State transition modeling of complex monitored health data

This article considers the analysis of complex monitored health data, where often one or several signals are reflecting the current health status that can be represented by a finite number of states, in addition to a set of covariates. In particular, we consider a novel application of a non-parametric state intensity regression method in order to study time-dependent effects of covariates on the state transition intensities. The method can handle baseline, time varying as well as dynamic covariates. Because of the non-parametric nature, the method can handle different data types and challenges under minimal assumptions. If the signal that is reflecting the current health status is of continuous nature, we propose the application of a weighted median and a hysteresis filter as data pre-processing steps in order to facilitate robust analysis. In intensity regression, covariates can be aggregated by a suitable functional form over a time history window. We propose to study the estimated cumulative regression parameters for different choices of the time history window in order to investigate short- and long-term effects of the given covariates. The proposed framework is discussed and applied to resuscitation data of newborns collected in Tanzania

Generalized vs Specialized activity recognition system for newborn resuscitation videos using Deep Neural Networks.

Birth asphyxia is a global problem which has resulted in a high mortality rate of newborn babies all over the globe, it is a newborn’s inability to establish breathing at birth. A notable breakthrough is the marrying of medical technology with information technology in an attempt to tackle this global health problem. An example of this is the Safer Births project which is focused on establishing technological advancement to curb newborn deaths. In the year 2013, the Safer Births project started and has till date gathered a lot of data captured during resuscitation sessions. The Haydom data used for the Safer Births project and additional data from Nepal and SUS will be used with the aim of comparing a specialized and generalized model trained on activity recognition system I3D and RGB stream excluding optical flow. With focus on only the newborn region, the reason for this is to simplify the existing model. The experiment was conducted in view of the possibility of achieving a system that can generalize or specialize with a combination of different hospital data on some specific activities of interest namely Ventilation, Suction, Stimulation. A new simplified pipeline, which is a reduction of the previous work done by the saferbirth group, showed a very poor performance when generalized

Complementary Pediatrics

Complementary Pediatrics covers complementary issues of pediatric subspecialties consisting of ophthalmologic, surgical, psychosocial and administrative issues of frequently used medications. This book volume with its 16 chapters will help get us and patients enlightened with the new developments on these subspecialties' area

Ability of early neurological assessment and continuous EEG to predict long term neurodevelopmental outcome at 5 years in infants following hypoxic-ischaemic encephalopathy

Hypoxic-ischaemic encephalopathy (HIE) symptoms evolve during the first days of life and their monitoring is critical for treatment decisions and long-term outcome predictions. This thesis aims to report the five-year outcome of a HIE cohort born in the pre-therapeutic hypothermia era and to evaluate the predictive value of (a) neonatal neurological and EEG markers and (b) development in the first 24 months, for outcome. Methods: Participants were recruited at age five from two birth cohorts; HIE and Comparison. Repeated neonatal neurological assessments using the Amiel-TisonNeurological-Assessment-at-Term, continuous video EEG monitoring in the first 72 hours, and Sarnat grading at 24 hours were recorded. EEG severity grades were assigned at 6, 12 and 24 hours. Development was assessed in the HIE cohort at 6, 12 and 24 months using the Griffiths Mental Development (0-2) Revised Scales. At age five, intellectual (WPPSI-IIIUK scale), neuropsychological (NEPSY-II scales), neurological and ophthalmic testing was completed. Results: 5-year outcomes were available for 81.5% (n=53) of HIE and 71.4% (n=30) of Comparison cohorts. In HIE, 47.2% (27% mild, 47% moderate, 83% severe Sarnat), had non-intact outcome vs. 3.3% of the Comparison cohort. Non-intact outcome rates by 6-hour EEG-grade were: grade0=3%, grade1=25%, grade2=54%, grade3/4=79%. In HIE, processing speed (p=0.01) and verbal short-term memory (p=0.005) were below test norms. No significant differences were found in IQ, NEPSY-II or ocular biometry scores between children following mild and moderate HIE. Median IQ scores for mild (99(94-112),p=grade 2) at 24hours had superior positive predictive value (74%; AUROC(95%CI)=0.70(0.55-0.85) for non-intact 5-year outcome than abnormal EEG at 6 hours (68%; AUROC(95%CI)=0.71(0.56-0.87). Within-child development scores were inconsistent across the first 24 months. Although all children with intact 24-month Griffiths quotient (n=30) had intact 5-year IQ, 8/30 had non-intact overall outcome. Conclusion: Predictive value of neonatal neurological assessments and an EEG grading system for outcome was confirmed. Intact early childhood outcomes post-HIE may mask subtle adverse neuropsychological sequelae into the school years. This thesis supports emerging evidence that mild-grade HIE is not a benign condition and its inclusion in studies of neuroprotective treatments for HIE is warranted

Automatic classification of resuscitation activities on birth-asphyxiated newborns using acceleration and ECG signals

Objectives Newborn deaths are reported to be caused mainly by birth asphyxia. Information learned from ventilation and other treatment could help increase survival rate of newborns in need of resuscitation. Characteristics of manual bag-mask ventilation have been studied in our previous works. However, other resuscitation activities could have important impacts as well. This paper illustrates the classification of several predefined resuscitation activities using information from acceleration and ECG signal. Methods Time and frequency domain features were extracted from the acceleration and ECG signals. A 2-stage classifier was trained on data of manually annotated activities by observing videos of 30 resuscitation babies. Leave-one-out cross validation was used: for each fold, the classifier was trained on activities of 29 patients and tested on activities of 1 patient. Results The average accuracy of the classification of activities is 79%. Conclusions The performance of the classification algorithms indicates that it is possible to use ECG and acceleration signals to automatically derive useful information regarding resuscitation activities

P14.02 An electronic behaviour diary: Monitoring the effects of advanced obstetric surgical skills training

Objective: Training should lead to improvements in the quality of clinical care delivery. It is essential to follow up participants after a training intervention to monitor changes in behaviour associated with adoption of lessons learned into clinical practice. We introduced an electronic diary to facilitate monitoring whilst minimising effort for participants. Method: An electronic diary was created using a freely available on-line platform. Following a training intervention on advanced obstetric surgical skills, obstetric residents from Kenya were invited to pilot completing the diary after their labour ward shifts. Entries were anonymised. Participants were asked to enumerate the times they utilised specific skills, or to state why they had been unable to do so, using tick box options. Reflections on skills used were entered using free comments. Results: All participants reported changed behaviours, for example, improved surgical knot-tying, safer needle handling, separate closure of uterine incision angles and techniques for delivery of the impacted fetal head. 6 reported conducting vaginal breech birth and 6 performed vacuum-assisted birth. All reported improvements in use of the safe surgical checklist, obtaining consent and respectful maternity care. 7 had participated in newborn resuscitation. Reflections suggested participants experienced improved levels of confidence and satisfaction when implementing new skills. Conclusion: This pilot study has demonstrated the feasibility of monitoring clinical behaviour change following training using an electronic platform. Monitoring the effect of training is essential to prove that training results in improvements to clinical practice. We plan to roll out this intervention following future training interventions