Background: Laryngospasm is usually easily detected and managed, but may present atypically and/or be precipitated by factors which are not immediately recognised. If poorly managed, it has the potential to cause morbidity and mortality such as severe hypoxaemia, pulmonary aspiration, and post-obstructive pulmonary oedema. Objectives: To examine the role of a previously described core algorithm ''COVER ABCD-A SWIFT CHECK'', supplemented by a specific sub-algorithm for laryngospasm, in the management of laryngospasm occurring in association with anaesthesia. Methods: The potential performance of this structured approach for the relevant incidents amongst the first 4000 reported to the Australian Incident Monitoring Study (AIMS) was compared with the actual management as reported by the anaesthetists involved. Results: There were 189 reports of laryngospasm among the first 4000 incidents reported to AIMS. These were extracted and analysed. In 77% of cases laryngospasm was clinically obvious, but 14% presented as airway obstruction, 5% as regurgitation or vomiting, and 4% as desaturation. Most were precipitated by direct airway stimulation (airway manipulation, regurgitation, vomiting, or blood or secretions in the pharynx), but patient movement, surgical stimulus, irritant volatile agents, and failure to deliver the anaesthetic were also precipitating factors. Desaturation occurred in over 60% of cases, bradycardia in 6% (23% in patients aged ,1 year), pulmonary oedema in 4%, and pulmonary aspiration in 3%. It was considered that, correctly applied, the combined core algorithm and sub-algorithm recommended for the diagnosis and management of laryngospasm would have led to earlier recognition of the problem and/or better management in 16% of cases. Conclusion: Laryngospasm may present atypically and, if not promptly managed effectively, may lead to morbidity and mortality. Although usually promptly recognised and appropriately managed, the use of a structured approach is recommended. If such an approach had been used in the 189 reported incidents, earlier recognition and/or better management may have occurred in 16% of cases.

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Background. Sarcopenia is the presence of low muscle mass and low muscle function. The aim of this study was to establish cutoffs for low muscle mass using three published methods and to compare the prevalence of sarcopenia in older Australians. Methods. Gender specific cutoffs levels were identified for low muscle mass using three different methods. Low grip strength was determined using established cutoffs of <30 kg for men and <20 kg for women to estimate the prevalence of sarcopenia. Results. Gender specific cutoffs levels for low muscle mass identified were (a) <6.89 kg/m2 for men and <4.32 kg/m2 for women, <2 standard deviation (SD) of a young reference population; (b) <7.36 kg/m2 for men and <5.81 kg/m2 for women from the lowest 20% percentile of the older group; and (c) <−2.15 for men and <−1.42 for women from the lowest 20% of the residuals of linear regressions of appendicular skeletal mass, adjusted for fat mass and height. Prevalence of sarcopenia in older (65 years and older) people by these three methods for men was 2.5%, 6.2%, and 6.4% and for women 0.3%, 9.3%, and 8.5%, respectively. Conclusions. Sarcopenia is common but consensus on the best method to confirm low muscle mass is required.

BackgroundThere is a loss of lean body mass (LBM) with increasing age. A low LBM has been associated with increased adverse effects from prescribed medications such as chemotherapy. Accurate assessment of LBM may allow for more accurate drug prescribing. The aims of this study were to develop new prediction equations (PEs) for LBM with anthropometric and biochemical variables from a development cohort and then validate the best performing PEs in validation cohorts.MethodsPEs were developed in a cohort of 188 healthy subjects and then validated in a convenience cohort of 52 healthy subjects. The best performing anthropometric PE was then compared to published anthropometric PEs in an older (age ≥ 50 years) cohort of 2287 people. Best subset regression analysis was used to derive PEs. Correlation, Bland-Altman and Sheiner & Beal methods were used to validate and compare the PEs against dual X-ray absorptiometry (DXA)-derived LBM.ResultsThe PE which included biochemistry variables performed only marginally better than the anthropometric PE. The anthropometric PE on average over-estimated LBM by 0.74 kg in the combined cohort. Across gender (male vs. female), body mass index (< 22, 22- < 27, 27- < 30 and ≥30 kg/m2) and age groups (50–64, 65–79 and ≥80 years), the maximum mean over-estimation of the anthropometric PE was 1.36 kg.ConclusionsA new anthropometric PE has been developed that offers an alternative for clinicians when access to DXA is limited. Further research is required to determine the clinical utility and if it will improve the safety of medication use.