Single-cut osteotomy for correction of a complex multiplanar deformity of the radius in a Shetland pony foal

Objective To describe the surgical correction of a multiplanar deformity of the radius in a pony using a single-cut osteotomy. Study design Case report. Animals A 9-week-old male Shetland pony foal with a bodyweight of 47 kg. Methods The foal presented with a complex multiplanar deformity of the right radius. A 3-dimensional model of the bone was created based on computed tomography (CT) imaging. To correct the deformity, the cutting plane for a single-cut osteotomy was calculated following the mathematical approach described by Sangeorzan et al. After osteotomy, the bone was realigned and stabilized with two 4.5 locking compression plates (LCPs). Results Recovery from surgery was uneventful, and the foal remained comfortable. A CT exam 15 weeks after surgery revealed that diaphyseal deformities improved substantially in procurvatum (from 8° to 1°), varus (from 27° to 0°), and rotation (30° to 5°). The operated radius was 2.1 cm shorter than the left. Eighteen-month follow up confirmed a functionally and cosmetically acceptable outcome. Conclusion The single-cut osteotomy resulted in the successful correction of a multiplanar equine long-bone deformity with a favorable outcome in a Shetland pony. Clinical significance Single-cut osteotomy is an alternative surgical technique for the correction of complex diaphyseal long-bone equine deformities. Computed tomography data and the possibility of printing 3D models provides a significant advantage for rehearsing the procedure and for evaluating the correction that was achieved

Crowdsourcing hypothesis tests: Making transparent how design choices shape research results

To what extent are research results influenced by subjective decisions that scientists make as they design studies? Fifteen research teams independently designed studies to answer fiveoriginal research questions related to moral judgments, negotiations, and implicit cognition. Participants from two separate large samples (total N > 15,000) were then randomly assigned to complete one version of each study. Effect sizes varied dramatically across different sets of materials designed to test the same hypothesis: materials from different teams renderedstatistically significant effects in opposite directions for four out of five hypotheses, with the narrowest range in estimates being d = -0.37 to +0.26. Meta-analysis and a Bayesian perspective on the results revealed overall support for two hypotheses, and a lack of support for three hypotheses. Overall, practically none of the variability in effect sizes was attributable to the skill of the research team in designing materials, while considerable variability was attributable to the hypothesis being tested. In a forecasting survey, predictions of other scientists were significantly correlated with study results, both across and within hypotheses. Crowdsourced testing of research hypotheses helps reveal the true consistency of empirical support for a scientific claim.</div

Crowdsourcing hypothesis tests: making transparent how design choices shape research results

To what extent are research results influenced by subjective decisions that scientists make as they design studies? Fifteen research teams independently designed studies to answer five original research questions related to moral judgments, negotiations, and implicit cognition. Participants from two separate large samples (total N > 15,000) were then randomly assigned to complete one version of each study. Effect sizes varied dramatically across different sets of materials designed to test the same hypothesis: materials from different teams rendered statistically significant effects in opposite directions for four out of five hypotheses, with the narrowest range in estimates being d = -0.37 to +0.26. Meta-analysis and a Bayesian perspective on the results revealed overall support for two hypotheses, and a lack of support for three hypotheses. Overall, practically none of the variability in effect sizes was attributable to the skill of the research team in designing materials, while considerable variability was attributable to the hypothesis being tested. In a forecasting survey, predictions of other scientists were significantly correlated with study results, both across and within hypotheses. Crowdsourced testing of research hypotheses helps reveal the true consistency of empirical support for a scientific claim