Jerome C. Hill: January 2019

Wednesday, January 30, 2019

Student Loan Forgiveness for Military Personnel

Here we will outline the many programs that servicemen and servicewomen can consider for student loan forgiveness.

The post Student Loan Forgiveness for Military Personnel appeared first on Earnest Blog | Money Advice for Young Professionals.

Monday, January 28, 2019

How balance task-specific training contributes to improving physical function in older subjects undergoing rehabilitation following hip fracture: a critical appraisal

This blog is a critical appraisal of the following randomized controlled trial: How balance task-specific training contributes to improving physical function in older subjects undergoing rehabilitation following hip fracture.

Background

Hip fractures are a common and severe problem for both the patient and the National Health Service (NHS); most occur when an elderly person has a fall. The Royal College of Physicians (RCP) (2017) reported that in 2016 Britain treated over 65,000 hip fractures in those aged 60 or older. Most spent an average of three weeks in hospital, costing the NHS over one billion pounds.

Within the research base there is a lack of evidence on which treatment method and outcome measure is best to assess for a fully functional recovery following surgery (Unnanuntana et al. 2018). In addition, there is a high level of mortality and comorbidity following a broken a hip. Regaining baseline mobility level may never be possible which can have a massive effect on a person’s quality of life (QoL) (RCP 2017). There is research suggesting that by using balance task-specific rehabilitation compared to active range of motion (AROM) and strengthening exercises will improve a patients confidence and mobility levels (Monticone et al. 2018).

What was the study?

There were 52 participants and a specific inclusion and exclusion criteria, focusing on elderly adults who were over the age of 70 who had suffered a hip fracture and had a surgical intervention. 19 participants were excluded due to issues such as stroke, chronic lung diseases, previous lower limb surgery and cognitive impairments. The participants were split evenly by a MATLAB blinded treatment code; both the biostatistician and lead researcher were blinded from the process. The physiotherapist and patients were not blinded to the different interventions, however they were blinded to the study’s hypothesis.

The intervention group were given balance specific tasks that involved proprioceptive exercises, motor-cognitive exercise and activities of daily living (ADL’s) exercises, compared to the control group who were given closed-chain exercises to improve AROM and muscle strength. The primary outcome measure was functional ability which was assessed by a self-report Western Ontario and McMaster University Osteoarthritis Index (WOMAC). Secondary outcomes measured pain, balance, ADLs and QoL. The questionnaires were distributed by the same secretary pre-treatment, before hospital discharge and at the 12 month follow up.

What were the results?

The researchers demonstrate that by focusing on balance task-specific training in rehabilitation, it can improve functional ability, reduce pain, and assist in the regaining of ADL and QoL within the elderly population after a hip fracture. There was a significant difference between the two groups, with a 95% confidence interval with primary outcome and the secondary outcome measures, with a P- <0.001. The study claims that balance task-specific training was better than general rehabilitation exercises for, at a minimum, 12 months post-surgery.

Strengths and weakness of the study?

Evaluating the study using the CASP tool, and by following the guideline and answering questions about the study, will aid a deeper understanding of the study and demonstrate whether the results can be used in a clinical environment.

The sample size of the study was small (52 Italian participants with a hip fracture) which can lead to a small number of outcome events. This, in turn, can lead to reduced confidence that any difference between the groups reflects the differences in the treatments rather than the effects of chance.

However, the recruitment was very similar between both groups. The intervention and control group were split very evenly using the MATLAB program, having similar age range, gender, BMI, social class, comorbidities and physical function/activity level as their baseline. The largest difference in the whole sample size was that 15 out of 52 were male; this is more likely due to women having a longer life expectancy compared to males (Sanders 2018). Furthermore, the exclusion criteria limits the ability to generalise due to other comorbidities and the high mortality rates following a hip fracture (Monticone et al. 2018).

Interestingly, in the study, it suggests that you can generalise within the same population and condition, using balance task-specific exercises during treatment (Monticone et al. 2018). This could be due to using strong outcome measures such as WOMAC and the Berg Balance Scale.

The intervention and control treatments were different between groups. Therefore, for the results to be valid, both groups had the same number and amount of treatment sessions over the three weeks of rehabilitation. Additionally, all mobility equipment and gait re-education was the same for both groups otherwise it would create an ethics issue which in turn would affect the validity of the results. The method of treatment in the control group was lying in supine, performing closed chain exercises. However, by not weight-bearing post surgery, this can have a negative effect on the rehabilitation and the functional ability outcome (Sherrington 2003).

Conclusion

The study demonstrates that there is a significant difference between using balance task-specific training in elderly adults who have had a broken hip, for up to a 12-month period post surgery. Yet we still need further research into this topic due to the high mortality rates following a fractured hip (RCP 2017).

References

CRITICAL APPRAISAL SKILLS PROGRAMME (CASP)., 2018. CASP Checklists – CASP – Critical Appraisal Skills Programme [online]. [viewed 3 December 2018].

MONTICONE, M., AMBROSINI, E., BRUNATI, R., CAPONE, A., PAGLIARI, G., SECCI, C., ZATTI, G. and FERRANTE, S., 2018. How balance task-specific training contributes to improving physical function in older subjects undergoing rehabilitation following hip fracture: a randomized controlled trial. Clinical Rehabilitation [online]. vol. 32(3):340-351 [viewed 4 December 2018].

SANDERS, S., 2018. National life tables, UK – Office for National Statistics [online]. [viewed 6 December 2018].

SHERRINGTON, C., LORD, S. and HERBERT, R., 2003. A randomised trial of weight-bearing versus non-weight-bearing exercise for improving physical ability in inpatients after hip fracture. Australian Journal of Physiotherapy [online]. vol. 49(1):15-22 [viewed 4 December 2018].

THE ROYAL COLLEGE OF PHYSICIANS (RCP)., 2017. National Hip Fracture Database annual report 2017 [online]. [viewed 6 December 2018].

UNNANUNTANA, A., JARUSRIWANNA, A. and NEPAL, S., 2018. Validity and responsiveness of Barthel index for measuring functional recovery after hemiarthroplasty for femoral neck fracture. Archives of Orthopaedic and Trauma Surgery [online]. vol. 138 (12):1671-1677 [viewed 5 December 2018].

The post How balance task-specific training contributes to improving physical function in older subjects undergoing rehabilitation following hip fracture: a critical appraisal appeared first on Students 4 Best Evidence.

How This Grad Used the ‘2+2’ Strategy to Minimize Student Loan Debt

"The nontraditional path to a bachelor's degree may not be the best option for everyone, but I am glad it is the route I took."

The post How This Grad Used the ‘2+2’ Strategy to Minimize Student Loan Debt appeared first on Earnest Blog | Money Advice for Young Professionals.

An early rehabilitation intervention to enhance recovery during hospital admission for an exacerbation of chronic respiratory disease: a critical appraisal

This blog is a critical appraisal of the following randomized controlled trial: An early rehabilitation intervention to enhance recovery during hospital admission for an exacerbation of chronic respiratory disease: randomised controlled trial.

Background

Acute exacerbations of chronic respiratory diseases are the second most common cause of unplanned hospital admissions per year, placing a significant financial burden on healthcare systems. Hospitalisation increases the patient’s risk of mortality, morbidity and re-admission (Hunter et al. 2016). It is therefore important to establish how admissions for acute respiratory disease can be optimally managed.

This blog will discuss and critically appraise a single-blinded, randomized controlled trial (RCT) that aimed to determine whether early rehabilitation provided within the first 48 hours of admission could improve clinical outcomes (Greening et al. 2014).

Study Design

This study was conducted over two hospital sites (urban and rural) in the United Kingdom. Having screened for eligibility (Table 1), participants (n=389, 45-93 years old) hospitalised for an acute exacerbation of respiratory disease were randomised into two groups using an automated internet-based service. The control group (n=196) were treated with ‘usual care’ whereas the intervention group (n=193) received an additional 6-week early rehabilitation package, initiated within 48 hours of admission and supervised by a member of the rehabilitation team. Early rehabilitation consisted of progressive aerobic, resistance and neuromuscular electrical stimulation training. On discharge, participants in the intervention group were required to continue the 6-week program unsupervised and were provided with educational and self-management advice in conjunction with three telephone consultations. Both groups were offered formal pulmonary rehabilitation (PR) at 3 months post-discharge.

The primary outcome measure was hospital readmission rate at 12 months, obtained using hospital databases and general practice records, and analysed on an intention to treat (ITT) basis. Secondary outcomes included mortality and physical performance. Functional outcome measures were taken at baseline, on discharge and at 6 weeks, 3 months and 12 months from randomisation. Only investigators assessing outcomes were blinded to treatment allocations.

Table 1: Eligibility criteria as outlined by Greening et al (2014, p. 4316)
Inclusion Criteria	Exclusion Criteria
Diagnosis of chronic respiratory disease (chronic obstructive pulmonary disease, chronic asthma, bronchiectasis or interstitial lung disease) Self-reported breathlessness on exertion when stable (Medical Research Council dyspnoea grade 3 or worse) Aged 40 years +	Inability to provide informed consent Concomitant acute cardiac event Presence of musculoskeletal, neurological, or psychiatric comorbidities that would prevent delivery of rehabilitation intervention More than four emergency admissions to hospital for any cause in the previous 12 months

Results

Overall, 60% of participants (control: 58%, intervention: 62%) were readmitted at least once within 12 months, but no statistical difference was found between groups (HR 1.1, 95% CI 0.86 to 1.43, P=0.4). The only statistically significant outcome was increased mortality in the intervention group (49/193) compared to the control (31/196) (OR 1.74, 95% CI 1.05 to 2.88, P=0.03).

Critical Appraisal

The CASP tool for RCT’s was used to assess the internal and external validity of the study and the pertinence of results to clinical practice.

A major strength of this study was its large sample size. This ensured the trial was adequately powered to detect a 15% difference in readmission rates, requiring ≥190 participants in each group. Additionally, concealed randomisation helped to ensure internal validity and eliminate selection bias. The study had robust handling of missing data and used ITT analysis, preventing attrition bias. ITT analysis ensures participants are analysed in their randomised group, maintaining equality of baseline characteristics, regardless of adherence to the intervention. This reflects clinical practice where non-compliance can occur, making ITT analysis more representative of the real-life effectiveness of interventions.

The main limitation of the study were issues relating to confounding. For example, although a number of variables were adjusted for in the model, the stable-state forced expiratory volume in one second (FEV1) at baseline (an indicator of disease severity) and cognitive impairment were not. The mean FEV1 (% predicted) differed between groups whereby the intervention group had more severe disease at baseline. The lack of significant differences in outcomes and increase in mortality may therefore be an artefact of confounding due to this baseline characteristic. Additionally, cognitive dysfunction was not screened for although it has been associated with increased mortality and disability. Estimated to affect over 50% of patients hospitalised with an exacerbation of chronic obstructive pulmonary disease (COPD), cognitive impairment may lead to a lack of understanding and compliance with the intervention, contributing to the study’s findings (Dodd et al. 2010). Indeed, only 54% of participants adhered to the intervention for the 6-week period.

A further limitation was short admission times allowing for an average of only 2.7 supervised sessions. For the majority of the 6-week intervention, participants self-reported their compliance which may have biased the results.

This study is likely generalisable to other UK hospitals with similar admission lengths given that the National Health Service aims to standardise care across the country. Results are also likely to be generalisable to different settings given that the RCT was conducted in both urban and rural hospitals. However, as the majority of participants suffered from COPD (82%), it is unclear how representative the findings are to patients with chronic asthma, interstitial lung disease and bronchiectasis.

The short admission time and poor compliance with the post-discharge protocol likely resulted in an intervention which was not sufficiently intense enough to elicit physiological changes and affect readmission rates or mortality. Subtle differences in baseline characteristics and changes in health behaviour, noted by a lower PR uptake in the intervention group at 3 months (14% vs 22%), are more likely responsible for differences in mortality.

Conclusion

This study indicates that an early rehabilitation program, initiated during acute admission for patients with chronic respiratory disease, does not improve clinical outcomes. However, given the limitations outlined above, additional research is required to further investigate optimal timing, dosing and setting of rehabilitation for these patients in order to reduce risks associated with hospitalisation. Conventional, supervised, post-exacerbation PR offered after discharge remains the most effective, evidence-based intervention for this population (Puhan et al. 2016).

References

Critical Appraisal Skills Programme (2018). CASP (Randomised Controlled Trial) Checklist. [online]. [Viewed: 25 November 2018].

DODD, J., GETOV, S. and JONES, P., 2010. Cognitive function in COPD. European Respiratory Journal [online]. July, vol. 35, no. 4, pp. 913-922 [viewed 11 December].

GREENING, N., WILLIAMS, J., HUSSAIN, S., HARVEY-DUNSTAN, T., BANKART, M., CHAPLIN, E., VINCENT, E., CHIMERA, R., MORGAN, M., SINGH, S. and STEINER, M., 2014. An early rehabilitation intervention to enhance recovery during hospital admission for an exacerbation of chronic respiratory disease: randomised controlled trial. British Medical Journal, [online]. July, vol.349, pp. 4315-4327 [Viewed 01 December 2018].

HUNTER, L., LEE, R., BUTCHER, I., WEIR, C., FISCHBACHER, C., MCALLISTER, D., WILD, S., HEWITT, N. AND HARDIE, R., 2016. Patient characteristics associated with risk of first hospital admission and readmission for acute exacerbation of chronic obstructive pulmonary disease (COPD) following primary care COPD diagnosis: a cohort study using linked electronic patient records. British Medical Journal Open, [online]. Vol 6, Issue 1 [Viewed 10 December 2018].

PUHAN, M., GIMENO-SANTOS, E., CATES, C. and TROOSTERS, T., 2016. Pulmonary rehabilitation following exacerbations of chronic obstructive pulmonary disease. Cochrane Database of Systematic Reviews [online]. December, no. 12. [viewed 11 December]. Art. No: CD005305. DOI: 10.1002/14651858.CD005305.pub4.

The post An early rehabilitation intervention to enhance recovery during hospital admission for an exacerbation of chronic respiratory disease: a critical appraisal appeared first on Students 4 Best Evidence.

Wednesday, January 23, 2019

How Much Does Law School Cost in 2019?

The cost of law school — factoring in tuition, fees, room and board, and more — is high at many institutions. Here's the data on the top 25 schools.

The post How Much Does Law School Cost in 2019? appeared first on Earnest Blog | Money Advice for Young Professionals.

Monday, January 21, 2019

How to Get Your First Credit Card

Building a strong credit history can start with your first credit card.

The post How to Get Your First Credit Card appeared first on Earnest Blog | Money Advice for Young Professionals.

Bias: how much difference does it really make in randomized trials?

Introduction

Randomized controlled trials (RCTs) can be subject to different kinds of bias. Cochrane’s Risk of Bias tool, outlined in chapter 8 of the Cochrane Handbook (version 5.1), is a commonly used way to assess RCTs for bias. We can classify the biases listed by this tool in the following manner:

Selection bias (due to inadequate sequence generation or inadequate allocation concealment)
Performance bias (due to inadequate blinding of participants/clinicians)
Detection bias (due to inadequate blinding of outcome assessors)
Attrition bias (due to incomplete outcome data)
Reporting bias (due to only selected outcomes being reported)
Other forms of bias (e.g., imbalance in baseline characteristics)

These were originally based on theoretical concerns and anecdotes. Starting inchoately in the 1980s, and primarily in the 1990s, reviewers began to compare trials with biases to trials without biases to see how much magnitude of effect was changed by the presence of bias. These studies are known as meta-epidemiological studies. At the current time, the most complete is the 2016 systematic review and meta-analysis of meta-epidemiological studies by Page et al. All results presented here are directly from this review’s meta-analyses or from studies cited therein. Note that results are presented either as a ratio of ratios or a difference in standardized mean difference (difference in SMD). A ratio of ratios < 1, or a negative difference in SMD, represents bias causing the estimate of effect to be overestimated/exaggerated.

Selection bias

You can read more about allocation concealment here:

Page et al. found that inadequate or unclear randomization sequencing caused the effect of treatment to be overestimated (ratio of odds ratios 0.93, 95% confidence interval 0.86 to 0.99). Inadequate or unclear allocation concealment overestimated effects similarly (ratio of odds ratios 0.90, 95% confidence interval 0.84 to 0.97). With allocation concealment (but not randomization sequence), a greater effect was noticed for subjective outcomes versus objective outcomes: the ratio of odds ratios was 0.80 (95% confidence interval 0.71 to 0.90) for subjective outcomes versus a non-statistically significant effect for objective outcomes (albeit with a wide confidence interval: 95% confidence interval of 0.84 to 1.15).

Note: to make these figures more applicable to continuous outcomes, divide the natural logarithm of the ratio, i.e., ln(ratio of odds ratios), by 1.814 to yield a difference in SMD.

Performance bias

The most rigorous evidence of the effect of performance bias due to lack of participant blinding comes from a 2014 meta-epidemiological study by Hróbjartsson and colleagues which looked at trials where patients were randomized either to a blinded or an unblinded arm. They discovered that when patients were unblinded, the SMD was overestimated by 0.56 standard deviations (difference in SMD -0.56, 95% confidence interval -0.41 to -0.71) compared to when patient blinding was present. This is nearly the difference between what are conventionally considered to be modest and large SMDs (0.2 and 0.8, respectively). Note that generalizability of these findings is limited, as all of these trials were performed on alternative therapies, dominated by acupuncture. The acupuncture trials showed greater response to bias (SMD overestimated by 0.63) than non-acupuncture trials (SMD overestimated by 0.17). Also note that all outcomes were subjective.

What is the purpose of blinding? You can read more about the general concept here.

Another study, by Nüesch et al., which had a weaker design (it did not use studies where patients were randomized to a blinded or unblinded arm), found similar results for alternative therapy trials, but found much less exaggeration of subjective outcomes for non-alternative therapy trials (SMD difference -0.04, 95% confidence interval -0.10 to 0.18).

Page and colleagues did a meta-analysis of three meta-epidemiological studies focusing more on binary outcomes, including a mix of subjective and objective outcomes, which showed some evidence of the effect of inadequate or unclear blinding of participants (ratio of odds ratios 0.92, 95% confidence interval 0.81 to 1.04).

There was not enough evidence to make a statement about the importance of blinding clinicians.

Detection bias

The best available evidence of the importance of detection bias comes from three meta-epidemiological studies by Hróbjartsson et al., each focusing on a different type of outcome (continuous, binary, time-to-event). These studies are preferable because instead of comparing one trial with outcome assessment blinding to another trial without, they compare outcomes in trials where patients received both blinded and unblinded outcome assessment. For continuous outcomes, lack of assessor blinding exaggerated the SMD by 0.23 standard deviations (difference in SMD -0.23, 95% confidence interval -0.06 to -0.40), and the result was similar in trials where all patients received both blinded and unblinded assessment (difference in SMD -0.29, 95% confidence interval -0.09 to -0.49). For binary outcomes, treatment effect was overestimated when blinding of assessment was absent (ratio of odds ratios 0.64, 95% confidence interval 0.43 to 0.96). Again, the result was similar in trials where all patients received both blinded and unblinded assessment (0.70, 0.52 to 0.96). For time-to-event outcomes, “typical” trials had an overestimation of treatment effect (ratio of hazard ratios 0.73, 95% confidence interval 0.57 to 0.93) but a set of “atypical” trials, in which a new oral form of a drug was compared to its conventional IV formulation in CMV retinitis, seemed to have an underestimation of effect when there was no blinding of assessment (ratio of hazard ratios 1.33, 0.98 to 1.82 – note a ratio of ratios > 1 represents an underestimation). However, this last result should be interpreted with some caution, as splitting trials into “typical” or “atypical” was not predefined.

Note that these three studies were only able to include subjective outcomes (e.g., disease severity score, progression of disease, or if an injury was healed). Other studies included in Page et al. reported results for objective outcomes, but the confidence intervals are too wide for them to be helpful.

Attrition, reporting, and other biases

Publication bias: read a further blog here.

There was little empirical evidence of the effects of attrition, reporting, or other kinds of biases. The definition of attrition bias varied considerably between meta-epidemiological studies, which may explain the heterogeneity in results found by Page et al. For the remaining biases, the meta-epidemiological studies that were performed were small and yielded results with wide confidence intervals.

Discussion

Written in 2008, the printed version of the Cochrane Handbook states that “the evidence base remains incomplete” for the effect of bias on randomized trials. This is still true today, as we can see clear limitations to these data.

First, evidence is unequal for different kinds of bias, e.g., attrition and reporting bias have very little data, and even detection bias has little data on objective outcomes. Second, most results had at least moderate heterogeneity so, at best, the figures are a rough approximation of the effect of bias. Third, newer meta-epidemiological studies have been published since the 2016 review by Page et al. (e.g., the 2018 ROBES study), so there is the possibility that new data may change these figures. Finally, although these numbers show that bias generally leads to an overestimation of effect, bias may also favour a null effect or an underestimation of effect.

The direction of effect is not always easy to predict: for example, when allocation concealment is absent, assignment to the treatment arm may be dominated by sicker patients (as doctors may want them to get the newest therapy), which would lead to underestimation of effect, or by healthier patients (as doctors may want the trial to show that the therapy works), which would lead to an overestimation of effect. For this reason, Hróbjartsson et al. (2012) wrote that “in any individual trial it is not possible to safely predict neither the direction nor the size of any bias. We would advise against using our pooled average as a simplistic correction factor.” On the other hand, the Cochrane Handbook suggests trying to consider the likely direction and magnitude of bias. A proper solution could be to only attempt to use these figures in trials where the likely direction of bias is relatively clear (e.g., lack of blinding in a trial of treatment vs. no treatment) and not to try to calculate the true/unbiased effect (which could only be determined by performing a trial at low risk of bias), but only as an aid to understanding how much bias can influence a trial.

To give one example of how to apply these figures: in the BATHE trial, children with atopic dermatitis were randomized to emollient bath additives or usual care and the primary outcome was severity of eczema as assessed on the POEM scale by parents/carers. Since they knew how the child was treated, there is obviously high risk of detection bias. Given that we are considering a subjective outcome and it is a common treatment vs. no treatment, it is reasonable to assume that bias would favor treatment, as meta-epidemiological studies show tends to happen. The mean POEM score over 16 weeks was 7.5 for treated children and 8.4 for untreated children (a lower score is better, but the result was not statistically significant), and the standard deviation for both was 6.0 points.

Above, we found that, on average, detection bias exaggerates subjective continuous outcomes by about 0.23 standard deviations. To put this in terms of the POEM scale, we multiply this by the standard deviation of the result: 0.23 × 6.0 = 1.4. Therefore, the mean difference in effect (8.4 – 7.5 = 0.9 points) may have been exaggerated by 1.4 points simply due to the lack of unblinded assessment, to give a very rough approximation. Detection bias is likely not to pose a threat to the trial authors’ conclusion that bath emollients had no appreciable benefit in treating atopic dermatitis.