Browsing by Author "Ansermino, J. Mark"
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Item Automated Validation of Capillary Refill Time Measurements Using Photo-plethysmogram from a Portable Device for Effective Triage in Children(Global Humanitarian Technology Conference, 2011) Karlen, Walter; Pickard, Amelia; Daniels, Jeremy; Kwizera, Arthur; Ibingira, Charles; Dumont, Guy; Ansermino, J. MarkCapillary refill time (CRT) is an important tool for the clinical assessment of trauma and dehydration. Indeed, it has been incorporated into advanced life support guidelines as part of the rapid assessment of critically ill patients. However, digitalized CRT techniques are not readily available and the standard assessment based on the visual inspection of CRT lacks standardization and is prone to a high inter-observer variability. We present an algorithm for the automatic validation of the CRT measurement on the finger using photo-plethysmogram recordings on a small portable device. It is based on a set of deterministic rules for the classification of finger pressure and regular plethysmographic pulses. Validation studies using the classification of 93 pediatric recordings from Canada and Uganda showed that the novel algorithm reliably detects invalid CRT measurements (sensitivity 98.4%). This includes patterns such as insufficient pressure, low perfusion signals, and artifacts. Since our device consists of widely available components already in use, the promising results suggest that the algorithm could be readily integrated in operating rooms and intensive care units around the world. This more robust assessment of CRT would produce a more powerful diagnostic tool for clinical triage in critical care settings.Item Prediction models for post-discharge mortality among under-five children with suspected sepsis in Uganda: A multicohort analysis(Public Library of Science, 2024-05) Wiens, Matthew O; Nguyen, Vuong; Bone, Jeffrey N.; Kumbakumba, Elias; Businge, Stephen; Tagoola, Abner; Sherine, Sheila Oyella; Byaruhanga, Emmanuel; Ssemwanga, Edward; Barigye, Celestine; Nsungwa, Jesca; Olaro, Charles; Ansermino, J. Mark; Kissoon, Niranjan; Singer, Joel; Larson, Charles P.; Lavoie, Pascal M; Dunsmuir, Dustin; Moschovis, Peter P.; Novakowski, Stefanie; Komugisha, Clare; Tayebwa, Mellon; Mwesigwa, Douglas; Knappett, Martina; West, Nicholas; Mugisha, Nathan Kenya; Kabakyenga, JeromeIn 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.Item A Risk Prediction Model for the Assessment and Triage of Women with Hypertensive Disorders of Pregnancy in Low-Resourced Settings: The miniPIERS (Pre-eclampsia Integrated Estimate of RiSk) Multi-country Prospective Cohort Study(PLOS Medicine, 2014-01) Payne, Beth A.; Hutcheon, Jennifer A.; Ansermino, J. Mark; Hall, David R.; Bhutta, Zulfiqar A.; Bhutta, Shereen Z.; Biryabarema, Christine; Grobman, William A.; Groen, Henk; Haniff{, Farizah; Li, Jing; Magee, Laura A.; Merialdi, Mario; Nakimuli, Annettee; Qu, Ziguang; Sikandar, Rozina; Sass, Nelson; Sawchuck, Diane; Steyn, D. Wilhelm; Widmer, Mariana; Zhou, Jian; Dadelszen, Peter vonBackground: Pre-eclampsia/eclampsia are leading causes of maternal mortality and morbidity, particularly in low- and middle- income countries (LMICs). We developed the miniPIERS risk prediction model to provide a simple, evidence-based tool to identify pregnant women in LMICs at increased risk of death or major hypertensive-related complications. Methods and Findings: From 1 July 2008 to 31 March 2012, in five LMICs, data were collected prospectively on 2,081 women with any hypertensive disorder of pregnancy admitted to a participating centre. Candidate predictors collected within 24 hours of admission were entered into a step-wise backward elimination logistic regression model to predict a composite adverse maternal outcome within 48 hours of admission. Model internal validation was accomplished by bootstrapping and external validation was completed using data from 1,300 women in the Pre-eclampsia Integrated Estimate of RiSk (fullPIERS) dataset. Predictive performance was assessed for calibration, discrimination, and stratification capacity. The final miniPIERS model included: parity (nulliparous versus multiparous); gestational age on admission; headache/visual disturbances; chest pain/dyspnoea; vaginal bleeding with abdominal pain; systolic blood pressure; and dipstick proteinuria. The miniPIERS model was well-calibrated and had an area under the receiver operating characteristic curve (AUC ROC) of 0.768 (95% CI 0.735–0.801) with an average optimism of 0.037. External validation AUC ROC was 0.713 (95% CI 0.658–0.768). A predicted probability $25% to define a positive test classified women with 85.5% accuracy. Limitations of this study include the composite outcome and the broad inclusion criteria of any hypertensive disorder of pregnancy. This broad approach was used to optimize model generalizability. Conclusions: The miniPIERS model shows reasonable ability to identify women at increased risk of adverse maternal outcomes associated with the hypertensive disorders of pregnancy. It could be used in LMICs to identify women who would benefit most from interventions such as magnesium sulphate, antihypertensives, or transportation to a higher level of care.Item Scheduled Follow-Up Referrals and Simple Prevention Kits Including Counseling to Improve Post-Discharge Outcomes Among Children in Uganda: A Proof-of-Concept Study(Global Health: Science and Practice, 2016) Wiens, Matthew O.; Kumbakumba, Elias; Larson, Charles P.; Moschovis, Peter P.; Barigye, Celestine; Kabakyenga, Jerome; Ndamira, Andrew; Kissoon, Niranjan; Ansermino, J. MarkRecurrent illness following hospital discharge is a major contributor to childhood mortality in resource-poor countries. Yet post-discharge care is largely ignored by health care workers and policy makers due to a lack of resources to identify children with recurrent illness and a lack of cohesive systems to provide care. The purpose of this proof-of-concept study was to evaluate the effectiveness of a bundle of interventions at discharge to improve health outcomes during the vulnerable post-discharge period. The study was conducted between December 2014 and April 2015. Eligible children were between ages 6 months and 5 years who were admitted with a suspected or proven infectious disease to one of two hospitals in Mbarara, Uganda. A bundle of interventions was provided at the time of discharge. This bundle included post-discharge referrals for follow-up visits and a discharge kit. The post-discharge referral was to ensure follow-up with a nearby health care provider on days 2, 7, and 14 following discharge. The discharge kit included brief educational counseling along with simple preventive items as incentives (soap, a mosquito net, and oral rehydration salts) to reinforce the education. The primary study outcome was the number of post-discharge referral visits completed. Secondary study outcomes included satisfaction with the intervention, rates of readmission after 60 days, and post-discharge mortality rates. In addition, outcomes were compared with a historical control group, enrolled using the same inclusion criteria and outcome-ascertainment methods. During the study, 216 children were admitted, of whom 14 died during hospitalization. Of the 202 children discharged, 85% completed at least 1 of the 3 follow-up referral visits, with 48% completing all 3 visits. Within 60 days after discharge, 22 children were readmitted at least once and 5 children (2.5%) died. Twelve (43%) readmissions occurred during a scheduled follow-up visit. Compared with prospectively enrolled historical controls, the post-discharge referral for follow-up increased the odds of readmission (odds ratio [OR], 1.92; 95% confidence interval [CI], 1.14 to 3.23) and care sought after discharge (OR, 14.61; 95% CI, 9.41 to 22.67). Overall satisfaction with the bundle of interventions was high, with most caregivers strongly agreeing that the discharge kit and post-discharge referrals improved their ability to care for their child. Interventions initiated at the time of discharge have the potential to profoundly affect the landscape of care during illness recovery and lead to significantly improved outcomes among children under 5 years of age.