Multicentre pilot randomised clinical trial of early in-bed cycle ergometry with ventilated patients.

Introduction: Acute rehabilitation in critically ill patients can improve post-intensive care unit (post-ICU) physical function. In-bed cycling early in a patient\u27s ICU stay is a promising intervention. The objective of this study was to determine the feasibility of recruitment, intervention delivery and retention in a multi centre randomised clinical trial (RCT) of early in-bed cycling with mechanically ventilated (MV) patients. Methods: We conducted a pilot RCT conducted in seven Canadian medical-surgical ICUs. We enrolled adults who could ambulate independently before ICU admission, within the first 4 days of invasive MV and first 7 days of ICU admission. Following informed consent, patients underwent concealed randomisation to either 30 min/day of in-bed cycling and routine physiotherapy (Cycling) or routine physiotherapy alone (Routine) for 5 days/week, until ICU discharge. Our feasibility outcome targets included: accrual of 1-2 patients/month/site; \u3e80% cycling protocol delivery; \u3e80% outcomes measured and \u3e80% blinded outcome measures at hospital discharge. We report ascertainment rates for our primary outcome for the main trial (Physical Function ICU Test-scored (PFIT-s) at hospital discharge). Results: Between 3/2015 and 6/2016, we randomised 66 patients (36 Cycling, 30 Routine). Our consent rate was 84.6 % (66/78). Patient accrual was (mean (SD)) 1.1 (0.3) patients/month/site. Cycling occurred in 79.3% (146/184) of eligible sessions, with a median (IQR) session duration of 30.5 (30.0, 30.7) min. We recorded 43 (97.7%) PFIT-s scores at hospital discharge and 37 (86.0%) of these assessments were blinded. Discussion: Our pilot RCT suggests that a future multicentre RCT of early in-bed cycling for MV patients in the ICU is feasible. Trial registration number: NCT02377830

GRADE Guidelines 30: the GRADE approach to assessing the certainty of modeled evidence—An overview in the context of health decision-making

Objectives: The objective of the study is to present the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) conceptual approach to the assessment of certainty of evidence from modeling studies (i.e., certainty associated with model outputs). / Study Design and Setting: Expert consultations and an international multidisciplinary workshop informed development of a conceptual approach to assessing the certainty of evidence from models within the context of systematic reviews, health technology assessments, and health care decisions. The discussions also clarified selected concepts and terminology used in the GRADE approach and by the modeling community. Feedback from experts in a broad range of modeling and health care disciplines addressed the content validity of the approach. / Results: Workshop participants agreed that the domains determining the certainty of evidence previously identified in the GRADE approach (risk of bias, indirectness, inconsistency, imprecision, reporting bias, magnitude of an effect, dose–response relation, and the direction of residual confounding) also apply when assessing the certainty of evidence from models. The assessment depends on the nature of model inputs and the model itself and on whether one is evaluating evidence from a single model or multiple models. We propose a framework for selecting the best available evidence from models: 1) developing de novo, a model specific to the situation of interest, 2) identifying an existing model, the outputs of which provide the highest certainty evidence for the situation of interest, either “off-the-shelf” or after adaptation, and 3) using outputs from multiple models. We also present a summary of preferred terminology to facilitate communication among modeling and health care disciplines. / Conclusion: This conceptual GRADE approach provides a framework for using evidence from models in health decision-making and the assessment of certainty of evidence from a model or models. The GRADE Working Group and the modeling community are currently developing the detailed methods and related guidance for assessing specific domains determining the certainty of evidence from models across health care–related disciplines (e.g., therapeutic decision-making, toxicology, environmental health, and health economics)

Clinical utility of combinatorial pharmacogenomic testing in depression: A Canadian patient- and rater-blinded, randomized, controlled trial

The pharmacological treatment of depression consists of stages of trial and error, with less than 40% of patients achieving remission during first medication trial. However, in a large, randomized-controlled trial (RCT) in the U.S. (“GUIDED”), significant improvements in response and remission rates were observed in patients who received treatment guided by combinatorial pharmacogenomic testing, compared to treatment-as-usual (TAU). Here we present results from the Canadian “GAPP-MDD” RCT. This 52-week, 3-arm, multi-center, participant- and rater-blinded RCT evaluated clinical outcomes among patients with depression whose treatment was guided by combinatorial pharmacogenomic testing compared to TAU. The primary outcome was symptom improvement (change in 17-item Hamilton Depression Rating Scale, HAM-D17) at week 8. Secondary outcomes included response (≥50% decrease in HAM-D17) and remission (HAM-D17 ≤ 7) at week 8. Numerically, patients in the guided-care arm had greater symptom improvement (27.6% versus 22.7%), response (30.3% versus 22.7%), and remission rates (15.7% versus 8.3%) compared to TAU, although these differences were not statistically significant. Given that the GAPP-MDD trial was ultimately underpowered to detect statistically significant differences in patient outcomes, it was assessed in parallel with the larger GUIDED RCT. We observed that relative improvements in response and remission rates were consistent between the GAPP-MDD (33.0% response, 89.0% remission) and GUIDED (31.0% response, 51.0% remission) trials. Together with GUIDED, the results from the GAPP-MDD trial indicate that combinatorial pharmacogenomic testing can be an effective tool to help guide depression treatment in the context of the Canadian healthcare setting (ClinicalTrials.gov NCT02466477)

Monitoring and evaluation of breast cancer screening programmes : Selecting candidate performance indicators

In the scope of the European Commission Initiative on Breast Cancer (ECIBC) the Monitoring and Evaluation (M&E) subgroup was tasked to identify breast cancer screening programme (BCSP) performance indicators, including their acceptable and desirable levels, which are associated with breast cancer (BC) mortality. This paper documents the methodology used for the indicator selection. The indicators were identified through a multi-stage process. First, a scoping review was conducted to identify existing performance indicators. Second, building on existing frameworks for making well-informed health care choices, a specific conceptual framework was developed to guide the indicator selection. Third, two group exercises including a rating and ranking survey were conducted for indicator selection using pre-determined criteria, such as: relevance, measurability, accurateness, ethics and understandability. The selected indicators were mapped onto a BC screening pathway developed by the M&E subgroup to illustrate the steps of BC screening common to all EU countries. A total of 96 indicators were identified from an initial list of 1325 indicators. After removing redundant and irrelevant indicators and adding those missing, 39 candidate indicators underwent the rating and ranking exercise. Based on the results, the M&E subgroup selected 13 indicators: screening coverage, participation rate, recall rate, breast cancer detection rate, invasive breast cancer detection rate, cancers > 20 mm, cancers ≤10 mm, lymph node status, interval cancer rate, episode sensitivity, time interval between screening and first treatment, benign open surgical biopsy rate, and mastectomy rate. This systematic approach led to the identification of 13 BCSP candidate performance indicators to be further evaluated for their association with BC mortality

A prospective, double-blind, randomized, controlled clinical trial comparing standard wound care with adjunctive hyperbaric oxygen therapy (HBOT) to standard wound care only for the treatment of chronic, non-healing ulcers of the lower limb in patients with diabetes mellitus: a study protocol

<p>Abstract</p> <p>Background</p> <p>It has been suggested that the use of adjunctive hyperbaric oxygen therapy improves the healing of diabetic foot ulcers, and decreases the risk of lower extremity amputations. A limited number of studies have used a double blind approach to evaluate the efficacy of hyperbaric oxygen therapy in the treatment of diabetic ulcers. The primary aim of this study is to assess the efficacy of hyperbaric oxygen therapy plus standard wound care compared with standard wound care alone in preventing the need for major amputation in patients with diabetes mellitus and chronic ulcers of the lower limb.</p> <p>Methods/Design</p> <p>One hundred and eighteen (59 patients per arm) patients with non-healing diabetic ulcers of the lower limb, referred to the Judy Dan Research and Treatment Centre are being recruited if they are at least 18 years of age, have either Type 1 or 2 diabetes with a Wagner grading of foot lesions 2, 3 or 4 on lower limb not healing for at least 4 weeks. Patients receive hyperbaric oxygen therapy every day for 6 weeks during the treatment phase and are provided ongoing wound care and weekly assessments. Patients are required to return to the study centre every week for an additional 6 weeks of follow-up for wound evaluation and management. The primary outcome is freedom from having, or meeting the criteria for, a major amputation (below knee amputation, or metatarsal level) up to 12 weeks after randomization. The decision to amputate is made by a vascular surgeon. Other outcomes include wound healing, effectiveness, safety, healthcare resource utilization, quality of life, and cost-effectiveness. The study will run for a total of about 3 years.</p> <p>Discussion</p> <p>The results of this study will provide detailed information on the efficacy of hyperbaric oxygen therapy for the treatment of non-healing ulcers of the lower limb. This will be the first double-blind randomized controlled trial for this health technology which evaluates the efficacy of hyperbaric oxygen therapy in prevention of amputations in diabetic patients.</p> <p>Trial registration</p> <p>ClinicalTrials.gov Identifier: <a href="http://www.clinicaltrials.gov/ct2/show/NCT00621608">NCT00621608</a></p

GRADE Guidelines 30: The GRADE Approach to Assessing the Certainty of Modelled Evidence - an Overview in the Context of Health Decision-making.

OBJECTIVES: To present the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) conceptual approach to the assessment of certainty of evidence from modelling studies (i.e. certainty associated with model outputs). STUDY DESIGN AND SETTING: Expert consultations and, an international multi-disciplinary workshop informed development of a conceptual approach to assessing the certainty of evidence from models within the context of systematic reviews, health technology assessments, and health care decisions. The discussions also clarified selected concepts and terminology used in the GRADE approach and by the modelling community. Feedback from experts in a broad range of modelling and health care disciplines addressed the content validity of the approach. RESULTS: Workshop participants agreed, that the domains determining the certainty of evidence previously identified in the GRADE approach (risk of bias, indirectness, inconsistency, imprecision, reporting bias, magnitude of an effect, dose-response relation, and the direction of residual confounding) also apply when of assessing the certainty of evidence from models. The assessment depends on the nature of model inputs and the model itself and on whether one is evaluating evidence from a single model or multiple models. We propose a framework for selecting the best available evidence from models: 1) developing de novo a model specific to the situation of interest, 2) identifying an existing model the outputs of which provide the highest certainty evidence for the situation of interest, either "off the shelf" or after adaptation, and 3) using outputs from multiple models. We also present a summary of preferred terminology to facilitate communication among modelling and health care disciplines. CONCLUSIONS: This conceptual GRADE approach provides a framework for using evidence from models in health decision making and the assessment of certainty of evidence from a model or models. The GRADE Working Group and the modelling community are currently developing the detailed methods and related guidance for assessing specific domains determining the certainty of evidence from models across health care-related disciplines (e.g. therapeutic decision-making, toxicology, environmental health, health economics)