Feasibility of implementing Extubation Advisor, a clinical decision support tool to improve extubation decision-making in the ICU: a mixed-methods observational study.

OBJECTIVES: Although spontaneous breathing trials (SBTs) are standard of care to extubation readiness, no tool exists that optimises prediction and standardises assessment. In this study, we evaluated the feasibility and clinical impressions of Extubation Advisor (EA), a comprehensive clinical extubation decision support (CDS) tool. DESIGN: Phase I mixed-methods observational study. SETTING: Two Canadian intensive care units (ICUs). PARTICIPANTS: We included patients on mechanical ventilation for ≥24 hours and clinicians (respiratory therapists and intensivists) responsible for extubation decisions. INTERVENTIONS: Components included a predictive model assessment, feasibility evaluation, questionnaires and interviews with clinicians. RESULTS: We enrolled 117 patients, totalling 151 SBTs and 80 extubations. The incidence of extubation failure was 11% in low-risk patients and 21% in high-risk patients stratified by the predictive model; 38% failed extubation when both the model and clinical impression were at high risk. The tool was well rated: 94% and 75% rated the data entry and EA report as average or better, respectively. Interviews (n=15) revealed favourable impressions regarding its user interface and functionality, but unexpectedly, also concerns regarding EA's potential impact on respiratory therapists' job security. CONCLUSIONS: EA implementation was feasible, and users perceived it to have potential to support extubation decision-making. This study helps to understand bedside implementation of CDS tools in a multidisciplinary ICU. TRIAL REGISTRATION NUMBER: NCT02988167.

Best practices for enhancing surgical research: a perspective from the Canadian Association of Chairs of Surgical Research

Summary: The Canadian Association of Chairs of Surgical Research was created in 2014, with representation from every departmental surgical research committee across Canada, to establish Canadian surgical research as a beacon for health care innovation and to propose solutions for the daily challenges facing surgeon-researchers. Our key mandate has been to identify challenges for surgeons and scientists performing research to prevent further erosion of this vital area of activity that benefits patients, health care service providers and Canadian society. This article outlines the findings of a nationwide survey sent to all members of departments of surgery across Canada, seeking input on current threats and potential solutions. The results suggest that surgical research in Canada is experiencing a decline in funding and an increase in challenges affecting research productivity of academic surgeons, such as pressures to be clinically active, unpredictable surgical schedules, growing administrative demands, and increasing complexity of patient populations. Although surgeons are productive in their research endeavours, institutional changes and sharing of best practices are needed to ensure sustainable growth of research programs.

Multicentre pilot randomised clinical trial of early in-bed cycle ergometry with ventilated patients.

Introduction: Acute rehabilitation in critically ill patients can improve post-intensive care unit (post-ICU) physical function. In-bed cycling early in a patient's ICU stay is a promising intervention. The objective of this study was to determine the feasibility of recruitment, intervention delivery and retention in a multi centre randomised clinical trial (RCT) of early in-bed cycling with mechanically ventilated (MV) patients. Methods: We conducted a pilot RCT conducted in seven Canadian medical-surgical ICUs. We enrolled adults who could ambulate independently before ICU admission, within the first 4 days of invasive MV and first 7 days of ICU admission. Following informed consent, patients underwent concealed randomisation to either 30 min/day of in-bed cycling and routine physiotherapy (Cycling) or routine physiotherapy alone (Routine) for 5 days/week, until ICU discharge. Our feasibility outcome targets included: accrual of 1-2 patients/month/site; >80% cycling protocol delivery; >80% outcomes measured and >80% blinded outcome measures at hospital discharge. We report ascertainment rates for our primary outcome for the main trial (Physical Function ICU Test-scored (PFIT-s) at hospital discharge). Results: Between 3/2015 and 6/2016, we randomised 66 patients (36 Cycling, 30 Routine). Our consent rate was 84.6 % (66/78). Patient accrual was (mean (SD)) 1.1 (0.3) patients/month/site. Cycling occurred in 79.3% (146/184) of eligible sessions, with a median (IQR) session duration of 30.5 (30.0, 30.7) min. We recorded 43 (97.7%) PFIT-s scores at hospital discharge and 37 (86.0%) of these assessments were blinded. Discussion: Our pilot RCT suggests that a future multicentre RCT of early in-bed cycling for MV patients in the ICU is feasible. Trial registration number: NCT02377830.

FLUID trial: a protocol for a hospital-wide open-label cluster crossover pragmatic comparative effectiveness randomised pilot trial.

INTRODUCTION: 0.9% saline and Ringer's lactate are the two most common resuscitation crystalloid fluids. 0.9% saline may lead to hyperchloraemic metabolic acidosis and may be associated with impaired kidney function and death. Few large multicentre randomised trials have been conducted to evaluate the effect of these two fluids on clinically important outcomes. METHODS: FLUID is a pragmatic pilot cluster randomised crossover trial in which four hospitals will be randomised to normal saline or Ringer's lactate for 14 weeks, then crossover to the alternative fluid for the subsequent 14 weeks after 1 to 3 week transition. With waiver of informed consent, all adult and paediatric patients admitted to participating sites will be included in the FLUID trial except for neonates. Primary feasibility outcome is study fluid protocol adherence (target:≥80%). Secondary feasibility outcomes include time to research ethics board (REB) approval and readiness to trial initiation (≤3 months from REB submission and approval). Primary (composite of death or re-admission to hospital in first 90 days of index hospitalisation) and secondary clinical outcomes for the future large FLUID trial will be described. Protocol adherence will be collected by site at specified time points. All clinical data will be obtained at patient level through provincial health administrative data held at the Institute for Clinical Evaluative Sciences (ICES). Event rates for the primary and secondary outcomes will be described using frequencies and proportions with 95% CIs. Intracluster and interperiod correlation coefficients will be calculated from population-level data available at ICES. ETHICS AND DISSEMINATION: The study protocol has been approved by the Ottawa Health Science Research Ethics Board. The FLUID pilot will determine feasibility, and ICES data across all potential sites in Ontario will allow calculation of sample size parameter estimates to inform the design and implementation of the large trial. TRIAL REGISTRATION NUMBER: NCT02721485; Pre-results.

Heart beat classification from single-lead ECG using the synchrosqueezing transform.

The processing of ECG signal provides a wealth of information on cardiac function and overall cardiovascular health. While multi-lead ECG recordings are often necessary for a proper assessment of cardiac rhythms, they are not always available or practical, for example in fetal ECG applications. Moreover, a wide range of small non-obtrusive single-lead ECG ambulatory monitoring devices are now available, from which heart rate variability (HRV) and other health-related metrics are derived. Proper beat detection and classification of abnormal rhythms is important for reliable HRV assessment and can be challenging in single-lead ECG monitoring devices. In this manuscript, we modelled the heart rate signal as an adaptive non-harmonic model and used the newly developed synchrosqueezing transform (SST) to characterize ECG patterns. We show how the proposed model can be used to enhance heart beat detection and classification between normal and abnormal rhythms. In particular, using the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database and the Association for the Advancement of Medical Instrumentation (AAMI) beat classes, we trained and validated a support vector machine (SVM) classifier on a portion of the annotated beat database using the SST-derived instantaneous phase, the R-peak amplitudes and R-peak to R-peak interval durations, based on a single ECG lead. We obtained sentivities and positive predictive values comparable to other published algorithms using multiple leads and many more features.

Correlating multidimensional fetal heart rate variability analysis with acid-base balance at birth.

Fetal monitoring during labour currently fails to accurately detect acidemia. We developed a method to assess the multidimensional properties of fetal heart rate variability (fHRV) from trans-abdominal fetal electrocardiogram (fECG) during labour. We aimed to assess this novel bioinformatics approach for correlation between fHRV and neonatal pH or base excess (BE) at birth.We enrolled a prospective pilot cohort of uncomplicated singleton pregnancies at 38-42 weeks' gestation in Milan, Italy, and Liverpool, UK. Fetal monitoring was performed by standard cardiotocography. Simultaneously, with fECG (high sampling frequency) was recorded. To ensure clinician blinding, fECG information was not displayed. Data from the last 60 min preceding onset of second-stage labour were analyzed using clinically validated continuous individualized multiorgan variability analysis (CIMVA) software in 5 min overlapping windows. CIMVA allows simultaneous calculation of 101 fHRV measures across five fHRV signal analysis domains. We validated our mathematical prediction model internally with 80:20 cross-validation split, comparing results to cord pH and BE at birth.The cohort consisted of 60 women with neonatal pH values at birth ranging from 7.44 to 6.99 and BE from -0.3 to -18.7 mmol L(-1). Our model predicted pH from 30 fHRV measures (R(2) = 0.90, P < 0.001) and BE from 21 fHRV measures (R(2) = 0.77, P < 0.001).Novel bioinformatics approach (CIMVA) applied to fHRV derived from trans-abdominal fECG during labor correlated well with acid-base balance at birth. Further refinement and validation in larger cohorts are needed. These new measurements of fHRV might offer a new opportunity to predict fetal acid-base balance at birth.

Clinical review: a review and analysis of heart rate variability and the diagnosis and prognosis of infection.

Bacterial infection leading to organ failure is the most common cause of death in critically ill patients. Early diagnosis and expeditious treatment is a cornerstone of therapy. Evaluating the systemic host response to infection as a complex system provides novel insights: however, bedside application with clinical value remains wanting. Providing an integrative measure of an altered host response, the patterns and character of heart rate fluctuations measured over intervals-in-time may be analysed with a panel of mathematical techniques that quantify overall fluctuation, spectral composition, scale-free variation, and degree of irregularity or complexity. Using these techniques, heart rate variability (HRV) has been documented to be both altered in the presence of systemic infection, and correlated with its severity. In this review and analysis, we evaluate the use of HRV monitoring to provide early diagnosis of infection, document the prognostic implications of altered HRV in infection, identify current limitations, highlight future research challenges, and propose improvement strategies. Given existing evidence and potential for further technological advances, we believe that longitudinal, individualized, and comprehensive HRV monitoring in critically ill patients at risk for or with existing infection offers a means to harness the clinical potential of this bedside application of complex systems science.