Prognostic models for identifying risk of poor outcome in people with acute ankle sprains: the SPRAINED development and external validation study

BACKGROUND: Ankle sprains are very common injuries. Although recovery can occur within weeks, around one-third of patients have longer-term problems. OBJECTIVES: To develop and externally validate a prognostic model for identifying people at increased risk of poor outcome after an acute ankle sprain. DESIGN: Development of a prognostic model in a clinical trial cohort data set and external validation in a prospective cohort study. SETTING: Emergency departments (EDs) in the UK. PARTICIPANTS: Adults with an acute ankle sprain (within 7 days of injury). SAMPLE SIZE: There were 584 clinical trial participants in the development data set and 682 recruited for the external validation study. PREDICTORS: Candidate predictor variables were chosen based on availability in the clinical data set, clinical consensus, face validity, a systematic review of the literature, data quality and plausibility of predictiveness of the outcomes. MAIN OUTCOME MEASURES: Models were developed to predict two composite outcomes representing poor outcome. Outcome 1 was the presence of at least one of the following symptoms at 9 months after injury: persistent pain, functional difficulty or lack of confidence. Outcome 2 included the same symptoms as outcome 1, with the addition of recurrence of injury. Rates of poor outcome in the external data set were lower than in the development data set, 7% versus 20% for outcome 1 and 16% versus 24% for outcome 2. ANALYSIS: Multiple imputation was used to handle missing data. Logistic regression models, together with multivariable fractional polynomials, were used to select variables and identify transformations of continuous predictors that best predicted the outcome based on a nominal alpha of 0.157, chosen to minimise overfitting. Predictive accuracy was evaluated by assessing model discrimination (c-statistic) and calibration (flexible calibration plot). RESULTS: (1) Performance of the prognostic models in development data set - the combined c-statistic for the outcome 1 model across the 50 imputed data sets was 0.74 [95% confidence interval (CI) 0.70 to 0.79], with good model calibration across the imputed data sets. The combined c-statistic for the outcome 2 model across the 50 imputed data sets was 0.70 (95% CI 0.65 to 0.74), with good model calibration across the imputed data sets. Updating these models, which used baseline data collected at the ED, with an additional variable at 4 weeks post injury (pain when bearing weight on the ankle) improved the discriminatory ability (c-statistic 0.77, 95% CI 0.73 to 0.82, for outcome 1 and 0.75, 95% CI 0.71 to 0.80, for outcome 2) and calibration of both models. (2) Performance of the models in the external data set - the combined c-statistic for the outcome 1 model across the 50 imputed data sets was 0.73 (95% CI 0.66 to 0.79), with a calibration plot intercept of -0.91 (95% CI -0.98 to 0.44) and slope of 1.13 (95% CI 0.76 to 1.50). The combined c-statistic for the outcome 2 model across the 50 imputed data sets was 0.63 (95% CI 0.58 to 0.69), with a calibration plot intercept of -0.25 (95% CI -0.27 to 0.11) and slope of 1.03 (95% CI 0.65 to 1.42). The updated models with the additional pain variable at 4 weeks had improved discriminatory ability over the baseline models but not better calibration. CONCLUSIONS: The SPRAINED (Synthesising a clinical Prognostic Rule for Ankle Injuries in the Emergency Department) prognostic models performed reasonably well, and showed benefit compared with not using any model; therefore, the models may assist clinical decision-making when managing and advising ankle sprain patients in the ED setting. The models use predictors that are simple to obtain. LIMITATIONS: The data used were from a randomised controlled trial and so were not originally intended to fulfil the aim of developing prognostic models. However, the data set was the best available, including data on the symptoms and clinical events of interest. FUTURE WORK: Further model refinement, including recalibration or identifying additional predictors, may be required. The effect of implementing and using either model in clinical practice, in terms of acceptability and uptake by clinicians and on patient outcomes, should be investigated. TRIAL REGISTRATION: Current Controlled Trials ISRCTN12726986. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 22, No. 64. See the NIHR Journals Library website for further project information. Funding was also recieved from the NIHR Collaboration for Leadership in Applied Health Research, Care Oxford at Oxford Health NHS Foundation Trust, NIHR Biomedical Research Centre, Oxford, and the NIHR Fellowship programme

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

The QuinteT Recruitment Intervention supported five randomized trials to recruit to target: a mixed-methods evaluation

Objective: To evaluate the impact of the QuinteT Recruitment Intervention (QRI) on recruitment in challenging randomized controlled trials (RCTs) that have applied the intervention. The QRI aims to understand recruitment difficulties and then implements “QRI actions” to address these as recruitment proceeds. Study Design and Setting: A mixed-methods study, comprising (1) before-and-after comparisons of recruitment rates and the numbers of patients approached and (2) qualitative case studies, including documentary analysis and interviews with RCT investigators. Results: Five UK-based publicly funded RCTs were included in the evaluation. All recruited to target. Randomized controlled trial 2 and RCT 5 both received up-front prerecruitment training before the intervention was applied. Randomized controlled trial 2 did not encounter recruitment issues and recruited above target from its outset. Recruitment difficulties, particularly communication issues, were identified and addressed through QRI actions in RCTs 1, 3, 4, and 5. Randomization rates significantly improved after QRI action in RCTs 1, 3, and 4. Quintet Recruitment Intervention actions addressed issues with approaching eligible patients in RCTs 3 and 5, which both saw significant increases in the number of patients approached. Trial investigators reported that the QRI had unearthed issues they had been unaware of and reportedly changed their practices after QRI action. Conclusion: There is promising evidence to suggest that the QRI can support recruitment to difficult RCTs. This needs to be substantiated with future controlled evaluations

The QuinteT Recruitment Intervention supported five randomized trials to recruit to target: a mixed-methods evaluation

ObjectiveTo evaluate the impact of the Quintet Recruitment Intervention (QRI) on recruitment in challenging randomized controlled trials (RCTs) that have applied the intervention. The QRI aims to understand recruitment difficulties, and then implements ‘QRI-actions’ to address these as recruitment proceeds.Study Design and SettingA mixed-methods study, comprising: a) before-and-after comparisons of recruitment rates and numbers of patients approached, and b) qualitative case studies, including documentary analysis and interviews with RCT investigators.ResultsFive UK-based publicly-funded RCTs were included in the evaluation. All recruited to target. RCT2 and RCT5 both received up-front pre-recruitment training before the intervention was applied. RCT2 did not encounter recruitment issues and recruited above target from its outset. Recruitment difficulties, particularly communication issues, were identified and addressed through QRI-actions in RCTs 1, 3, 4 and 5. Randomization rates significantly improved post-QRI-action in RCTs 1,3, and 4. QRI-actions addressed issues with approaching eligible patients in RCTs 3 and 5, which both saw significant increases in patients approached. Trial investigators reported that the QRI had unearthed issues they had been unaware of, and reportedly changed their practices post QRI-action.ConclusionThere is promising evidence to suggest the QRI can support recruitment to difficult RCTs. This needs to be substantiated with future controlled evaluations

The role of ionic K+ in the regulation of apoptosis

Cell shrinkage is a major characteristic of apoptotic cell death and is associated with a decrease in intracellular K+ concentration. Intracellular K+ ions have an important role in setting and modulating the plasma membrane potential and can profoundly affect the activity of a number of cellular enzymes.;Following initial investigations into the role of K+ in cell survival and apoptosis in primary cultures of cerebellar granule neurons, flux of cellular K+ following induction of apoptosis by death receptor ligation or chemical stress was assessed in Jurkat T cells loaded with the K+ ion surrogate 86Rb+. A time-dependent efflux of intracellular K+ was demonstrated that accompanies cell shrinkage, reduction of mitochondrial transmembrane potential (m) and phosphatidylserine (PS) externalisation. An apparent increase in mitochondrial K+ concentration following treatment of cells with anti-CD95 antibody was also demonstrated. Induction of CD95- or chemical-mediated apoptosis results in depolarisation of the plasma membrane that accompanies PS externalisation and reduction of m. Both depolarisation of the plasma membrane and efflux of intracellular K+ are dependent upon caspase activation in CD95- but not chemical-mediated apoptosis. Consistent with the hypothesis that efflux of intracellular K+ is required for the progression of apoptosis, formation of the caspase-activating ~700 kDa Apaf-1-containing apoptosome complex is inhibited in vitro by 50mM K+.;The data imply that K+ plays an important role in the regulation and progression of apoptosis by influencing transmembrane voltage or ion-sensitive enzymatic processes

Estimating outcomes and cost effectiveness using a single-arm clinical trial: ofatumumab for double-refractory chronic lymphocytic leukemia

Abstract Background Ofatumumab (Arzerra®, Novartis) is a treatment for chronic lymphocytic leukemia refractory to fludarabine and alemtuzumab [double refractory (DR-CLL)]. Ofatumumab was licensed on the basis of an uncontrolled Phase II study, Hx-CD20-406, in which patients receiving ofatumumab survived for a median of 13.9 months. However, the lack of an internal control arm presents an obstacle for the estimation of comparative effectiveness. Methods The objective of the study was to present a method to estimate the cost effectiveness of ofatumumab in the treatment of DR-CLL. As no suitable historical control was available for modelling, the outcomes from non-responders to ofatumumab were used to model the effect of best supportive care (BSC). This was done via a Cox regression to control for differences in baseline characteristics between groups. This analysis was included in a partitioned survival model built in Microsoft® Excel with utilities and costs taken from published sources, with costs and quality-adjusted life years (QALYs) were discounted at a rate of 3.5% per annum. Results Using the outcomes seen in non-responders, ofatumumab is expected to add approximately 0.62 life years (1.50 vs. 0.88). Using published utility values this translates to an additional 0.30 QALYs (0.77 vs. 0.47). At the list price, ofatumumab had a cost per QALY of £130,563, and a cost per life year of £63,542. The model was sensitive to changes in assumptions regarding overall survival estimates and utility values. Conclusions This study demonstrates the potential of using data for non-responders to model outcomes for BSC in cost-effectiveness evaluations based on single-arm trials. Further research is needed on the estimation of comparative effectiveness using uncontrolled clinical studies