Seasonal influenza epidemics have been responsible for causing increased economic expenditures and many deaths worldwide. Evidence exists to support the claim that the virus can be spread through the air, but the relative significance of airborne transmission has not been well defined. Particle image velocimetry (PIV) and hot‐wire anemometry (HWA) measurements were conducted at 1 m away from the mouth of human subjects to develop a model for cough flow behavior at greater distances from the mouth than were studied previously. Biological aerosol sampling was conducted to assess the risk of exposure to airborne viruses. Throughout the investigation, 77 experiments were conducted from 58 different subjects. From these subjects, 21 presented with influenza‐like illness. Of these, 12 subjects had laboratory‐confirmed respiratory infections. A model was developed for the cough centerline velocity magnitude time history. The experimental results were also used to validate computational fluid dynamics (CFD) models. The peak velocity observed at the cough jet center, averaged across all trials, was 1.2 m/s, and an average jet spread angle of θ = 24° was measured, similar to that of a steady free jet. No differences were observed in the velocity or turbulence characteristics between coughs from sick, convalescent, or healthy participants.

PurposeThis study aims (1) to numerically investigate the characteristics of a human cough jet in a quiescent environment, such as the variation with time of the velocity field, streamwise jet penetration and maximum jet width. Two different turbulence modelling approaches, the unsteady Reynolds-averaged Navier–Stokes (URANS) and large eddy simulation (LES), are used for comparison purposes. (2) To validate the numerical results with the experimental data.Design/methodology/approachTwo different approaches, the URANS and LES, are used to simulate a human cough jet flow. The numerical results for the velocity magnitude contours and the spatial average of the two-dimensional velocity magnitude over the corresponding particle image velocimetry (PIV) field of view are compared with the relevant PIV measurements. Similarly, the numerical results for the streamwise velocity component at the hot-wire probe location are compared with the hot-wire anemometry (HWA) measurements. Furthermore, the numerical results for the streamwise jet penetration are compared with the data from the previous experimental work.FindingsBased on the comparison with the URANS approach and the experimental data, the LES approach can predict the temporal development of a human cough jet reasonably well. In addition, the maximum width of the cough jet is found to grow practically linearly with time in the far-field, interrupted-jet stage, while the corresponding axial distance from the mouth of the jet front increases with time in an approximately quadratic manner.Originality/valueCurrently, no numerical study of human cough flow has been conducted using the LES approach due to the following challenges: (1) the computational cost is much higher than that of the URANS approach; (2) it is difficult to specify the turbulent fluctuations at the mouth for the cough jet properly; (3) it is necessary to define the appropriate conditions for the droplets to obtain statistically valid results. Therefore, this work fills this research gap.

ObjectivesOur objectives were to review the literature to identify frailty instruments in use for transcatheter aortic valve implantation (TAVI) recipients and synthesise prognostic data from these studies, in order to inform clinical management of frail patients undergoing TAVI.MethodsWe systematically reviewed the literature published in 2006 or later. We included studies of patients with aortic stenosis, diagnosed as frail, who underwent a TAVI procedure that reported mortality or clinical outcomes. We categorised the frailty instruments and reported on the prevalence of frailty in each study. We summarised the frequency of clinical outcomes and pooled outcomes from multiple studies. We explored heterogeneity and performed subgroup analysis, where possible. We also used Grading of Recommendations, Assessment, Development and Evaluation (GRADE) to assess the overall certainty of the estimates.ResultsOf 49 included studies, 21 used single-dimension measures to assess frailty, 3 used administrative data-based measures, and 25 used multidimensional measures. Prevalence of frailty ranged from 5.67% to 90.07%. Albumin was the most commonly used single-dimension frailty measure and the Fried or modified Fried phenotype were the most commonly used multidimensional measures. Meta-analyses of studies that used either the Fried or modified Fried phenotype showed a 30-day mortality of 7.86% (95% CI 5.20% to 11.70%) and a 1-year mortality of 26.91% (95% CI 21.50% to 33.11%). The GRADE system suggests very low certainty of the respective estimates.ConclusionsFrailty instruments varied across studies, leading to a wide range of frailty prevalence estimates for TAVI recipients and substantial heterogeneity. The results provide clinicians, patients and healthcare administrators, with potentially useful information on the prognosis of frail patients undergoing TAVI. This review highlights the need for standardisation of frailty measurement to promote consistency.PROSPERO registration numberCRD42018090597.

Background A physical performance evaluation can inform fall risk in older people, however, the predictiveness of a one‐time assessment is limited. The trajectory of physical performance over time has not been well characterized and might improve fall prediction. We aimed to characterize trajectories in physical performance and determine if fall prediction improves using trajectories of performance. Methods This was a cohort design using data from the National Health and Aging Trends Study. Physical performance was measured by the short physical performance battery (SPPB) with scores ranging from 0 (worst) to 12 (best). The trajectory of SPPB was categorized using latent class modeling and slope‐based multilevel linear regression. We used Cox proportional hazards models with an outcome of time to ≥2 falls from annual self‐report to assess predictiveness after adding SPPB trajectories to models of baseline SPPB and established non‐physical‐performance‐based variables. Results The sample was 5969 community‐dwelling Medicare beneficiaries aged ≥65 years. The median number of annual SPPB evaluations was 4 (IQR, 3–7). Mean baseline SPPB was 9.2 (SD, 3.0). The latent class model defined SPPB trajectories over a range of two to nineteen categories. The mean slope from the slope‐based model was −0.01 SPPB points/year (SD, 0.14). Discrimination of the baseline SPPB model to predict time to ≥2 falls was fair (Harrell's C, 0.65) and increased after adding the non‐performance‐based predictors (Harrell's C, 0.70). Discrimination slightly improved with the SPPB trajectory category variable that had the best fit (Harrell's C, 0.71) but did not improve with the SPPB linear slope. Calibration with and without the trajectory categories was similar. Conclusions We found that the trajectory of physical performance did not meaningfully improve upon fall prediction from a baseline physical performance assessment and established non‐performance‐based information. These results do not support longitudinal SPPB assessments for fall prediction.

Viral encephalitis is a common clinical condition. Its clinical manifestations are variable and include neurological symptoms and psychiatric abnormalities, which makes clinical diagnosis and treatment difficult. To date, there are only a few reported cases on mental symptoms of chronic viral encephalitis. We present a case of a 16-year-old male patient who was previously hospitalised and diagnosed with schizophrenia and treated with aripiprazole 15 mg/day but failed to respond. The patient was then given antiviral therapy and recovered after 2 weeks. Clinicians should be aware of the possbility that chronic mental disorders could be caused by viral encephalitis. In the future, diagnosis of chronic functional mental disorders should include viral encephalitis in the differential diagnosis.