Alcohol sales and fatal alcohol poisonings: a time-series analysis

Aims To discover whether the number of fatal alcohol peaks during festivities characterized by unrestrained drinking and relates to sales of alcoholic beverages. Design Time‐series and cross‐sectional. Data Fatal alcohol poisonings and retail alcohol sales in Finland in 1983–99. Findings Fatal alcohol poisonings were found to peak during weekends and in the May Day, Midsummer Day and Christmas celebrations. Regression analysis of quarterly series lead to a model showing that 1% increase in the sales of spirits increases the number of fatal alcohol poisonings by 0.4%. Conclusions At the population level, increases in the sales of spirits and periods of hard drinking seem to increase deaths from alcohol poisoning. The findings could be of use in efforts to decrease hard drinking.     

Immediate and short-term effects of mulligan concept positional sustained natural apophyseal glides on an athletic young-adult population classified with mechanical neck pain: an exploratory investigation

Objectives: Mechanical neck pain (MNP) is common in the athletic population. While symptoms may present at the cervical spine for patients complaining of MNP, thoracic spinal alignment or dysfunction may influence cervical positioning and overall cervical function. Clinicians often employ cervical high-velocity low-amplitude (HVLA) thrust manipulations to treat MNP, albeit with a small level of inherent risk. Mulligan Concept positional sustained natural apophyseal glides (SNAGs) directed at the cervicothoracic region are emerging to treat patients with cervical pain and dysfunction, as evidence supporting an interdependent relationship between the thoracic and cervical spine grows. The purpose of this a priori study was to evaluate outcome measures of patients classified with MNP treated with the Mulligan Concept Positional SNAGs. Methods: Ten consecutive young-adult patients, ages ranging from 15 to 18 years (mean = 16.5 ± 1.78), classified with MNP were treated utilizing Mulligan Concept Positional SNAGs. The Numeric Rating Scale (NRS), Patient-Specific Functional Scale (PSFS), Neck Disability Index (NDI), Disablement in the Physically Active (DPAS), and Fear-Avoidance Based Questionnaire-Physical Activity (FABQPA) were collected for inclusion criteria and to identify patient-reported pain and dysfunction. Results: Patients reported decreases in pain on the NRS [5.4 to .16, p = .001], increases in function on the PSFS [5.2 to 10, p = .001], and increases in cervical range of motion (CROM) [ext p = .003, flex p = .009, left rot p = .001, right rot p = .002] immediately post-treatment and between treatments. Discussion: Positional SNAGs directed at the cervicothoracic region may address a variety of patient reported symptoms for MNP, and the number of treatment sessions needed for symptom resolution may be closer to a single session rather than multiple treatments. Level of Evidence: 4.     

Modeling Dynamic Contrast-Enhanced MRI Data with a Constrained Local AIF

Purpose

This study aims to develop a constrained local arterial input function (cL-AIF) to improve quantitative analysis of dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) data by accounting for the contrast-agent bolus amplitude error in the voxel-specific AIF.

Procedures

Bayesian probability theory-based parameter estimation and model selection were used to compare tracer kinetic modeling employing either the measured remote-AIF (R-AIF, i.e., the traditional approach) or an inferred cL-AIF against both in silico DCE-MRI data and clinical, cervical cancer DCE-MRI data.

Results

When the data model included the cL-AIF, tracer kinetic parameters were correctly estimated from in silico data under contrast-to-noise conditions typical of clinical DCE-MRI experiments. Considering the clinical cervical cancer data, Bayesian model selection was performed for all tumor voxels of the 16 patients (35,602 voxels in total). Among those voxels, a tracer kinetic model that employed the voxel-specific cL-AIF was preferred (i.e., had a higher posterior probability) in 80 % of the voxels compared to the direct use of a single R-AIF. Maps of spatial variation in voxel-specific AIF bolus amplitude and arrival time for heterogeneous tissues, such as cervical cancer, are accessible with the cL-AIF approach.

Conclusions

The cL-AIF method, which estimates unique local-AIF amplitude and arrival time for each voxel within the tissue of interest, provides better modeling of DCE-MRI data than the use of a single, measured R-AIF. The Bayesian-based data analysis described herein affords estimates of uncertainties for each model parameter, via posterior probability density functions, and voxel-wise comparison across methods/models, via model selection in data modeling.