Total arthrodesis for non-rheumatoid wrists: Outcomes at 5 and 20years of follow-up.

INTRODUCTION: Total wrist arthrodesis (TWA) aims to obtain a painless wrist with a strong grip. Its main disadvantage is compromised mobility and for many authors it remains a rescue intervention. However, after one or more palliative interventions, TWA confers poorer results. The objective of our study was to evaluate the medium-term results of TWA, and their long-term stability. HYPOTHESIS: Our hypothesis was that the results are reliable and persistent for pain and strength, without repercussions to other joints. MATERIAL AND METHODS: This was a single-center consecutive series of TWA performed with a dedicated plate, excluding rheumatoid wrists, evaluated at 5.4 and 21.1years of follow-up. RESULTS: Thirty wrists were assessed at the first review and 17 reassessed at the last follow-up. At the mean follow-up of 5.4years, 93% of patients considered themselves "very satisfied" or "satisfied" with the TWA surgery. No infectious complications occurred. At the mean follow-up of 21.1years, all were "very satisfied" or "satisfied" and 88% of them considered their result stable or improved compared to the first revision. The average VAS had gone from 8.4/10 preoperatively to 1.8/10 at the first evaluation and to 0.3/10 at the last follow-up. Except for a patient with both wrists operated on for whom comparison was not possible, the strength of the operated side was on average 89.7% of that of the contralateral side (from 45% to 150%). The mean Quick DASH score was 30.3 (4.5 to 61.4) and the mean PRWE score was 32.5 (1 to 77). DISCUSSION: TWA using a plate provides excellent results for both pain control and strength restoration. The clinical results remain stable over time, and arthrodesis at more than 20years of follow-up does not seem to have any impact on the other joints of the upper limb. After wrist surgery, the main complaint of patients is the limited range of motion, but the main cause of dissatisfaction is persistent pain. Arthrodesis can be performed first-line in case of questionable indication of partial arthrodesis on a stiff wrist because the results of TWA are better in the absence of a surgical history. LEVEL OF EVIDENCE: IV; retrospective study.

Identifying Homogeneous Patient Clusters in Swiss University Hospital Through Latent Class Analysis.

In hospitalized populations, there is significant heterogeneity in patients' characteristics, disease severity, and treatment responses, which translates into different related outcomes and costs. Identifying inpatient clusters with similar clinical profiles could lead to better quality and personalized care while improving clinical resources used. Super-utilizers (SUs) are one such a group, who contribute a substantial proportion of health care costs and utilize a disproportionately high share of health care resources. This study uses cost, utilization metrics and clinical information to segment the population of patients (N=32,759) admitted to the University Hospitals of Geneva per year in 2017 - 2019. Using Latent Class Analysis it identifies 8 subgroups with highly similar patients demographics, medical conditions, types of service and costs within groups and which are highly different between groups. As such 82% of all SU patients, 99% of all patients less than 20 years old and 78% of all orthopedics patients are clustered into only 3 separate groups while one group contain only adult women 90% of them 20 to 40 years of age.

Arthroscopic Foveal Reattachment of the Triangular Fibro Cartilaginous Complex.

Background Foveal attachment of the triangular fibrocartilaginous complex (TFCC) is essential for distal radioulnar joint stability. Controversy still exists as to which is the best treatment in case of foveal lesions. Actual arthroscopic techniques either require mini open steps or are complex and expensive. We present a simple all inside knotless repair, providing a strong bony fixation in the fovea. Materials and Methods Through 3-4 and 6R portals, the ulnar fovea is debrided and a wire is passed percutaneously through the TFCC to place a mattress suture at its free end. It is then reattached to the fovea with an impacted anchor. Retrospective Study Between 2013 and 2016, a cohort of 5 patients presenting with isolated Palmer 1B, EWAS 2 lesions of the TFCC were operated on with this technique. Clinical evaluation was based on a compared measurement of the grip strength, pain on a visual analogic scale (VAS), different ranges of motion, and distal radioulnar joint (DRUJ) stability. We also used functional scores: Mayo modified wrist score (MMWS), Quick disability arm, shoulder and hand (DASH), and patient-related wrist evaluation (PRWE). The average follow-up was 29.4 months (range 9-42 months). Results On postoperative evaluation, pain was reduced by 5 points (range 1-9) and grip strength averaged 94% of the unaffected side. Range of motion averaged 92% on the unaffected side. DRUJ instability was slight in 4 patients and mild in 1 patient. MMWS was excellent for 1, good for 1, and satisfactory for 3 patients. Quick Dash averaged 17.68 (range 0-38.6) compared with preoperative average of 59.48 (range 45-77) with an amelioration of 43 (range 34-57). PRWE averaged 20 (range 1-41.5) compared with preoperative average of 60.3 (range 33.5-76.5) with an amelioration of 41 (range 32-58). We reported no complications and particularly no lesions of the dorsal sensory branch of the ulnar nerve. Conclusions We present a simple arthroscopic technique using a single suture anchor placed in the ulnar fovea. Repairs performed with this technique are simple and the results achieved seem to be similar to those obtained with conventional open or arthroscopic techniques, although further investigation with an increased number of patients and follow-up are required. It however became our first choice of treatment in European Wrist Arthroscopy Society (EWAS) 2 lesions of the TFCC.

Does colonization with methicillin-susceptible Staphylococcus aureus protect against nosocomial acquisition of methicillin-resistant S. aureus?

OBJECTIVE: To test the hypothesis that methicillin-susceptible Staphylococcus aureus (MSSA) carriage may protect against nosocomial methicillin-resistant S. aureus (MRSA) acquisition by competing for colonization of the anterior nares. DESIGN: Prospective cohort and nested case-control study. SETTING: Swiss university hospital. PATIENTS: All adult patients admitted to 14 wards of the general medicine division between April 1 and October 31, 2007. METHODS: Patients were screened for MRSA and MSSA carriage at admission to and discharge from the division. Associations between nosocomial MRSA acquisition and MSSA colonization at admission and other confounders were analyzed by univariable and multivariable analysis. RESULTS: Of 898 patients included, 183 (20%) were treated with antibiotics. Nosocomial MRSA acquisition occurred in 70 (8%) of the patients (case patients); 828 (92%) of the patients (control subjects) were free of MRSA colonization at discharge. MSSA carriage at admission was 20% and 21% for case patients and control subjects, respectively. After adjustment by multivariate logistic regression, no association was observed between MSSA colonization at admission and nosocomial MRSA acquisition (adjusted odds ratio [aOR], 1.2 [95% confidence interval (CI), 0.6-2.3]). By contrast, 4 independent predictors of nosocomial MRSA acquisition were identified: older age (aOR per 1-year increment, 1.05 [95% CI, 1.02-1.08]); increased length of stay (aOR per 1-day increment, 1.05 [95% CI, 1.02-1.09]); increased nursing workload index (aOR per 1-point increment, 1.02 [95% CI, 1.01-1.04]); and previous treatment with macrolides (aOR, 5.6 [95% CI, 1.8-17.7]). CONCLUSIONS: Endogenous MSSA colonization does not appear to protect against nosocomial MRSA acquisition in a population of medical patients without frequent antibiotic exposure.

Carriage of extended-spectrum beta-lactamase-producing enterobacteriacae among internal medicine patients in Switzerland.

BACKGROUND: The incidence of extended-spectrum beta-lactamase producing-enterobacteriacae (ESBL-E) infection is rising worldwide. We aimed to determine the prevalence and nosocomial acquisition rate of ESBL-E as well as the risk factors for ESBL-E carriage and acquisition amongst patients consecutively admitted to 13 internal medicine units at our hospital who were not previously known to be ESBL-E carriers. FINDINGS: We screened all patients admitted or transferred to internal medicine units for ESBL-E on admission and discharge using rectal swabs. Of 1072 patients screened, 51 (4.8%) were carriers of an ESBL-E at admission. Of 473 patients who underwent admission and discharge screening, 21 (4.4%) acquired an ESBL-E. On multivariate analysis, diabetes mellitus without end-organ complications (OR 2.87 [1.09-7.08]), connective tissue disease (OR 7.22 [1.17-44.59]), and liver failure (OR 8.39 [1.55-45.45]) were independent risk factors for carriage of an ESBL-E upon admission to hospital (area under the ROC curve, 0.68). Receipt of a first- or second-generation cephalosporin (OR 9.25 [2.22-37.82]), intra-hospital transfer (OR 6.68 [1.71-26.06]), and a hospital stay >21 days (OR 25.17 [4.18-151.68]) were associated with acquisition of an ESBL-E during hospitalisation; whilst admission from home was protective (OR 0.16 [0.06-0.39]) on univariate regression. No risk profile with sufficient accuracy to predict previously unknown carriage on admission or acquisition of ESBL-E could be developed using readily available patient information. CONCLUSIONS: ESBL-E carriage is endemic amongst internal medicine patients at our institution. We were unable to develop a clinical risk profile to accurately predict ESBL-E carriage amongst these patients.

Methicillin-resistant Staphylococcus aureus risk profiling: who are we missing?

BACKGROUND: Targeted screening of patients at high risk for methicillin-resistant Staphylococcus aureus (MRSA) carriage is an important component of MRSA control programs, which rely on prediction tools to identify those high-risk patients. Most previous risk studies reported a substantial rate of patients who are eligible for screening, but failed to be enrolled. The characteristics of these missed patients are seldom described. We aimed to determine the rate and characteristics of patients who were missed by a MRSA screening programme at our institution to see how the failure to include these patients might impact the accuracy of clinical prediction tools. FINDINGS: From March-June 2010 all patients admitted to 13 internal medicine wards at the University of Geneva Hospital (HUG) were prospectively screened for MRSA carriage. Of 1968 patients admitted to the ward, 267 patients (13.6%) failed to undergo appropriate MRSA screening. Forty-one (2.4%) screened patients were MRSA carriers at admission. On multivariate regression, patients who were missed by screening were more likely to be aged < 50 years (OR 2.4 [1.4-3.9]), transferred to internal medicine from another ward in the hospital (OR 2.8 [1.1-7.1]), and have a history of malignancy (OR 3.2[2.1-5.1]). There was no significant difference in the rate of previous MRSA carriage between screened and unscreened patients. CONCLUSIONS: Our findings highlight the potential bias that "missed" patients may introduce into MRSA risk scores. Reporting on the proportions and characteristics of missed patients is essential for accurate interpretation of MRSA prediction tools.

Optimal asymmetrical SVM using pattern search. A health care application.

This paper considers the model selection problem for Support Vector Machines. A well-known derivative Pattern Search method, which aims to tune hyperparameter values using an empirical error estimate as a steering criterion, is proposed. This approach is experimentally evaluated on a health care problem which involves discriminating nosocomially infected patients from non-infected patients. The Hooke and Jeeves Pattern Search (HJPS) method is shown to improve the results achieved by Grid Search (GS) in terms of solution quality and computational efficiency. Unlike most other parameter tuning techniques, our approach does not require supplementary effort such as computation of derivatives, making them well suited for practical purposes. This method produces encouraging results: it exhibits good performance and convergence properties.

Measuring the effectiveness of hospital-acquired infection prevention.

This article deals with data on nosocomial infections acquired in the Geneva University Hospitals. Goal of the work is to derive a model from a hospital-acquired infection (HAI) prevalence survey of year Y and apply them to a prevalence survey of years Y+1, Y+2. This analysis permits to evaluate the effectiveness of preventive measures taken after the prevalence survey in year Y. It also analyzes the robustness of the SVM algorithm on time-variable attributes. The model build on the dataset of year Y gives better results than in a previous study. The application of the model on the Y+1 and Y+2 prevalence surveys shows simultaneously improvements and deteriorations of 5 performance measures. This highlights the effectiveness of prevention and reduces the risk of HAI after the prevalence survey of year Y. We introduce a new method to detect redundancy in a dataset with the SVM algorithm.

Fusing visual and clinical information for lung tissue classification in high-resolution computed tomography.

OBJECTIVE: We investigate the influence of the clinical context of high-resolution computed tomography (HRCT) images of the chest on tissue classification. METHODS AND MATERIALS: 2D regions of interest in HRCT axial slices from patients affected with an interstitial lung disease are automatically classified into five classes of lung tissue. Relevance of the clinical parameters is studied before fusing them with visual attributes. Two multimedia fusion techniques are compared: early versus late fusion. Early fusion concatenates features in one single vector, yielding a true multimedia feature space. Late fusion consisting of the combination of the probability outputs of two support vector machines. RESULTS AND CONCLUSION: The late fusion scheme allowed a maximum of 84% correct predictions of testing instances among the five classes of lung tissue. This represents a significant improvement of 10% compared to a pure visual-based classification. Moreover, the late fusion scheme showed high robustness to the number of clinical parameters used, which suggests that it is appropriate for mining clinical attributes with missing values in clinical routine.

Comparative performance analysis of state-of-the-art classification algorithms applied to lung tissue categorization.

In this paper, we compare five common classifier families in their ability to categorize six lung tissue patterns in high-resolution computed tomography (HRCT) images of patients affected with interstitial lung diseases (ILD) and with healthy tissue. The evaluated classifiers are naive Bayes, k-nearest neighbor, J48 decision trees, multilayer perceptron, and support vector machines (SVM). The dataset used contains 843 regions of interest (ROI) of healthy and five pathologic lung tissue patterns identified by two radiologists at the University Hospitals of Geneva. Correlation of the feature space composed of 39 texture attributes is studied. A grid search for optimal parameters is carried out for each classifier family. Two complementary metrics are used to characterize the performances of classification. These are based on McNemar's statistical tests and global accuracy. SVM reached best values for each metric and allowed a mean correct prediction rate of 88.3% with high class-specific precision on testing sets of 423 ROIs.

Revealing triage behaviour patterns in ER using a new technology for handwritten data acquisition.

INTRODUCTION: Data acquisition is still one of the important challenges to be met in clinical settings. This is even more critic in settings with high cognitive workloads, such as emergency room (ER). Observations in these settings are difficult to realize without biases and there is little means to trace fine acquisition activities done in natural environments, using pen and papers. This study is based on the usage of a digital pen and paper (DPP) technology for the acquisition of triage information by nurses in ER. The DPP technology has been used to ease acquisition using a natural mechanism; it also minimizes the external influence of observation during acquisition activities. The aim of this study is to determine whether data recorded by the DPP technology allows explaining how ER triage nurses use the triage forms in real working conditions. METHODOLOGY: The chief physicians of the ER service wanted to have answers about three main concerns pertaining to the triage process: (1) the average time spent during the triage process; (2) the sequence in which the fields of the forms were filled and; (3) the contribution of objective measurements, such as vital signs, to the triage emergency level and decisions. In order to answer these questions, detailed log data recorded by the DPP during form filling as been analyzed and allowed to built several representations of the triage process. In addition, we completed this analysis with ethnographical-like observations. RESULTS: For seven consecutive days, 1183 triage forms have been recorded in the ER for all patients admitted. Among them, 954 forms have been digitalized and 906 forms have been considered as valid and complete. Based on this set of data, the median duration of the triage process is 143 s. There are no converging habits in filling the forms and the sequence of filling fields present a high variability. The emphasis of the objective measurements in the decisional process is rather low, as vital signs are recorded in less than 17% of the cases. CONCLUSION: The DPP technology is an original approach to study data acquisition processes in unbiased conditions. The technical raw data recorded by the DPP allows building the time series of all activities on the paper, therefore letting to constructing several representations of the process. However, the technology is not able to provide information about the context of use, for example interruptions of the form filling processes due to calls or other activities. Therefore, it is necessary to complete these analyses with qualitative approaches such as observational studies and interviews. Noticeably, as a result of this study, the head physicians of ER have redesigned the triage form to enforce the use of objective measurements and ease the data acquisition process.

Novelty detection using one-class Parzen density estimator. An application to surveillance of nosocomial infections.

Nosocomial infections (NIs) - those acquired in health care settings - represent one of the major causes of increased mortality in hospitalized patients. As they are a real problem for both patients and health authorities, the development of an effective surveillance system to monitor and detect them is of paramount importance. This paper presents a retrospective analysis of a prevalence survey of NIs done in the Geneva University Hospital. The objective is to identify patients with one or more NIs based on clinical and other data collected during the survey. In this classification task, the main difficulty lies in the significant imbalance between positive and negative cases. To overcome this problem, we investigate one-class Parzen density estimator which can be trained to differentiate two classes taking examples from a single class. The results obtained are encouraging: whereas standard 2-class SVMs scored a baseline sensitivity of 50.6% on this problem, the one-class approach increased sensitivity to as much as 88.6%. These results suggest that one-class Parzen density estimator can provide an effective and efficient way of overcoming data imbalance in classification problems.

Learning from imbalanced data in surveillance of nosocomial infection.

OBJECTIVE: An important problem that arises in hospitals is the monitoring and detection of nosocomial or hospital acquired infections (NIs). This paper describes a retrospective analysis of a prevalence survey of NIs done in the Geneva University Hospital. Our goal is to identify patients with one or more NIs on the basis of clinical and other data collected during the survey. METHODS AND MATERIAL: Standard surveillance strategies are time-consuming and cannot be applied hospital-wide; alternative methods are required. In NI detection viewed as a classification task, the main difficulty resides in the significant imbalance between positive or infected (11%) and negative (89%) cases. To remedy class imbalance, we explore two distinct avenues: (1) a new re-sampling approach in which both over-sampling of rare positives and under-sampling of the noninfected majority rely on synthetic cases (prototypes) generated via class-specific sub-clustering, and (2) a support vector algorithm in which asymmetrical margins are tuned to improve recognition of rare positive cases. RESULTS AND CONCLUSION: Experiments have shown both approaches to be effective for the NI detection problem. Our novel re-sampling strategies perform remarkably better than classical random re-sampling. However, they are outperformed by asymmetrical soft margin support vector machines which attained a sensitivity rate of 92%, significantly better than the highest sensitivity (87%) obtained via prototype-based re-sampling.

SVM Modeling via a Hybrid Genetic Strategy. A Health Care Application.

This paper addresses the model selection problem for Support Vector Machines. A hybrid genetic algorithm guided by Direct Simplex Search to evolves hyperparameter values using an empirical error estimate as a steering criterion. This approach is specificaly tailored and experimentally evaluated on a health care problem which involves discriminating 11 % nosocomially infected patients from 89 % non infected patients. The combination of Direct Search Simplex with GAs is shown to improve the performance of GAs in terms of solution quality and computational efficiency. Unlike most other hyperparameter tuning techniques, our hybrid approach does not require supplementary effort such as computation of derivatives, making them well suited for practical purposes. This method produces encouraging results: it exhibits high performance and good convergence properties.

An application of one-class support vector machine to nosocomial infection detection.

Nosocomial infections (NIs)---those acquired in health care settings---are among the major causes of increased mortality among hospitalized patients. They are a significant burden for patients and health authorities alike; it is thus important to monitor and detect them through an effective surveillance system. This paper describes a retrospective analysis of a prevalence survey of NIs done in the Geneva University Hospital. Our goal is to identify patients with one or more NIs on the basis of clinical and other data collected during the survey. In this two-class classification task, the main difficulty lies in the significant imbalance between positive or infected (11%) and negative (89%) cases. To cope with class imbalance, we investigate one-class SVMs which can be trained to distinguish two classes on the basis of examples from a single class (in this case, only "normal" or non infected patients). The infected ones are then identified as "abnormal" cases or outliers that deviate significantly from the normal profile. Experimental results are encouraging: whereas standard 2-class SVMs scored a baseline sensitivity of 50.6% on this problem, the one-class approach increased sensitivity to as much as 92.6%. These results are comparable to those obtained by the authors in a previous study on asymmetrical soft margin SVMs; they suggest that one-class SVMs can provide an effective and efficient way of overcoming data imbalance in classification problems.