Resistive simulated weightbearing exercise with whole body vibration reduces lumbar spine deconditioning in bed-rest

STUDY DESIGN: Randomized controlled trial. OBJECTIVE: Determine the effectiveness a resistive exercise countermeasure with whole-body vibration in relation to lumbo-pelvic muscle and spinal morphology changes during simulated spaceflight (bed-rest). SUMMARY OF BACKGROUND DATA: Spinal lengthening, flattening of the spinal curves, increases in disc size, and muscle atrophy are commonly seen in spaceflight simulation. This may represent a risk for low back injury. Consideration of exercise countermeasures against these changes is critical for success of long-term spaceflight missions. METHODS: Twenty healthy male subjects underwent 8-weeks of bed-rest with 6-months follow-up and were randomly allocated to an inactive control or countermeasure exercise group. Magnetic resonance imaging of the lumbo-pelvic region was conducted at regular time-points during and after bed-rest. Using uniplanar images at L4, cross-sectional areas of the multifidus, lumbar erector spinae, quadratus lumborum, psoas, anterolateral abdominal, and rectus abdominis muscles were measured. Sagittal scans were used to assess lumbar spine morphology (length, sagittal disc area and height, and intervertebral angles). RESULTS: The countermeasure group exhibited less multifidus muscle atrophy (P = 0.024) and its atrophy did not persist long-term as in the control group (up to 3-months; P < 0.006). Spinal lengthening (P = 0.03) and increases in disc area (P = 0.041) were also reduced. Significant partial correlations (P < 0.001) existed between spinal morphology and muscle cross-sectional area changes. CONCLUSION: The resistive vibration exercise countermeasure reduced, but did not entirely prevent, multifidus muscle atrophy and passive spinal tissue deconditioning during bed-rest. Atrophy of the multifidus muscles was persistent long-term in the inactive subjects. Future work could consider closer attention to spinal posture during exercise and optimizing exercise dose.

Muscle atrophy and changes in spinal morphology: is the lumbar spine vulnerable after prolonged bed-rest?

STUDY DESIGN: prospective longitudinal study. OBJECTIVE: to evaluate the effect of bed-rest on the lumbar musculature and soft-tissues. SUMMARY OF BACKGROUND DATA: earlier work has suggested that the risk of low back injury is higher after overnight bed-rest or spaceflight. Changes in spinal morphology and atrophy in musculature important in stabilizing the spine could be responsible for this, but there are limited data on how the lumbar musculature and vertebral structures are affected during bed-rest. METHODS: nine male subjects underwent 60-days head-down tilt bed-rest as part of the second Berlin Bed-Rest Study. Disc volume, intervertebral spinal length, intervertebral lordosis angle, and disc height were measured on sagittal plane magnetic resonance images. Axial magnetic resonance images were used to measure cross-sectional areas (CSAs) of the multifidus (MF), erector spinae, quadratus lumborum, and psoas from L1 to L5. Subjects completed low back pain (LBP) questionnaires for the first 7-days after bed-rest. RESULTS: increases in disc volume, spinal length (greatest at lower lumbar spine), loss of the lower lumbar lordosis, and move to a more lordotic position at the upper lumbar spine (P < 0.0097) were seen. The CSAs of all muscles changed (P < 0.002), with the rate of atrophy greatest at L4 and L5 in MF (P < 0.002) and at L1 and L2 in the erector spinae (P = 0.0006). Atrophy of the quadratus lumborum was consistent throughout the muscle (P = 0.15), but CSA of psoas muscle increased (P < 0.0001). Subjects who reported LBP after bed-rest showed, before reambulation, greater increases in posterior disc height, and greater losses of MF CSA at L4 and L5 than subjects who did not report pain (all P < 0.085). CONCLUSION: these results provide evidence that changes in the lumbar discs during bed-rest and selective atrophy of the MF muscle may be important factors in the occurrence of LBP after prolonged bed-rest.

Influences of spatial practices on pressure ulcer management in the context of spinal cord injury

Nursing practice is significantly influenced by the type and use of space in which nursing is practised. While investigating current patterns of service delivery for the management of pressure ulcers from the perspective of people with spinal cord injuries and their families, the space in which care was delivered was identified as a central determinant of care. Qualitative methods were used to investigate consumer perspectives among patients residing in both metropolitan and rural communities who had been hospitalized for the management of pressure ulcers. Issues related to the spatial practices of the hospital are discussed, demonstrating a link between well-being and the creation of an appropriate caring milieu. It is concluded that service could be improved markedly if health-care professionals placed more consideration on the impact of space on their service delivery.

The effect of osteoporotic vertebral fracture of predicted spinal loads in vivo

he aetiology of osteoporotic vertebral fractures is multi-factorial, and cannot be explained solely by low bone mass. After sustaining an initial vertebral fracture, the risk of subsequent fracture increases greatly. Examination of physiologic loads imposed on vertebral bodies may help to explain a mechanism underlying this fracture cascade. This study tested the hypothesis that model-derived segmental vertebral loading is greater in individuals who have sustained an osteoporotic vertebral fracture compared to those with osteoporosis and no history of fracture. Flexion moments, and compression and shear loads were calculated from T2 to L5 in 12 participants with fractures (66.4 ± 6.4 years, 162.2 ± 5.1 cm, 69.1 ± 11.2 kg) and 19 without fractures (62.9 ± 7.9 years, 158.3 ± 4.4 cm, 59.3 ± 8.9 kg) while standing. Static analysis was used to solve gravitational loads while muscle-derived forces were calculated using a detailed trunk muscle model driven by optimization with a cost function set to minimise muscle fatigue. Least squares regression was used to derive polynomial functions to describe normalised load profiles. Regression co-efficients were compared between groups to examine differences in loading profiles. Loading at the fractured level, and at one level above and below, were also compared between groups. The fracture group had significantly greater normalised compression (p = 0.0008) and shear force (p < 0.0001) profiles and a trend for a greater flexion moment profile. At the level of fracture, a significantly greater flexion moment (p = 0.001) and shear force (p < 0.001) was observed in the fracture group. A greater flexion moment (p = 0.003) and compression force (p = 0.007) one level below the fracture, and a greater flexion moment (p = 0.002) and shear force (p = 0.002) one level above the fracture was observed in the fracture group. The differences observed in multi-level spinal loading between the groups may explain a mechanism for increased risk of subsequent vertebral fractures. Interventions aimed at restoring vertebral morphology or reduce thoracic curvature may assist in normalising spine load profiles.

Joint range of motion limitations in children and young adults with spinal muscular atrophy

Objectives
To elicit descriptive data about limited joint range of motion (ROM) in subjects with type II or III spinal muscular atrophy (SMA) and to examine the relation between the number of motions with limited range and both age and functional ability.
Design
Descriptive cross-sectional study.
Setting
Neurologic pediatric outpatient clinic at a hospital in Taiwan.
Participants
Twenty-seven subjects with SMA type II (mean age, 9.8±6.5y) and 17 with SMA type III (mean age, 12.2±8.7y).
Intervention
Measurement with transparent goniometers of joint ROM bilaterally of the shoulder, elbow, wrist, hip, knee, and ankle.
Main outcome measures
The proportion of participants with each ROM limitation compared with all participants with the same SMA type, age distribution of the participants with each ROM limitation, mean range loss of each motion limitation, and the contracture index (risk index of joint contracture).
Results
Eighty-nine percent of the participants with SMA type II experienced knee extension limitation. Approximately 50% of the participants with both types of SMA had ankle dorsiflexion limitation. The motions of knee and hip extension and ankle dorsiflexion also had a relatively high contracture index. The number of motions with limited range positively correlated (P<.001) with age and upper-extremity functional grade (the higher the functional grade, the poorer the functional ability) for SMA type II.
Conclusions
We found varying degrees of joint ROM limitation. Certain motions were noted to be high risks for the development of contractures. This risk was higher mostly in younger children.

Learning from large data : bias, variance, sampling, and learning curves

One of the fundamental machine learning tasks is that of predictive classification. Given that organisations collect an ever increasing amount of data, predictive classification methods must be able to effectively and efficiently handle large amounts of data. However, it is understood that present requirements push existing algorithms to, and sometimes beyond, their limits since many classification prediction algorithms were designed when currently common data set sizes were beyond imagination. This has led to a significant amount of research into ways of making classification learning algorithms more effective and efficient. Although substantial progress has been made, a number of key questions have not been answered. This dissertation investigates two of these key questions. The first is whether different types of algorithms to those currently employed are required when using large data sets. This is answered by analysis of the way in which the bias plus variance decomposition of predictive classification error changes as training set size is increased. Experiments find that larger training sets require different types of algorithms to those currently used. Some insight into the characteristics of suitable algorithms is provided, and this may provide some direction for the development of future classification prediction algorithms which are specifically designed for use with large data sets. The second question investigated is that of the role of sampling in machine learning with large data sets. Sampling has long been used as a means of avoiding the need to scale up algorithms to suit the size of the data set by scaling down the size of the data sets to suit the algorithm. However, the costs of performing sampling have not been widely explored. Two popular sampling methods are compared with learning from all available data in terms of predictive accuracy, model complexity, and execution time. The comparison shows that sub-sampling generally products models with accuracy close to, and sometimes greater than, that obtainable from learning with all available data. This result suggests that it may be possible to develop algorithms that take advantage of the sub-sampling methodology to reduce the time required to infer a model while sacrificing little if any accuracy. Methods of improving effective and efficient learning via sampling are also investigated, and now sampling methodologies proposed. These methodologies include using a varying-proportion of instances to determine the next inference step and using a statistical calculation at each inference step to determine sufficient sample size. Experiments show that using a statistical calculation of sample size can not only substantially reduce execution time but can do so with only a small loss, and occasional gain, in accuracy. One of the common uses of sampling is in the construction of learning curves. Learning curves are often used to attempt to determine the optimal training size which will maximally reduce execution time while nut being detrimental to accuracy. An analysis of the performance of methods for detection of convergence of learning curves is performed, with the focus of the analysis on methods that calculate the gradient, of the tangent to the curve. Given that such methods can be susceptible to local accuracy plateaus, an investigation into the frequency of local plateaus is also performed. It is shown that local accuracy plateaus are a common occurrence, and that ensuring a small loss of accuracy often results in greater computational cost than learning from all available data. These results cast doubt over the applicability of gradient of tangent methods for detecting convergence, and of the viability of learning curves for reducing execution time in general.

Monitoring the corrosion of concrete reinforcement using control curves

Corrosion testing (half-cell and LPR) was carried out on a number reinforced concrete panels which had been taken from the fascia of a twenty five year old high rise building in Melbourne, Australia. Corrosion, predominantly as a result of carbonation of the concrete, was associated with a limited amount of cracking. A monitoring technique was established in which probe electrodes (reference and counter) were retro-fitted into the concrete. The probe electrode setup was identical for all panels tested. It was found that the corrosion behaviour of all panels tested closely fitted a family of results when the corrosion potential is plotted against the polarisation resistance (Rp). This enabled the development of a so-called 'control curve' relating the corrosion potential to the Rp for all of the panels under investigation. This relationship was also confirmed on laboratory samples, indicating that for a fixed geometry and experimental conditions a relationship between the potential and polarisation resistance of steel can be established for the steel-concrete system. Experimental results will be presented which indicate that for a given monitoring cell geometry, it may be possible to propose criteria for the point at which remediation measures should be considered. The establishment of such a control curve has enabled the development of a powerful monitoring tool for the assessment of a number of proposed corrosion remediation techniques. The actual effect of any corrosion remediation technique becomes clearly apparent via the type and magnitude of deviation of post remediation data from the original (preremediation) control curve.

Effect of an arginine-containing nutritional supplement on pressure ulcer healing in community spinal patients

Objective: To determine whether or not the use of an arginine-containing nutritional supplement could result in signifi cantly shorter pressure ulcer (PU) healing times in people with spinal cord injuries living in the community, compared with a comparative historical control group. Method: Eighteen spinal-cord-injured patients (all part of a hospital spinal outreach service) received 9g of a commercial powdered arginine supplement per day until full PU healing occurred. Healing rates were compared against 17 historical control patients (as assessed by medical history audit). 
Results: Baseline characteristics (age, gender, injury level and time) were similar between groups. Mean ulcer healing times were 10.5 ± 1.3 weeks versus 21 ± 3.7 weeks (p<0.05) in the intervention and control groups respectively. Comparison of healing rates in the intervention group against expected healing rates derived from the medical literature showed that intervention patients had a signifi cantly shorter mean healing time (category 2 PU: 5.5±1.3 weeks versus 13.4 weeks; category 3 PU: 12.5 ± 1.9 weeks versus 18.2 weeks; category 4 PU: 14.4 ± 4.8 weeks versus 22.1 weeks). A diagnosis of diabetes did not significantly alter healing rates in either group. Conclusion: Results from this observational study show a promising benefit of arginine supplementation on PU healing for individuals with spinal cord injury living in the community.