Increased tender point counts before and after total hip arthroplasty are associated with poorer outcomes but are not individually predictive.

In a prospective study, total hip arthroplasty (THA) patients were assessed preoperatively and postoperatively (n = 95) to determine if tender points (TPs) are associated with poor THA outcomes. Patients with high follow-up TP counts had higher visual analog scale (VAS) for pain and sleep, higher follow-up Western Ontario and McMaster Universities Arthritis Index (pain, stiffness, function), lower Health Assessment Questionnaire, Harris Hip, and Short Form 36 (physical functioning, bodily pain, physical component summary) scores. High follow-up TP were associated with increased pain, pain not relieved by surgery, poor function, and poor sleep. Visual analog scale pain and sleep, Short Form 36 (physical functioning, bodily pain), Western Ontario and McMaster Universities Arthritis Index, Health Assessment Questionnaire, and Harris hip scores improved significantly after THA; TP scores did not. Higher preoperative TP were predictive of higher follow-up TP but were poorly predictive of poor outcome measures after surgery in individual patients, suggesting that preoperative TPs are contraindicative for THA.

Continuous determination of optimal cerebral perfusion pressure in traumatic brain injury.

OBJECTIVES: We have sought to develop an automated methodology for the continuous updating of optimal cerebral perfusion pressure (CPPopt) for patients after severe traumatic head injury, using continuous monitoring of cerebrovascular pressure reactivity. We then validated the CPPopt algorithm by determining the association between outcome and the deviation of actual CPP from CPPopt. DESIGN: Retrospective analysis of prospectively collected data. SETTING: Neurosciences critical care unit of a university hospital. PATIENTS: A total of 327 traumatic head-injury patients admitted between 2003 and 2009 with continuous monitoring of arterial blood pressure and intracranial pressure. MEASUREMENTS AND MAIN RESULTS: Arterial blood pressure, intracranial pressure, and CPP were continuously recorded, and pressure reactivity index was calculated online. Outcome was assessed at 6 months. An automated curve fitting method was applied to determine CPP at the minimum value for pressure reactivity index (CPPopt). A time trend of CPPopt was created using a moving 4-hr window, updated every minute. Identification of CPPopt was, on average, feasible during 55% of the whole recording period. Patient outcome correlated with the continuously updated difference between median CPP and CPPopt (chi-square=45, p<.001; outcome dichotomized into fatal and nonfatal). Mortality was associated with relative "hypoperfusion" (CPP<CPPopt), severe disability with "hyperperfusion" (CPP>CPPopt), and favorable outcome was associated with smaller deviations of CPP from the individualized CPPopt. While deviations from global target CPP values of 60 mm Hg and 70 mm Hg were also related to outcome, these relationships were less robust. CONCLUSIONS: Real-time CPPopt could be identified during the recording time of majority of the patients. Patients with a median CPP close to CPPopt were more likely to have a favorable outcome than those in whom median CPP was widely different from CPPopt. Deviations from individualized CPPopt were more predictive of outcome than deviations from a common target CPP. CPP management to optimize cerebrovascular pressure reactivity should be the subject of future clinical trial in severe traumatic head-injury patients.

Migrated foreign body liver abscess: illustrative case report, systematic review, and proposed diagnostic algorithm.

Pyogenic liver abscess is a severe condition and a therapeutic challenge. Treatment failure may be due to an unrecognized ingested foreign body that migrated from the gastrointestinal tract. There has recently been a marked increase in the number of reported cases of this condition, but initial misdiagnosis as cryptogenic liver abscess still occurs in the majority of cases. We conducted the current study to characterize this entity and provide a diagnostic strategy applicable worldwide. To this end, data were collected from our case and from a systematic review that identified 59 well-described cases. Another systematic review identified series of cryptogenic-and Asian Klebsiella-liver abscess; these data were pooled and compared with the data from the cases of migrated foreign body liver abscess. The review points out the low diagnostic accuracy of history taking, modern imaging, and even surgical exploration. A fistula found through imaging procedures or endoscopy warrants surgical exploration. Findings suggestive of foreign body migration are symptoms of gastrointestinal perforation, computed tomography demonstration of a thickened gastrointestinal wall in continuity with the abscess, and adhesions seen during surgery. Treatment failure, left lobe location, unique location (that is, only 1 abscess location within the liver), and absence of underlying conditions also point to the diagnosis, as shown by comparison with the cryptogenic liver abscess series. This study demonstrates that migrated foreign body liver abscess is a specific entity, increasingly reported. It usually is not cured when unrecognized, and diagnosis is mainly delayed. This study provides what we consider the best available evidence for timely diagnosis with worldwide applicability. Increased awareness is required to treat this underestimated condition effectively, and further studies are needed.

Measuring potentially avoidable hospital readmissions.

The objectives of this study were to develop a computerized method to screen for potentially avoidable hospital readmissions using routinely collected data and a prediction model to adjust rates for case mix. We studied hospital information system data of a random sample of 3,474 inpatients discharged alive in 1997 from a university hospital and medical records of those (1,115) readmitted within 1 year. The gold standard was set on the basis of the hospital data and medical records: all readmissions were classified as foreseen readmissions, unforeseen readmissions for a new affection, or unforeseen readmissions for a previously known affection. The latter category was submitted to a systematic medical record review to identify the main cause of readmission. Potentially avoidable readmissions were defined as a subgroup of unforeseen readmissions for a previously known affection occurring within an appropriate interval, set to maximize the chance of detecting avoidable readmissions. The computerized screening algorithm was strictly based on routine statistics: diagnosis and procedures coding and admission mode. The prediction was based on a Poisson regression model. There were 454 (13.1%) unforeseen readmissions for a previously known affection within 1 year. Fifty-nine readmissions (1.7%) were judged avoidable, most of them occurring within 1 month, which was the interval used to define potentially avoidable readmissions (n = 174, 5.0%). The intra-sample sensitivity and specificity of the screening algorithm both reached approximately 96%. Higher risk for potentially avoidable readmission was associated with previous hospitalizations, high comorbidity index, and long length of stay; lower risk was associated with surgery and delivery. The model offers satisfactory predictive performance and a good medical plausibility. The proposed measure could be used as an indicator of inpatient care outcome. However, the instrument should be validated using other sets of data from various hospitals.

Paper 5: Surveillance of multiple congenital anomalies: implementation of a computer algorithm in European registers for classification of cases.

BACKGROUND: Surveillance of multiple congenital anomalies is considered to be more sensitive for the detection of new teratogens than surveillance of all or isolated congenital anomalies. Current literature proposes the manual review of all cases for classification into isolated or multiple congenital anomalies. METHODS: Multiple anomalies were defined as two or more major congenital anomalies, excluding sequences and syndromes. A computer algorithm for classification of major congenital anomaly cases in the EUROCAT database according to International Classification of Diseases (ICD)v10 codes was programmed, further developed, and implemented for 1 year's data (2004) from 25 registries. The group of cases classified with potential multiple congenital anomalies were manually reviewed by three geneticists to reach a final agreement of classification as "multiple congenital anomaly" cases. RESULTS: A total of 17,733 cases with major congenital anomalies were reported giving an overall prevalence of major congenital anomalies at 2.17%. The computer algorithm classified 10.5% of all cases as "potentially multiple congenital anomalies". After manual review of these cases, 7% were agreed to have true multiple congenital anomalies. Furthermore, the algorithm classified 15% of all cases as having chromosomal anomalies, 2% as monogenic syndromes, and 76% as isolated congenital anomalies. The proportion of multiple anomalies varies by congenital anomaly subgroup with up to 35% of cases with bilateral renal agenesis. CONCLUSIONS: The implementation of the EUROCAT computer algorithm is a feasible, efficient, and transparent way to improve classification of congenital anomalies for surveillance and research.

Fuzzy logic algorithm to extract specific interaction forces from atomic force microscopy data

The atomic force microscope is not only a very convenient tool for studying the topography of different samples, but it can also be used to measure specific binding forces between molecules. For this purpose, one type of molecule is attached to the tip and the other one to the substrate. Approaching the tip to the substrate allows the molecules to bind together. Retracting the tip breaks the newly formed bond. The rupture of a specific bond appears in the force-distance curves as a spike from which the binding force can be deduced. In this article we present an algorithm to automatically process force-distance curves in order to obtain bond strength histograms. The algorithm is based on a fuzzy logic approach that permits an evaluation of "quality" for every event and makes the detection procedure much faster compared to a manual selection. In this article, the software has been applied to measure the binding strength between tubuline and microtubuline associated proteins.

Success of referral for alcohol dependent patients from a general hospital : predictive value of patient and process characteristics

RESUME: Introduction L'objectif de cette étude prospective de cohorte était d'estimer l'efficacité d'un processus de prise en charge standardisé de patients dépendants de l'alcool dans le contexte d'un hôpital universitaire de soins généraux. Ce modèle de prise en charge comprenait une évaluation multidisciplinaire puis des propositions de traitements individualisées et spécifiques (« projet thérapeutique »). Patients et méthode 165 patients alcoolo-dépendants furent recrutés dans différents services de l'hôpital universitaire, y compris la policlinique de médecine. Ils furent dans un premier temps évalués par une équipe multidisciplinaire (médecin interniste, psychiatre, assistant social), puis un projet thérapeutique spécialisé et individualisé leur fut proposé lors d'une rencontre réunissant le patient et l'équipe. Tous les patients éligibles acceptant de participer à l'étude (n=68) furent interrogés au moment de l'inclusion puis 2 et 6 mois plus tard par une psychologue. Des informations standardisées furent recueillies sur les caractéristiques des patients, le processus de prise en charge et l'évolution à 6 mois. Les critères de succès utilisés à 6 mois furent: l'adhérence au traitement proposé et l'abstinence d'alcool. Résultats Lors de l'évaluation à 6 mois, 43% des patients étaient toujours en traitement et 28% étaient abstinents. Les variables prédictrices de succès parmi les caractéristiques des patients étaient un âge de plus de 45 ans, ne pas vivre seul, avoir un travail et être motivé pour un traitement (RAATE-A <18). Pour les variables dépendantes du processus de prise en charge, un sevrage complet de l'alcool lors de la rencontre multidisciplinaire ainsi que la présence de tous les membres de l'équipe à cette réunion étaient des facteurs associés au succès. Conclusion L'efficacité de ce modèle d'intervention pour patients dépendants de l'alcool en hôpital de soins généraux s'est montrée satisfaisante, en particulier pour le critère de succès adhérence au traitement. Des variables associées au succès ou à l'échec à 6 mois ont pu être mises en évidence, permettant d'identifier des populations de patients évoluant différemment. Des stratégies de prise en charge tenant compte de ces éléments pourraient donc être développées, permettant de proposer des traitements plus adaptés ainsi qu'une meilleure rétention des patients alcooliques dans les programmes thérapeutiques. ABSTRACT. To assess the effectiveness of a multidisciplinary evaluation and referral process in a prospective cohort of general hospital patients with alcohol dependence, alcohol-dependent patients were identified in the wards of the general hospital and its primary care center. They were evaluated and then referred to treatment by a multidisciplinary team; those patients who accepted to participate in this cohort study were consecutively included and followed for 6 months. Not included patients were lost for follow-up, whereas all included patients were assessed at time of inclusion, 2 and 6 months later by a research psychologist in order to collect standardized baseline patients' characteristics, process salient features and patients outcomes (defined as treatment adherence and abstinence). Multidisciplinary evaluation and therapeutic referral was feasible and effective, with a success rate of 43% for treatment adherence and 28% for abstinence at 6 months. Among patients' characteristics, predictors of success were an age over 45, not living alone, being employed and being motivated to treatment (RAATE-A score < 18), whereas successful process characteristics included detoxification of the patient at time of referral and a full multidisciplinary referral meeting. This multidisciplinary model of evaluation and referral of alcohol dependent patients of a general hospital had a satisfactory level of effectiveness. Predictors of success and failure allow the identification of subsets of patients for whom new strategies of motivation and treatment referral should be designed.

Diagnostic algorithm for a validated displacement grading of pediatric supracondylar fractures.

Background: The first AO comprehensive pediatric long bone fracture classification system has been established following a structured path of development and validation with experienced pediatric surgeons. Methods: A follow-up series of agreement studies was applied to specify and evaluate a grading system for displacement of pediatric supracondylar fractures. An iterative process comprising an international group of 5 experienced pediatric surgeons (Phase 1) followed by a pragmatic multicenter agreement study involving 26 raters (Phase 2) was used. The last evaluations were conducted on a consecutive collection of 154 supracondylar fractures documented by standard anteroposterior and lateral radiographs. Results: Fractures were classified according to 1 of 4 grades: I = incomplete fracture with no or minimal displacement; II = Incomplete fracture with continuity of the posterior (extension fracture) or anterior cortex (flexion fracture); III = lack of bone continuity (broken cortex), but still some contact between the fracture planes; IV = complete fracture with no bone continuity (broken cortex), and no contact between the fracture planes. A diagnostic algorithm to support the practical application of the grading system in a clinical setting, as well as an aid using a circle placed over the capitellum was proposed. The overall kappa coefficients were 0.68 and 0.61 in the Phase 1 and Phase 2 studies, respectively. In the Phase 1 study, fracture grades I, II, III, and IV were classified with median accuracies of 91%, 82%, 83%, and 99.5%, respectively. Similar median accuracies of 86% (Grade I), 73% (Grade II), 83%(Grade III), and 92% were reported for the Phase 2 study. Reliability was high in distinguishing complete, unstable fractures from stable injuries [ie, kappa coefficients of 0.84 (Phase 1) and 0.83 (Phase 2) were calculated]; in Phase 2, surgeons' accuracies in classifying complete fractures were all above 85%. Conclusions: With clear and unambiguous definition, this new grading system for supracondylar fracture displacement has proved to be sufficiently reliable and accurate when applied by pediatric surgeons in the framework of clinical routine as well as research.

Use of the Cognitive Performance Scale (CPS) to detect cognitive impairment in the acute care setting: concurrent and predictive validity.

The Cognitive Performance Scale (CPS) was initially designed to assess cognition in long term care residents. Subsequently, the CPS has also been used among in-home, post-acute, and acute care populations even though CPS' clinimetric performance has not been studied in these settings. This study aimed to determine CPS agreement with the Mini Mental Status Exam (MMSE) and its predictive validity for institutionalization and death in a cohort (N=401) of elderly medical inpatients aged 75 years and over. Medical, physical and mental status were assessed upon admission. The same day, the patient's nurse completed the CPS by interview. Follow-up data were gathered from the central billing system (nursing home stay) and proxies (death). Cognitive impairment was present in 92 (23%) patients according to CPS (score >or= 2). Agreement with MMSE was moderate (kappa 0.52, P<.001). Analysis of discordant results suggested that cognitive impairment was overestimated by the CPS in dependent patients with comorbidities and depressive symptoms, and underestimated in older ones. During follow-up, subjects with abnormal CPS had increased risks of death (adjusted hazard ratio (adjHR) 1.7, 95% CI 1.0-2.8, P=.035) and institutionalization (adjHR 2.7, 95% CI 1.3-5.3, P=.006), independent of demographic, health and functional status. Interestingly, subjects with abnormal CPS were at increased risk of death only if they also had abnormal MMSE. The CPS predicted death and institutionalization during follow-up, but correlated moderately well with the MMSE. Combining CPS and MMSE provided additional predictive information, suggesting that domains other than cognition are assessed by professionals when using the CPS in elderly medical inpatients.

Les biomarqueurs prédictifs dans le cancer colorectal [Predictive biomarkers in colorectal cancer]

While for many years the diagnosis and therapy of colon cancer did not change drastically, recently new drugs (irinotecan and oxaliplatin, used in adjuvant or neo-adjuvant approaches) and even more recently the introduction of therapies targeting the epidermal growth factor receptor (EGFR) through the monoclonal antibodies cetuximab and panitumumab, are revolutionizing the field. The finding that only patients with a tumor with a wild type (non mutated) KRAS gene respond to anti-EGFR therapy has also affected the way pathologists address colorectal cancer. Molecular analysis of the KRAS gene has become almost a routine in a very short period of time. Pathologists will have to be prepared for a new era: from standard morphology based diagnostic procedures to the prediction of response to therapy using molecular tools.

Predictive analysis and mapping of indoor radon concentrations in a complex environment using kernel estimation: an application to Switzerland.

PURPOSE: The aim of this study was to develop models based on kernel regression and probability estimation in order to predict and map IRC in Switzerland by taking into account all of the following: architectural factors, spatial relationships between the measurements, as well as geological information. METHODS: We looked at about 240,000 IRC measurements carried out in about 150,000 houses. As predictor variables we included: building type, foundation type, year of construction, detector type, geographical coordinates, altitude, temperature and lithology into the kernel estimation models. We developed predictive maps as well as a map of the local probability to exceed 300 Bq/m(3). Additionally, we developed a map of a confidence index in order to estimate the reliability of the probability map. RESULTS: Our models were able to explain 28% of the variations of IRC data. All variables added information to the model. The model estimation revealed a bandwidth for each variable, making it possible to characterize the influence of each variable on the IRC estimation. Furthermore, we assessed the mapping characteristics of kernel estimation overall as well as by municipality. Overall, our model reproduces spatial IRC patterns which were already obtained earlier. On the municipal level, we could show that our model accounts well for IRC trends within municipal boundaries. Finally, we found that different building characteristics result in different IRC maps. Maps corresponding to detached houses with concrete foundations indicate systematically smaller IRC than maps corresponding to farms with earth foundation. CONCLUSIONS: IRC mapping based on kernel estimation is a powerful tool to predict and analyze IRC on a large-scale as well as on a local level. This approach enables to develop tailor-made maps for different architectural elements and measurement conditions and to account at the same time for geological information and spatial relations between IRC measurements.

Syndromic algorithms for detection of gambiense human african trypanosomiasis in South Sudan.

BACKGROUND: Active screening by mobile teams is considered the best method for detecting human African trypanosomiasis (HAT) caused by Trypanosoma brucei gambiense but the current funding context in many post-conflict countries limits this approach. As an alternative, non-specialist health care workers (HCWs) in peripheral health facilities could be trained to identify potential cases who need testing based on their symptoms. We explored the predictive value of syndromic referral algorithms to identify symptomatic cases of HAT among a treatment-seeking population in Nimule, South Sudan. METHODOLOGY/PRINCIPAL FINDINGS: Symptom data from 462 patients (27 cases) presenting for a HAT test via passive screening over a 7 month period were collected to construct and evaluate over 14,000 four item syndromic algorithms considered simple enough to be used by peripheral HCWs. For comparison, algorithms developed in other settings were also tested on our data, and a panel of expert HAT clinicians were asked to make referral decisions based on the symptom dataset. The best performing algorithms consisted of three core symptoms (sleep problems, neurological problems and weight loss), with or without a history of oedema, cervical adenopathy or proximity to livestock. They had a sensitivity of 88.9-92.6%, a negative predictive value of up to 98.8% and a positive predictive value in this context of 8.4-8.7%. In terms of sensitivity, these out-performed more complex algorithms identified in other studies, as well as the expert panel. The best-performing algorithm is predicted to identify about 9/10 treatment-seeking HAT cases, though only 1/10 patients referred would test positive. CONCLUSIONS/SIGNIFICANCE: In the absence of regular active screening, improving referrals of HAT patients through other means is essential. Systematic use of syndromic algorithms by peripheral HCWs has the potential to increase case detection and would increase their participation in HAT programmes. The algorithms proposed here, though promising, should be validated elsewhere.

Another way of thinking about ADHD: the predictive role of early attachment deprivation in adolescents' level of symptoms.

PURPOSE: Attention deficit and hyperactivity disorder (ADHD) is one of the most frequent disorders in childhood and adolescence. Both neurocognitive and environmental factors have been related to ADHD. The current study contributes to the documentation of the predictive relation between early attachment deprivation and ADHD. METHOD: Data were collected from 641 adopted adolescents (53.2 % girls) aged 11-16 years in five countries, using the DSM oriented scale for ADHD of the Child Behavior Checklist (CBCL) (Achenbach and Rescorla, Manual for the ASEBA school-age forms and profiles. University of Vermont, Research Center for Children, Youth and Families, Burlington, 2001). The influence of attachment deprivation on ADHD symptoms was initially tested taking into consideration several key variables that have been reported as influencing ADHD at the adoptee level (age, gender, length of time in the adoptive family, parents' educational level and marital status), and at the level of the country of origin and country of adoption (poverty, quality of health services and values). The analyses were computed using the multilevel modeling technique. RESULTS: The results showed that an increase in the level of ADHD symptoms was predicted by the duration of exposure to early attachment deprivation, estimated from the age of adoption, after controlling for the influence of adoptee and country variables. The effect of the age of adoption was also demonstrated to be specific to the level of ADHD symptoms in comparison to both the externalizing and internalizing behavior scales of the CBCL. CONCLUSION: Deprivation of stable and sensitive care in infancy may have long-lasting consequences for children's development.

Introduction of snow and geomorphic disturbance variables into predictive models of alpine plant distribution in the Western Swiss Alps

Indirect topographic variables have been used successfully as surrogates for disturbance processes in plant species distribution models (SDM) in mountain environments. However, no SDM studies have directly tested the performance of disturbance variables. In this study, we developed two disturbance variables: a geomorphic index (GEO) and an index of snow redistribution by wind (SNOW). These were developed in order to assess how they improved both the fit and predictive power of presenceabsence SDM based on commonly used topoclimatic (TC) variables for 91 plants in the Western Swiss Alps. The individual contribution of the disturbance variables was compared to TC variables. Maps of models were prepared to spatially test the effect of disturbance variables. On average, disturbance variables significantly improved the fit but not the predictive power of the TC models and their individual contribution was weak (5.6% for GEO and 3.3% for SNOW). However their maximum individual contribution was important (24.7% and 20.7%). Finally, maps including disturbance variables (i) were significantly divergent from TC models in terms of predicted suitable surfaces and connectivity between potential habitats, and (ii) were interpreted as more ecologically relevant. Disturbance variables did not improve the transferability of models at the local scale in a complex mountain system, and the performance and contribution of these variables were highly species-specific. However, improved spatial projections and change in connectivity are important issues when preparing projections under climate change because the future range size of the species will determine the sensitivity to changing conditions.

A new spin on a compositionalist predictive modelling framework for conservation planning: a tropical case study in Ecuador

Knowledge about spatial biodiversity patterns is a basic criterion for reserve network design. Although herbarium collections hold large quantities of information, the data are often scattered and cannot supply complete spatial coverage. Alternatively, herbarium data can be used to fit species distribution models and their predictions can be used to provide complete spatial coverage and derive species richness maps. Here, we build on previous effort to propose an improved compositionalist framework for using species distribution models to better inform conservation management. We illustrate the approach with models fitted with six different methods and combined using an ensemble approach for 408 plant species in a tropical and megadiverse country (Ecuador). As a complementary view to the traditional richness hotspots methodology, consisting of a simple stacking of species distribution maps, the compositionalist modelling approach used here combines separate predictions for different pools of species to identify areas of alternative suitability for conservation. Our results show that the compositionalist approach better captures the established protected areas than the traditional richness hotspots strategies and allows the identification of areas in Ecuador that would optimally complement the current protection network. Further studies should aim at refining the approach with more groups and additional species information.