Can all healthy adults use the current evidential breath alcohol analysers? An investigation using a large spirometry database.

People failing to give a specimen of breath at a police station are assumed to be deliberately obstructive and are charged with Failure to Provide under the Road Traffic Act 1988. However, spirometry records of 281,210 healthy individuals from UK BioBank showed that a significant minority cannot use existing evidential breath analysis machines. Women were three times more likely to be unable to use them than men (1.64% vs 0.54%) with the risk rising with age six-fold from those in their 40s (0.43%) to 2.7% in their 70s, with women more affected (0.65% to 3.8%). Short stature was a further risk factor: 2.6% of men and 3.8% of women below the 2nd percentile of height could not use the current machines, with almost one in ten elderly, short women unable to do so, while smokers aged 50+ were twice as likely as non-smokers of the same age to be unable to provide breath specimens.

Accidental hypothermia: direct evidence for consciousness as a marker of cardiac arrest risk in the acute assessment of cold patients.

BACKGROUND: Rapid stratification of the risk of cardiac arrest is essential in the assessment of patients with isolated accidental hypothermia. Traditional methods based on measurement of core temperature are unreliable in the field. Behavioural observations have been used as predictors of core temperature and thus indirect predictors of cardiac arrest. This study aims to quantify the direct relationship between observed conscious level and cardiac arrest. METHODS: Retrospective case report analysis identified 114 cases of isolated accidental hypothermia meeting inclusion criteria. Level of consciousness in the acute assessment and management phase was classified using the AVPU system with an additional category of "Alert with confusion"; statistical analysis then related level of consciousness to incidence of cardiac arrest. RESULTS: All patients who subsequently suffered cardiac arrest showed some impairment of consciousness (p < < .0001), and the risk of arrest increased directly with the level of impairment; none of the 33 fully alert patients arrested. In the lowest impairment category, Alert confused, a quarter of the 12 patients went on to arrest, while in the highest Unresponsive category, two thirds of the 43 patients arrested. Where core temperature was available (62 cases), prediction of arrest by consciousness level was at least as good as prediction from core temperature. CONCLUSIONS: This study provides retrospective analytical evidence that consciousness level is a valid predictor of cardiac arrest risk in isolated accidental hypothermia; the importance of including confusion as a criterion is a new finding. This study suggests the use of consciousness alone may be at least as good as core temperature in cardiac arrest risk prediction. These results are likely to be of particular relevance to the management of accidental hypothermia in the pre-hospital and mass casualty environment, allowing for rapid and accurate triage of hypothermic patients.

Data Collection during the COVID-19 Pandemic: Learning from Experience, Resulting in a Bayesian Repertory.

BACKGROUND: A novel pandemic disease offered the opportunity to create new, disease-specific, symptom rubrics for the homeopathic repertory. OBJECTIVE: The aim of this study was to discover the relationship between specific symptoms and specific medicines, especially of symptoms occurring frequently in this disease. MATERIALS AND METHODS: Worldwide collection of data in all possible formats by various parties was coordinated by the Liga Medicorum Homeopathica Internationalis. As the data came in, more symptoms were assessed prospectively. Frequent analysis and feedback by electronic newsletters were used to improve the quality of the data. Likelihood ratios (LRs) of symptoms were calculated. An algorithm for combining symptom LRs was programmed and published in the form of an app. The app was tested against 18 well-described successful cases from Hong Kong. RESULTS: LRs of common symptoms such as 'Fatigue' and 'Headache' provided better differentiation between medicines than did existing repertory entries, which are based only on the narrow presence or absence of symptoms. A mini-repertory for COVID-19 symptoms was published and supported by a web-based algorithm. With a choice of 20 common symptoms, this algorithm produced the same outcome as a full homeopathic analysis based upon a larger number of symptoms, including some that are traditionally considered more specific to particular medicines. CONCLUSION: A repertory based on clinical data and LRs can differentiate between homeopathic medicines using a limited number of frequently occurring epidemic symptoms. A Bayesian computer algorithm to combine symptoms can complement a full homeopathic analysis of cases.

Electric measurement of ultra-high dilutions: a blinded controlleds experiment

This experiment was designed to test the hypothesis put forward by P. Bourkas, A. Delinick and C. Karragiannopoulos of the National Technical University of Athens (NTUA) that Ultra High Succussed Dilutions (UHSD) can be distinguished from control solutions by an Electric Measurement Device (EMD), developed by the NTUA team. A pre-formulated experimental protocol was followed, measuring in random sequence test solutions of double-distilled and deionised water... (AU)