The 2024 Pediatric Sepsis Challenge: Predicting In-Hospital Mortality in Children With Suspected Sepsis in Uganda.

The aim of this "Technical Note" is to inform the pediatric critical care data research community about the "2024 Pediatric Sepsis Data Challenge." This competition aims to facilitate the development of open-source algorithms to predict in-hospital mortality in Ugandan children with sepsis. The challenge is to first develop an algorithm using a synthetic training dataset, which will then be scored according to standard diagnostic testing criteria, and then be evaluated against a nonsynthetic test dataset. The datasets originate from admissions to six hospitals in Uganda (2017-2020) and include 3837 children, 6 to 60 months old, who were confirmed or suspected to have a diagnosis of sepsis. The synthetic dataset was created from a random subset of the original data. The test validation dataset closely resembles the synthetic dataset. The challenge should generate an optimal model for predicting in-hospital mortality. Following external validation, this model could be used to improve the outcomes for children with proven or suspected sepsis in low- and middle-income settings.

Assessment of Facility Readiness for Pediatric Emergency and Critical Care Utilizing a 2-Phase Survey Conducted in Six Hospitals in Uganda and Cameroon: A Quality Improvement Study.

OBJECTIVES: Each year, 5.3 million children under 5 years of age die in low-resource settings, often due to delayed recognition of disease severity, inadequate treatment, or a lack of supplies. We describe the use of a comprehensive digital facility-readiness survey tool, recently developed by the Pediatric Sepsis Data CoLaboratory, which aims to identify target areas for quality improvement related to pediatric emergency and critical care. METHODS: Facility-readiness surveys were conducted at six sub-Saharan African hospitals providing pediatric emergency and critical care in Uganda (n = 4) and Cameroon (n = 2). The tool is a 2-phase survey to assess readiness to provide pediatric essential emergency and critical care: (1) an "environmental scan," focusing on infrastructure, availability, and functionality of resources, and (2) an "observational scan" assessing the quality and safety of care through direct observation of patients receiving treatment for common diseases. Data were captured in a mobile application and the findings analyzed descriptively. RESULTS: Varying levels of facility readiness to provide pediatric emergency care were observed. Only 1 of 6 facilities had a qualified staff member to assess children for danger signs upon arrival, and only 2 of 6 had staff with skills to manage emergency conditions. Only 21% of essential medicines required for pediatric emergency and critical care were available at all six facilities. Most facilities had clean running water and soap or disinfectants, but most also experienced interruptions to their electricity supply. Less than half of patients received an appropriate discharge note and fewer received counseling on postdischarge care; follow-up was arranged in less than a quarter of cases. CONCLUSIONS: These pilot findings indicate that facilities are partially equipped and ready to provide pediatric emergency and critical care. This facility-readiness tool can be utilized in low-resource settings to assist hospital administrators and policymakers to determine priority areas to improve quality of care for the critically ill child.

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.

Risk factors for postpartum maternal mortality and hospital readmission in low- and middle-income countries: a systematic review.

BACKGROUND: In low- and middle-income countries, approximately two thirds of maternal deaths occur in the postpartum period. Yet, care for women beyond 24 h after discharge is limited. The objective of this systematic review is to summarize current evidence on socio-demographic and clinical risk factors for (1) postpartum mortality and (2) postpartum hospital readmission. METHODS: A combination of keywords and subject headings (i.e. MeSH terms) for postpartum maternal mortality or readmission were searched. Articles published up to January 9, 2021 were identified in MEDLINE, EMBASE, and CINAHL databases, without language restrictions. Studies reporting socio-demographic or clinical risk factors for postpartum mortality or readmission within six weeks of delivery among women who delivered a livebirth in a low- or middle-income country were included. Data were extracted independently by two reviewers based on study characteristics, population, and outcomes. Included studies were assessed for quality and risk of bias using the Downs and Black checklist for ratings of randomized and non-randomized studies. RESULTS: Of 8783 abstracts screened, seven studies were included (total N = 387,786). Risk factors for postpartum mortality included Caesarean mode of delivery, nulliparity, low or very low birthweight, and shock upon admission. Risk factors for postpartum readmission included Caesarean mode of delivery, HIV positive serostatus, and abnormal body temperature. CONCLUSIONS: Few studies reported individual socio-demographic or clinical risk factors for mortality or readmission after delivery in low- and middle-income countries; only Caesarean delivery was consistently reported. Further research is needed to identify factors that put women at greatest risk of post-discharge complications and mortality. Understanding post-discharge risk would facilitate targeted postpartum care and reduce adverse outcomes in women after delivery. TRIAL REGISTRATION: PROSPERO registration number: CRD42018103955.

Cost-effectiveness analysis of Smart Triage, a data-driven pediatric sepsis triage platform in Eastern Uganda.

BACKGROUND: Sepsis, characterized by organ dysfunction due to presumed or proven infection, has a case-fatality over 20% in severe cases in low-and-middle income countries. Early diagnosis and treatment have proven benefits, prompting our implementation of Smart Triage at Jinja Regional Referral Hospital in Uganda, a program that expedites treatment through a data-driven triage platform. We conducted a cost-effectiveness analysis of Smart Triage to explore its impact on patients and inform multicenter scale up. METHODS: The parent clinical trial for Smart Triage was pre-post in design, using the proportion of children receiving sepsis treatment within one hour as the primary outcome, a measure linked to mortality benefit in existing literature. We used a decision-analytic model with Monte Carlo simulation to calculate the cost per year-of-life-lost (YLL) averted of Smart Triage from societal, government, and patient perspectives. Healthcare utilization and lost work for seven days post-discharge were translated into costs and productivity losses via secondary linkage data. RESULTS: In 2021 United States dollars, Smart Triage requires an annuitized program cost of only $0.05 per child, but results in $15.32 saved per YLL averted. At a willingness-to-pay threshold of only $3 per YLL averted, well below published cost-effectiveness threshold estimates for Uganda, Smart Triage approaches 100% probability of cost-effectiveness over the baseline manual triage system. This cost-effectiveness was observed from societal, government, and patient perspectives. The cost-effectiveness observed was driven by a reduction in admission that, while explainable by an improved triage mechanism, may also be partially attributable to changes in healthcare utilization influenced by the coronavirus pandemic. However, Smart Triage remains cost-effective in sensitivity analyses introducing a penalty factor of up to 50% in the reduction in admission. CONCLUSION: Smart Triage's ability to both save costs and avert YLLs indicates that patients benefit both economically and clinically, while its high probability of cost-effectiveness strongly supports multicenter scale up. Areas for further research include the incorporation of years lived with disability when sepsis disability weights in low-resource settings become available and analyzing budget impact during multicenter scale up. TRIAL REGISTRATION: NCT04304235 (registered on 11/03/2020, clinicaltrials.gov).

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 Effect of Low-Dose Intraoperative Ketamine on Closed-Loop-Controlled General Anesthesia: A Randomized Controlled Equivalence Trial.

BACKGROUND: Closed-loop control of propofol-remifentanil anesthesia using the processed electroencephalography depth-of-hypnosis index provided by the NeuroSENSE monitor (WAVCNS) has been previously described. The purpose of this placebo-controlled study was to evaluate the performance (percentage time within ±10 units of the setpoint during the maintenance of anesthesia) of a closed-loop propofol-remifentanil controller during induction and maintenance of anesthesia in the presence of a low dose of ketamine. METHODS: Following ethical approval and informed consent, American Society of Anesthesiologist (ASA) physical status I-II patients aged 19-54 years, scheduled for elective orthopedic surgery requiring general anesthesia for >60 minutes duration, were enrolled in a double-blind randomized, placebo-controlled, 2-group equivalence trial. Immediately before induction of anesthesia, participants in the ketamine group received a 0.25 mg·kg-1 bolus of intravenous ketamine over 60 seconds followed by a continuous 5 µg·kg-1·min-1 infusion for up to 45 minutes. Participants in the control group received an equivalent volume of normal saline. After the initial study drug bolus, closed-loop induction of anesthesia was initiated; propofol and remifentanil remained under closed-loop control until the anesthetic was tapered and turned off at the anesthesiologist's discretion. An equivalence range of ±8.99% was assumed for comparing controller performance. RESULTS: Sixty patients participated: 41 males, 54 ASA physical status I, with a median (interquartile range [IQR]) age of 29 [23, 38] years and weight of 82 [71, 93] kg. Complete data were available from 29 cases in the ketamine group and 27 in the control group. Percentage time within ±10 units of the WAVCNS setpoint was median [IQR] 86.6% [79.7, 90.2] in the ketamine group and 86.4% [76.5, 89.8] in the control group (median difference, 1.0%; 95% confidence interval [CI] -3.6 to 5.0). Mean propofol dose during maintenance of anesthesia for the ketamine group was higher than for the control group (median difference, 24.9 µg·kg-1·min-1; 95% CI, 6.5-43.1; P = .005). CONCLUSIONS: Because the 95% CI of the difference in controller performance lies entirely within the a priori equivalence range, we infer that this analgesic dose of ketamine did not alter controller performance. Further study is required to confirm the finding that mean propofol dosing was higher in the ketamine group, and to investigate the implication that this dose of ketamine may have affected the WAVCNS.

Multiparameter Continuous Physiological Monitoring Technologies in Neonates Among Health Care Providers and Caregivers at a Private Tertiary Hospital in Nairobi, Kenya: Feasibility, Usability, and Acceptability Study.

BACKGROUND: Continuous physiological monitoring technologies are important for strengthening hospital care for neonates, particularly in resource-constrained settings, and understanding user perspectives is critical for informing medical technology design, development, and optimization. OBJECTIVE: This study aims to assess the feasibility, usability, and acceptability of 2 noninvasive, multiparameter, continuous physiological monitoring technologies for use in neonates in an African health care setting. METHODS: We assessed 2 investigational technologies from EarlySense and Sibel, compared with the reference Masimo Rad-97 technology through in-depth interviews and direct observations. A purposive sample of health care administrators, health care providers, and caregivers at Aga Khan University Hospital, a tertiary, private hospital in Nairobi, Kenya, were included. Data were analyzed using a thematic approach in NVivo 12 software. RESULTS: Between July and August 2020, we interviewed 12 health care providers, 5 health care administrators, and 10 caregivers and observed the monitoring of 12 neonates. Staffing and maintenance of training in neonatal units are important feasibility considerations, and simple training requirements support the feasibility of the investigational technologies. Key usability characteristics included ease of use, wireless features, and reduced number of attachments connecting the neonate to the monitoring technology, which health care providers considered to increase the efficiency of care. The main factors supporting acceptability included caregiver-highlighted perceptions of neonate comfort and health care respondent technology familiarity. Concerns about the side effects of wireless connections, electromagnetic fields, and mistrust of unfamiliar technologies have emerged as possible acceptability barriers to investigational technologies. CONCLUSIONS: Overall, respondents considered the investigational technologies feasible, usable, and acceptable for the care of neonates at this health care facility. Our findings highlight the potential of different multiparameter continuous physiological monitoring technologies for use in different neonatal care settings. Simple and user-friendly technologies may help to bridge gaps in current care where there are many neonates; however, challenges in maintaining training and ensuring feasibility within resource-constrained health care settings warrant further research. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2019-035184.

Effect of ketamine on the NeuroSENSE WAVCNS during propofol anesthesia; a randomized feasibility trial.

Dose-dependent effects of ketamine on processed electroencephalographic depth-of-hypnosis indices have been reported. Limited data are available for the NeuroSENSE WAVCNS index. Our aim was to establish the feasibility of closed-loop propofol-remifentanil anesthesia guided by the WAVCNS index in the presence of an analgesic dose of ketamine. Thirty ASA I-II adults, 18-54 years, requiring general anesthesia for anterior cruciate ligament surgery were randomized to receive: full-dose [ketamine, 0.5 mg kg-1 initial bolus, 10 mcg kg-1 min-1 infusion] (recommended dose for postoperative pain management); half-dose [ketamine, 0.25 mg kg-1 bolus, 5 mcg kg-1 min-1 infusion]; or control [no ketamine]. After the ketamine bolus, patients received 1.0 mcg kg-1 remifentanil over 30 s, then 1.5 mg kg-1 propofol over 30 s, followed by manually-adjusted propofol-remifentanil anesthesia. The WAVCNS was > 60 for 7/9 patients in the full-dose group at 7 min after starting the propofol infusion. This was inconsistent with clinical observations of depth-of-hypnosis and significantly higher than control (median difference [MD] 17.0, 95% confidence interval [CI] 11.4-26.8). WAVCNS was median [interquartile range] 49.3 [42.2-62.6] in the half-dose group, and not different to control (MD 5.1, 95% CI - 4.9 to 17.9). During maintenance of anesthesia, the WAVCNS was higher in the full-dose group compared to control (MD 14.7, 95% CI 10.2-19.2) and in the half-dose group compared to control (MD 11.4, 95% CI 4.7-20.4). The full-dose of ketamine recommended for postoperative pain management had a significant effect on the WAVCNS. This effect should be considered when using the WAVCNS to guide propofol-remifentanil dosing.Trial Registration ClinicalTrails.gov No. NCT02908945.

The effect of ketamine on depth of hypnosis indices during total intravenous anesthesia-a comparative study using a novel electroencephalography case replay system.

Ketamine may affect the reliability of electroencephalographic (EEG) depth-of-hypnosis indices as it affects power in high-frequency EEG components. The purpose of this study was to compare the effects of ketamine on three commonly-used depth-of-hypnosis indices by extending our EEG simulator to allow replay of previously-recorded EEG. Secondary analysis of previously-collected data from a randomized controlled trial of intravenous anesthesia with ketamine: Group 0.5 [ketamine, 0.5 mg kg-1 bolus followed by a 10 mcg kg-1 min-1 infusion], Group 0.25 [ketamine, 0.25 mg kg-1 bolus, 5 mcg kg-1 min-1 infusion], and Control [no ketamine]. EEG data were replayed to three monitors: NeuroSENSE (WAV), Bispectral Index (BIS), and Entropy (SE). Differences in depth-of-hypnosis indices during the initial 15 min after induction of anesthesia were compared between monitors, and between groups. Monitor agreement was evaluated using Bland-Altman analysis. Available data included 45.6 h of EEG recordings from 27 cases. Ketamine was associated with higher depth-of-hypnosis index values measured at 10 min (BIS, χ2 = 8.01, p = 0.018; SE, χ2 = 11.44, p = 0.003; WAV, χ2 = 9.19, p = 0.010), and a higher proportion of index values > 60 for both ketamine groups compared to the control group. Significant differences between monitors were not observed, except between BIS and SE in the control group. Ketamine did not change agreement between monitors. The ketamine-induced increase in depth-of-hypnosis indices was observed consistently across the three EEG monitoring algorithms evaluated. The observed increase was likely caused by a power increase in the beta and gamma bands. However, there were no lasting differences in depth-of-hypnosis reported between the three compared indices.

Placental growth factor for the prognosis of women with preeclampsia (fullPIERS model extension): context matters.

BACKGROUND: The fullPIERS risk prediction model was developed to identify which women admitted with confirmed diagnosis of preeclampsia are at highest risk of developing serious maternal complications. The model discriminates well between women who develop (vs. those who do not) adverse maternal outcomes. It has been externally validated in several populations. We assessed whether placental growth factor (PlGF), a biomarker associated with preeclampsia risk, adds incremental value to the fullPIERS model. METHODS: Using a cohort of women admitted into tertiary hospitals in well-resourced settings (the USA and Canada), between May 2010 to February 2012, we evaluated the incremental value of PlGF added to fullPIERS for prediction of adverse maternal outcomes within 48 h after admission with confirmed preeclampsia. The discriminatory performance of PlGF and the fullPIERS model were assessed in this cohort using the area under the receiver's operating characteristic curve (AUROC) while the extended model (fullPIERS +PlGF) was assessed based on net reclassification index (NRI) and integrated discrimination improvement (IDI) performances. RESULTS: In a cohort of 541 women delivered shortly (< 1 week) after presentation, 8.1% experienced an adverse maternal outcome within 48 h of admission. Prediction of adverse maternal outcomes was not improved by addition of PlGF to fullPIERS (NRI: -8.7, IDI - 0.06). Discriminatory performance (AUROC) was 0.67 [95%CI: 0.59-0.75] for fullPIERS only and 0.67 [95%CI: 0.58-0.76]) for fullPIERS extended with PlGF, a performance worse than previously documented in fullPIERS external validation studies (AUROC > 0.75). CONCLUSIONS: While fullPIERS model performance may have been affected by differences in healthcare context between this study cohort and the model development and validation cohorts, future studies are required to confirm whether PlGF adds incremental benefit to the fullPIERS model for prediction of adverse maternal outcomes in preeclampsia in settings where expectant management is practiced.

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.

Evaluating NeuroSENSE for assessing depth of hypnosis during desflurane anesthesia: an adaptive, randomized-controlled trial.

PURPOSE: Processed electroencephalography (EEG) monitors support depth-of-hypnosis assessment during anesthesia. This randomized-controlled trial investigated the performance of the NeuroSENSE electroencephalography (EEG) monitor to determine whether its wavelet anesthetic value for central nervous system (WAVCNS) index distinguishes consciousness from unconsciousness during induction of anesthesia (as assessed by the anesthesiologist) and emergence from anesthesia (indicated by patient responsiveness), and whether it correlates with changes in desflurane minimum alveolar concentration (MAC) during maintenance of anesthesia. METHODS: EEG was collected using a fronto-temporal bilateral montage. The WAVCNS was continuously recorded by the NeuroSENSE monitor, to which the anesthesiologist was blinded. Anesthesia was induced with propofol/remifentanil and maintained with desflurane, with randomized changes of -0.4, 0, or +0.4 MAC every 7.5 min within the 0.8-1.6 MAC range, if clinically acceptable to the anesthesiologist. During emergence from anesthesia, desflurane was stepped down by 0.2 MAC every five minutes. RESULTS: Data from 75 patients with a median [interquartile range] age of 41[35-52] yr were obtained. The WAVCNS distinguished consciousness from unconsciousness as assessed by the anesthesiologist, with area under the receiver operating characteristic curve of 99.5% (95% confidence interval [CI], 98.5 to 100.0) at loss of consciousness and 99.4% (95% CI, 98.5 to 100.0) at return of consciousness. Bilateral WAVCNS changes correlated with desflurane concentrations, with -8.0 and -8.6 WAVCNS units, respectively, per 1 MAC change in the 0.8-1.6 MAC range during maintenance of anesthesia and -10.0 and -10.5 WAVCNS units, respectively, in the 0.4-1.6 MAC range including emergence from anesthesia. CONCLUSION: The NeuroSENSE monitor can reliably discriminate between consciousness and unconsciousness, as assessed by the anesthesiologist, during induction of anesthesia and with a lower level of reliability during emergence from anesthesia. The WAVCNS correlates with desflurane concentration but plateaus at higher concentrations, similar to other EEG monitors, which suggests limited utility to titrate higher concentrations of anesthetic vapour. TRIAL REGISTRATION: clinicaltrials.gov, NCT02088671; registered 17 March, 2014.

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.

Augmented intelligence in pediatric anesthesia and pediatric critical care.

PURPOSE OF REVIEW: Acute care technologies, including novel monitoring devices, big data, increased computing capabilities, machine-learning algorithms and automation, are converging. This enables the application of augmented intelligence for improved outcome predictions, clinical decision-making, and offers unprecedented opportunities to improve patient outcomes, reduce costs, and improve clinician workflow. This article briefly explores recent work in the areas of automation, artificial intelligence and outcome prediction models in pediatric anesthesia and pediatric critical care. RECENT FINDINGS: Recent years have yielded little published research into pediatric physiological closed loop control (a type of automation) beyond studies focused on glycemic control for type 1 diabetes. However, there has been a greater range of research in augmented decision-making, leveraging artificial intelligence and machine-learning techniques, in particular, for pediatric ICU outcome prediction. SUMMARY: Most studies focusing on artificial intelligence demonstrate good performance on prediction or classification, whether they use traditional statistical tools or novel machine-learning approaches. Yet the challenges of implementation, user acceptance, ethics and regulation cannot be underestimated. Areas in which there is easy access to routinely labeled data and robust outcomes, such as those collected through national networks and quality improvement programs, are likely to be at the forefront of the adoption of these advances.

A transformation of oxygen saturation (the saturation virtual shunt) to improve clinical prediction model calibration and interpretation.

BACKGROUND: The relationship between peripheral oxygen saturation (SpO2) and the inspired oxygen concentration is non-linear. SpO2 is frequently used as a dichotomized predictor, to manage this non-linearity. We propose the saturation virtual shunt (VS) as a transformation of SpO2 to a continuous linear variable to improve interpretation of disease severity within clinical prediction models. METHOD: We calculate the saturation VS based on an empirically derived approximation formula between physiological VS and SpO2. We evaluated the utility of the saturation VS in a clinical study predicting the need for facility admission in children in a low resource health-care setting. RESULTS: The transformation was saturation VS = 68.864 × log10(103.711 - SpO2) - 52.110. The ability to predict hospital admission based on a dichotomized SpO2 produced an area under the receiver operating characteristic curve of 0.57, compared to 0.71 based on the untransformed SpO2 and saturation VS. However, the untransformed SpO2 demonstrated a lack of fit compared to the saturation VS (goodness-of-fit test p value < 0.0001 vs 0.098). The observed admission rates varied non-linearly with the untransformed SpO2 but varied linearly with the saturation VS. CONCLUSION: The saturation VS estimates a continuous linearly interpretable disease severity based on SpO2 and improves clinical prediction.

A Systematic Review of Tools to Measure Respiratory Rate in Order to Identify Childhood Pneumonia.

Pneumonia is the leading infectious cause of death in children worldwide, with most deaths occurring in developing countries. Measuring respiratory rate is critical to the World Health Organization's guidelines for diagnosing childhood pneumonia in low-resource settings, yet it is difficult to accurately measure. We conducted a systematic review to landscape existing respiratory rate measurement technologies. We searched PubMed, Embase, and Compendex for studies published through September 2017 assessing the accuracy of respiratory rate measurement technologies in children. We identified 16 studies: 2 describing manual devices and 14 describing automated devices. Although both studies describing manual devices took place in low-resource settings, all studies describing automated devices were conducted in well-resourced settings. Direct comparison between studies was complicated by small sample size, absence of a consistent reference standard, and variations in comparison methodology. There is an urgent need for affordable and appropriate innovations that can reliably measure a child's respiratory rate in low-resource settings. Accelerating development or scale-up of these technologies could have the potential to advance childhood pneumonia diagnosis worldwide.