial learning and 7%(SD±11%) of refresher assignments. 130 (67%) providers had ≥1 episode of inactivity >30 day, no episodes were due to lack of internet access. Baseline conscious-competence was 53% [IQR:38-63%], unconscious-incompetence 32% [IQR:23-42%], conscious-incompetence 7% [IQR:2-15%], and unconscious-competence 2% [IQR:0-3%]. Higher baseline conscious-competence (OR 31.6 [95%CI:5.8, 183.5) and being a nursing officer (aOR: 5.6 [95%CI:1.8, 18.1]), compared to medical officer) were associated with initial learning completion or persistent activity. Conclusion: aESNC reach was high in a population of frontline providers across diverse levels of care in Tanzania. Use of in-person support and nudging increased reach, initial learning, and refresher assignment completion, but refresher assignment completion remains low. Providers were often unaware of knowledge gaps, and lower baseline knowledge may decrease initial learning completion or activity. Further study to identify barriers to adaptive e-learning normalization is needed.
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Universities and medical schools often work towards operationalizing their shared mission of facilitating community-engaged work independently. Based on their experience teaching the COVID-19 Elective course at Stanford University School of Medicine, the authors proposed a novel solution for universities and medical schools to achieve an interdisciplinary collaboration within a diverse student population by creating targeted, project-based, and community-engaged courses for addressing emergent health needs. In this article, the authors discuss their curriculum, which was created using Kern's six-step approach for curriculum development, to address emergent health needs related to the novel coronavirus pandemic. The curriculum provides an opportunity for universities and medical schools to advance community health, educate students across the medical and non-medical education continuum, and foster interdisciplinary cooperation.
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BACKGROUND: In 2019, 2.4 million neonates died globally, with most deaths occurring in low-resource settings. Despite the introduction of neonatal intensive care units (NICUs) in these settings, neonatal mortality remains high, and caring for sick neonates around the clock can be challenging due to limited staff and resources. OBJECTIVE: To evaluate whether neonatal intensive care admissions during daytime and overnight hours affects in-hospital neonatal mortality. METHODS: A retrospective case-control study was conducted using 2016 chart data at a University hospital in Ethiopia. Cases were defined as neonates who died in the NICU, and controls were defined as neonates who survived. Overnight hours were defined as 17:00 to 07:59, and day hours were defined as 08:00 to 16:59. Univariate and multivariate logistic regressions were used to investigate the relationship between time of admission and mortality, along with perinatal characteristics. RESULTS: A total of 812 neonates, 207 cases and 605 controls, met inclusion criteria. There were 342 admissions during the day and 470 overnight. Neonatal mortality (aOR 1.02, 95% CI [0.64-1.62], p = 0.93) was not associated with overnight admissions after controlling for maternal age, parity, C-section, birthweight, and gestational age, respiratory distress, and admission level of consciousness. Admission heart rate >160 (aOR 0.52, 95% CI [0.30-0.91], p = 0.02) was the only variable significantly associated with overnight admissions. CONCLUSION: Being admitted overnight to the NICU in Gondar, Ethiopia was not associated with increased mortality, consistent with a constant level of care, regardless of the time of admission. Further qualitative and implementation research are needed to understand contextual factors that have affected these data.
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Mortalidade Infantil , Unidades de Terapia Intensiva Neonatal , Estudos de Casos e Controles , Etiópia/epidemiologia , Feminino , Humanos , Recém-Nascido , Gravidez , Estudos RetrospectivosRESUMO
Background: The majority of childhood deaths occur in low- and middle-income countries (LMICs). Many of these deaths are avoidable with basic critical care interventions. Quantifying the burden of pediatric critical illness in LMICs is essential for targeting interventions to reduce childhood mortality. Objective: To determine the burden of hospitalization and mortality associated with acute pediatric critical illness in LMICs through a systematic review and meta-analysis of the literature. Data Sources and Search Strategy: We will identify eligible studies by searching MEDLINE, EMBASE, CINAHL, and LILACS using MeSH terms and keywords. Results will be limited to infants or children (ages >28 days to 12 years) hospitalized in LMICs and publications in English, Spanish, or French. Publications with non-original data (e.g., comments, editorials, letters, notes, conference materials) will be excluded. Study Selection: We will include observational studies published since January 1, 2005, that meet all eligibility criteria and for which a full text can be located. Data Extraction: Data extraction will include information related to study characteristics, hospital characteristics, underlying population characteristics, patient population characteristics, and outcomes. Data Synthesis: We will extract and report data on study, hospital, and patient characteristics; outcomes; and risk of bias. We will report the causes of admission and mortality by region, country income level, and age. We will report or calculate the case fatality rate (CFR) for each diagnosis when data allow. Conclusions: By understanding the burden of pediatric critical illness in LMICs, we can advocate for resources and inform resource allocation and investment decisions to improve the management and outcomes of children with acute pediatric critical illness in LMICs.
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In Ethiopia, evidence is lacking about maternal care-taking and environmental risk factors that contribute to acute diarrhoea and the case management of diarrhoea. The aim of this study was to identify the risk factors and to understand the management of acute diarrhoea. A pretested structured questionnaire was used for interviewing mothers of 440 children in a prospective, matched, case-control study at the University of Gondar Referral and Teaching Hospital in Gondar, Ethiopia. Results of multivariate analysis demonstrated that children who were breastfed and not completely weaned and mothers who were farmers were protective factors; risk factors for diarrhoea included sharing drinking-water and introducing supplemental foods. Children presented with acute diarrhoea for 3.9 days with 4.3 stools per day. Mothers usually did not increase breastmilk and other fluids during diarrhoea episodes and generally did not take children with diarrhoea to traditional healers. Incorporating messages about the prevention and treatment of acute diarrhoea into child-health interventions will help reduce morbidity and mortality associated with this disease.
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Diarreia/epidemiologia , Diarreia/terapia , Doença Aguda , Estudos de Casos e Controles , Pré-Escolar , Etiópia/epidemiologia , Feminino , Humanos , Lactente , Masculino , Fatores de RiscoRESUMO
Many national organizations call for medical students to receive more public health education in medical school. Nonetheless, limited evidence exists about successful servicelearning programs that administer preventive health services in nonclinical settings. The Flu Crew program, started in 2001 at the Stanford University School of Medicine, provides preclinical medical students with opportunities to administer influenza immunizations in the local community. Medical students consider Flu Crew to be an important part of their medical education that cannot be learned in the classroom. Through delivering vaccines to where people live, eat, work, and pray, Flu Crew teaches medical students about patient care, preventive medicine, and population health needs. Additionally, Flu Crew allows students to work with several partners in the community in order to understand how various stakeholders improve the delivery of population health services. Flu Crew teaches students how to address common vaccination myths and provides insights into implementing public health interventions. This article describes the Stanford Flu Crew curriculum, outlines the planning needed to organize immunization events, shares findings from medical students' attitudes about population health, highlights the program's outcomes, and summarizes the lessons learned. This article suggests that Flu Crew is an example of one viable service-learning modality that supports influenza vaccinations in nonclinical settings while simultaneously benefiting future clinicians.