J L Darbyshire

Three-year efficacy of complex insulin regimens in type 2 diabetes.

BACKGROUND Evidence supporting the addition of specific insulin regimens to oral therapy in patients with type 2 diabetes mellitus is limited. METHODS In this 3-year open-label, multicenter trial, we evaluated 708 patients who had suboptimal glycated hemoglobin levels while taking metformin and sulfonylurea therapy. Patients were randomly assigned to receive biphasic insulin aspart twice daily, prandial insulin aspart three times daily, or basal insulin detemir once daily (twice if required). Sulfonylurea therapy was replaced by a second type of insulin if hyperglycemia became unacceptable during the first year of the study or subsequently if glycated hemoglobin levels were more than 6.5%. Outcome measures were glycated hemoglobin levels, the proportion of patients with a glycated hemoglobin level of 6.5% or less, the rate of hypoglycemia, and weight gain. RESULTS Median glycated hemoglobin levels were similar for patients receiving biphasic (7.1%), prandial (6.8%), and basal (6.9%) insulin-based regimens (P=0.28). However, fewer patients had a level of 6.5% or less in the biphasic group (31.9%) than in the prandial group (44.7%, P=0.006) or in the basal group (43.2%, P=0.03), with 67.7%, 73.6%, and 81.6%, respectively, taking a second type of insulin (P=0.002). [corrected] Median rates of hypoglycemia per patient per year were lowest in the basal group (1.7), higher in the biphasic group (3.0), and highest in the prandial group (5.7) (P<0.001 for the overall comparison). The mean weight gain was higher in the prandial group than in either the biphasic group or the basal group. Other adverse event rates were similar in the three groups. CONCLUSIONS Patients who added a basal or prandial insulin-based regimen to oral therapy had better glycated hemoglobin control than patients who added a biphasic insulin-based regimen. Fewer hypoglycemic episodes and less weight gain occurred in patients adding basal insulin. (Current Controlled Trials number, ISRCTN51125379.)

An investigation of sound levels on intensive care units with reference to the WHO guidelines

IntroductionPatients in intensive care units (ICUs) suffer from sleep deprivation arising from nursing interventions and ambient noise. This may exacerbate confusion and ICU-related delirium. The World Health Organization (WHO) suggests that average hospital sound levels should not exceed 35 dB with a maximum of 40 dB overnight. We monitored five ICUs to check compliance with these guidelines.MethodsSound levels were recorded in five adult ICUs in the UK. Two sound level monitors recorded concurrently for 24 hours at the ICU central stations and adjacent to patients. Sample values to determine levels generated by equipment and external noise were also recorded in an empty ICU side room.ResultsAverage sound levels always exceeded 45 dBA and for 50% of the time exceeded between 52 and 59 dBA in individual ICUs. There was diurnal variation with values decreasing after evening handovers to an overnight average minimum of 51 dBA at 4 AM. Peaks above 85 dBA occurred at all sites, up to 16 times per hour overnight and more frequently during the day. WHO guidelines on sound levels could be only achieved in a side room by switching all equipment off.ConclusionAll ICUs had sound levels greater than WHO recommendations, but the WHO recommended levels are so low they are not achievable in an ICU. Levels adjacent to patients are higher than those recorded at central stations. Unit-wide noise reduction programmes or mechanical means of isolating patients from ambient noise, such as earplugs, should be considered.

Go/no-go decision in anaesthesia: wide variation in risk tolerance amongst anaesthetists

Background. The variability in risk tolerance in medicine is not well understood. Parallels are often drawn between aviation and anaesthesia. The aviation industry is perceived as culturally risk averse, and part of preflight checks involves a decision on whether the flight can operate. This is sometimes termed a go/no‐go decision. This questionnaire study was undertaken to explore the equivalent go/no‐go decision in anaesthesia. We presented anaesthetists with a range of situations in which additional risk might be expected and asked them to decide whether they would proceed with the case. Methods. An electronic questionnaire was distributed to anaesthetic colleagues of all grades in one National Health Service Trust. Eleven scenarios, all drawn from critical incident data, were presented. Participants were invited to consider whether they would proceed, how they would modify their anaesthetic technique, and to predict whether a colleague with similar experience would make the same decision. Textual responses were analysed qualitatively. Results. The scenario response rate was 28%. Consultants were significantly more likely to proceed than trainees. In no scenario was there absolute agreement over whether to proceed, even in scenarios where national guidelines would suggest a case should be cancelled. Thematic analysis suggested a wide variability in what anaesthetists consider acceptable or professional behaviour. Conclusions. It is clear that safety decisions cannot be made in isolation and that clinicians must consider operational requirements, such as throughput, when making a go/no‐go decision. The level of variability in decision‐making was surprising, particularly for scenarios that appeared to go against guidelines.

“I Can Remember Sort of Vivid People…but to Me They Were Plasticine.” Delusions on the Intensive Care Unit: What Do Patients Think Is Going On?

Introduction Patients who develop intensive care unit (ICU) acquired delirium stay longer in the ICU, and hospital, and are at risk of long-term mental and physical health problems. Despite guidelines for patient assessment, risk limitation, and treatment in the ICU population, delirium and associated delusions remain a relatively common occurrence on the ICU. There is considerable information in the literature describing the incidence, suspected causes of, and discussion of the benefits and side-effects of the various treatments for delirium in the ICU. But peer-reviewed patient-focused research is almost non-existent. There is therefore a very limited understanding of the reality of delusions in the intensive care unit from the patient’s point of view. Method A secondary analysis of the original interviews conducted by the University of Oxford Health Experiences Research Group was undertaken to explore themes relating specifically to sleep and delirium. Results Patients describe a liminal existence on the ICU. On the threshold of consciousness their reality is uncertain and their sense of self is exposed. Lack of autonomy in an unfamiliar environment prompts patients to develop explanations and understandings for themselves with no foothold in fact. Conclusion Patients on the ICU are perhaps more disoriented than they appear and early psychological intervention in the form of repeated orientation whilst in the ICU might improve the patient experience and defend against development of side-effects.

Excessive noise in intensive care units

Bad for staff and very bad for patients

Using the experience-based co-design method to design a teaching package

What problems were addressed? The World Health Organization recommends average noise levels in patient care areas no higher than 35 dB, with peaks below 40 dB. In reality, most intensive care units (ICUs) worldwide average 55-60 dB, with peaks up to 120 dB. Staff acclimatise to this, often rationalising high noise levels as necessary because of the equipment and monitoring needs of patients. There is limited awareness that many sources of noise are modifiable, understanding of the patient experience of intensive care is low, and prior to training there is little motivation to implement change. The objective of this training was to facilitate reflection on the patient experience, with a view to enabling selfdirected change to reduce noise levels in the ICU. What was tried? Building on interviews with former ICU patients and ethnographic observations, we used the experience-based co-design method to create a training course to increase knowledge about noise in the ICU. A collaboration between patients, clinical staff, researchers and medical educationalists ensured learning objectives were relevant, practical and of high educational quality. The course combines a multimedia e-learning package and an in situ simulated patient experience that combines a binaural soundtrack of ICU noises with live-action nursing activities. The e-learning takes approximately 20 minutes to complete and individual experiences last 15 minutes, which includes post-experience debriefing. The authenticity of teaching materials is ensured by using real patient experiences and replicating behaviours observed during ethnography sessions. An online self-assessment is included because formative assessment is both motivational and guides onward learning. Assessment points were mapped to course materials using a curriculum blueprint, and participant feedback was used to refine the simulation experience. What lessons were learned? The simulation invoked feelings of worry, fear, stress, confusion and loneliness. This maps well to patient narratives and indicated our simulation had been successful despite only lasting a few minutes. Post-experience debriefing allowed participants to decompress before returning to work. The negative emotional component was intended to prompt staff reflection, as per Kolb’s learning cycle, and proved effective. All 116 participants described the experience as useful, >90% reporting they should do more to improve the environment for their patients. After the experience, 97% of staff indicated they would modify their behaviours, and this appeared to be carried into practice. Noise level monitoring confirmed a perceivable drop of ~4 dB from a baseline of 57.0 to 53.2 dB during the 4-month post-intervention period. We have been unable to incorporate this training into recurring education sessions. The in situ experience is heavily workload dependent, requiring a bed space and members of the education team to be free at an appropriate time. This requires a flexible, imaginative and highly motivated faculty member to deliver training opportunistically; it was therefore difficult to embed. We are now exploring alternative models to enable stand-alone delivery of this innovative training. We have been able to demonstrate that meaningful teaching can be delivered even in a tightly compressed time format, and that this can successfully modify behaviour. This makes this style of teaching practical in a busy unit, but maintaining momentum after the initial wave of interest remains challenging.

Acoustic source localization with microphone arrays for remote noise monitoring in an Intensive Care Unit

An approach is described to apply spatial filtering with microphone arrays to localize acoustic sources in an Intensive Care Unit (ICU). This is done to obtain more detailed information about disturbing noise sources in the ICU with the ultimate goal of facilitating the reduction of the overall background noise level, which could potentially improve the patients’ experience and reduce the time needed for recovery. This paper gives a practical description of the system, including the audio hardware setup as well as the design choices for the microphone arrays. Additionally, the necessary signal processing steps required to produce meaningful data are explained, focusing on a novel clustering approach that enables an automatic evaluation of the spatial filtering results. This approach allows the data to be presented to the nursing staff in a way that enables them to act on the results produced by the system.

Machine listening in combination with microphone arrays for noise source localization and identification

In a recent project, a large microphone array system has been created to localize and quantify noise sources in an Intensive Care Unit (ICU). In the current state, the output of the system is the location and level of the most dominant noise sources, which is also presented in real-time to the nursing staff. However, both staff as well as patients have expressed the need for information about the types of noise sources. This additional source identification can also help to find means of reducing the overall noise level in the ICU. To accomplish the source identification, the approach of machine listening with a deep neural network is chosen. A feed-forward pattern recognition network is considered in this work. However, it is not clear which types of features are best suited for the given application. This contribution thus examines the problem from a practical point of view, comparing different features including those related to sound perception, such as specific loudness, Mel-frequency cepstral coefficients, as well as the output of a gamma-tone filter bank. Additionally, the concept of time-delay networks is tested to see whether a better classification of the signals can be achieved by including their time history.In a recent project, a large microphone array system has been created to localize and quantify noise sources in an Intensive Care Unit (ICU). In the current state, the output of the system is the location and level of the most dominant noise sources, which is also presented in real-time to the nursing staff. However, both staff as well as patients have expressed the need for information about the types of noise sources. This additional source identification can also help to find means of reducing the overall noise level in the ICU. To accomplish the source identification, the approach of machine listening with a deep neural network is chosen. A feed-forward pattern recognition network is considered in this work. However, it is not clear which types of features are best suited for the given application. This contribution thus examines the problem from a practical point of view, comparing different features including those related to sound perception, such as specific loudness, Mel-frequency cepstral coeffi...

Measuring Sleep in the Intensive Care Unit: A Critical Appraisal of the Use of Subjective Methods:

Objectives: To collate and appraise the use of subjective measures to assess sleep in the intensive care unit (ICU). Design: A systematic search and critical review of the published literature. Data Sources: Medline, Scopus, and Cumulative Index to Nursing and Allied Health Literature were searched using combinations of the key words “Sleep,” “Critical Care,” “Intensive Care,” and “Sleep Disorders,” and this was complemented by hand searching the most recent systematic reviews on related topics. Study Eligibility Criteria: Papers were limited to non-gray English-language studies of the adult population, published in the last 10 years. Outcome Measures: Primary outcomes were the number and categorization of quantitative studies reporting measures of sleep, the number of participants for each data collection method, and a synthesis of related material to appraise the use of survey tools commonly used for sleep measurement in the ICU. Results: Thirty-eight papers reported quantitative empirical data collection on sleep, 17 of which used a primary method of subjective assessment of sleep by the patient or nurse. Thirteen methods of subjective sleep assessment were identified. Many of these tools lacked validity and reliability testing. Conclusions: Research using questionnaires to assess sleep is commonplace in light of practical barriers to polysomnography or other measures of sleep. A methodologically sound approach to tool development and testing is crucial to gather meaningful data, and this robust approach was lacking in many cases. Further research measuring sleep subjectively in ICU should use the Richards Campbell Sleep Questionnaire, and researchers should maintain a commitment to transparency in describing methods.