Predicting Non Return to Work after Orthopaedic Trauma: The Wallis Occupational Rehabilitation RisK (WORRK) Model.

BACKGROUND: Workers with persistent disabilities after orthopaedic trauma may need occupational rehabilitation. Despite various risk profiles for non-return-to-work (non-RTW), there is no available predictive model. Moreover, injured workers may have various origins (immigrant workers), which may either affect their return to work or their eligibility for research purposes. The aim of this study was to develop and validate a predictive model that estimates the likelihood of non-RTW after occupational rehabilitation using predictors which do not rely on the worker's background. METHODS: Prospective cohort study (3177 participants, native (51%) and immigrant workers (49%)) with two samples: a) Development sample with patients from 2004 to 2007 with Full and Reduced Models, b) External validation of the Reduced Model with patients from 2008 to March 2010. We collected patients' data and biopsychosocial complexity with an observer rated interview (INTERMED). Non-RTW was assessed two years after discharge from the rehabilitation. Discrimination was assessed by the area under the receiver operating curve (AUC) and calibration was evaluated with a calibration plot. The model was reduced with random forests. RESULTS: At 2 years, the non-RTW status was known for 2462 patients (77.5% of the total sample). The prevalence of non-RTW was 50%. The full model (36 items) and the reduced model (19 items) had acceptable discrimination performance (AUC 0.75, 95% CI 0.72 to 0.78 and 0.74, 95% CI 0.71 to 0.76, respectively) and good calibration. For the validation model, the discrimination performance was acceptable (AUC 0.73; 95% CI 0.70 to 0.77) and calibration was also adequate. CONCLUSIONS: Non-RTW may be predicted with a simple model constructed with variables independent of the patient's education and language fluency. This model is useful for all kinds of trauma in order to adjust for case mix and it is applicable to vulnerable populations like immigrant workers

Adapting the "Chester step test" to predict peak oxygen uptake in children.

Maximal exercise testing may be difficult to perform in clinical practice, especially in obese children who have low cardiorespiratory fitness and exercise tolerance. We aimed to elaborate a model predicting peak oxygen consumption (VO2) in lean and obese children with use of the submaximal Chester step test. We performed a maximal step test, which consisted of 2-minute stages with increasing intensity to exhaustion, in 169 lean and obese children (age range: 7-16 years). VO2 was measured with indirect calorimetry. A statistical Tobit model was used to predict VO2 from age, gender, body mass index (BMI) z-score and intensity levels. Estimated VO2peak was then determined from the heart rate-VO2 linear relationship extrapolated to maximal heart rate (220 minus age, in beats.min-1). VO2 (ml/kg/min) can be predicted using the following equation: VO2 = 22.82 - [0.68*BMI z-score] - [0.46*age (years)] - [0.93*gender (male = 0; female = 1)] + [4.07*intensity level (stage 1, 2, 3 etc.)] - [0.24*BMI z-score *intensity level] - [0.34*gender*intensity level]. VO2 was lower in participants with high BMI z-scores and in female subjects. The Chester step test can assess cardiorespiratory fitness in lean and obese children in clinical settings. Our adapted equation allows the Chester step test to be used to estimate peak aerobic capacity in children

Assessing the impact of a food supplement on the nutritional status and body composition of HIV-infected Zambian women on ARVs

Background Zambia is a sub-Saharan country with one of the highest prevalence rates of HIV, currently estimated at 14%. Poor nutritional status due to both protein-energy and micronutrient malnutrition has worsened this situation. In an attempt to address this combined problem, the government has instigated a number of strategies, including the provision of antiretroviral (ARV) treatment coupled with the promotion of good nutrition. High-energy protein supplement (HEPS) is particularly promoted; however, the impact of this food supplement on the nutritional status of people living with HIV/AIDS (PLHA) beyond weight gain has not been assessed. Techniques for the assessment of nutritional status utilising objective measures of body composition are not commonly available in Zambia. The aim of this study is therefore to assess the impact of a food supplement on nutritional status using a comprehensive anthropometric protocol including measures of skinfold thickness and circumferences, plus the criterion deuterium dilution technique to assess total body water (TBW) and derive fat-free mass (FFM) and fat mass (FM). Methods/Design This community-based controlled and longitudinal study aims to recruit 200 HIV-infected females commencing ARV treatment at two clinics in Lusaka, Zambia. Data will be collected at four time points: baseline, 4-month, 8-month and 12-month follow-up visits. Outcome measures to be assessed include body height and weight, body mass index (BMI), body composition, CD4, viral load and micronutrient status. Discussion This protocol describes a study that will provide a longitudinal assessment of the impact of a food supplement on the nutritional status of HIV-infected females initiating ARVs using a range of anthropometric and body composition assessment techniques

Heat and moisture exchangers (HMEs) and heated humidifiers (HHs) in adult critically ill patients: a systematic review, meta-analysis and meta-regression of randomized controlled trials

The aims of this systematic review and meta-analysis of randomized controlled trials are to evaluate the effects of active heated humidifiers (HHs) and moisture exchangers (HMEs) in preventing artificial airway occlusion and pneumonia, and on mortality in adult critically ill patients. In addition, we planned to perform a meta-regression analysis to evaluate the relationship between the incidence of artificial airway occlusion, pneumonia and mortality and clinical features of adult critically ill patients

Predictors of return to work after a knee injury in patients hospitalized in vocational rehabilitation

Introduction.- Knee injuries are frequent in a young and active population. Most of the patients resume their professional activity but few studies were interested in factors that predict a return to work. The aim of this study is to identify these predictors from a large panel of bio-psychosocial variables. We postulated that the return to work 3 months and 2 years after discharge is mostly predicted by psychosocial variables.Patients and methods.- Prospective study, patients hospitalized for a knee injury. Variables measured: the abbreviated injury score (AIS) for the gravity of the injuries, analog visual scale for the intensity of pain, INTERMED for the bio-psychosocial complexity, SF-36 for the quality of life, HADs for the anxiety/depression symptoms and IKDC score for the knee function. Univariate logistic regressions, adjusted for age and gender, were performed in order to predict return to work.Results.- One hundred and twenty-six patients hospitalized during 8 months after the accident were included into this prospective study. A total of 73 (58%) and 75 (59%) questionnaires were available after 3 months and 2 years, respectively. The SF-36 pain was the sole predictor of return to work at 3 months (odds Ratio 1.06 [1.02-1.10], P = 0.01; for a one point increase) and 2 years (odds Ratio 1.06 [1.02-1.10], P = 0.01). At three months, other factors are SF-36 (physic sub-scale), IKDC score, the presence of a work contract and the presence of litigation. The bio-psychosocial complexity, the presence of depressive symptoms predicts the return to work at two years.Discussion.- Our working hypothesis was partially confirmed: some psychosocial factors (i.e. depressive symptoms, work contract, litigation, INTERMED) predict the return to work but the physical health and the knee function, perceived by the patient, are also correlated. Pain is the sole factor isolated at both times (i.e. 3 months and 2 years) and, consequently, appears a key element in the prediction of the return to work. Some factors are accessible to the rehabilitation program but only if an interdisciplinary approach is performed

INTERMED predicts non-return to work in an occupational rehabilitation setting for individuals with orthopaedic trauma-Part I

Introduction.- Knowledge of predictors of an unfavourable outcome, e.g. non-return to work after an injury enables to identify patients at risk and to target interventions for modifiable predictors. It has been recently shown that INTERMED; a tool to measure biopsychosocial complexity in four domains (biologic, psychologic, social and care, with a score between 0-60 points) can be useful in this context. The aim of this study was to set up a predictive model for non-return to work using INTERMED in patients in vocational rehabilitation after orthopaedic injury.Patients and methods.- In this longitudinal prospective study, the cohort consisted of 2156 consecutively included inpatients with orthopaedic trauma attending a rehabilitation hospital after a work, traffic or sport related injury. Two years after discharge, a questionnaire regarding return to work was sent (1502 returned their questionnaires). In addition to INTERMED, 18 predictors known at baseline of the rehabilitation were selected based on previous research. A multivariable logistic regression was performed.Results.- In the multivariate model, not-returning to work at 2 years was significantly predicted by the INTERMED: odds-ratio (OR) 1.08 (95% confidence interval, CI [1.06; 1.11]) for a one point increase in scale; by qualified work-status before the injury OR = 0.74, CI (0.54; 0.99), by using French as preferred language OR = 0.60, CI (0.45; 0.80), by upper-extremity injury OR = 1.37, CI (1.03; 1.81), by higher education (> 9 years) OR = 0.74, CI (0.55; 1.00), and by a 10 year increase in age OR = 1.15, CI (1.02; 1.29). The area under the receiver-operator-characteristics curve (ROC)-curve was 0.733 for the full model (INTERMED plus 18 variables).Discussion.- These results confirm that the total score of the INTERMED is a significant predictor for return to work. The full model with 18 predictors combined with the total score of INTERMED has good predictive value. However, the number of variables (19) to measure is high for the use as screening tool in a clinic