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\"Scurvy, a disease often associated with long stretches of maritime travel, generated sensations exceeding the standard of what was normal. Eyes dazzled, skin was morbidly sensitive, emotions veered between disgust and delight. In this book, Jonathan Lamb presents an intellectual history of scurvy unlike any other, probing the speechless encounter with powerful sensations to tell the story of the disease that its victims couldn't because they found their illness too terrible and, in some cases, too exciting. Drawing on historical accounts from scientists and voyagers as well as major literary works, Lamb traces the cultural impact of scurvy during the eighteenth-century age of geographical and scientific discovery. He explains the medical knowledge surrounding scurvy and the debates about its cause, prevention, and attempted cures. He vividly describes the phenomenon and experience of \"scorbutic nostalgia,\" in which victims imagined mirages of food, water, or home, and then wept when such pleasures proved impossible to consume or reach. Lamb argues that a culture of scurvy arose in the colony of Australia, which was prey to the disease in its early years, and identifies a literature of scurvy in the works of such figures as Herman Melville, Samuel Taylor Coleridge, Francis Bacon, and Jonathan Swift.\" -- Publisher description.

Delirium is a postoperative complication that occurs frequently in patients older than 65 years, and presages adverse outcomes. We investigated whether prophylactic low-dose dexmedetomidine, a highly selective α2 adrenoceptor agonist, could safely decrease the incidence of delirium in elderly patients after non-cardiac surgery. We did this randomised, double-blind, placebo-controlled trial in two tertiary-care hospitals in Beijing, China. We enrolled patients aged 65 years or older, who were admitted to intensive care units after non-cardiac surgery, with informed consent. We used a computer-generated randomisation sequence (in a 1:1 ratio) to randomly assign patients to receive either intravenous dexmedetomidine (0·1 μg/kg per h, from intensive care unit admission on the day of surgery until 0800 h on postoperative day 1), or placebo (intravenous normal saline). Participants, care providers, and investigators were all masked to group assignment. The primary endpoint was the incidence of delirium, assessed twice daily with the Confusion Assessment Method for intensive care units during the first 7 postoperative days. Analyses were done by intention-to-treat and safety populations. This study is registered with Chinese Clinical Trial Registry, www.chictr.org.cn, number ChiCTR-TRC-10000802. Between Aug 17, 2011, and Nov 20, 2013, of 2016 patients assessed, 700 were randomly assigned to receive either placebo (n=350) or dexmedetomidine (n=350). The incidence of postoperative delirium was significantly lower in the dexmedetomidine group (32 [9%] of 350 patients) than in the placebo group (79 [23%] of 350 patients; odds ratio [OR] 0·35, 95% CI 0·22–0·54; p<0·0001). Regarding safety, the incidence of hypertension was higher with placebo (62 [18%] of 350 patients) than with dexmedetomidine (34 [10%] of 350 patients; 0·50, 0·32–0·78; p=0·002). Tachycardia was also higher in patients given placebo (48 [14%] of 350 patients) than in patients given dexmedetomidine (23 [7%] of 350 patients; 0·44, 0·26–0·75; p=0·002). Occurrence of hypotension and bradycardia did not differ between groups. For patients aged over 65 years who are admitted to the intensive care unit after non-cardiac surgery, prophylactic low-dose dexmedetomidine significantly decreases the occurrence of delirium during the first 7 days after surgery. The therapy is safe. Braun Anaesthesia Scientific Research Fund and Wu Jieping Medical Foundation, Beijing, China. Study drugs were manufactured and supplied by Jiangsu Hengrui Medicine Co, Ltd, Jiangsu, China.

Background Delirium occurs commonly in older adults and is associated with adverse outcomes. Multicentre clinical trials evaluating interventions to prevent delirium are needed. The Confusion Assessment Method (CAM) is a validated instrument for delirium detection. We hypothesised it would be possible for a large feasibility study to train a large number of research assistants, with varying experience levels, to conduct CAM assessments reliably in multiple hospital sites. Methods A standardised training programme was followed, incorporating structured training at a central location and at study sites. CAM practice sessions on both delirious and non-delirious patients by research assistants were conducted and, thereafter, there was ongoing inter-rater reliability assessment on the CAM between research assistant pairs at study sites. The setting was eight acute care hospitals in England and Wales. Participants were research assistants working on a multicentre feasibility study of delirium prevention. The measurement used was the Confusion Assessment Method. Results Thirty-seven research assistants were trained in CAM assessment and 33 returned training logs. The logs showed there was 100% overall agreement between research assistant pairs on 295 CAM assessments, of which 263 (89.2%) were negative for delirium and 32 (10.8%) were positive. In the course of the feasibility study, research assistants successfully completed 5065 (89.7%) of the 5645 expected CAM assessments, with minimal missing data. Conclusion Using the training methods described in this study, it is possible to achieve high quality delirium assessments for large numbers of patients with little missing data across geographically dispersed sites in multicentre studies. The standardisation of multisite delirium assessments is an important contribution to research methodology, and provides a much-needed advance for the field. Trial registration ISRCT ISRCTN01187372 . Registered 13 March 2014.

Background Delirium affects > 15% of hospitalised patients but is grossly underdetected, contributing to poor care. The 4 ‘A’s Test (4AT, www.the4AT.com ) is a short delirium assessment tool designed for routine use without special training. The primary objective was to assess the accuracy of the 4AT for delirium detection. The secondary objective was to compare the 4AT with another commonly used delirium assessment tool, the Confusion Assessment Method (CAM). Methods This was a prospective diagnostic test accuracy study set in emergency departments or acute medical wards involving acute medical patients aged ≥ 70. All those without acutely life-threatening illness or coma were eligible. Patients underwent (1) reference standard delirium assessment based on DSM-IV criteria and (2) were randomised to either the index test (4AT, scores 0–12; prespecified score of > 3 considered positive) or the comparator (CAM; scored positive or negative), in a random order, using computer-generated pseudo-random numbers, stratified by study site, with block allocation. Reference standard and 4AT or CAM assessments were performed by pairs of independent raters blinded to the results of the other assessment. Results Eight hundred forty-three individuals were randomised: 21 withdrew, 3 lost contact, 32 indeterminate diagnosis, 2 missing outcome, and 785 were included in the analysis. Mean age was 81.4 (SD 6.4) years. 12.1% (95/785) had delirium by reference standard assessment, 14.3% (56/392) by 4AT, and 4.7% (18/384) by CAM. The 4AT had an area under the receiver operating characteristic curve of 0.90 (95% CI 0.84–0.96). The 4AT had a sensitivity of 76% (95% CI 61–87%) and a specificity of 94% (95% CI 92–97%). The CAM had a sensitivity of 40% (95% CI 26–57%) and a specificity of 100% (95% CI 98–100%). Conclusions The 4AT is a short, pragmatic tool which can help improving detection rates of delirium in routine clinical care. Trial registration International standard randomised controlled trial number (ISRCTN) 53388093 . Date applied 30/05/2014; date assigned 02/06/2014.

The primary objective was to evaluate agreement between researchers' and family members' postoperative delirium assessment. The secondary objective was to assess the incidence of positive FAM-CAM after hospital discharge up to 30-days postoperatively. This was a pre-specified sub-study of two multicenter randomized controlled trials that evaluated interventions to prevent postoperative delirium in older adults undergoing major elective surgery. In the hospital, delirium was ascertained using the Confusion Assessment Method (CAM) long-form or the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU), and structured chart review. Family members completed a Family Confusion Assessment Method (FAM-CAM) concurrent with researchers' assessments in the afternoons on postoperative days 1–3. At the time of hospital discharge, a booklet of FAM-CAM surveys was provided to complete daily until postoperative day 30. Agreement between researcher-rated CAM/CAM-ICU and family-rated FAM-CAM was analyzed using Generalized Linear Mixed Model with repeated measures, and Bland-Altman analysis. Inter-rater reliability for each instrument was modeled using intraclass correlation coefficient (ICC). Overall agreement beyond chance between researcher's assessment and the FAM-CAM was evaluated using repeated measure Cohen's Kappa and sensitivity, specificity, and positive and negative predicted values. Post-discharge FAM-CAM data were summarized descriptively. A total of 817 patients had 1349 concurrent delirium assessments. Postoperative delirium incidence by researchers' assessment was 18.8 % and detection of delirium symptoms by FAM-CAM was 22.4 %. Analysis comparing delirium assessments showed there is an observed agreement beyond chance of 79.7 % with a kappa of 0.33 between the assessments by Generalized Linear Mixed Modeling with repeated measures, treating patients and raters as random effects, with FAM-CAM being more likely to report a positive delirium outcome. Assessment by features showed similar results. Both methods had an excellent degree of internal validity (CAM/CAM-ICU intraclass correlation =0.938, FAM-CAM intraclass correlation = 0.985). Repeated measures Cohen's kappa indicated good overall agreement (kappa = 0.72 [95 % confidence interval, 0.63 to 0.81]). Of the 330 booklets, 133 (40.3 %) were returned. A total of 18 patients exhibited symptoms indicative of delirium based on the FAM-CAM assessment between hospital discharge and 30 days postoperatively. Out of these, 9 (50 %) had also been diagnosed with postoperative delirium during their hospitalization. This study demonstrated that family member completed FAM-CAM had acceptable agreement with researchers' delirium assessments. Postoperative delirium symptoms were detected more frequently by family-administered FAM-CAM compared to delirium incidence identified by researcher assessments. Family members identified that some patients experienced delirium symptoms after hospital discharge. •The FAM-CAM is a useful tool to detect delirium symptoms postoperatively in the hospital and after hospital discharge.•Some surgical patients may show delirium symptoms after discharge, despite no delirium identified during hospitalization.•Family members can help detect delirium symptoms after hospital discharge when other methods are less practical.

For a student, classes are vital factors for gaining knowledge. The lectures may be online or offline, but getting knowledge without confusion is a major issue. Confusion of students can be rectified after knowing that students are suffering from confusion and the confusion labels can be measured from the electroencephalography signals of the students. Machine learning approaches were implemented on electroencephalography signals to identify the suffering of students from confusion. The performance of traditionalmachine learning approaches in predicting confusion status is found as poor. The one-dimensional convolution neural network is implemented on the electroencephalography signals of students, when they were watching video classes, to detect confusion inthe students. Students’ attention, mediation, electroencephalography signals frequency, delta, theta, alpha1, alpha2, beta1, beta2, gamma1 and gamma2 are generated from electroencephalography signals and are taken into consideration to training one-dimensional convolution neural network classifier and have achieved a better accuracy in detecting the confusion of the students. Besides finding confusion label of students, when understandable classes are creating confusion and difficult classes is understandable by students are identified from electroencephalography signals. This identification can help for improving students’ deficiencies by examining and treating. For future work, more data and different aspects of the students can be taken into consideration for detecting confusion and different obstacles to having perfect knowledge from the classes.

Evaluating binary classifications is a pivotal task in statistics and machine learning, because it can influence decisions in multiple areas, including for example prognosis or therapies of patients in critical conditions. The scientific community has not agreed on a general-purpose statistical indicator for evaluating two-class confusion matrices (having true positives, true negatives, false positives, and false negatives) yet, even if advantages of the Matthews correlation coefficient (MCC) over accuracy and F 1 score have already been shown.In this manuscript, we reaffirm that MCC is a robust metric that summarizes the classifier performance in a single value, if positive and negative cases are of equal importance. We compare MCC to other metrics which value positive and negative cases equally: balanced accuracy (BA), bookmaker informedness (BM), and markedness (MK). We explain the mathematical relationships between MCC and these indicators, then show some use cases and a bioinformatics scenario where these metrics disagree and where MCC generates a more informative response.Additionally, we describe three exceptions where BM can be more appropriate: analyzing classifications where dataset prevalence is unrepresentative, comparing classifiers on different datasets, and assessing the random guessing level of a classifier. Except in these cases, we believe that MCC is the most informative among the single metrics discussed, and suggest it as standard measure for scientists of all fields. A Matthews correlation coefficient close to +1, in fact, means having high values for all the other confusion matrix metrics. The same cannot be said for balanced accuracy, markedness, bookmaker informedness, accuracy and F 1 score.

Objective To implement delirium monitoring, test reliability, and monitor compliance of performing the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) in trauma patients. Design and setting Prospective, observational study in a level 1 trauma unit of a tertiary care, university-based medical center. Patients Acutely injured patients admitted to the trauma unit between 1 February 2006 and 16 April 2006. Measurements and results Following web-based teaching modules and group in-services, bedside nurses evaluated patients daily for depth of sedation with the Richmond Agitation-Sedation Scale (RASS) and for the presence of delirium with the CAM-ICU. On randomly assigned days over a 10-week period, evaluations by nursing staff were followed by evaluations by an expert evaluator of the RASS and the CAM-ICU to assess compliance and reliability of the CAM-ICU in trauma patients. Following the audit period the nurses completed a postimplementation survey. The expert evaluator performed 1,011 random CAM-ICU assessments within 1 h of the bedside nurse's assessments. Nurses completed the CAM-ICU assessments in 84% of evaluations. Overall agreement (κ) between nurses and expert evaluator was 0.77 (0.721–0.822; p  < 0.0001), in TBI patients 0.75 (0.667–0.829; p  < 0.0001) and in mechanically ventilated patients 0.62 (0.534–0.704; p  < 0.0001). The survey revealed that nurses were confident in performing the CAM-ICU, realized the importance of delirium, and were satisfied with the training that they received. It also acknowledged obstacles to implementation including nursing time and failure of physicians/surgeons to address treatment approaches for delirium. Conclusions The CAM-ICU can be successfully implemented in a university-based trauma unit with high compliance and reliability. Quality improvement projects seeking to implement delirium monitoring would be wise to address potential pitfalls including time complaints and the negative impact of physician indifference regarding this form of organ dysfunction.

The present study evaluated, using a well-controlled dehydration protocol, the effects of 24 h fluid deprivation (FD) on selected mood and physiological parameters. In the present cross-over study, twenty healthy women (age 25 ( se 0·78) years) participated in two randomised sessions: FD-induced dehydration v . a fully hydrated control condition. In the FD period, the last water intake was between 18.00 and 19.00 hours and no beverages were allowed until 18.00 hours on the next day (23–24 h). Water intake was only permitted at fixed periods during the control condition. Physiological parameters in the urine, blood and saliva (osmolality) as well as mood and sensations (headache and thirst) were compared across the experimental conditions. Safety was monitored throughout the study. The FD protocol was effective as indicated by a significant reduction in urine output. No clinical abnormalities of biological parameters or vital signs were observed, although heart rate was increased by FD. Increased urine specific gravity, darker urine colour and increased thirst were early markers of dehydration. Interestingly, dehydration also induced a significant increase in saliva osmolality at the end of the 24 h FD period but plasma osmolality remained unchanged. The significant effects of FD on mood included decreased alertness and increased sleepiness, fatigue and confusion. The most consistent effects of mild dehydration on mood are on sleep/wake parameters. Urine specific gravity appears to be the best physiological measure of hydration status in subjects with a normal level of activity; saliva osmolality is another reliable and non-invasive method for assessing hydration status.

Background Health and social care provision for an ageing population is a global priority. Provision for those with dementia and hip fracture has specific and growing importance. Older people who break their hip are recognised as exceptionally vulnerable to experiencing confusion (including but not exclusively, dementia and/or delirium and/or cognitive impairment(s)) before, during or after acute admissions. Older people experiencing hip fracture and confusion risk serious complications, linked to delayed recovery and higher mortality post-operatively. Specific care pathways acknowledging the differences in patient presentation and care needs are proposed to improve clinical and process outcomes. Methods This protocol describes a multi-centre, feasibility, cluster-randomised, controlled trial (CRCT) to be undertaken across ten National Health Service hospital trusts in the UK. The trial will explore the feasibility of undertaking a CRCT comparing the multicomponent PERFECTED enhanced recovery intervention (PERFECT-ER), which acknowledges the differences in care needs of confused older patients experiencing hip fracture, with standard care. The trial will also have an integrated process evaluation to explore how PERFECT-ER is implemented and interacts with the local context. The study will recruit 400 hip fracture patients identified as experiencing confusion and will also recruit “suitable informants” (individuals in regular contact with participants who will complete proxy measures). We will also recruit NHS professionals for the process evaluation. This mixed methods design will produce data to inform a definitive evaluation of the intervention via a large-scale pragmatic randomised controlled trial (RCT). Discussion The trial will provide a preliminary estimate of potential efficacy of PERFECT-ER versus standard care; assess service delivery variation, inform primary and secondary outcome selection, generate estimates of recruitment and retention rates, data collection difficulties, and completeness of outcome data and provide an indication of potential economic benefits. The process evaluation will enhance knowledge of implementation delivery and receipt. Trial registration ISRCTN, 99336264 . Registered on 5 September 2016.