Pressure to Perform: Is Cardiac Output Estimation from Arterial Waveforms Good Enough for Routine Use?

journal articleBiomedical Informatic

Are existing biodiversity conservation strategies appropriate in a changing climate?

Many countries have conservation plans for threatened species, but such plans have generally been developed without taking into account the potential impacts of climate change. Here, we apply a decision framework, specifically developed to identify and prioritise climate change adaptation actions and demonstrate its use for 30 species threatened in the UK. Our aim is to assess whether government conservation recommendations remain appropriate under a changing climate. The species, associated with three different habitats (lowland heath, broadleaved woodland and calcareous grassland), were selected from a range of taxonomic groups (primarily moths and vascular plants, but also including bees, bryophytes, carabid beetles and spiders). We compare the actions identified for these threatened species by the decision framework with those included in existing conservation plans, as developed by the UK Government's statutory adviser on nature conservation. We find that many existing conservation recommendations are also identified by the decision framework. However, there are large differences in the spatial prioritisation of actions when explicitly considering projected climate change impacts. This includes recommendations for actions to be carried out in areas where species do not currently occur, in order to allow them to track movement of suitable conditions for their survival. Uncertainties in climate change projections are not a reason to ignore them. Our results suggest that existing conservation plans, which do not take into account potential changes in suitable climatic conditions for species, may fail to maximise species persistence. Comparisons across species also suggest a more habitat-focused approach could be adopted to enable climate change adaptation for multiple species

High frequency oscillatory ventilation compared with conventional mechanical ventilation in adult respiratory distress syndrome: a randomized controlled trial [ISRCTN24242669]

INTRODUCTION: To compare the safety and efficacy of high frequency oscillatory ventilation (HFOV) with conventional mechanical ventilation (CV) for early intervention in adult respiratory distress syndrome (ARDS), a multi-centre randomized trial in four intensive care units was conducted. METHODS: Patients with ARDS were randomized to receive either HFOV or CV. In both treatment arms a priority was given to maintain lung volume while minimizing peak pressures. CV ventilation strategy was aimed at reducing tidal volumes. In the HFOV group, an open lung strategy was used. Respiratory and circulatory parameters were recorded and clinical outcome was determined at 30 days of follow up. RESULTS: The study was prematurely stopped. Thirty-seven patients received HFOV and 24 patients CV (average APACHE II score 21 and 20, oxygenation index 25 and 18 and duration of mechanical ventilation prior to randomization 2.1 and 1.5 days, respectively). There were no statistically significant differences in survival without supplemental oxygen or on ventilator, mortality, therapy failure, or crossover. Adjustment by a priori defined baseline characteristics showed an odds ratio of 0.80 (95% CI 0.22–2.97) for survival without oxygen or on ventilator, and an odds ratio for mortality of 1.15 (95% CI 0.43–3.10) for HFOV compared with CV. The response of the oxygenation index (OI) to treatment did not differentiate between survival and death. In the HFOV group the OI response was significantly higher than in the CV group between the first and the second day. A post hoc analysis suggested that there was a relatively better treatment effect of HFOV compared with CV in patients with a higher baseline OI. CONCLUSION: No significant differences were observed, but this trial only had power to detect major differences in survival without oxygen or on ventilator. In patients with ARDS and higher baseline OI, however, there might be a treatment benefit of HFOV over CV. More research is needed to establish the efficacy of HFOV in the treatment of ARDS. We suggest that future studies are designed to allow for informative analysis in patients with higher OI

Extraction of respiratory signals from the electrocardiogram and photoplethysmogram: technical and physiological determinants.

OBJECTIVE: Breathing rate (BR) can be estimated by extracting respiratory signals from the electrocardiogram (ECG) or photoplethysmogram (PPG). The extracted respiratory signals may be influenced by several technical and physiological factors. In this study, our aim was to determine how technical and physiological factors influence the quality of respiratory signals. APPROACH: Using a variety of techniques 15 respiratory signals were extracted from the ECG, and 11 from PPG signals collected from 57 healthy subjects. The quality of each respiratory signal was assessed by calculating its correlation with a reference oral-nasal pressure respiratory signal using Pearson's correlation coefficient. MAIN RESULTS: Relevant results informing device design and clinical application were obtained. The results informing device design were: (i) seven out of 11 respiratory signals were of higher quality when extracted from finger PPG compared to ear PPG; (ii) laboratory equipment did not provide higher quality of respiratory signals than a clinical monitor; (iii) the ECG provided higher quality respiratory signals than the PPG; (iv) during downsampling of the ECG and PPG significant reductions in quality were first observed at sampling frequencies of  <250 Hz and  <16 Hz respectively. The results informing clinical application were: (i) frequency modulation-based respiratory signals were generally of lower quality in elderly subjects compared to young subjects; (ii) the qualities of 23 out of 26 respiratory signals were reduced at elevated BRs; (iii) there were no differences associated with gender. SIGNIFICANCE: Recommendations based on the results are provided regarding device designs for BR estimation, and clinical applications. The dataset and code used in this study are publicly available

An impedance pneumography signal quality index: Design, assessment and application to respiratory rate monitoring.

Impedance pneumography (ImP) is widely used for respiratory rate (RR) monitoring. However, ImP-derived RRs can be imprecise. The aim of this study was to develop a signal quality index (SQI) for the ImP signal, and couple it with a RR algorithm, to improve RR monitoring. An SQI was designed which identifies candidate breaths and assesses signal quality using: the variation in detected breath durations, how well peaks and troughs are defined, and the similarity of breath morphologies. The SQI categorises 32 s signal segments as either high or low quality. Its performance was evaluated using two critical care datasets. RRs were estimated from high-quality segments using a RR algorithm, and compared with reference RRs derived from manual annotations. The SQI had a sensitivity of 77.7 %, and specificity of 82.3 %. RRs estimated from segments classified as high quality were accurate and precise, with mean absolute errors of 0.21 and 0.40 breaths per minute (bpm) on the two datasets. Clinical monitor RRs were significantly less precise. The SQI classified 34.9 % of real-world data as high quality. In conclusion, the proposed SQI accurately identifies high-quality segments, and RRs estimated from those segments are precise enough for clinical decision making. This SQI may improve RR monitoring in critical care. Further work should assess it with wearable sensor data.This work was supported by a UK Engineering and Physical Sciences Research Council (EPSRC) Impact Acceleration Award awarded to PHC; the EPSRC [EP/H019944/1]; the Wellcome EPSRC Centre for Medical Engineering at King’s College London [WT 203148/Z/16/Z]; the Oxford and King’s College London Centres of Excellence in Medical Engineering funded by the Wellcome Trust and EPSRC under grants [WT88877/Z/09/Z] and [WT088641/Z/09/Z]; the National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy’s & St Thomas’ NHS Foundation Trust and King’s College London; the NIHR Oxford Biomedical Research Centre Programme; a Royal Academy of Engineering Research Fellowship (RAEng) awarded to DAC; and EPSRC grants EP/P009824/1 and EP/N020774/1 to DAC

Case report: Severe mercuric sulphate poisoning treated with 2,3-dimercaptopropane-1-sulphonate and haemodiafiltration

INTRODUCTION: Inorganic mercury poisoning is uncommon, but when it occurs it can result in severe, life-threatening features and acute renal failure. Previous reports on the use of extracorporeal procedures such as haemodialysis and haemoperfusion have shown no significant removal of mercury. We report here the successful use of the chelating agent 2,3-dimercaptopropane-1-sulphonate (DMPS), together with continuous veno-venous haemodiafiltration (CVVHDF), in a patient with severe inorganic mercury poisoning. CASE REPORT: A 40-year-old man presented with haematemesis after ingestion of 1 g mercuric sulphate and rapidly deteriorated in the emergency department, requiring intubation and ventilation. His initial blood mercury was 15 580 μg/l. At 4.5 hours after ingestion he was started on DMPS. He rapidly developed acute renal failure and so he was started on CVVHDF for renal support and in an attempt to improve mercury clearance; CVVHDF was continued for 14 days. METHODS: Regular ultradialysate and pre- and post-filtrate blood samples were taken and in addition all ultradialysate generated was collected to determine its mercury content. RESULTS: The total amount of mercury in the ultrafiltrate was 127 mg (12.7% of the ingested dose). The sieving coefficient ranged from 0.13 at 30-hours to 0.02 at 210-hours after ingestion. He developed no neurological features and was discharged from hospital on day 50. Five months after discharge from hospital he remained asymptomatic, with normal creatinine clearance. DISCUSSION: We describe a patient with severe inorganic mercury poisoning in whom full recovery occurred with the early use of the chelating agent DMPS and CVVHDF. There was removal of a significant amount of mercury by CVVHDF. CONCLUSION: We feel that CVVHDF should be considered in patients with inorganic mercury poisoning, particularly those who develop acute renal failure, together with meticulous supportive care and adequate doses of chelation therapy with DMPS

Predicting Clinical Deteriorations using Wearable Sensors

Introduction Acutely-ill hospitalised patients are at risk of clinical deteriorations such as cardiac arrest, admission to intensive care, or unexpected death. Currently, patients are manually assessed every 4-6 hours to determine the likelihood of subsequent deterioration. However, this is limited to intermittent assessments, delaying time-sensitive interventions. Wearable sensors, combined with an alerting system, could provide continuous automated assessments of the likelihood of deteriorations. To be suitable for hospital use, wearable sensors must be unobtrusive and provide reliable measurements of key vital signs including breathing rate (BR), a key predictor of deteriorations. The aims of this work were: (i) to develop a technique for monitoring BR unobtrusively using wearable sensors, and (ii) to assess whether wearable sensors provide reliable predictions of deteriorations when using this technique. Monitoring breathing rate (BR) unobtrusively Current methods for monitoring BR using wearable sensors are obtrusive. An alternative approach is to estimate BR from electrocardiogram or pulse oximeter signals, which are already acquired by wearable sensors to monitor heart rate and blood oxygen levels. Both signals are subtly modulated by breathing, providing opportunity to use them to monitor BR. I assessed the performance of previously proposed signal processing techniques for estimating BR from these signals in both healthy and hospitalised subjects. Although some techniques were precise enough for use with healthy subjects in the laboratory, they were imprecise when used with hospital patients. Therefore, I developed a novel technique, combining the strengths of time- and frequency-domain techniques. Its performance was assessed on data from 264 subjects. In hospital patients, the technique provided highly precise BRs 86% of the time, which exceeds the performance of manual observation, the current clinical standard. Assessing the reliability of wearable sensors for predicting deteriorations I implemented methods for rejecting unreliable sensor data, and for fusing continuous multiparametric data, to predict deteriorations. These were used alongside the novel technique for monitoring BR to predict deteriorations using wearable sensors. The system was assessed in a clinical trial of 184 hospital patients, conducted in collaboration with clinicians. The reliability of the system was assessed by comparing its predictions against documented deteriorations. Its predictive value was similar to that of the routine manual assessments (AUROCs of 0.78 vs 0.79). Crucially it provided continuous assessment, potentially providing predictions of deteriorations hours earlier than routine practice. Conclusion This work has demonstrated the potential for wearable sensors to reliably and unobtrusively predict deteriorations, when coupled with a novel technique for monitoring BR. This could improve patient outcomes, and reduce costs. Further work should investigate which patients would benefit most from this technology, and whether it could reduce clinical workload. In the future the technology could potentially be used with consumer wearables to improve patient safety in the community, where clinical expertise is less readily available.This poster was displayed at the STEM for Britain event, held in the Houses of Parliament (London, UK) on 12th March 2018

Respiratory rate monitoring to detect deteriorations using wearable sensors

This poster provides an overview of the work described in: P. H. Charlton, "Continuous respiratory rate monitoring to detect clinical deteriorations using wearable sensors," Ph.D. Thesis, King’s College London, 2017.This poster was first presented at the Bioengenuity Keynotes Conference, held on Monday 6th March at the University of Oxford