Gait analysis and functional outcome in patients after Lisfranc injury treatment

Introduction: Lisfranc injuries involve any bony or ligamentous disruption of the tarsometatarsal joint. Outcome results after treatment are mainly evaluated using patient-reported outcome measures (PROM), physical examination and radiographic findings. Less is known about the kinematics during gait.Methods: Nineteen patients (19 feet) treated for Lisfranc injury were recruited. Patients with conservative treatment and surgical treatment consisting of open reduction and internal fixation (ORIF) or primary arthrodesis were included. PROM, radiographic findings and gait analysis using the Oxford Foot Model (OFM) were analysed. Results were compared with twenty-one healthy subjects (31 feet). Multivariable logistic regression was used to determine factors influencing outcome.Results: Patients treated for Lisfranc injury had a significantly lower walking speed than healthy subjects (P &lt;0.001). There was a significant difference between the two groups regarding the range of motion (ROM) in the sagittal plane (flexion-extension) in the midfoot durieng the push-off phase (p &lt;0.001). The ROM in the sagittal plane was significantly correlated with the AOFAS midfoot score (r2 = 0.56, p = 0.012), FADI (r(2) = 0.47, p = 0.043) and the SF-36-physical impairment score (r(2) = 0.60, p = 0.007) but not with radiographic parameters for quality of reduction. In a multivariable analysis, the best explanatory factors were ROM in the sagittal plane during the push-off phase (beta = 0.707, p = 0.001), stability (beta = 0.423, p = 0.028) and BMI (beta = -0.727 p = &lt;0.001). This prediction model explained 87% of patient satisfaction.Conclusions: This study showed that patients treated for Lisfranc injury had significantly lower walking speed and significantly lower flexion/extension in the midfoot than healthy subjects. The ROM in these patients was significantly correlated with PROM, but not with radiographic quality of reduction. Most important satisfaction predictors were BMI, ROM in the sagittal plane during the push-off phase and fracture stability. (c) 2017 European Foot and Ankle Society. Published by Elsevier Ltd. All rights reserved.</p

Post-extubation stridor after prolonged intubation in the pediatric intensive care unit (PICU): a prospective observational cohort study

Purpose: Prolonged endotracheal intubation may lead to laryngeal damage, with stridor being the most relevant clinical symptom. Our objective was to determine the incidence of post-extubation stridor and their clinical consequences in children within a tertiary referral center and to identify contributing factors. Methods: 150 children, aged 0–16 years, intubated for more than 24 h were prospectively enrolled until discharge of the hospital. Potential relevant factors, thought to mediate the risk of laryngeal damage, were recorded and analyzed. Results: The median duration of intubation was 4 days, ranging from 1 to 31 days. Stridor following extubation occurred in 28 patients (18.7%); 3 of them required reintubation due t

Constraint Programming for LNG Ship Scheduling and Inventory Management

Abstract We propose a constraint programming approach for the optimization of inventory routing in the liquefied natural gas industry. We present two constraint programming models that rely on a disjunctive scheduling representation of the problem. We also propose an iterative search heuristic to generate good feasible solutions for these models. Computational results on a set of largescale test instances demonstrate that our approach can find better solutions than existing approaches based on mixed integer programming, while being 4 to 10 times faster on average

Predictors of treatment dropout in patients with posttraumatic stress disorder due to childhood abuse

Background: Knowledge about patient characteristics predicting treatment dropout for post-traumatic stress disorder (PTSD) is scarce, whereas more understanding about this topic may give direction to address this important issue. Method: Data were obtained from a randomized controlled trial in which a phase-based treatment condition (Eye Movement Desensitization and Reprocessing [EMDR] therapy preceded by Skills Training in Affect and Interpersonal Regulation [STAIR]; n = 57) was compared with a direct trauma-focused treatment (EMDR therapy only; n = 64) in people with a PTSD due to childhood abuse. All pre-treatment variables included in the trial were examined as possible predictors for dropout using machine learning techniques. Results: For the dropout prediction, a model was developed using Elastic Net Regularization. The ENR model correctly predicted dropout in 81.6% of all individuals. Males, with a low education level, suicidal thoughts, problems in emotion regulation, high levels of general psychopathology and not using benzodiazepine medication at screening proved to have higher scores on dropout. Conclusion: Our results provide directions for the development of future programs in addition to PTSD treatment or for the adaptation of current treatments, aiming to reduce treatment dropout among patients with PTSD due to childhood abuse

External validation and clinical utility assessment of PREDICT breast cancer prognostic model in young, systemic treatment-naïve women with node-negative breast cancer

Background: The validity of the PREDICT breast cancer prognostic model is unclear for young patients without adjuvant systemic treatment. This study aimed to validate PREDICT and assess its clinical utility in young women with node-negative breast cancer who did not receive systemic treatment. Methods: We selected all women from the Netherlands Cancer Registry who were diagnosed with node-negative breast cancer under age 40 between 1989 and 2000, a period when adjuvant systemic treatment was not standard practice for women with node-negative disease. We evaluated the calibration and discrimination of PREDICT using the observed/expected (O/E) mortality ratio, and the area under the receiver operating characteristic curve (AUC), respectively. Additionally, we compared the potential clinical utility of PREDICT for selectively administering chemotherapy to the chemotherapy-to-all strategy using decision curve analysis at predefined thresholds. Results: A total of 2264 women with a median age at diagnosis of 36 years were included. Of them, 71.2% had estrogen receptor (ER)-positive tumors and 44.0% had grade 3 tumors. Median tumor size was 16 mm. PREDICT v2.2 underestimated 10-year all-cause mortality by 33% in all women (O/E ratio:1.33, 95%CI:1.22–1.43). Model discrimination was moderate overall (AUC10-year:0.65, 95%CI:0.62–0.68), and poor for women with ER-negative tumors (AUC10-year:0.56, 95%CI:0.51–0.62). Compared to the chemotherapy-to-all strategy, PREDICT only showed a slightly higher net benefit in women with ER-positive tumors, but not in women with ER-negative tumors. Conclusions: PREDICT yields unreliable predictions for young women with node-negative breast cancer. Further model updates are needed before PREDICT can be routinely used in this patient subset.</p

Fatal outcomes following immunization errors as reported to the EudraVigilance: A case series

Background: Serious adverse reactions after immunization are rare but do occur. In very rare instances, cases with fatal outcome have been reported. These reports can have a huge impact and even more so when due to an immunization error. The aim of this study is to systematically review immunization errors with fatal outcomes in EudraVigilance. Methods: This was a case-series analysis of Individual Case Safety Reports (ICSRs) reporting immunization errors and a fatal outcome. To determine the level of certainty of a causal association between the immunization errors and fatal outcomes two independent reviewers assessed all ICSRs using the WHO tool “Causality assessment of an Adverse Event Following Immunization (AEFI)”. In accordance with the tool, the ICSRs were classified as consistent, indeterminate, inconsistent/coincidental, or unclassifiable. In addition, we estimated the contribution of reported errors to the fatal outcomes as large, moderate, small, none, or unclassifiable using a classification developed f

Predictors of treatment dropout in patients with posttraumatic stress disorder due to childhood abuse1

BackgroundKnowledge about patient characteristics predicting treatment dropout for post-traumatic stress disorder (PTSD) is scarce, whereas more understanding about this topic may give direction to address this important issue.MethodData were obtained from a randomized controlled trial in which a phase-based treatment condition (Eye Movement Desensitization and Reprocessing [EMDR] therapy preceded by Skills Training in Affect and Interpersonal Regulation [STAIR]; n = 57) was compared with a direct trauma-focused treatment (EMDR therapy only; n = 64) in people with a PTSD due to childhood abuse. All pre-treatment variables included in the trial were examined as possible predictors for dropout using machine learning techniques.ResultsFor the dropout prediction, a model was developed using Elastic Net Regularization. The ENR model correctly predicted dropout in 81.6% of all individuals. Males, with a low education level, suicidal thoughts, problems in emotion regulation, high levels of general psychopathology and not using benzodiazepine medication at screening proved to have higher scores on dropout.ConclusionOur results provide directions for the development of future programs in addition to PTSD treatment or for the adaptation of current treatments, aiming to reduce treatment dropout among patients with PTSD due to childhood abuse

Fitting model of ABR age dependency in a clinical population of normal hearing children

The purpose of this study was to present a simple and powerful fitting model that describes age-dependent changes of auditory brainstem responses (ABR) in a clinical population of normal hearing children. A total of 175 children (younger than 200 weeks postconceptional age) were referred for audiologic assessment with normal ABR results. ABR parameters of normal hearing children between 2003 and 2008 were included. The results of the right ears recorded at 90 dB nHL were analyzed. A simple and accurate fitting model was formulated based on these data. A very similar age-dependent effect was found for peaks III and V, and I–III and I–V intervals; latencies decrease as postconceptional age increases. It shows that the total age-dependent effect will be completed after 1.5–2 years. The age-dependent effect can be modeled by a relatively simple and accurate exponential function. This fitting model can be easily implemented to analyze ABR results of infants in daily clinical practice. We speculate about the underlying physiological processes