Choosing blood pressure thresholds to inform pregnancy care in the community: An analysis of cluster trials.

OBJECTIVE: To inform digital health design by evaluating diagnostic test properties of antenatal blood pressure (BP) outputs and levels to identify women at risk of adverse outcomes. DESIGN: Planned secondary analysis of cluster randomised trials. SETTING: India, Pakistan, Mozambique. POPULATION: Women with in-community BP measurements and known pregnancy outcomes. METHODS: Blood pressure was defined by its outputs (systolic and/or diastolic, systolic only, diastolic only or mean arterial pressure [calculated]) and level: normotension-1 (<135/85 mmHg), normotension-2 (135-139/85-89 mmHg), non-severe hypertension (140-149/90-99 mmHg; 150-154/100-104 mmHg; 155-159/105-109 mmHg) and severe hypertension (≥160/110 mmHg). Dose-response (adjusted risk ratio [aRR]) and diagnostic test properties (negative [-LR] and positive [+LR] likelihood ratios) were estimated. MAIN OUTCOME MEASURES: Maternal/perinatal composites of mortality/morbidity. RESULTS: Among 21 069 pregnancies, different BP outputs had similar aRR, -LR, and +LR for adverse outcomes. No BP level (even normotension-1) was associated with low risk (all -LR ≥0.20). Across outcomes, risks rose progressively with higher BP levels above normotension-1. For each of maternal central nervous system events and stillbirth, BP ≥155/105 mmHg showed at least good diagnostic test performance (+LR ≥5.0) and BP ≥135/85 mmHg at least fair performance, similar to BP ≥140/90 mmHg (+LR 2.0-4.99). CONCLUSIONS: In the community, normal BP values do not provide reassurance about subsequent adverse outcomes. Given the similar performance of BP cut-offs of 135/85 and 140/90 mmHg for hypertension, and 155/105 and 160/110 mmHg for severe hypertension, digital decision support for women in the community should consider using these lower thresholds.

Variability of respiratory rate measurements in neonates- every minute counts.

BACKGROUND: Respiratory rate is difficult to measure, especially in neonates who have an irregular breathing pattern. The World Health Organisation recommends a one-minute count, but there is limited data to support this length of observation. We sought to evaluate agreement between the respiratory rate (RR) derived from capnography in neonates, over 15 s, 30 s, 120 s and 300 s, against the recommended 60 s. METHODS: Neonates at two hospitals in Nairobi were recruited and had capnograph waveforms recorded using the Masimo Rad 97. A single high quality 5 min epoch was randomly chosen from each subject. For each selected epoch, the mean RR was calculated using a breath-detection algorithm applied to the waveform. The RR in the first 60 s was compared to the mean RR measured over the first 15 s, 30 s, 120 s, full 300 s, and last 60 s. We calculated bias and limits of agreement for each comparison and used Bland-Altman plots for visual comparisons. RESULTS: A total of 306 capnographs were analysed from individual subjects. The subjects had a median gestation age of 39 weeks with slightly more females (52.3%) than males (47.7%). The majority of the population were term neonates (70.1%) with 39 (12.8%) having a primary respiratory pathology. There was poor agreement between all the comparisons based on the limits of agreement [confidence interval], ranging between 11.9 [- 6.79 to 6.23] breaths per minute in the one versus 2 min comparison, and 34.7 [- 17.59 to 20.53] breaths per minute in the first versus last minute comparison. Worsening agreement was observed in plots with higher RRs. CONCLUSIONS: Neonates have high variability of RR, even over a short period of time. A slight degradation in the agreement is noted over periods shorter than 1 min. However, this is smaller than observations done 3 min apart in the same subject. Longer periods of observation also reduce agreement. For device developers, precise synchronization is needed when comparing devices to reduce the impact of RR variation. For clinicians, where possible, continuous or repeated monitoring of neonates would be preferable to one time RR measurements.

Health worker perspectives of Smart Triage, a digital triaging platform for quality improvement at a referral hospital in Uganda: a qualitative analysis.

BACKGROUND: Effective triage at hospitals can improve outcomes for children globally by helping identify and prioritize care for those most at-risk of death. Paper-based pediatric triage guidelines have been developed to support frontline health workers in low-resource settings, but these guidelines can be challenging to implement. Smart Triage is a digital triaging platform for quality improvement (QI) that aims to address this challenge. Smart Triage represents a major cultural and behavioural shift in terms of managing patients at health facilities in low-and middle-income countries. The purpose of this study is to understand user perspectives on the usability, feasibility, and acceptability of Smart Triage to inform ongoing and future implementation. METHODS: This was a descriptive qualitative study comprising of face-to-face interviews with health workers (n = 15) at a regional referral hospital in Eastern Uganda, conducted as a sub-study of a larger clinical trial to evaluate Smart Triage (NCT04304235). Thematic analysis was used to assess the usability, feasibility, and acceptability of the platform, focusing on its use in stratifying and prioritizing patients according to their risk and informing QI initiatives implemented by health workers. RESULTS: With appropriate training and experience, health workers found most features of Smart Triage usable and feasible to implement, and reported the platform was acceptable due to its positive impact on reducing the time to treatment for emergency pediatric cases and its use in informing QI initiatives within the pediatric ward. Several factors that reduced the feasibility and acceptability were identified, including high staff turnover, a lack of medical supplies at the hospital, and challenges with staff attitudes. CONCLUSION: Health workers can use the Smart Triage digital triaging platform to identify and prioritize care for severely ill children and improve quality of care at health facilities in low-resource settings. Future innovation is needed to address identified feasibility and acceptability challenges; however, this platform could potentially address some of the challenges to implementing current paper-based systems.

A 2-Phase Survey to Assess a Facility's Readiness for Pediatric Essential Emergency and Critical Care in Resource-Limited Settings: A Literature Review and Survey Development.

OBJECTIVE: Infectious diseases, including pneumonia, malaria, and diarrheal diseases, are the leading causes of death in children younger than 5 years worldwide. The vast majority of these deaths occur in resource-limited settings where there is significant variation in the availability and type of human, physical, and infrastructural resources. The ability to identity gaps in healthcare systems that may hinder their ability to deliver care is an important step to determining specific interventions for quality improvement. Our study objective was to develop a comprehensive, digital, open-access health facility survey to assess facility readiness to provide pediatric critical care in resource-limited settings (eg, low- and lower middle-income countries). METHODS: A literature review of existing facility assessment tools and global guidelines was conducted to generate a database of survey questions. These were then mapped to one of the following 8 domains: hospital statistics, services offered, operational flow, facility infrastructure, staff and training, medicines and equipment, diagnostic capacity, and quality of clinical care. A 2-phase survey was developed and an iterative review process of the survey was undertaken with 12 experts based in low- and middle-income countries. This was built into the REDCap Mobile Application for electronic data capture. RESULTS: The literature review process yielded 7 facility assessment tools and 7 global guidelines for inclusion. After the iterative review process, the final survey consisted of 11 sections with 457 unique questions in the first phase, "environmental scan," focusing on the infrastructure, availability, and functionality of resources, and 3 sections with 131 unique questions in the second phase, "observation scan," focusing on the level of clinical competency. CONCLUSIONS: A comprehensive 2-phase survey was created to evaluate facility readiness for pediatric critical care. Results will assist hospital administrators and policymakers to determine priority areas for quality improvement, enabling them to implement a Plan-Do-Study-Act cycle to improve care for the critically ill child.

Assessment of neonatal respiratory rate variability.

Accurate measurement of respiratory rate (RR) in neonates is challenging due to high neonatal RR variability (RRV). There is growing evidence that RRV measurement could inform and guide neonatal care. We sought to quantify neonatal RRV during a clinical study in which we compared multiparameter continuous physiological monitoring (MCPM) devices. Measurements of capnography-recorded exhaled carbon dioxide across 60-s epochs were collected from neonates admitted to the neonatal unit at Aga Khan University-Nairobi hospital. Breaths were manually counted from capnograms and using an automated signal detection algorithm which also calculated mean and median RR for each epoch. Outcome measures were between- and within-neonate RRV, between- and within-epoch RRV, and 95% limits of agreement, bias, and root-mean-square deviation. Twenty-seven neonates were included, with 130 epochs analysed. Mean manual breath count (MBC) was 48 breaths per minute. Median RRV ranged from 11.5% (interquartile range (IQR) 6.8-18.9%) to 28.1% (IQR 23.5-36.7%). Bias and limits of agreement for MBC vs algorithm-derived breath count, MBC vs algorithm-derived median breath rate, MBC vs algorithm-derived mean breath rate were - 0.5 (- 2.7, 1.66), - 3.16 (- 12.12, 5.8), and - 3.99 (- 11.3, 3.32), respectively. The marked RRV highlights the challenge of performing accurate RR measurements in neonates. More research is required to optimize the use of RRV to improve care. When evaluating MCPM devices, accuracy thresholds should be less stringent in newborns due to increased RRV. Lastly, median RR, which discounts the impact of extreme outliers, may be more reflective of the underlying physiological control of breathing.

The use of the Panda-Nerve Block pain app in single-shot peripheral nerve block patients: a feasibility study.

PURPOSE: Peripheral nerve blocks (PNBs) provide excellent perioperative analgesia but can increase the risk of severe postoperative pain once the block wears off. Poor adherence to discharge instructions may increase this risk. Panda-Nerve Block (Panda) is an app that alerts the patient to assess their PNB, score their pain, and take scheduled pain medication. We assessed the usability and feasibility of Panda for assisting patients after receiving a PNB. METHODS: Twenty-nine patients tested Panda in three rounds, for two to seven days, postoperatively to assess and manage their pain and PNB. Feedback was provided via phone interview and the Computer System Usability Questionnaire (CSUQ). Additionally, each user's usage log was analyzed for parameters such as alert response times. Feasibility was determined by alert responses that occurred before the next alert, with a goal of greater than 50%. User adherence was measured as percentage compliance with alerts within one hour; usability and user satisfaction were determined from the CSUQ and interviews. RESULTS: A median [interquartile range (IQR)] of 68 [34-93]% responded before the next alert during the first 48 hr of app use, and 83 [54-92]% responded before the next alert with 87 [75-96]% of these within one hour. There were no significant differences in usage between rounds. Ninety-three percent of patients reported Panda to be easy to use and helpful, and 79% of patients would use Panda again. Critical themes included changes to the layout and appearance, clarification of the language of the PNB check, and requests for dynamic adjustments to the medication schedule based on user responses. CONCLUSION: Panda-Nerve Block is a feasible method for PNB patients to manage postoperative pain with a high response rate. Future work should include providing two-way communication for patients and clinicians and assessing its effect on pain outcomes. TRIAL REGISTRATION: www.clinicaltrials.gov (NCT03369392); registered 5 December 2017.

RéSUMé: OBJECTIF: Les blocs nerveux périphériques (BNP) procurent une excellente analgésie périopératoire mais peuvent augmenter le risque de douleur postopératoire élevée une fois que le bloc disparait. Un mauvais respect des instructions de congé pourrait augmenter ce risque. L'application Panda (Panda-Nerve Block) avertit le patient afin qu'il évalue son BNP, quantifie sa douleur, et prenne ses médicaments analgésiques prescrits. Nous avons évalué la facilité d'utilisation et la faisabilité de l'application Panda pour aider les patients ayant reçu un BNP. MéTHODE: Vingt-neuf patients ont testé l'application Panda en trois itérations de deux à sept jours après leur opération afin d'évaluer et de prendre en charge leur douleur et le BNP. Les rétroactions étaient partagées par entretien téléphonique et via le Questionnaire sur la convivialité du système informatique (CSUQ - Computer System Usability Questionnaire). En outre, le journal d'utilisation de chaque utilisateur a été analysé pour en étudier certains paramètres tels que les temps de réponse aux alertes. La faisabilité était déterminée par les réponses aux alertes survenant avant la prochaine alerte, avec un objectif de plus de 50 %. L'observance des utilisateurs était mesurée en tant que pourcentage de conformité aux alertes dans l'heure suivante; la facilité d'utilisation et la satisfaction des utilisateurs étaient déterminées à partir du CSUQ et des entretiens. RéSULTATS: En moyenne [écart interquartile (ÉIQ)], 68 [34­93] % des patients ont répondu avant la prochaine alerte au cours des premières 48 h d'utilisation de l'application, et 83 [54­92] % ont répondu avant la prochaine alerte, avec 87 [75­96] % de ces patients dans l'heure qui suivait. Il n'y a pas eu de différence significative dans l'utilisation entre les itérations. Quatre-vingt-treize pour cent des patients ont rapporté qu'ils trouvaient l'application Panda conviviale et utile, et 79 % l'utiliseraient à nouveau. Les critiques comprenaient des modifications de la disposition et de l'apparence de l'application, la clarification du langage lors des vérifications du BNP, et des demandes pour des ajustements dynamiques du traitement selon les réponses des utilisateurs. CONCLUSION: L'application Panda constitue une méthode possible de prise en charge de la douleur postopératoire pour les patients ayant reçu un BNP, avec un taux de réponse élevé. Les travaux futurs devraient inclure la fourniture d'une communication bidirectionnelle pour les patients et les cliniciens et l'évaluation de l'effet de l'utilisation de l'application sur des devenirs de douleur. ENREGISTREMENT DE L'éTUDE: www.clinicaltrials.gov (NCT03369392); enregistrée le 5 décembre 2017.

Smart triage: triage and management of sepsis in children using the point-of-care Pediatric Rapid Sepsis Trigger (PRST) tool.

BACKGROUND: Sepsis is the leading cause of death and disability in children. Every hour of delay in treatment is associated with an escalating risk of morbidity and mortality. The burden of sepsis is greatest in low- and middle-income countries where timely treatment may not occur due to delays in diagnosis and prioritization of critically ill children. To circumvent these challenges, we propose the development and clinical evaluation of a digital triage tool that will identify high risk children and reduce time to treatment. We will also implement and clinically validate a Radio-Frequency Identification system to automate tracking of patients. The mobile platform (mobile device and dashboard) and automated patient tracking system will create a low cost, highly scalable solution for critically ill children, including those with sepsis. METHODS: This is pre-post intervention study consisting of three phases. Phase I will be a baseline period where data is collected on key predictors and outcomes before implementation of the digital triage tool. In Phase I, there will be no changes to healthcare delivery processes in place at the study hospitals. Phase II will involve model derivation, technology development, and usability testing. Phase III will be the intervention period where data is collected on key predictors and outcomes after implementation of the digital triage tool. The primary outcome, time to treatment initiation, will be compared to assess effectiveness of the digital health intervention. DISCUSSION: Smart technology has the potential to overcome the barrier of limited clinical expertise in the identification of the child at risk. This mobile health platform, with sensors and data-driven applications, will provide real-time individualized risk prediction to rapidly triage patients and facilitate timely access to life-saving treatments for children in low- and middle-income countries, where specialists are not regularly available and deaths from sepsis are common. TRIAL REGISTRATION: Clinical Trials.gov Identifier: NCT04304235, Registered 11 March 2020.

The evaluation of smartphone versions of the visual analogue scale and numeric rating scale as postoperative pain assessment tools: a prospective randomized trial.

PURPOSE: The Pain assessment using a novel digital application (Panda) is a smartphone application that contains the digital versions of the visual analogue scale (VAS-100) and numeric rating scale (NRS-11). This study aimed to investigate if the Panda versions of these two pain scales are equivalent to the paper versions in adult patients. METHODS: This was a prospective, randomized, cross-over-controlled trial of subjects aged 19-75 yr undergoing procedures with anticipated post-surgical pain. Each subject used both the Panda and paper versions of VAS-100 or NRS-11 pain scores after emergence from anesthesia and after meeting postanesthesia care unit (PACU) discharge criteria. Correlations between the two tools were analyzed, and Bland-Altman agreement was calculated. The smartphone and paper versions were considered equivalent at each time point if the differences (and their 95% confidence interval [CI]) between them were less than 20 points for the VAS-100 and 2.1 for NRS-11. RESULTS: The two versions of the VAS-100 correlated strongly after emergence (Pearson's r = 0.93; P < 0.001) and upon meeting discharge criteria (r = 0.94; P < 0.001); the mean (standard deviation [SD]) Panda score after emergence was 35 (27) compared with the paper score of 37 (26) (mean difference, - 2; 95% CI, - 22 to 19). The mean (SD) VAS-100 Panda score upon meeting discharge criteria was 21 (20) compared with the paper score of 23 (21) (mean difference, - 2; 95% CI, - 17 to 13). For the NRS-11, Panda again correlated strongly with the original tool scores after emergence (r = 0.93; P < 0.001) and upon meeting discharge criteria (r = 0.96; P < 0.001); the mean (SD) Panda and paper scores after emergence were both 4 (3) (mean difference, 0.05; 95% CI, - 1.87 to 1.96). The mean (SD) NRS-11 Panda and paper scores upon meeting PACU discharge criteria were both 3 (2) (mean difference, - 0.08; 95% CI, - 1.41 to 1.26). CONCLUSION: Following emergence from anesthesia in adult patients, the digital Panda version of the NRS-11, but not the VAS-100, is equivalent to the validated paper version. In those who are ready for discharge from the PACU, the digital Panda versions of both the VAS-100 and NRS-11 agreed adequately and can be used in place of the original paper versions.

In-hospital usability and feasibility evaluation of Panda, an app for the management of pain in children at home.

BACKGROUND: Postoperative pain in children is often poorly managed at home, leading to slower functional recovery, poor oral intake, sleep disturbances, and behavioral changes. Panda is a smartphone application (app) designed to support parents in assessing their child's pain and managing medications. AIMS: The aim of this study was to evaluate the Panda app's usability and feasibility in hospital prior to testing the app at home. METHODS: The study comprised two phases. Phase I evaluated Panda's usability with nurses, parents, and adolescents using simulated scenarios. Usability was measured by task completion rate, user error rates, and the Computer Systems Usability Questionnaire. Phase II evaluated Panda's feasibility by observing parents/guardians of pediatric patients using the app on the postsurgical ward. Feasibility was measured using response frequency and delay following app notifications from an audit trail of app function, and parental satisfaction from an interview. Feedback was used to guide iterative app improvements. RESULTS: In Phase I, 13 nurses, 12 parents, and 5 adolescents evaluated the app. A total of 103 usability issues were identified, analyzed, and addressed. In Phase II, 29 parents responded to a total of 151 app notifications, with 84% responding within 1 hour in the final round of testing; 93% of participants reported the app was easy to use, and rated the app with a median [interquartile range] Computer Systems Usability Questionnaire score of 2 [1-4]. Significant barriers to use included lack of flexibility in the medication scheduling, low volume of alert sounds, and the extra time spent on medication safety checks. CONCLUSION: Panda's usability was improved and its feasibility demonstrated in the controlled hospital environment. The next step is to evaluate its feasibility for use at home.

Assessing the incremental value of blood oxygen saturation (SpO(2)) in the miniPIERS (Pre-eclampsia Integrated Estimate of RiSk) Risk Prediction Model.

OBJECTIVE: To assess the incremental value of blood oxygen saturation (SpO(2)) as a predictor in the miniPIERS model, a risk prediction model for adverse outcomes among women with a diagnosis of hypertensive disorder of pregnancy (HDP) in low-resourced settings. METHODS: Using data from a prospective cohort including 852 women admitted to hospital for a HDP, the association between SpO(2) and adverse maternal outcome was assessed using logistic regression. The miniPIERS model was recalibrated and extended to include SpO(2). The incremental value of adding SpO(2) to the model was measured using a net reclassification index (NRI), sensitivity, specificity, positive and negative predictive values, and likelihood ratios. RESULTS: SpO(2) of < 93% was associated with a 30-fold increase in risk (95% CI 14 to 68) of adverse maternal outcome compared to women with SpO(2) > 97%. After recalibration and extension, the miniPIERS model including SpO(2) (vs. not including SpO(2)) had improved sensitivity (32.8% vs. 49.6%) at the cost of minimally decreased specificity (91.5% vs. 96.2%) with a NRI of 0.122. CONCLUSION: SpO(2) is a significant independent predictor of risk in women with a HDP. Adding SpO(2) to the miniPIERS model improved the model's ability to correctly identify high-risk patients who would benefit most from interventions.

Objectif : Évaluer la valeur cumulative de la saturation en oxygène (SaO2) à titre de facteur prédictif dans le cadre du modèle miniPIERS, soit un modèle de prévision des risques en ce qui concerne les issues indésirables chez les femmes ayant obtenu un diagnostic de trouble hypertensif de la grossesse (THG) dans des milieux qui ne disposent que de faibles ressources. Méthodes : Grâce à des données issues d'une cohorte prospective ayant porté sur 852 femmes hospitalisées en raison d'un THG, l'association entre la SaO2 et les issues indésirables maternelles a été évaluée au moyen d'une régression logistique. Le modèle miniPIERS a été recalibré et élargi de façon à inclure la SaO2. La valeur cumulative de l'ajout de la SaO2 à ce modèle a été mesurée en ayant recours à l'indice NRI (net reclassification index), à la sensibilité, à la spécificité, aux coefficients de prévision d'un test positif et d'un test négatif et aux rapports de vraisemblance. Résultats : La SaO2 < 93 % a été associée à un risque 30 fois plus élevé (IC à 95 %, 14 - 68) de constater une issue maternelle indésirable, par comparaison avec une SaO2 > 97 %. Après avoir été recalibré et élargi, le modèle miniPIERS comprenant la SaO2 (par comparaison avec le modèle ne comprenant pas la SaO2) présentait une sensibilité améliorée (32,8 % vs 49,6 %); cela a toutefois mené à une baisse minime de la spécificité (91,5 % vs 96,2 %) en présence d'un indice NRI de 0,122. Conclusion : La SaO2 constitue un facteur prédictif indépendant significatif pour ce qui est du risque auquel sont exposées les femmes qui présentent un THG. L'ajout de la SaO2 au modèle miniPIERS a mené à l'amélioration de la capacité de ce dernier à identifier correctement les patientes exposées à des risques élevés qui tireraient le plus avantage de la tenue d'interventions.

A smartphone version of the Faces Pain Scale-Revised and the Color Analog Scale for postoperative pain assessment in children.

BACKGROUND: Effective pain assessment is essential during postoperative recovery. Extensive validation data are published supporting the Faces Pain Scale-Revised (FPS-R) and the Color Analog Scale (CAS) in children. Panda is a smartphone-based application containing electronic versions of these scales. OBJECTIVES: To evaluate agreement between Panda and original paper/plastic versions of the FPS-R and CAS and to determine children's preference for either Panda or original versions of these scales. METHODS: ASA I-III children, 4-18 years, undergoing surgery were assessed using both Panda and original versions of either the FPS-R or CAS. Pain assessments were conducted within 10 min of waking from anesthesia and 30 min later. RESULTS: Sixty-two participants, median (range) age 7.5 (4-12) years, participated in the FPS-R trial; Panda scores correlated strongly with the original scores at both time points (Pearson's r > 0.93) with limits of agreement within clinical significance (80% CI). Sixty-six participants, age 13 (5-18) years, participated in the CAS trial. Panda scores correlated strongly with the original scores at both time points (Pearson's r > 0.87); mean pain scores were higher (up to +0.47 out of 10) with Panda than with the original tool, representing a small systematic bias, but limits of agreement were within clinical significance. Most participants who expressed a preference preferred Panda over the original tool (81% of FPS-R, 76% of CAS participants). CONCLUSION: The Panda smartphone application can be used in lieu of the original FPS-R and CAS for assessment of pain in children. Children's preference for Panda may translate to improved cooperation with self-report of pain.

External validation of a paediatric Smart triage model for use in resource limited facilities.

Models for digital triage of sick children at emergency departments of hospitals in resource poor settings have been developed. However, prior to their adoption, external validation should be performed to ensure their generalizability. We externally validated a previously published nine-predictor paediatric triage model (Smart Triage) developed in Uganda using data from two hospitals in Kenya. Both discrimination and calibration were assessed, and recalibration was performed by optimizing the intercept for classifying patients into emergency, priority, or non-urgent categories based on low-risk and high-risk thresholds. A total of 2539 patients were eligible at Hospital 1 and 2464 at Hospital 2, and 5003 for both hospitals combined; admission rates were 8.9%, 4.5%, and 6.8%, respectively. The model showed good discrimination, with area under the receiver-operator curve (AUC) of 0.826, 0.784 and 0.821, respectively. The pre-calibrated model at a low-risk threshold of 8% achieved a sensitivity of 93% (95% confidence interval, (CI):89%-96%), 81% (CI:74%-88%), and 89% (CI:85%-92%), respectively, and at a high-risk threshold of 40%, the model achieved a specificity of 86% (CI:84%-87%), 96% (CI:95%-97%), and 91% (CI:90%-92%), respectively. Recalibration improved the graphical fit, but new risk thresholds were required to optimize sensitivity and specificity.The Smart Triage model showed good discrimination on external validation but required recalibration to improve the graphical fit of the calibration plot. There was no change in the order of prioritization of patients following recalibration in the respective triage categories. Recalibration required new site-specific risk thresholds that may not be needed if prioritization based on rank is all that is required. The Smart Triage model shows promise for wider application for use in triage for sick children in different settings.

Geographical validation of the Smart Triage Model by age group.

Infectious diseases in neonates account for half of the under-five mortality in low- and middle-income countries. Data-driven algorithms such as clinical prediction models can be used to efficiently detect critically ill children in order to optimize care and reduce mortality. Thus far, only a handful of prediction models have been externally validated and are limited to neonatal in-hospital mortality. The aim of this study is to externally validate a previously derived clinical prediction model (Smart Triage) using a combined prospective baseline cohort from Uganda and Kenya with a composite endpoint of hospital admission, mortality, and readmission. We evaluated model discrimination using area under the receiver-operator curve (AUROC) and visualized calibration plots with age subsets (< 30 days, ≤ 2 months, ≤ 6 months, and < 5 years). Due to reduced performance in neonates (< 1 month), we re-estimated the intercept and coefficients and selected new thresholds to maximize sensitivity and specificity. 11595 participants under the age of five (under-5) were included in the analysis. The proportion with an endpoint ranged from 8.9% in all children under-5 (including neonates) to 26% in the neonatal subset alone. The model achieved good discrimination for children under-5 with AUROC of 0.81 (95% CI: 0.79-0.82) but poor discrimination for neonates with AUROC of 0.62 (95% CI: 0.55-0.70). Sensitivity at the low-risk thresholds (CI) were 85% (83%-87%) and 68% (58%-76%) for children under-5 and neonates, respectively. After model revision for neonates, we achieved an AUROC of 0.83 (95% CI: 0.79-0.87) with 13% and 41% as the low- and high-risk thresholds, respectively. The updated Smart Triage performs well in its predictive ability across different age groups and can be incorporated into current triage guidelines at local healthcare facilities. Additional validation of the model is indicated, especially for the neonatal model.

Comparison between the Smart Triage model and the Emergency Triage Assessment and Treatment guidelines in triaging children presenting to the emergency departments of two public hospitals in Kenya.

Several triage systems have been developed, but little is known about their performance in low-resource settings. Evaluating and comparing novel triage systems to existing triage scales provides essential information about their added value, reliability, safety, and effectiveness before adoption. This study included children aged < 15 years who presented to the emergency departments of two public hospitals in Kenya between February and December 2021. We compared the performance of Emergency Triage Assessment and Treatment (ETAT) guidelines and Smart Triage (ST) models (ST model with independent triggers, and recalibrated ST model with independent triggers) in categorizing children into emergency, priority, and non-urgent triage categories. Sankey diagrams were used to visualize the distribution of children into similar or different triage categories by ETAT and ST models. Sensitivity, specificity, negative and positive predictive values for mortality and admission were calculated. 5618 children were enrolled, and the majority (3113, 55.4%) were aged between one and five years of age. Overall admission and mortality rates were 7% and 0.9%, respectively. ETAT classified 513 (9.2%) children into the emergency category compared to 1163 (20.8%) and 1161 (20.7%) by the ST model with independent triggers and recalibrated model with independent triggers, respectively. ETAT categorized 3089 (55.1%) children as non-urgent compared to 2097 (37.4%) and 2617 (46.7%) for the respective ST models. ETAT classified 191/395 (48.4%) admitted patients as emergencies compared to more than half by all the ST models. ETAT and ST models classified 25/49 (51%) and 39/49 (79.6%) deceased children as emergencies. Sensitivity for admission and mortality was 48.4% and 51% for ETAT and 74.9% and 79.6% for the ST models, respectively. Smart Triage shows potential for identifying critically ill children in low-resource settings, particularly when combined with independent triggers and performs comparably to ETAT. Evaluation of Smart Triage in other contexts and comparison to other triage systems is required.

Prediction models for post-discharge mortality among under-five children with suspected sepsis in Uganda: A multicohort analysis.

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. 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. 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. Simple prediction models at admission with suspected sepsis can identify children at risk of post-discharge mortality. Further external validation is recommended for different contexts. Models can be digitally integrated into existing processes to improve peri-discharge care as children transition from the hospital to the community.

Repeatability of Pulse Oximetry Measurements in Children During Triage in 2 Ugandan Hospitals.

BACKGROUND: In low- and middle-income countries, health workers use pulse oximeters for intermittent spot measurements of oxygen saturation (SpO2). However, the accuracy and reliability of pulse oximeters for spot measurements have not been determined. We evaluated the repeatability of spot measurements and the ideal observation time to guide recommendations during spot check measurements. METHODS: Two 1-minute measurements were taken for the 3,903 subjects enrolled in the study conducted April 2020-January 2022 in Uganda, collecting 1 Hz SpO2 and signal quality index (SQI) data. The repeatability between the 2 measurements was assessed using an intraclass correlation coefficient (ICC), calculated using a median of all seconds of non-zero SpO2 values for each recording (any quality, Q1) and again with a quality filter only using seconds with SQI 90% or higher (good quality, Q2). The ICC was also recalculated for both conditions of Q1 and Q2 using the initial 5 seconds, then the initial 10 seconds, and continuing with 5-second increments up to the full 60 seconds. Lastly, the whole minute ICC was calculated with good quality (Q2), including only records where both measurements had a mean SQI of more than 70% (Q3). RESULTS: The repeatability ICC with condition Q1 was 0.591 (95% confidence interval [CI]=0.570, 0.611). Using only the first 5 seconds of each measurement reduced the repeatability to 0.200 (95% CI=0.169, 0.230). Filtering with Q2, the whole-minute ICC was 0.855 (95% CI=0.847, 0.864). The ICC did not improve beyond the first 35 seconds. For Q3, the repeatability rose to 0.908 (95% CI=0.901, 0.914). CONCLUSIONS: Training guidelines must emphasize the importance of signal quality and duration of measurement, targeting a minimum of 35 seconds of adequate-quality, stable data. In addition, the design of new devices should incorporate user prompts and force quality checks to encourage more accurate pulse oximetry measurements.

Mortality after hospital discharge among children younger than 5 years admitted with suspected sepsis in Uganda: a prospective, multisite, observational cohort study.

BACKGROUND: 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. METHODS: In this prospective, multisite, observational cohort study, we recruited and consecutively enrolled children aged 0-60 months admitted with suspected sepsis from the community to the paediatric wards of six Ugandan hospitals. Suspected sepsis was defined as the need for admission due to a suspected or proven infectious illness. At admission, trained study nurses systematically collected data on clinical variables, sociodemographic variables, and baseline characteristics with encrypted study tablets. Participants were followed up for 6 months after discharge by field officers who contacted caregivers at 2 months and 4 months after discharge by telephone and at 6 months after discharge in person to measure vital status, health-care seeking after discharge, and readmission details. We assessed 6-month mortality after hospital discharge among those discharged alive, with verbal autopsies conducted for children who had died after hospital discharge. FINDINGS: Between July 13, 2017, and March 30, 2020, 16 991 children were screened for eligibility. 6545 children (2927 [44·72%] female children and 3618 [55·28%] male children) were enrolled and 6191 were discharged from hospital alive. 6073 children (2687 [44·2%] female children and 3386 [55·8%] male children) completed follow-up. 366 children died in the 6-month period after discharge (weighted mortality rate 5·5%). Median time from discharge to death was 28 days (IQR 9-74). For the 360 children for whom location of death was documented, deaths occurred at home (162 [45·0%]), in transit to care (66 [18·3%]), or in hospital (132 [36·7%]) during a subsequent readmission. Death after hospital discharge was strongly associated with weight-for-age Z scores less than -3 (adjusted risk ratio [aRR] 4·7, 95% CI 3·7-5·8 vs a Z score of >-2), discharge or referral to a higher level of care (7·3, 5·6-9·5), and unplanned discharge (3·2, 2·5-4·0). Hazard ratios (HRs) for severe anaemia (<7g/dL) increased with time since discharge, from 1·7 (95% CI 0·9-3·0) for death occurring in the first time tertile to 5·2 (3·1-8·5) in the third time tertile. HRs for some discharge vulnerabilities decreased significantly with increasing time since discharge, including unplanned discharge (from 4.5 [2·9-6·9] in the first tertile to 2·0 [1·3-3·2] in the third tertile) and poor feeding status (from 7·7 [5·4-11·0] to 1·84 [1·0-3·3]). Age interacted with several variables, including reduced weight-for-age Z score, severe anaemia, and reduced admission temperature. INTERPRETATION: Paediatric mortality following hospital discharge after suspected sepsis is common, with diminishing, although persistent, risk during the first 6 months after discharge. Efforts to improve outcomes after hospital discharge are crucial to achieving Sustainable Development Goal 3.2 (ending preventable childhood deaths under age 5 years). FUNDING: Grand Challenges Canada, Thrasher Research Fund, BC Children's Hospital Foundation, and Mining4Life.

A vibro-tactile display for clinical monitoring: real-time evaluation.

BACKGROUND: Vibro-tactile displays use human skin to convey information from physiological monitors to anesthesiologists, providing cues about changes in the status of the patient. In this investigation, we evaluated, in a real-time clinical environment, the usability and wearability of a novel vibro-tactile display belt recently developed by our group, and determined its accuracy in identifying events when used by anesthesiologists. METHODS: A prospective observational study design was used. During routine anesthesia, a standard physiological monitor was connected to a software tool that used algorithms to automatically identify changing trends in mean noninvasive arterial blood pressure, expired minute ventilation, peak airway pressure, and end-tidal carbon dioxide partial pressure. The software was wirelessly interfaced to a vibro-tactile belt worn by the anesthesiologist. Each physiological variable was mapped to 1 of 4 tactor locations within the belt. The direction (increase/decrease) and 2 levels of change (small/large) were encoded in the stimulation patterns. A training session was completed by each anesthesiologist. The system was activated in real-time during anesthesia alongside routine physiological monitors. When the algorithms detected changes in the patient, the belt vibrated at the appropriate location with the pattern corresponding to the level and direction of change. Using a touch screen monitor the anesthesiologist was to enter the vibro-tactile message by first identifying the variable, then identifying the level and direction of change. Usability and wearability questionnaires were to be completed. The percentage of correct identification of the physiological trend, the direction of change, and the level of change were primary outcome variables. The mean usability score and wearability results were secondary outcome variables. We hypothesized that anesthesiologists would correctly identify the events communicated to them through the vibro-tactile belt 90% of the time, and that anesthesiologists would find the vibro-tactile belt usable and wearable. RESULTS: Seventeen anesthesiologists evaluated the display during 57 cases. The belt was operational for a mean (SD) duration of 75 (41) minutes per case. Seven cases were excluded from analysis because of technical failures. Eighty-one percent (confidence interval [CI], 77% to 84%) of all stimuli were decoded. The physiological trend, the direction of change, and the level of change were correctly identified for 97.7% (CI 96%-99%), 94.9% (CI 92%-97%), and 93.5% of these stimuli (CI, 91%-96%), respectively. Fourteen anesthesiologists completed the usability and wearability questionnaires. The mean usability score was 4.8 of a maximum usability score of 7. CONCLUSIONS: Anesthesiologists found a vibro-tactile belt to be wearable and usable and could accurately decode vibro-tactile messages in a real-time clinical environment.

Evaluation of Sibel's Advanced Neonatal Epidermal (ANNE) wireless continuous physiological monitor in Nairobi, Kenya.

BACKGROUND: Neonatal multiparameter continuous physiological monitoring (MCPM) technologies assist with early detection of preventable and treatable causes of neonatal mortality. Evaluating accuracy of novel MCPM technologies is critical for their appropriate use and adoption. METHODS: We prospectively compared the accuracy of Sibel's Advanced Neonatal Epidermal (ANNE) technology with Masimo's Rad-97 pulse CO-oximeter with capnography and Spengler's Tempo Easy reference technologies during four evaluation rounds. We compared accuracy of heart rate (HR), respiratory rate (RR), oxygen saturation (SpO2), and skin temperature using Bland-Altman plots and root-mean-square deviation analyses (RMSD). Sibel's ANNE algorithms were optimized between each round. We created Clarke error grids with zones of 20% to aid with clinical interpretation of HR and RR results. RESULTS: Between November 2019 and August 2020 we collected 320 hours of data from 84 neonates. In the final round, Sibel's ANNE technology demonstrated a normalized bias of 0% for HR and 3.1% for RR, and a non-normalized bias of -0.3% for SpO2 and 0.2°C for temperature. The normalized spread between 95% upper and lower limits-of-agreement (LOA) was 4.7% for HR and 29.3% for RR. RMSD for SpO2 was 1.9% and 1.5°C for temperature. Agreement between Sibel's ANNE technology and the reference technologies met the a priori-defined thresholds for 95% spread of LOA and RMSD. Clarke error grids showed that all HR and RR observations were within a 20% difference. CONCLUSION: Our findings suggest acceptable agreement between Sibel's ANNE and reference technologies. Clinical effectiveness, feasibility, usability, acceptability, and cost-effectiveness investigations are necessary for large-scale implementation.

Smart triage: Development of a rapid pediatric triage algorithm for use in low-and-middle income countries.

Introduction: Early and accurate recognition of children at risk of progressing to critical illness could contribute to improved patient outcomes and resource allocation. In resource limited settings digital triage tools can support decision making and improve healthcare delivery. We developed a model for rapid identification of critically ill children at triage. Methods: This was a prospective cohort study of acutely ill children presenting at Jinja Regional Referral Hospital in Eastern Uganda. Variables collected in the emergency department informed the development of a logistic model based on hospital admission using bootstrap stepwise regression. Low and high-risk thresholds for 90% minimum sensitivity and specificity, respectively generated three risk level categories. Performance was assessed using receiver operating characteristic curve analysis on a held-out test set generated by an 80:20 split with 10-fold cross validation. A risk stratification table informed clinical interpretation. Results: The model derivation cohort included 1,612 participants, with an admission rate of approximately 23%. The majority of admitted patients were under five years old and presenting with sepsis, malaria, or pneumonia. A 9-predictor triage model was derived: logit (p) = -32.888 + (0.252, square root of age) + (0.016, heart rate) + (0.819, temperature) + (-0.022, mid-upper arm circumference) + (0.048 transformed oxygen saturation) + (1.793, parent concern) + (1.012, difficulty breathing) + (1.814, oedema) + (1.506, pallor). The model afforded good discrimination, calibration, and risk stratification at the selected thresholds of 8% and 40%. Conclusion: In a low income, pediatric population, we developed a nine variable triage model with high sensitivity and specificity to predict who should be admitted. The triage model can be integrated into any digital platform and used with minimal training to guide rapid identification of critically ill children at first contact. External validation and clinical implementation are in progress.