Developing and evaluating prediction models in rehabilitation populations

Diagnostic clinical prediction rules for categorising low back pain: A systematic review

BACKGROUND

Low back pain (LBP) is a common complex condition, where specific diagnoses are hard to identify. Diagnostic clinical prediction rules (CPRs) are known to improve clinical decision-making. A review of LBP diagnostic-CPRs by Haskins et al. (2015) identified six diagnostic-CPRs in derivation phases of development, with one tool ready for implementation. Recent progress on these tools is unknown. Therefore, this review aimed to investigate developments in LBP diagnostic-CPRs and evaluate their readiness for implementation.

METHODS

A systematic review was performed on five databases (Medline, Amed, Cochrane Library, PsycInfo, and CINAHL) combined with hand-searching and citation-tracking to identify eligible studies. Study and tool quality were appraised for risk of bias (Quality Assessment of Diagnostic Accuracy Studies-2), methodological quality (checklist using accepted CPR methodological standards), and CPR tool appraisal (GRade and ASsess Predictive).

RESULTS

Of 5021 studies screened, 11 diagnostic-CPRs were identified. Of the six previously known, three have been externally validated but not yet undergone impact analysis. Five new tools have been identified since Haskin et al. (2015); all are still in derivation stages. The most validated diagnostic-CPRs include the Lumbar-Spinal-Stenosis-Self-Administered-Self-Reported-History-Questionnaire and Diagnosis-Support-Tool-to-Identify-Lumbar-Spinal-Stenosis, and the StEP-tool which differentiates radicular from axial-LBP.

CONCLUSIONS

This updated review of LBP diagnostic CPRs found five new tools, all in the early stages of development. Three previously known tools have now been externally validated but should be used with caution until impact evaluation studies are undertaken. Future funding should focus on externally validating and assessing the impact of existing CPRs on clinical decision-making.

Predicting Aesthetic Outcome of the Nuss Procedure in Patients with Pectus Excavatum

Patients suffering from pectus excavatum often experience psychosocial distress due to perceived anomalies in their physical appearance. The ability to visually inform patients about their expected aesthetic outcome after surgical correction is still lacking. This study aims to develop an automatic, patient-specific model to predict aesthetic outcome after the Nuss procedure. Patients prospectively received preoperative and postoperative 3-dimensional optical surface scanning of their chest during the Nuss procedure. A prediction model was composed based on nonlinear least squares data-fitting, regression methods and a 2-dimensional Gaussian function with adjustable amplitude, variance, rotation, skewness, and kurtosis components. Morphological features of pectus excavatum were extracted from preoperative images using a previously developed surface analysis tool to generate a patient-specific model. Prediction accuracy was evaluated through cross-validation, utilizing the mean root squared deviation and maximum positive and negative deviations as performance measures. The prediction model was evaluated on 30 (90% male) prospectively imaged patients. The model achieved an average root mean squared deviation of 6.3 ± 2.0 mm, with average maximum positive and negative deviations of 12.7 ± 6.1 and -10.2 ± 5.7 mm, respectively, between the predicted and actual postoperative aesthetic result. Our developed 2-dimensional Gaussian model based on 3-dimensional optical surface images is a clinically promising tool to predict postsurgical aesthetic outcome in patients with pectus excavatum. Prediction of the aesthetic outcome after the Nuss procedure potentially improves information provision and expectation management among patients. Further research should assess whether increasing the sample size may reduce deviations and improve performance.

Which psychosocial factors are related to severe pain and functional limitation in patients with low back pain?: Psychosocial factors related to severe low back pain

BACKGROUND

Low back pain (LBP) is a global public health issue. Psychosocial factors are linked to LBP. However, there is a lack of knowledge about the relation of psychosocial factors to clinical outcomes of patients with severe LBP.

OBJECTIVE

To investigate the relationship between specific psychosocial factors with severe pain and functional limitation of patients with LBP.

METHODS

A cross-sectional study of 472 participants with LBP was conducted. Participants completed self-reported questionnaires, including psychosocial factors, characteristics of pain, and functional limitations. Two multivariable logistic regression models were performed with severe pain intensity (≥ 7 out of 10) and functional limitation (≥ 7 out of 10) (dependent variables) and 15 psychosocial factors (independent variables).

RESULTS

One hundred twenty-five (26.5%) participants had severe LBP. Patients with catastrophising symptoms were 2.21 [95%Confidence Interval (CI): 1.30, 3.77] times more likely to have severe pain and 2.72 (95%CI: 1.75, 4.23) times more likely to have severe functional limitation than patients without catastrophising symptoms. Patients with maladaptive beliefs about rest were 2.75 (95%CI: 1.37, 5.52) times more likely to present with severe pain and 1.72 (95%CI: 1.04, 2.83) times more likely to have severe functional limitation. Patients with kinesiophobia were 3.34 (95%CI: 1.36, 8.24) times more likely to present with severe pain, and patients with social isolation were 1.98 (95%CI: 1.25, 3.14) times more likely to have severe functional limitation.

CONCLUSION

Catastrophising, kinesiophobia, maladaptive beliefs about rest, and social isolation are related to unfavourable clinical outcomes of patients with LBP.

Development and external validation of a prediction model for patient-relevant outcomes in patients with chronic widespread pain and fibromyalgia

BACKGROUND

The objective of this study was to develop prediction models and explore the external validity of the models in a large sample of patients with chronic widespread pain (CWP) and fibromyalgia (FM).

METHODS

Patients with CWP and FM referred to rehabilitation services in Norway (n=986) self-reported data on potential predictors prior to entering rehabilitation, and self-reported outcomes at one-year follow-up. Logistic regression models of improvement, worsening and work status, and a linear regression model of health-related quality of life (HRQoL), were developed using lasso regression. Externally validated estimates of model performance were obtained from the validation set.

RESULTS

The number of participants in the development and the validation sets was 771 and 215 respectively; only participants with outcome data (n = 519-532 and 185, respectively) were included in the analyses. On average, HRQoL and work status changed little over one year. The prediction models included 10-11 predictors. Discrimination (AUC statistic) for prediction of outcome at follow-up was 0.71 for improvement, 0.67 for worsening, and 0.87 for working. The median absolute error of predictions of HRQoL was 0.36 (0.22-0.51). Reasonably good predictions of working at follow-up and HRQoL could be obtained using only the baseline scores as predictors.

CONCLUSIONS

Moderately complex predictions models (10-11 predictors) generated poor to excellent predictions of patient-relevant outcomes. Simple prediction models of working and HRQoL at follow-up may be nearly as accurate and more practical.

Beginning power mobility: An exploration of factors associated with child use of early power mobility devices and parent device preference

Objectives

Describe and compare young children's use of four early power mobility devices and examine associations between child and environmental factors that may influence power mobility use and parent device preference.

Design

Cross-sectional observational study.

Methods

Power Mobility Days introduced four devices: Wizzybug, Bugzi, Tiger Cub, and a switch-adapted ride-on toy car in a single 60-90 min, play-based session.

Results

A convenience sample of 74 children, aged 9-68 months (mean: 32.45, SD: 14.08) with mobility limitations, and their parents participated. Children had a range of motor, postural and communication profiles, with cerebral palsy being the most common condition (n = 55; 73.33%). Assessment of Learning Powered mobility use phase achieved ranged from 1 to 6; mean: 2.34; median: 2. For children who tried all four devices (n = 51), Friedman test (χ²: 8.27, p = 0.04) suggests Assessment of Learning Powered mobility use phase differs across devices. Of 73 parents who identified a device preference, 43 (59%) chose Wizzybug. Regression analyses suggest that access method and communication function may influence children's power mobility use, while age, access and postural support requirements may influence parent device choice.

Discussion

Parent impressions of an early power mobility device may be influenced by many factors, yet be less influenced by child performance.

Prediction of Prolonged Length of Stay for Stroke Patients on Admission for Inpatient Rehabilitation Based on the International Classification of Functioning, Disability, and Health (ICF) Generic Set: A Study from 50 Centers in China

Background

This study aimed to develop a risk prediction model for prolonged length of stay (LOS) in stroke patients in 50 inpatient rehabilitation centers in 20 provinces across mainland China based on the International Classification of Functioning, Disability, and Health (ICF) Generic Set case mix on admission.

Material/Methods

In this cohort study, 383 stroke patients were included from inpatient rehabilitation settings of 50 hospitals across mainland China. Independent predictors of prolonged LOS were identified using multivariate logistic regression analysis. A prediction model was established and then evaluated by receiver operating characteristic (ROC) curve analysis and the Hosmer-Lemeshow test.

Results

Multivariate logistic regression analysis showed that the type of medical insurance and the performance of daily activities (ICF, d230) were associated with prolonged LOS (P<0.05). Age and mobility level measured by the ICF Generic Set demonstrated no significant predictive value. The prediction model showed acceptable discrimination shown by an area under the curve (AUC) of 0.699 (95% CI, 0.646–0.752) and calibration (χ²=11.66; P=0.308).

Conclusions

The risk prediction model for prolonged LOS in stroke patients in 50 rehabilitation centers in China, based on the ICF Generic Set, showed that the scores for the type of medical insurance and the performance of daily activities (ICF, d230) on admission were independent predictors of prolonged LOS. This prediction model may allow stakeholders to estimate the risk of prolonged LOS on admission quantitatively, facilitate the financial planning, treatment regimens during hospitalization, referral after discharge, and reimbursement.

The new frontiers of rehabilitation medicine in people with chronic disabling illnesses

Because of the demographic shift and the increased proportion of patients surviving acute critical illnesses, the number of people living with severely disabling chronic diseases and, consequently, the demand for rehabilitation are expected to increase sharply over time. As underscored by the World Health Organization, there is substantial evidence that the provision of inpatient rehabilitation in specialized rehabilitation units to people with complex needs is effective in fostering functional recovery, improving health-related quality of life, increasing independence, reducing institutionalization rate, and improving prognosis. Recent studies in the real world setting reinforce the evidence that patients with ischemic heart disease or stroke benefit from rehabilitation in terms of improved prognosis. In addition, there is evidence of the effectiveness of rehabilitation for the prevention of functional deterioration in patients with complex and/or severe chronic diseases. Given this evidence of effectiveness, rehabilitation should be regarded as an essential part of the continuum of care. Nonetheless, rehabilitation still is underdeveloped and underused. Efforts should be devoted to foster healthcare professional awareness of the benefits of rehabilitation and to increase referral and participation.

Development of a multivariate model of the six-minute walked distance to predict functional exercise capacity in hypertension

BACKGROUND

Hypertension is associated with deterioration of musculoskeletal function and functional capacity. Existing prediction models for assessment of the 6-min walk test (6MWT) do not capture the disease-related functional capacity. This study developed a multivariate prediction model of the measured 6-min walked distance (6MWD_M) in hypertension and proposed target-values based on optimal therapeutic aims.

METHODS

Seventy-six patients (38 men, 56.1 ± 14.3 years, systolic pressure 156.7 ± 17.5 mmHg, diastolic pressure 92.9 ± 6.9 mmHg) underwent anamnesis, physical examination, and laboratory analysis. Functional capacity was assessed using the 6MWT, being the 6MWD_M considered as the dependent variable. Independent variables included sex (S, coded 'male' = 1, 'female' = 0), age (A), body height (H), body mass, mean blood pressure (MBP), and physical activity (IPAQ, coded 1-5). Target-values were derived from theoretical scenarios of optimal blood pressure and physical activity, separately and combined.

RESULTS

Patients walked 324.5 ± 10.1 m in the average of two trials 30-min apart. Pearson's correlation coefficient showed moderate-to-weak significant associations between 6MWD_M and all independent variables. The final multivariate model was 6MWD_P = 611.347-4.446 × MBP + 267.630 × H - 1.511 × A + IPAQ_code + S_code (adjusted R² = 0.680, SE of bias = 6.3 m), suggesting that clinical, anthropometric, and hemodynamic information determines functional capacity. Predicted values yielded a group-average of 325 ± 87 m. Target-values under the optimal scenario resulted in 420 ± 60 m.

CONCLUSIONS

Sex (men), higher body height, higher physical activity, lower mean blood pressure, and lower age are independently correlated with higher 6MWD_M in patients with hypertension. Target-values can be estimated for therapeutic aims related to hemodynamics and lifestyle.

Rehabilitation Outcomes of Patients With Severe Disability Poststroke

OBJECTIVE

To characterize rehabilitation outcomes of patients with severe poststroke motor impairment (MI) and develop a predictive model for treatment failure.

DESIGN

Retrospective cohort study. Correlates of treatment failure, defined as the persistence of severe MI after rehabilitation, were identified using logistic regression analysis. Then, an integer-based scoring rule was developed from the logistic model.

SETTING

Three specialized inpatient rehabilitation facilities.

PARTICIPANTS

Patients (N=1265) classified as case-mix groups (CMGs) 0108, 0109, and 0110 of the Medicare classification system.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURE

Change in the severity of MI, as assessed by the FIM, from admission to discharge.

RESULTS

Median FIM-motor (FIM-M) score increased from 17 (interquartile range [IQR] 14-23) to 38 (IQR, 25-55) points. Median proportional recovery, as expressed by FIM-M effectiveness, was 26% (IQR, 12-47). Median FIM-M change was 18 (IQR, 9-34) points. About 38.5% patients achieved the minimal clinically important difference. Eighteen point six percent and 32.0% of the patients recovered to a stage of either mild (FIM-M ≥62) or moderate (FIM-M 38-61) MI, respectively. All between-CMG differences were statistically significant. Outcomes have also been analyzed according to classification systems used in Australia and Canada. The scoring rule had an area under the curve of 0.833 (95% confidence interval, 0.808-0.858). Decision curve analysis displayed large net benefit of using the risk score compared with the treat all strategy.

CONCLUSIONS

This study provides a snapshot of rehabilitation outcomes in a large cohort of patients with severe poststroke MI, thus filling a gap in knowledge. The scoring rule accurately identified the patients at risk for treatment failure.

All metrics are equal, but some metrics are more equal than others: A systematic search and review on the use of the term 'metric'

OBJECTIVE

To examine the use of the term 'metric' in health and social sciences' literature, focusing on the interval scale implication of the term in Modern Test Theory (MTT).

MATERIALS AND METHODS

A systematic search and review on MTT studies including 'metric' or 'interval scale' was performed in the health and social sciences literature. The search was restricted to 2001-2005 and 2011-2015. A Text Mining algorithm was employed to operationalize the eligibility criteria and to explore the uses of 'metric'. The paradigm of each included article (Rasch Measurement Theory (RMT), Item Response Theory (IRT) or both), as well as its type (Theoretical, Methodological, Teaching, Application, Miscellaneous) were determined. An inductive thematic analysis on the first three types was performed.

RESULTS

70.6% of the 1337 included articles were allocated to RMT, and 68.4% were application papers. Among the number of uses of 'metric', it was predominantly a synonym of 'scale'; as adjective, it referred to measurement or quantification. Three incompatible themes 'only RMT/all MTT/no MTT models can provide interval measures' were identified, but 'interval scale' was considerably more mentioned in RMT than in IRT.

CONCLUSION

'Metric' is used in many different ways, and there is no consensus on which MTT metric has interval scale properties. Nevertheless, when using the term 'metric', the authors should specify the level of the metric being used (ordinal, ordered, interval, ratio), and justify why according to them the metric is at that level.

Objective and Subjective Burden of Informal Caregivers 4 Years After a Severe Traumatic Brain Injury: Results From the PariS-TBI Study

OBJECTIVE

Prospective assessment of informal caregiver (IC) burden 4 years after the traumatic brain injury of a relative.

SETTING

Longitudinal cohort study (metropolitan Paris, France).

PARTICIPANTS

Home dwelling adults (N = 98) with initially severe traumatic brain injury and their primary ICs.

MAIN OUTCOME MEASURES

Informal caregiver objective burden (Resource Utilization in Dementia measuring Informal Care Time [ICT]), subjective burden (Zarit Burden Inventory), monetary self-valuation of ICT (Willingness-to-pay, Willingness-to-accept).

RESULTS

Informal caregivers were women (81%) assisting men (80%) of mean age of 37 years. Fifty-five ICs reported no objective burden (ICT = 0) and no/low subjective burden (average Zarit Burden Inventory = 12.1). Forty-three ICs reported a major objective burden (average ICT = 5.6 h/d) and a moderate/severe subjective burden (average Zarit Burden Inventory = 30.3). In multivariate analyses, higher objective burden was associated with poorer Glasgow Outcome Scale-Extended scores, with more severe cognitive disorders (Neurobehavioral Rating Scale-revised) and with no coresidency status; higher subjective burden was associated with poorer Glasgow Outcome Scale-Extended scores, more Neurobehavioral Rating Scale-revised disorders, drug-alcohol abuse, and involvement in litigation. Economic valuation showed that on average, ICs did not value their ICT as free and preferred to pay a mean Willingness-to-pay = &OV0556;17 per hour to be replaced instead of being paid for providing care themselves (Willingness-to-accept = &OV0556;12).

CONCLUSION

Four years after a severe traumatic brain injury, 44% of ICs experienced a heavy multidimensional burden.

Prediction of transition to psychosis in patients with a clinical high risk for psychosis: a systematic review of methodology and reporting

BACKGROUND

To enhance indicated prevention in patients with a clinical high risk (CHR) for psychosis, recent research efforts have been increasingly directed towards estimating the risk of developing psychosis on an individual level using multivariable clinical prediction models. The aim of this study was to systematically review the methodological quality and reporting of studies developing or validating such models.

METHOD

A systematic literature search was carried out (up to 14 March 2016) to find all studies that developed or validated a clinical prediction model predicting the transition to psychosis in CHR patients. Data were extracted using a comprehensive item list which was based on current methodological recommendations.

RESULTS

A total of 91 studies met the inclusion criteria. None of the retrieved studies performed a true external validation of an existing model. Only three studies (3.5%) had an event per variable ratio of at least 10, which is the recommended minimum to avoid overfitting. Internal validation was performed in only 14 studies (15%) and seven of these used biased internal validation strategies. Other frequently observed modeling approaches not recommended by methodologists included univariable screening of candidate predictors, stepwise variable selection, categorization of continuous variables, and poor handling and reporting of missing data.

CONCLUSIONS

Our systematic review revealed that poor methods and reporting are widespread in prediction of psychosis research. Since most studies relied on small sample sizes, did not perform internal or external cross-validation, and used poor model development strategies, most published models are probably overfitted and their reported predictive accuracy is likely to be overoptimistic.

Patient Effort in Traumatic Brain Injury Inpatient Rehabilitation: Course and Associations With Age, Brain Injury Severity, and Time Postinjury

OBJECTIVE

To describe patients' level of effort in occupational, physical, and speech therapy sessions during traumatic brain injury (TBI) inpatient rehabilitation and to evaluate how age, injury severity, cognitive impairment, and time are associated with effort.

DESIGN

Prospective, multicenter, longitudinal cohort study.

SETTING

Acute TBI rehabilitation programs.

PARTICIPANTS

Patients (N=1946) receiving 138,555 therapy sessions.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Effort in rehabilitation sessions rated on the Rehabilitation Intensity of Therapy Scale, FIM, Comprehensive Severity Index brain injury severity score, posttraumatic amnesia (PTA), and Agitated Behavior Scale (ABS).

RESULTS

The Rehabilitation Intensity of Therapy Scale effort ratings in individual therapy sessions closely conformed to a normative distribution for all 3 disciplines. Mean Rehabilitation Intensity of Therapy Scale ratings for patients' therapy sessions were higher in the discharge week than in the admission week (P<.001). For patients who completed 2, 3, or 4 weeks of rehabilitation, differences in effort ratings (P<.001) were observed between 5 subgroups stratified by admission FIM cognitive scores and over time. In linear mixed-effects modeling, age and Comprehensive Severity Index brain injury severity score at admission, days from injury to rehabilitation admission, days from admission, and daily ratings of PTA and ABS score were predictors of level of effort (P<.0001).

CONCLUSIONS

Patients' level of effort can be observed and reliably rated in the TBI inpatient rehabilitation setting using the Rehabilitation Intensity of Therapy Scale. Patients who sustain TBI show varying levels of effort in rehabilitation therapy sessions, with effort tending to increase over the stay. PTA and agitated behavior are primary risk factors that substantially reduce patient effort in therapies.

Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD): The TRIPOD Statement

CONTEXT

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed.

OBJECTIVE

The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes.

EVIDENCE ACQUISITION

This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors.

EVIDENCE SYNTHESIS

The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document.

CONCLUSIONS

To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

PATIENT SUMMARY

The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes.

Outcome prediction in home- and community-based brain injury rehabilitation using the Mayo-Portland Adaptability Inventory

The objective of the study was to develop statistical formulas to predict levels of community participation on discharge from post-hospital brain injury rehabilitation using retrospective data analysis. Data were collected from seven geographically distinct programmes in a home- and community-based brain injury rehabilitation provider network. Participants were 642 individuals with post-traumatic brain injury. Interventions consisted of home- and community-based brain injury rehabilitation. The main outcome measure was the Mayo-Portland Adaptability Inventory (MPAI-4) Participation Index. Linear discriminant models using admission MPAI-4 Participation Index score and log chronicity correctly predicted excellent (no to minimal participation limitations), very good (very mild participation limitations), good (mild participation limitations), and limited (significant participation limitations) outcome levels at discharge. Predicting broad outcome categories for post-hospital rehabilitation programmes based on admission assessment data appears feasible and valid. Equations to provide patients and families with probability statements on admission about expected levels of outcome are provided. It is unknown to what degree these prediction equations can be reliably applied and valid in other settings.

Validation and impact analysis of prognostic clinical prediction rules for low back pain is needed: a systematic review

OBJECTIVES

To identify prognostic forms of clinical prediction rules (CPRs) related to the nonsurgical management of adults with low back pain (LBP) and to evaluate their current stage of development.

STUDY DESIGN AND SETTING

Systematic review using a sensitive search strategy across seven databases with hand searching and citation tracking.

RESULTS

A total of 10,005 records were screened for eligibility with 35 studies included in the review. The included studies report on the development of 30 prognostic LBP CPRs. Most of the identified CPRs are in their initial phase of development. Three CPRs were found to have undergone validation--the Cassandra rule for predicting long-term significant functional limitations and the five-item and two-item Flynn manipulation CPRs for predicting a favorable functional prognosis in patients being treated with lumbopelvic manipulation. No studies were identified that investigated whether the implementation of a CPR resulted in beneficial patient outcomes or improved resource efficiencies.

CONCLUSION

Most of the identified prognostic CPRs for LBP are in the initial phase of development and are consequently not recommended for direct application in clinical practice at this time. The body of evidence provides emergent confidence in the limited predictive performance of the Cassandra rule and the five-item Flynn manipulation CPR in comparable clinical settings and patient populations.

Transparent reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement

Prediction models are developed to aid healthcare providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision-making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) initiative developed a set of recommendations for the reporting of studies developing, validating or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a web-based survey and revised during a 3-day meeting in June 2011 with methodologists, healthcare professionals and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study, regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement

BACKGROUND

Prediction models are developed to aid healthcare providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision-making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed.

MATERIALS AND METHODS

The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) initiative developed a set of recommendations for the reporting of studies developing, validating or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, healthcare professionals and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors.

RESULTS

The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document.

CONCLUSIONS

To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Diagnostic clinical prediction rules for specific subtypes of low back pain: a systematic review

STUDY DESIGN

Systematic review.

OBJECTIVES

To identify diagnostic clinical prediction rules (CPRs) for low back pain (LBP) and to assess their readiness for clinical application.

BACKGROUND

Significant research has been invested into the development of CPRs that may assist in the meaningful subgrouping of patients with LBP. To date, very little is known about diagnostic forms of CPRs for LBP, which relate to the present status or classification of an individual, and whether they have been developed sufficiently to enable their application in clinical practice.

METHODS

A sensitive electronic search strategy using 7 databases was combined with hand searching and citation tracking to identify eligible studies. Two independent reviewers identified relevant studies for inclusion using a 2-stage selection process. The quality appraisal of included studies was conducted by 2 independent raters using the Quality Assessment of Diagnostic Accuracy Studies-2 and checklists composed of accepted methodological standards for the development of CPRs.

RESULTS

Of 10 014 studies screened for eligibility, the search identified that 13 diagnostic CPRs for LBP have been derived. Among those, 1 tool for identifying lumbar spinal stenosis and 2 tools for identifying inflammatory back pain have undergone validation. No impact analysis studies were identified.

CONCLUSION

Most diagnostic CPRs for LBP are in their initial development phase and cannot be recommended for use in clinical practice at this time. Validation and impact analysis of the diagnostic CPRs identified in this review are warranted, particularly for those tools that meet an identified unmet need of clinicians who manage patients with LBP.

LEVEL OF EVIDENCE

Diagnosis, level 2a-.

Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): the TRIPOD Statement

BACKGROUND

Prediction models are developed to aid healthcare providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision-making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed.

METHODS

An extensive list of items based on a review of the literature was created, which was reduced after a web-based survey and revised during a 3-day meeting in June 2011 with methodologists, healthcare professionals and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors.

RESULTS

The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study.

CONCLUSION

The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. A complete checklist is available at http://www.tripod-statement.org.

Development and Validation of Prognostic Indices for Recovery of Physical Functioning Following Stroke: Part 1

OBJECTIVE

To develop a prognostic index using Functional Independence Measure grades and stages that would enable clinicians to determine the likelihood of achieving a level of minimum assistance with physical functioning after a stroke. Grades define varying levels of physical function, and stages define varying levels of cognitive functioning.

DESIGN

Retrospective cohort study.

SETTING

Veterans Affairs Medical Centers throughout the United States.

PARTICIPANTS

Veterans with a diagnosis of a new stroke discharged between October 1, 2006, and September 30, 2008, who were below physical grade IV (requiring minimal assistance) at initial rehabilitation assessment.

MAIN OUTCOME MEASURE

Achievement of physical grade IV or above at final rehabilitation assessment.

RESULTS

Physical grade IV was reached by 25.8% of participants who were initially below this grade. Seven variables remained independently predictive of physical grade IV after adjustment. These variables were assigned the following points: age, ≤69 years = 2, 70-79 years = 1, ≥80 years = 0; initial physical grade, I = 0, II = 3, III = 4; initial cognitive stage, I or II = 0, III = 2, IV or V = 3, VI or VII = 4; absence of renal failure = 1; no serious nutritional compromise = 3; the type of rehabilitation services received, consultative = 0, comprehensive = 4; and recovery time between admission and discharge physical grade assessment, 1-2 days = 0, 3-7 days = 4, and ≥8 days = 5. The area under the receiver operating characteristic curve was 0.84 and 0.83 for the point system in the derivation and validation cohorts, respectively. The Hosmer-Lemeshow statistic was not significant (P = .93) in the derivation cohort, indicating that the regression model demonstrated adequate fit. The proportions of patients recovered to physical grade IV in the first (score ≥9), second (score = 10-12), third (score = 13-15), and fourth (score >15) score quartiles were 2.72%, 11.38%, 28.96%, and 60.34%, respectively.

CONCLUSION

By using a simple tool, clinicians can forecast the likelihood of recovery to or above the physical grade IV benchmark by the conclusion of rehabilitation services during the acute stroke hospitalization.

Development and Validation of Prognostic Indices for Recovery of Physical Functioning Following Stroke: Part 2

OBJECTIVE

To develop a prognostic index for achievement of modified independence (Functional Independence Measure grade VI) after completion of either comprehensive or consultative rehabilitation after stroke.

DESIGN

Retrospective cohort study.

SETTING

Veterans Affairs Medical Centers (VAMCs) throughout the United States.

PARTICIPANTS

Data included 5316 patients with stroke discharged from VAMCs who received rehabilitation services while hospitalized and who were physically dependent at initial assessment. The index was derived with use of 60% of the sample and validated in the remaining 40% of the sample. Points derived from the β coefficients of a multivariable logistic model were added to scores that were associated with the probability of recovery.

MAIN OUTCOME MEASURE

Recovery to modified independence or above at final rehabilitation assessment, defined as when patients no longer need physical assistance with eating; grooming; dressing the upper and lower body; toileting; sphincter management; bed to chair, toilet, and tub transfers; and walking/wheelchair use and when they require no more than supervision with bathing or climbing stairs.

RESULTS

Seven independent predictors were identified through logistic regression in the derivation sample: initial physical grade (I or II = 0 points; III = 2 points; IV = 4 points; V = 5 points), initial cognitive stage (I or II = 0 points; III = 2 points; IV = 3 points, V or VI = 4 points; VII =5 points), type of rehabilitation (consultative = 0 points; comprehensive = 4 points), age (<60 years = 3 points; 60-79 years = 2 points; ≥80 years = 0 points), time from initial to final physical grade assessment (1-2 days = 0 points; ≥3 days = 2 points), absence of urinary procedures (3 points), and absence of diabetes with complications (1 point). The following proportions of patients recovered to physical grade VI for the first, second, third, and fourth quartile scores, respectively: 0.59% (score ≤9), 3.87% (score = 9-11), 14.19% (score = 12-15), and 37.38% (score ≥16).

CONCLUSION

Functional recovery to physical grade VI can be predicted on the basis of patients' initial status after a stroke occurs and the type of rehabilitation services to be provided by using a simple scoring system.

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement

Prediction models are developed to aid health-care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health-care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. The TRIPOD Group

BACKGROUND

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed.

METHODS

The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors.

RESULTS

The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document.

CONCLUSIONS

To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration

The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) Statement includes a 22-item checklist, which aims to improve the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. This explanation and elaboration document describes the rationale; clarifies the meaning of each item; and discusses why transparent reporting is important, with a view to assessing risk of bias and clinical usefulness of the prediction model. Each checklist item of the TRIPOD Statement is explained in detail and accompanied by published examples of good reporting. The document also provides a valuable reference of issues to consider when designing, conducting, and analyzing prediction model studies. To aid the editorial process and help peer reviewers and, ultimately, readers and systematic reviewers of prediction model studies, it is recommended that authors include a completed checklist in their submission. The TRIPOD checklist can also be downloaded from www.tripod-statement.org.

Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Modification of diet in renal disease (MDRD) study and CKD epidemiology collaboration (CKD-EPI) equations for Taiwanese adults

Background

Estimated glomerular filtration rate (eGFR) using the Modification of Diet in Renal Disease (MDRD) study or the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations may not be accurate for Asians; thus, we developed modified eGFR equations for Taiwanese adults.

Methods

This cross-sectional study compared the Taiwanese eGFR equations, the MDRD study, and the CKD-EPI equations with inulin clearance (C_in). A total of 695 adults including 259 healthy volunteers and 436 CKD patients were recruited. Participants from the Kaohsiung Medical University Hospital were used as the development set (N = 556) to develop the Taiwanese eGFR equations, whereas participants from the National Taiwan University Hospital were used as the validation set (N = 139) for external validation.

Results

The Taiwanese eGFR equations were developed by using the extended Bland-Altman plot in the development set. The Taiwanese MDRD equation was 1.309×MDRD^0.912, Taiwanese CKD-EPI was 1.262×CKD-EPI^0.914 and Taiwanese four-level CKD-EPI was 1.205×four-level CKD-EPI^0.914. In the validation set, the Taiwanese equations had the lowest bias, the Taiwanese equations and the Japanese CKD-EPI equation had the lowest RMSE, whereas the Taiwanese and the Japanese equations had the best precision and the highest P₃₀ among all equations. However, the Taiwanese MDRD equation had higher concordance correlation than did the Taiwanese CKD-EPI, the Taiwanese four-level CKD-EPI and the Japanese equations. Moreover, only the Taiwanese equations had no proportional bias among all of the equations. Finally, the Taiwanese MDRD equation had the best diagnostic performance in terms of ordinal logistic regression among all of the equations.

Conclusion

The Taiwanese MDRD equation is better than the MDRD, CKD-EPI, Japanese, Asian, Thai, Taiwanese CKD-EPI, and Taiwanese four-level CKD-EPI equations for Taiwanese adults.

One-year all-cause mortality after stroke: a prediction model

OBJECTIVE

By using data from Department of Veterans Affairs (VA) national databases, this article presents and internally validates a 1-year all-cause mortality prediction index after hospitalization for acute stroke.

DESIGN

An observational cohort.

SETTING

VA medical centers.

PARTICIPANTS

Veterans with a diagnosis of a new stroke who were discharged between October 1, 2006, and September 30, 2008.

MAIN OUTCOME MEASURE

Death due to any cause that occurred between the index hospital discharge date and the 1-year anniversary of that date.

RESULTS

Within 1-year after discharge, 1542 (12.3%) of the total 12,565 patients had died. Seventeen risk factors known at the point of hospital discharge remained in the predictive model of 1-year postdischarge mortality after backward selection, including advanced age, admission from extended care, type of stroke, 8 comorbid conditions, 4 types of procedures that occurred during the index hospitalization, hospital length of stay (longer than 3 weeks), and discharge location. We assigned a score to each variable in the final model and a risk score was determined for each patient by adding up the points for all risk factors present. According to these risk scores, the patients were divided into approximate quartiles that yielded low, moderate, high, and highest mortality likelihood strata. The risk of 1-year mortality ranged from 2.24% in the lowest quartile to 29.50% in the highest quartile in the derivation cohort and from 2.11%-30.77% in the validation cohort. Model discrimination demonstrated an area under the receiver operating characteristic curve of 0.785 in the derivation cohort and 0.787 in the validation cohort. The Hosmer-Lemeshow goodness of fit indicated that the model fit was adequate (P = .69).

CONCLUSION

When using readily available data, a simple index that stratifies stroke patients at hospital discharge according to low, moderate, high, and highest likelihood of all-cause 1-year mortality is feasible and can inform the postdischarge planning process, depending on level of risk.

The effectiveness of selected Tai Chi exercises in a program of strategic rehabilitation aimed at improving the self-care skills of patients aroused from prolonged coma after severe TBI

Background

Difficulties in self-care constitute a very common problem for patients recovering from prolonged coma after a severe TBI, and a major factor reducing their quality of life. Effective new rehabilitation programs that would help solve this problem are urgently needed. The purpose of our experiment was to evaluate improvement in this respect in a group of patients aroused from prolonged coma who participated in a goal-oriented rehabilitation program (Rehab-3), enhanced with selected elements of Tai-Chi.

Material/Methods

We examined 40 patients aroused from prolonged coma after a severe TBI, undergoing long-term rehabilitation according to a standard phased rehabilitation program. These patients were divided into two numerically even groups: a control group treated according to the standard program, and an experimental group, who received an additional goal oriented program enhanced with selected Tai-Chi exercises. The research methods included analysis of documentation (MRI, CT), a structured clinical interview, and the Standard Self-Care Scale.

Results

The experimental group achieved significant improvement of self-care skills, whereas in the control group the improvement was slight and not statistically significant. The value of co-efficient j (0.64) indicates a very strong association between the rehabilitation procedure and improved self-care in the experimental group, but not in the control group.

Conclusions

Our results confirmed that a goal-oriented rehabilitation program enhanced with elements of Tai-Chi was more effective than the standard program in improving the performance of activities of daily living.

Evidence-based practice for rehabilitation professionals: concepts and controversies

This article describes evidence-based practice (EBP) in the health professions and sciences in general and in the rehabilitation disciplines specifically. It discusses the following: what counts as evidence and how that has changed over the last 4 decades, trends in the short history of evidence-based medicine and EBP, the fallacious nature of most criticisms of EBP, (perceived) shortcomings of clinical research and the resulting evidence in rehabilitation, resources available to clinicians who want their practice to be evidence-based, and the barriers these clinicians face in keeping up with the evidence and applying it in practice. Lastly, it describes how the development of a new art and science, knowledge translation, may play a role in truly making EBP feasible in rehabilitation services.