Differences in femoral fracture localizations in men and women in Switzerland between 1998 and 2021-reversal of the secular trend?

Number and age-standardized incidences of femoral fractures by sex and localization were determined annually between 1998 and 2021 in subjects aged 45 years or older living in Switzerland. The number and incidences of femoral neck, pertrochanteric, subtrochanteric, and femoral shaft fractures followed distinct unexpected trend patterns.

INTRODUCTION

Long-term incidence trends for femoral fractures by individual localizations are unknown.

METHODS

Annual absolute number of hospitalizations and median age at hospital admission between 1998 and 2021 were extracted from the medical database of the Swiss Federal Office of Statistics by sex and 10-year age groups for the following 10th International Classification of Diseases (ICD-10) codes: femoral neck (ICD-10 S72.0), pertrochanteric (S72.1), subtrochanteric (S72.2), and femoral shaft fractures (S72.3). Age-standardized incidence rates (ASI) and corresponding trends were calculated.

RESULTS

Over 24 years, the number of femoral neck fractures increased in men (+ 45%) but decreased in women (- 7%) with ASI significantly decreasing by 20% and 37% (p < 0.001 for trend for both), respectively. By contrast, the number of pertrochanteric fractures increased by 67% and 45% in men and women, respectively, corresponding to a horizontal ASI-trend in men (n.s.) and a modest significant decreasing ASI-trend in women (p < 0.001). The number of subtrochanteric fractures increased in both sexes with corresponding modest significant reductions in ASI-trends (p = 0.015 and 0.002, respectively). Femoral shaft fractures almost doubled in men (+ 71%) and doubled in women (+ 100%) with corresponding significant increases in ASI-trends (p = 0.001 and p < 0.001, respectively). Age at admission increased for all fracture localizations, more so in men than in women and more so for subtrochanteric and shaft fractures than for "typical" hip fractures.

CONCLUSION

Incidence changes of pertrochanteric fractures and femoral shaft fractures deserve increased attention, especially in men. Pooling diagnostic codes for defining hip fractures may hide differing patterns by localization and sex.

Development of Predictive Models to Inform a Novel Risk Categorization Framework for Antibiotic Resistance in E. coli-Causing Uncomplicated Urinary Tract Infection

BACKGROUND

In clinical practice, challenges in identifying patients with uncomplicated urinary tract infections (uUTIs) at risk of antibiotic non-susceptibility may lead to inappropriate prescribing and contribute to antibiotic resistance. We developed predictive models to quantify risk of non-susceptibility to four commonly prescribed antibiotic classes for uUTI, identify predictors of non-susceptibility to each class, and construct a corresponding risk categorization framework for non-susceptibility.

METHODS

Eligible females aged ≥12 years with E. coli-caused uUTI were identified from Optum's de-identified Electronic Health Record dataset (10/1/2015‒2/29/2020). Four predictive models were developed to predict non-susceptibility to each antibiotic class and a risk categorization framework was developed to classify patients' isolates as low, moderate, and high risk of non-susceptibility to each antibiotic class.

RESULTS

Predictive models were developed among 87487 patients. Key predictors of having a non-susceptible isolate to ≥3 antibiotic classes included number of previous UTI episodes, prior β-lactam non-susceptibility, prior fluoroquinolone treatment, census bureau region, and race. The risk categorization framework classified 8.1%, 14.4%, 17.4%, and 6.3% of patients as having isolates at high risk of non-susceptibility to nitrofurantoin, trimethoprim-sulfamethoxazole, β-lactams, and fluoroquinolones, respectively. Across classes, the proportion of patients categorized as having high-risk isolates was 3-12 folds higher among patients with non-susceptible isolates versus susceptible isolates.

CONCLUSIONS

Our predictive models highlight factors that increase risk of non-susceptibility to antibiotics for uUTIs, while the risk categorization framework contextualizes risk of non-susceptibility to these treatments. Our findings provide valuable insight to clinicians treating uUTIs and may help inform empiric prescribing in this population.

Unsupervised machine learning identifies distinct ALS molecular subtypes in post-mortem motor cortex and blood expression data

Amyotrophic lateral sclerosis (ALS) displays considerable clinical and genetic heterogeneity. Machine learning approaches have previously been utilised for patient stratification in ALS as they can disentangle complex disease landscapes. However, lack of independent validation in different populations and tissue samples have greatly limited their use in clinical and research settings. We overcame these issues by performing hierarchical clustering on the 5000 most variably expressed autosomal genes from motor cortex expression data of people with sporadic ALS from the KCL BrainBank (N = 112). Three molecular phenotypes linked to ALS pathogenesis were identified: synaptic and neuropeptide signalling, oxidative stress and apoptosis, and neuroinflammation. Cluster validation was achieved by applying linear discriminant analysis models to cases from TargetALS US motor cortex (N = 93), as well as Italian (N = 15) and Dutch (N = 397) blood expression datasets, for which there was a high assignment probability (80-90%) for each molecular subtype. The ALS and motor cortex specificity of the expression signatures were tested by mapping KCL BrainBank controls (N = 59), and occipital cortex (N = 45) and cerebellum (N = 123) samples from TargetALS to each cluster, before constructing case-control and motor cortex-region logistic regression classifiers. We found that the signatures were not only able to distinguish people with ALS from controls (AUC 0.88 ± 0.10), but also reflect the motor cortex-based disease process, as there was perfect discrimination between motor cortex and the other brain regions. Cell types known to be involved in the biological processes of each molecular phenotype were found in higher proportions, reinforcing their biological interpretation. Phenotype analysis revealed distinct cluster-related outcomes in both motor cortex datasets, relating to disease onset and progression-related measures. Our results support the hypothesis that different mechanisms underpin ALS pathogenesis in subgroups of patients and demonstrate potential for the development of personalised treatment approaches. Our method is available for the scientific and clinical community at https://alsgeclustering.er.kcl.ac.uk .

Addressing the unresolved challenge of quantifying skiing exposure-A proof of concept using smartphone sensors

In epidemiological studies related to winter sports, especially alpine skiing, an unresolved methodological challenge is the quantification of actual on-snow activity exposure. Such information would be relevant for reporting meaningful measures of injury incidence, which refers to the number of new injuries that occur in a given population and time period. Accordingly, accurate determination of the denominator, i.e., actual "activity exposure time", is critical for injury surveillance and reporting. In this perspective article, we explore the question of whether wearable sensors in combination with mHealth applications are suitable tools to accurately quantify the periods in a ski day when the skier is physically skiing and not resting or using a mechanical means of transport. As a first proof of concept, we present exemplary data from a youth competitive alpine skier who wore his smartphone with embedded sensors on his body on several ski days during one winter season. We compared these data to self-reported estimates of ski exposure, as used in athletes' training diaries. In summary, quantifying on-snow activity exposure in alpine skiing using sensor data from smartphones is technically feasible. For example, the sensors could be used to track ski training sessions, estimate the actual time spent skiing, and even quantify the number of runs and turns made as long as the smartphone is worn. Such data could be very useful in determining actual exposure time in the context of injury surveillance and could prove valuable for effective stress management and injury prevention in athletes.

The osteoporosis treatment gap in Switzerland between 1998 and 2018

The annual number of patients treated for osteoporosis between 1998 and 2018 in Switzerland increased until 2008 and steadily decreased thereafter. With a continuously growing population at fracture risk exceeding an intervention threshold, the treatment gap has increased and the incidence of hip fractures has stopped declining in the past decade.

INTRODUCTION

The existence of an osteoporosis treatment gap, defined as the percentage of patients at risk for osteoporotic fractures exceeding an intervention threshold but remaining untreated, is widely acknowledged. Between 1998 and 2018, new bone active substances (BAS) indicated for the treatment of osteoporosis became available. Whether and if so to what extent these new introductions have altered the treatment gap is unknown.

METHODS

The annual number of patients treated with a BAS was calculated starting from single-drug unit sales. The number of patients theoretically eligible for treatment with a BAS was estimated based on four scenarios corresponding to different intervention thresholds (one based solely on a bone mineral density T score threshold and three FRAX-based thresholds) and the resulting annual treatment gaps were calculated.

RESULTS

In Switzerland, the estimated number of patients on treatment with a BAS increased from 35,901 in year 1998 to 233,381 in year 2018. However, this number grew regularly since 1998, peaked in 2008, and steadily decreased thereafter, in timely coincidence with the launch of intravenous bisphosphonates and the RANKL inhibitor denosumab. When expressed in numbers of untreated persons at risk for osteoporotic fractures exceeding a given intervention threshold, the treatment gaps were of similar magnitude in 1998 (when the first BSAs just had become available) and 2018. There was a strong association, which does not imply causation, between the proportion of patients treated and hip fracture incidence.

CONCLUSION

In Switzerland, the osteoporosis treatment gap has increased over the past decade. The availability of new BAS has not contributed to its decrease.

Hospitalizations for major osteoporotic fractures in Switzerland: a long-term trend analysis between 1998 and 2018

Between 1998 and 2018, the number of hospitalizations for major osteoporotic fractures increased. After standardization for age, these numerical increases translated into a reduced incidence of hospitalizations for hip fractures and an increased incidence of hospitalizations for spine, proximal humerus, and distal radius fractures in both sexes.

INTRODUCTION

The longterm epidemiological trends of hospitalizations for major osteoporotic fractures (MOF) between 1998 and 2018 in Switzerland are unknown.

METHODS

The absolute number of acute hospitalizations for MOF (hip fractures and fractures of the spine, proximal humerus, and distal radius) and related length of acute hospital stay were extracted from the medical database of the Swiss Federal Office of Statistics. Age-standardized incidence rates were calculated using 1998 as the reference year.

RESULTS

Hospitalizations for MOF increased from 4483 to 7542 (+ 68.2%) in men and from 13,242 to 19,362 (+ 46.2%) in women. The age-standardized incidence of hospitalizations for MOF increased by 5.7% in men (p = 0.002) and by 5.1% in women (p = 0.018). The age-standardized incidence of hip fractures decreased by 15.3% in men (p < 0.001) and by 21.5% in women (p < 0.001). In parallel, the age-standardized incidence of MOF other than hip fractures increased by 31.8% in men (p < 0.001) and by 40.1% in women (p < 0.001). The mean length of acute hospital stays for MOF decreased from 16.3 to 8.5 days in men and from 16.9 to 8.1 days in women.

CONCLUSION

Between 1998 and 2018, the number of hospitalizations for MOF increased significantly by a larger extent than expected based on the ageing of the Swiss population alone. This increase was solely driven by an increased incidence of MOF other than hip fractures as incident hip fractures decreased over time in both sexes, more so in women than in men.

Global healthcare fairness: We should be sharing more, not less, data

The availability of large, deidentified health datasets has enabled significant innovation in using machine learning (ML) to better understand patients and their diseases. However, questions remain regarding the true privacy of this data, patient control over their data, and how we regulate data sharing in a way that that does not encumber progress or further potentiate biases for underrepresented populations. After reviewing the literature on potential reidentifications of patients in publicly available datasets, we argue that the cost-measured in terms of access to future medical innovations and clinical software-of slowing ML progress is too great to limit sharing data through large publicly available databases for concerns of imperfect data anonymization. This cost is especially great for developing countries where the barriers preventing inclusion in such databases will continue to rise, further excluding these populations and increasing existing biases that favor high-income countries. Preventing artificial intelligence's progress towards precision medicine and sliding back to clinical practice dogma may pose a larger threat than concerns of potential patient reidentification within publicly available datasets. While the risk to patient privacy should be minimized, we believe this risk will never be zero, and society has to determine an acceptable risk threshold below which data sharing can occur-for the benefit of a global medical knowledge system.

Forecasting the COVID-19 Pandemic: Lessons learned and future directions

I.The Coronavirus Disease 2019 (COVID-19) has demonstrated that accurate forecasts of infection and mortality rates are essential for informing healthcare resource allocation, designing countermeasures, implementing public health policies, and increasing public awareness. However, there exist a multitude of modeling methodologies, and their relative performances in accurately forecasting pandemic dynamics are not currently comprehensively understood. In this paper, we introduce the non-mechanistic MIT-LCP forecasting model, and assess and compare its performance to various mechanistic and non-mechanistic models that have been proposed for forecasting COVID-19 dynamics. We performed a comprehensive experimental evaluation which covered the time period of November 2020 to April 2021, in order to determine the relative performances of MIT-LCP and seven other forecasting models from the United States' Centers for Disease Control and Prevention (CDC) Forecast Hub. Our results show that there exist forecasting scenarios well-suited to both mechanistic and non-mechanistic models, with mechanistic models being particularly performant for forecasts that are further in the future when recent data may not be as informative, and non-mechanistic models being more effective with shorter prediction horizons when recent representative data is available. Improving our understanding of which forecasting approaches are more reliable, and in which forecasting scenarios, can assist effective pandemic preparation and management.

Detection of diabetes from whole-body MRI using deep learning

Obesity is one of the main drivers of type 2 diabetes, but it is not uniformly associated with the disease. The location of fat accumulation is critical for metabolic health. Specific patterns of body fat distribution, such as visceral fat, are closely related to insulin resistance. There might be further, hitherto unknown, features of body fat distribution that could additionally contribute to the disease. We used machine learning with dense convolutional neural networks to detect diabetes-related variables from 2371 T1-weighted whole-body MRI data sets. MRI was performed in participants undergoing metabolic screening with oral glucose tolerance tests. Models were trained for sex, age, BMI, insulin sensitivity, HbA1c, and prediabetes or incident diabetes. The results were compared with those of conventional models. The area under the receiver operating characteristic curve was 87% for the type 2 diabetes discrimination and 68% for prediabetes, both superior to conventional models. Mean absolute regression errors were comparable to those of conventional models. Heatmaps showed that lower visceral abdominal regions were critical in diabetes classification. Subphenotyping revealed a group with high future diabetes and microalbuminuria risk.Our results show that diabetes is detectable from whole-body MRI without additional data. Our technique of heatmap visualization identifies plausible anatomical regions and highlights the leading role of fat accumulation in the lower abdomen in diabetes pathogenesis.

Overcoming barriers to data sharing with medical image generation: a comprehensive evaluation

Privacy concerns around sharing personally identifiable information are a major barrier to data sharing in medical research. In many cases, researchers have no interest in a particular individual's information but rather aim to derive insights at the level of cohorts. Here, we utilise generative adversarial networks (GANs) to create medical imaging datasets consisting entirely of synthetic patient data. The synthetic images ideally have, in aggregate, similar statistical properties to those of a source dataset but do not contain sensitive personal information. We assess the quality of synthetic data generated by two GAN models for chest radiographs with 14 radiology findings and brain computed tomography (CT) scans with six types of intracranial haemorrhages. We measure the synthetic image quality by the performance difference of predictive models trained on either the synthetic or the real dataset. We find that synthetic data performance disproportionately benefits from a reduced number of classes. Our benchmark also indicates that at low numbers of samples per class, label overfitting effects start to dominate GAN training. We conducted a reader study in which trained radiologists discriminate between synthetic and real images. In accordance with our benchmark results, the classification accuracy of radiologists improves with an increasing resolution. Our study offers valuable guidelines and outlines practical conditions under which insights derived from synthetic images are similar to those that would have been derived from real data. Our results indicate that synthetic data sharing may be an attractive alternative to sharing real patient-level data in the right setting.

Diurnal variations in multi-sensor wearable-derived sleep characteristics in morning- and evening-type shift workers under naturalistic conditions

Consumer-grade, multi-sensor, rest-activity trackers may be powerful tools, to help optimize rest-activity management in shiftwork populations undergoing circadian misalignment. Nevertheless, performance testing of such devices under field conditions is scarce. We previously validated Fitbit Charge 2^TM against home polysomnography and now evaluated the potential of this device to document differences in rest-activity behavior, including sleep macrostructure, in first-responder shift workers in an operational setting. We continuously monitored 89 individuals (54% females; mean age: 33.9 ± 7.7 years) for 32.5 ± 9.3 days and collected 2,974 individual sleep episodes scattered around the clock. We stratified the study participants according to their self-reported circadian preference on the reduced Horne-Östberg Morningness-Evening Questionnaire (rMEQ; the scores from 4 participants were missing). Fitbit estimates of sleep duration, wakefulness after sleep onset (WASO), REM sleep percentage in the first NREM-REM sleep cycle, and REM sleep latency formed approximately sinusoidal oscillations across 24 hours. Generalized additive mixed model analyses revealed that the phase position of sleep duration minimum was delayed by 2.8 h in evening types (ET; rMEQ ≤ 11; n = 20) and by 2.6 h in intermediate types (IT; 11 < rMEQ < 18; n = 45) when compared to morning types (MT; rMEQ ≥ 18; n = 20). Similarly, the phase position of WASO was delayed by 2.7 h in ET compared to MT. While nocturnal sleep duration did not differ among the three groups, sleep episodes during the biological day decreased in duration from ET to IT to MT. Together, the findings support the notion that a consumer-grade, rest-activity tracker allows estimation of behavioral sleep/wake cycles and sleep macrostructure in shift workers under naturalistic conditions that are consistent with their self-reported chronotype.

A Deep Learning Approach to Diagnosing Multiple Sclerosis from Smartphone Data

Multiple sclerosis (MS) affects the central nervous system with a wide range of symptoms. MS can, for example, cause pain, changes in mood and fatigue, and may impair a person's movement, speech and visual functions. Diagnosis of MS typically involves a combination of complex clinical assessments and tests to rule out other diseases with similar symptoms. New technologies, such as smartphone monitoring in free-living conditions, could potentially aid in objectively assessing the symptoms of MS by quantifying symptom presence and intensity over long periods of time. Here, we present a deep-learning approach to diagnosing MS from smartphone-derived digital biomarkers that uses a novel combination of a multilayer perceptron with neural soft attention to improve learning of patterns in long-term smartphone monitoring data. Using data from a cohort of 774 participants, we demonstrate that our deep-learning models are able to distinguish between people with and without MS with an area under the receiver operating characteristic curve of 0.88 (95% CI: 0.70, 0.88). Our experimental results indicate that digital biomarkers derived from smartphone data could in the future be used as additional diagnostic criteria for MS.

Crowdsourcing digital health measures to predict Parkinson's disease severity: the Parkinson's Disease Digital Biomarker DREAM Challenge

Consumer wearables and sensors are a rich source of data about patients' daily disease and symptom burden, particularly in the case of movement disorders like Parkinson's disease (PD). However, interpreting these complex data into so-called digital biomarkers requires complicated analytical approaches, and validating these biomarkers requires sufficient data and unbiased evaluation methods. Here we describe the use of crowdsourcing to specifically evaluate and benchmark features derived from accelerometer and gyroscope data in two different datasets to predict the presence of PD and severity of three PD symptoms: tremor, dyskinesia, and bradykinesia. Forty teams from around the world submitted features, and achieved drastically improved predictive performance for PD status (best AUROC = 0.87), as well as tremor- (best AUPR = 0.75), dyskinesia- (best AUPR = 0.48) and bradykinesia-severity (best AUPR = 0.95).

Real-time prediction of COVID-19 related mortality using electronic health records

Coronavirus disease 2019 (COVID-19) is a respiratory disease with rapid human-to-human transmission caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Due to the exponential growth of infections, identifying patients with the highest mortality risk early is critical to enable effective intervention and prioritisation of care. Here, we present the COVID-19 early warning system (CovEWS), a risk scoring system for assessing COVID-19 related mortality risk that we developed using data amounting to a total of over 2863 years of observation time from a cohort of 66 430 patients seen at over 69 healthcare institutions. On an external cohort of 5005 patients, CovEWS predicts mortality from 78.8% (95% confidence interval [CI]: 76.0, 84.7%) to 69.4% (95% CI: 57.6, 75.2%) specificity at sensitivities greater than 95% between, respectively, 1 and 192 h prior to mortality events. CovEWS could enable earlier intervention, and may therefore help in preventing or mitigating COVID-19 related mortality.

Clinical Predictive Models for COVID-19: Systematic Study

BACKGROUND

COVID-19 is a rapidly emerging respiratory disease caused by SARS-CoV-2. Due to the rapid human-to-human transmission of SARS-CoV-2, many health care systems are at risk of exceeding their health care capacities, in particular in terms of SARS-CoV-2 tests, hospital and intensive care unit (ICU) beds, and mechanical ventilators. Predictive algorithms could potentially ease the strain on health care systems by identifying those who are most likely to receive a positive SARS-CoV-2 test, be hospitalized, or admitted to the ICU.

OBJECTIVE

The aim of this study is to develop, study, and evaluate clinical predictive models that estimate, using machine learning and based on routinely collected clinical data, which patients are likely to receive a positive SARS-CoV-2 test or require hospitalization or intensive care.

METHODS

Using a systematic approach to model development and optimization, we trained and compared various types of machine learning models, including logistic regression, neural networks, support vector machines, random forests, and gradient boosting. To evaluate the developed models, we performed a retrospective evaluation on demographic, clinical, and blood analysis data from a cohort of 5644 patients. In addition, we determined which clinical features were predictive to what degree for each of the aforementioned clinical tasks using causal explanations.

RESULTS

Our experimental results indicate that our predictive models identified patients that test positive for SARS-CoV-2 a priori at a sensitivity of 75% (95% CI 67%-81%) and a specificity of 49% (95% CI 46%-51%), patients who are SARS-CoV-2 positive that require hospitalization with 0.92 area under the receiver operator characteristic curve (AUC; 95% CI 0.81-0.98), and patients who are SARS-CoV-2 positive that require critical care with 0.98 AUC (95% CI 0.95-1.00).

CONCLUSIONS

Our results indicate that predictive models trained on routinely collected clinical data could be used to predict clinical pathways for COVID-19 and, therefore, help inform care and prioritize resources.

Onsager relations in a two-dimensional electron gas with spin-orbit coupling

Theory predicts for the two-dimensional electron gas with only a Rashba spin-orbit interaction a vanishing spin Hall conductivity and at the same time a finite inverse spin Hall effect. We show how these seemingly contradictory results are compatible with the Onsager relations: The latter do hold for spin and particle (charge) currents in the two-dimensional electron gas, although (i) their form depends on the experimental setup and (ii) a vanishing bulk spin Hall conductivity does not necessarily imply a vanishing spin Hall effect. We also discuss the situation in which extrinsic spin orbit from impurities is present and the bulk spin Hall conductivity can be different from zero.

Comparative trends in hospitalizations for osteoporotic fractures and other frequent diseases between 2000 and 2008

In Switzerland, the number, incidence, and cost of acute hospitalizations for major osteoporotic fractures (MOF) and major cardiovascular events (MCE) increased in both women and men between 2000 and 2008, although the mean length of stay (LOS) was significantly reduced. Similar trend patterns were observed for hip fractures and strokes (decrease) and nonhip fractures and acute myocardial infarctions (increase).

INTRODUCTION

The purpose of this study was to compare the trends and epidemiological characteristics of hospitalizations for MOF and other frequent diseases between years 2000 and 2008 in Switzerland.

METHODS

Trends in the number, age-standardized incidence, mean LOS, and cost of hospitalized MOF and MCE (acute myocardial infarction, stroke, and heart failure) were compared in women and men aged ≥ 45 years, based on data from the Swiss Federal Statistical Office.

RESULTS

Between 2000 and 2008, the incidence of acute hospitalizations for MOF increased by 3.4% in women and 0.3% in men. In both sexes, a significant decrease in hip fractures (-15.0% and -11.0%) was compensated by a concomitant, significant increase in nonhip fractures (+24.8% and +13.8%). Similarly, the incidence of acute hospitalizations for MCE increased by 4.4% in women and 8.2% in men, as an aggregated result from significantly increasing acute myocardial infarctions and significantly decreasing strokes. While the mean LOS in the acute inpatient setting decreased almost linearly between years 2000 and 2008 in all indications, the inpatient costs increased significantly (p < 0.001) for MOF (+30.1% and +42.7%) and MCE (+22.6% and +47.1%) in women and men, respectively.

CONCLUSIONS

Between years 2000 and 2008, the burden of hospitalized osteoporotic fractures to the Swiss healthcare system has continued to increase in both sexes. In women, this burden was significantly higher than that of MCE and the gap widened over time.

Fracture hospitalizations between years 2000 and 2007 in Switzerland: a trend analysis

In Switzerland, the total number and incidence of hospitalizations for major osteoporotic fractures increased between years 2000 and 2007, while hospitalizations due to hip fracture decreased. The cost impact of shorter hospital stays was offset by the increasing cost per day of hospitalization.

INTRODUCTION

The aim of the study was to establish the trends and epidemiological characteristics of hospitalizations for major osteoporotic fractures (MOF) between years 2000 and 2007 in Switzerland.

METHODS

Sex- and age-specific trends in the number and crude and age-standardized incidences of hospitalized MOF (hip, clinical spine, distal radius, and proximal humerus) in women and men aged ≥45 years were analyzed, together with the number of hospital days and cost of hospitalization, based on data from the Swiss Federal Statistical Office hospital database and population statistics.

RESULTS

Between 2000 and 2007, the absolute number of hospitalizations for MOF increased by 15.9% in women and 20.0% in men, mainly due to an increased number of non-hip fractures (+37.7% in women and +39.7% in men). Hospitalizations for hip fractures were comparatively stable (-1.8% in women and +3.3% in men). In a rapidly aging population, in which the number of individuals aged ≥45 years grew by 11.1% (women) and 14.6% (men) over the study period, the crude and age-standardized incidences of hospitalizations decreased for hip fractures and increased for non-hip MOF, both in women and men. The length of hospital stay decreased for all MOF in women and men, the cost impact of which was offset by an increase in the daily costs of hospitalization.

CONCLUSIONS

Between years 2000 and 2007, hospitalizations for MOF continued to increase in Switzerland, driven by an increasing number and incidence of hospitalizations for non-hip fractures, although the incidence of hip fractures has declined.

Dynamic switching of the magnetization in a driven molecular nanomagnet

We study the magnetization dynamics of a single molecular nanomagnet driven by static and variable magnetic fields within a classical treatment. The underlying analysis is valid for a regime where the energy is definitely lower than the anisotropy barrier, but still a substantial number of states are excited. We find the phase space to contain a separatrix line. Solutions far from it are oscillatory whereas the separatrix solution is of a soliton type. States near the separatrix are extremely sensitive to small perturbations, a fact that we utilize in obtaining dynamically induced magnetization switching. A new type of magnetization switching is proposed.

Report of a National Conference on Donation after cardiac death

A national conference on organ donation after cardiac death (DCD) was convened to expand the practice of DCD in the continuum of quality end-of-life care. This national conference affirmed the ethical propriety of DCD as not violating the dead donor rule. Further, by new developments not previously reported, the conference resolved controversy regarding the period of circulatory cessation that determines death and allows administration of pre-recovery pharmacologic agents, it established conditions of DCD eligibility, it presented current data regarding the successful transplantation of organs from DCD, it proposed a new framework of data reporting regarding ischemic events, it made specific recommendations to agencies and organizations to remove barriers to DCD, it brought guidance regarding organ allocation and the process of informed consent and it set an action plan to address media issues. When a consensual decision is made to withdraw life support by the attending physician and patient or by the attending physician and a family member or surrogate (particularly in an intensive care unit), a routine opportunity for DCD should be available to honor the deceased donor's wishes in every donor service area (DSA) of the United States.

The effect of plants on the degradation and toxicity of petroleum contaminants in soil: a field assessment

A field project located at the US Naval Base at Port Hueneme, California was designed to evaluate changes in contaminant concentrations and toxicity during phytoremediation. Vegetated plots were established in petroleum (diesel and heavy oil) contaminated soil and were evaluated over a two-year period. Plant species were chosen based on initial germination studies and included native California grasses. The toxicity of the impacted soil in vegetated and unvegetated plots was evaluated using Microtox, earthworm, and seed germination assays. The reduction of toxicity was affected more by contaminant aging than the establishment of plants. However, total petroleum hydrocarbon concentrations were lower by the end of the study in the vegetated plots when compared to the unvegetated soil. Although phytoremediation is an effective approach for cleaning-up of petroleum contaminated soil, a long-term management plan is required for significant reductions in contaminant concentrations.

Selection of specific endophytic bacterial genotypes by plants in response to soil contamination

Plant-bacterial combinations can increase contaminant degradation in the rhizosphere, but the role played by indigenous root-associated bacteria during plant growth in contaminated soils is unclear. The purpose of this study was to determine if plants had the ability to selectively enhance the prevalence of endophytes containing pollutant catabolic genes in unrelated environments contaminated with different pollutants. At petroleum hydrocarbon contaminated sites, two genes encoding hydrocarbon degradation, alkane monooxygenase (alkB) and naphthalene dioxygenase (ndoB), were two and four times more prevalent in bacteria extracted from the root interior (endophytic) than from the bulk soil and sediment, respectively. In field sites contaminated with nitroaromatics, two genes encoding nitrotoluene degradation, 2-nitrotoluene reductase (ntdAa) and nitrotoluene monooxygenase (ntnM), were 7 to 14 times more prevalent in endophytic bacteria. The addition of petroleum to sediment doubled the prevalence of ndoB-positive endophytes in Scirpus pungens, indicating that the numbers of endophytes containing catabolic genotypes were dependent on the presence and concentration of contaminants. Similarly, the numbers of alkB- or ndoB-positive endophytes in Festuca arundinacea were correlated with the concentration of creosote in the soil but not with the numbers of alkB- or ndoB-positive bacteria in the bulk soil. Our results indicate that the enrichment of catabolic genotypes in the root interior is both plant and contaminant dependent.

Selection of specific endophytic bacterial genotypes by plants in response to soil contamination

Plant-bacterial combinations can increase contaminant degradation in the rhizosphere, but the role played by indigenous root-associated bacteria during plant growth in contaminated soils is unclear. The purpose of this study was to determine if plants had the ability to selectively enhance the prevalence of endophytes containing pollutant catabolic genes in unrelated environments contaminated with different pollutants. At petroleum hydrocarbon contaminated sites, two genes encoding hydrocarbon degradation, alkane monooxygenase (alkB) and naphthalene dioxygenase (ndoB), were two and four times more prevalent in bacteria extracted from the root interior (endophytic) than from the bulk soil and sediment, respectively. In field sites contaminated with nitroaromatics, two genes encoding nitrotoluene degradation, 2-nitrotoluene reductase (ntdAa) and nitrotoluene monooxygenase (ntnM), were 7 to 14 times more prevalent in endophytic bacteria. The addition of petroleum to sediment doubled the prevalence of ndoB-positive endophytes in Scirpus pungens, indicating that the numbers of endophytes containing catabolic genotypes were dependent on the presence and concentration of contaminants. Similarly, the numbers of alkB- or ndoB-positive endophytes in Festuca arundinacea were correlated with the concentration of creosote in the soil but not with the numbers of alkB- or ndoB-positive bacteria in the bulk soil. Our results indicate that the enrichment of catabolic genotypes in the root interior is both plant and contaminant dependent.

Carbenerhodium complexes of the half-sandwich-type: synthesis, substitution, and addition reactions

A series of carbenerhodium(I) complexes of the general composition [(eta5-C5H5)Rh(=CRR')(L)] (2a-2i) with R = R'= aryl and L = SbiPr3 or PR3 has been prepared from the square-planar precursors trans-[RhCl(=CRR')(L)2] and NaC5H5 in excellent yields. Reaction of the triisopropylsibane derivative 2a. which contains a rather labile Rh-Sb bond, with CO, PMe3, and CNR (R = Me, CH2Ph, tBu) leads to the displacement of the SbiPr3 ligand and affords the substitution products [(eta5-C5H5)Rh(=CPh2)(L)] (3-7). In contrast, treatment of the triisopropylphosphane compound 2c with CO and CNtBu leads to the cleavage of the Rh=CPh2 bond and gives besides [(eta5-C5H5)Rh(PiPr3)(L)] (10, 12) by metal-assisted C-C coupling diphenylketene Ph2C=C=O (11) or the corresponding imine Ph2C=C=NtBu (13). While the reaction of 2a, c with C2H4 yields [(eta5-C5H5)Rh(C2H4)(L)] (14, 15) and the trisubstituted olefin Ph2C=CHCH3 (16), treatment of 2a, c with RN3 leads to the cleavage of both the Rh-EiPr3 and Rh=CPh2 bonds and gives the chelate complexes [(eta5-C5H5)Rh(kappa2-RNNNNR)] (19, 20). The substitution products 3 (L=CO) and 4 (L= PMe3) react with an equimolar amount of sulfur or selenium by addition of the chalcogen to the Rh=CPh2 bond to generate the complexes [(eta5-C5H5)Rh(kappa2-ECPh2)(L)] (21-24) with thio- or selenobenzophenone as ligand. Similarly, treatment of 3 with CuCl affords the unusual 1:2 adduct [(eta5-C5H5)(CO)Rh(mu-CPh2)(CuCl)2] (25), which reacts with NaC5H5 to form [(eta5-C5H5)(CO)Rh(muCPh2)Cu(eta5-C5H5)] (26). The molecular structures of 3 and 22 have been determined by X-ray crystallography.

The bridging function of an apparently nonbridging ligand: dinuclear rhodium complexes with Rh(mu-SbR3)Rh as a molecular unit

Novel dinuclear rhodium complexes of the general composition [Rh2Cl2(mu-CRR')2(mu-SbiPr3)] (4-6) were prepared by thermolysis of the mononuclear precursors trans-[RhCl(=CRR')(SbiPr3)2] in excellent yield. The X-ray crystal structure analysis of 4 (R = R' = Ph) confirms the symmetrical bridging position of the stibane ligand. Related compounds [Rh2Cl2(mu-CPh2)(mu-CRR')(mu-SbiPr3)] (7, 8) with two different carbene units were obtained either from trans-[RhCl(=CPh2)(SbiPr3)2] (1) and RR'CN2 or by a conproportionation of 4 and 5 (R = R' = p-Tol) or 4 and 6 (R= Ph, R' = p-Tol), respectively. While CO reacts with 4 to give the polymeric product [[RhCl(CPh2)(CO)]n] (9), tert-butyl isocyanide replaces the bridging stibane and yields [Rh2Cl2(mu-CPh2)2(mu-CNtBu)] (10). The reaction of 4 with tertiary phosphanes PR3 leads to complete bridge cleavage and affords the mononuclear compounds trans-[RhCl(=CPh2)(PR3)2] (11-15). In contrast, treatment of 4 with SbMe3 and SbEt3 yields the related triply bridged complexes [Rh2Cl2(mu-CPh2)2(mu-SbR3)] (16, 17) by substitution of SbiPr3 for the smaller stibanes. The displacement of the chloro ligands in 4-6 and 10 by n5-cyclopentadienyl gives the dinuclear complexes [(n5-C5H5)2Rh2(mu-CRR')2] (18-20) and [(n5-C5H5)2Rh2(mu-CPh2)2(mu-CNtBu)] (21), of which 18 (R = R' = Ph) was characterized crystallographically.

T-cell studies in the spondyloarthropathies

A growing body of evidence suggests that T lymphocytes play an important role in initiating and maintaining the inflammatory process characteristic of the human leukocyte antigen (HLA)-B27-associated spondyloarthropathies. T cells seem to be involved in the primary defense reaction against arthritis-triggering gram-negative bacteria at the site of extra-articular infection, in determining the systemic cytokine pattern, in the recirculation process between gut mucosa and the joint, and in mediating secondary autoimmune joint inflammation. The factors involved in disease chronicity (namely in ankylosing spondylitis and psoriatic arthritis) are still unknown. Autoreactive T cells may contribute to this process by recognition of cross-reactive self-epitopes (ie, molecular mimicry between bacterial and self-antigens). Autoreactive T cells may as well be inappropriately upregulated by bacterial superantigens, or by local inflammatory reactions leading to the uncovering of former cryptic self-epitopes. In this paper, we review recent studies on peripheral blood and synovial T cells in patients with reactive arthritis, enteropathic spondyloarthropathy, psoriatic arthritis, and ankylosing spondylitis.

Effects of Helicobacter pylori on gastritis, pentagastrin-stimulated gastric acid secretion, and meal-stimulated plasma gastrin release in the absence of peptic ulcer disease

OBJECTIVE

There is strong evidence accumulating that chronic infection with Helicobacter pylori (H. pylori) interferes with inhibitory pathways of the regulation of acid secretion. The increase in maximum acid output (MAO), and the increase in the sensitivity of the parietal cell to gastrin commonly observed in patients suffering from duodenal ulcer disease (DU), however, remains largely unexplained. Insufficient evidence is available concerning how these parameters are influenced by H. pylori infection in patients not suffering from peptic ulcer disease (PUD) and how they are related to H. pylori-induced gastritis. The aim of this study was to compare basal gastric acid secretion (BAO), MAO, and the sensitivity of the parietal cell to gastrin in H. pylori-positive and H. pylori-negative patients not suffering from PUD, and to study the relationship with their individual postprandial gastrin release and the degree of gastric antral and corpus gastritis.

METHODS

H. pylori status was assessed by CLO test and histology (two biopsies each from the antrum and the corpus) in 14 H. pylori-positive and 16 H. pylori-negative nonulcer patients of comparable age, weight and gender. Gastritis score was assessed by a pathologist, who was unaware of the acid secretory data. Following determination of BAO, the relation of pentagastrin and gastric acid secretion was established with a cumulative pentagastrin dose response curve for the dose range 0.03-6.0 microg/kg(-1) h(-1) and MAO (Vmax) and pentagastrin sensitivity (ED50) were determined. Basal and postprandial gastrin release was measured by radioimmunoassay.

RESULTS

There was a significant higher gastritis score in the H. pylori-positive compared with the H. pylori-negative subjects. The dose response curves of the pentagastrin stimulated gastric acid secretion were not different between H. pylori-positive and H. pylori-negative groups. No correlation was seen between the gastritis score, basal acid output (BAO) peak acid output (PAO), maximum acid output (MAO), ED50 values and the plasma gastrin values. There was, however, a considerable larger variation of the PAO and MAO data of the H. pylori-infected subjects and >50% of the respective data was above or below the relatively low range of the respective values of the noninfected subjects.

CONCLUSIONS

H. pylori-induced gastritis does not regularly enhance maximum acid output in nonulcer patients, nor does it modify the sensitivity of the parietal cell to gastrin. H. pylori infection is thus unlikely to be directly responsible for an increase of these parameters in DU disease. Our data support, however, the concept that chronic H. pylori infection can either enhance or attenuate maximum acid secretory capacity in certain subgroups of patients.

Continuous quality improvement and the education of the generalist physician

The new health care environment--centered on patients, focused on health, and managed by generalists--requires new competencies for the generalist physician. Among these are knowledge and skills for the continuous improvement of health care. In many areas, generalist physicians already use quality improvement methods and principles to improve the health and health care of their communities. Efforts to teach medical students and residents to improve quality continuously in health care are beginning. Early lessons are: (1) quality improvement is most effectively learned in the context of real work; (2) initial emphasis must be on the basics; (3) the focus is on the needs of those we serve; (4) interdisciplinary skills are essential and best learned during clinical training; and (5) the best learning environment for future generalist physicians, one which results in optimism about the future and the ability to make things better, is an environment that is continuously improving.

Learning by mutual commitment: broadening the concept of learning contracts

A learning environment where students may negotiate with the course directors on the objectives and contents of a course, and where the teachers from pre-stated teaching and pedagogical obligations, may also negotiate with the students on what realistic demands they can meet when adjusting to individual students' needs, could be regarded as a set-up where learning by mutual commitment takes place. In order to support and to elaborate on reported experiences from using contracts as a learning device (Solomon, 1992), experiences gained from the Medical School of Witten/Herdecke, Germany, will be presented.