A program of nurse algorithm-guided care for adult patients with acute minor illnesses in primary care

Background: Attention to patients with acute minor-illnesses requesting same-day consultation represents a major burden in primary care. The workload is assumed by general practitioners in many countries. A number of reports suggest that care to these patients may be provided, at in least in part, by nurses. However, there is scarce information with respect to the applicability of a program of nurse management for adult patients with acute minor-illnesses in large areas. The aim of this study is to assess the effectiveness of a program of nurse algorithm-guided care for adult patients with acute minor illnesses requesting same-day consultation in primary care in a largely populated area. Methods: A cross-sectional study of all adult patients seeking same day consultation for 16 common acute minor illnesses in a large geographical area with 284 primary care practices. Patients were included in a program of nurse case management using management algorithms. The main outcome measure was case resolution, defined as completion of the algorithm by the nurse without need of referral of the patient to the general practitioner. The secondary outcome measure was return to consultation, defined as requirement of new consultation for the same reason as the first one, in primary care within a 7-day period. Results: During a two year period (April 2009-April 2011), a total of 1,209,669 consultations were performed in the program. Case resolution was achieved by nurses in 62.5% of consultations. The remaining cases were referred to a general practitioner. Resolution rates ranged from 94.2% in patients with burns to 42% in patients with upper respiratory symptoms. None of the 16 minor illnesses had a resolution rate below 40%. Return to consultation during a 7-day period was low, only 4.6%. Conclusions: A program of algorithms-guided care is effective for nurse case management of patients requesting same day consultation for minor illnesses in primary care.

A program of nurse algorithm-guided care for adult patients with acute minor illnesses in primary care

Background: Attention to patients with acute minor-illnesses requesting same-day consultation represents a major burden in primary care. The workload is assumed by general practitioners in many countries. A number of reports suggest that care to these patients may be provided, at in least in part, by nurses. However, there is scarce information with respect to the applicability of a program of nurse management for adult patients with acute minor-illnesses in large areas. The aim of this study is to assess the effectiveness of a program of nurse algorithm-guided care for adult patients with acute minor illnesses requesting same-day consultation in primary care in a largely populated area. Methods: A cross-sectional study of all adult patients seeking same day consultation for 16 common acute minor illnesses in a large geographical area with 284 primary care practices. Patients were included in a program of nurse case management using management algorithms. The main outcome measure was case resolution, defined as completion of the algorithm by the nurse without need of referral of the patient to the general practitioner. The secondary outcome measure was return to consultation, defined as requirement of new consultation for the same reason as the first one, in primary care within a 7-day period. Results: During a two year period (April 2009-April 2011), a total of 1,209,669 consultations were performed in the program. Case resolution was achieved by nurses in 62.5% of consultations. The remaining cases were referred to a general practitioner. Resolution rates ranged from 94.2% in patients with burns to 42% in patients with upper respiratory symptoms. None of the 16 minor illnesses had a resolution rate below 40%. Return to consultation during a 7-day period was low, only 4.6%. Conclusions: A program of algorithms-guided care is effective for nurse case management of patients requesting same day consultation for minor illnesses in primary care.

Test result-based sampling: an efficient design for estimating the accuracy of patient safety indicators.

OBJECTIVE: Accuracy studies of Patient Safety Indicators (PSIs) are critical but limited by the large samples required due to low occurrence of most events. We tested a sampling design based on test results (verification-biased sampling [VBS]) that minimizes the number of subjects to be verified. METHODS: We considered 3 real PSIs, whose rates were calculated using 3 years of discharge data from a university hospital and a hypothetical screen of very rare events. Sample size estimates, based on the expected sensitivity and precision, were compared across 4 study designs: random and VBS, with and without constraints on the size of the population to be screened. RESULTS: Over sensitivities ranging from 0.3 to 0.7 and PSI prevalence levels ranging from 0.02 to 0.2, the optimal VBS strategy makes it possible to reduce sample size by up to 60% in comparison with simple random sampling. For PSI prevalence levels below 1%, the minimal sample size required was still over 5000. CONCLUSIONS: Verification-biased sampling permits substantial savings in the required sample size for PSI validation studies. However, sample sizes still need to be very large for many of the rarer PSIs.

A program of nurse algorithm-guided care for adult patients with acute minor illnesses in primary care

Background: Attention to patients with acute minor-illnesses requesting same-day consultation represents a major burden in primary care. The workload is assumed by general practitioners in many countries. A number of reports suggest that care to these patients may be provided, at in least in part, by nurses. However, there is scarce information with respect to the applicability of a program of nurse management for adult patients with acute minor-illnesses in large areas. The aim of this study is to assess the effectiveness of a program of nurse algorithm-guided care for adult patients with acute minor illnesses requesting same-day consultation in primary care in a largely populated area. Methods: A cross-sectional study of all adult patients seeking same day consultation for 16 common acute minor illnesses in a large geographical area with 284 primary care practices. Patients were included in a program of nurse case management using management algorithms. The main outcome measure was case resolution, defined as completion of the algorithm by the nurse without need of referral of the patient to the general practitioner. The secondary outcome measure was return to consultation, defined as requirement of new consultation for the same reason as the first one, in primary care within a 7-day period. Results: During a two year period (April 2009-April 2011), a total of 1,209,669 consultations were performed in the program. Case resolution was achieved by nurses in 62.5% of consultations. The remaining cases were referred to a general practitioner. Resolution rates ranged from 94.2% in patients with burns to 42% in patients with upper respiratory symptoms. None of the 16 minor illnesses had a resolution rate below 40%. Return to consultation during a 7-day period was low, only 4.6%. Conclusions: A program of algorithms-guided care is effective for nurse case management of patients requesting same day consultation for minor illnesses in primary care.

Efficient total variation algorithm for fetal brain MRI reconstruction.

Fetal MRI reconstruction aims at finding a high-resolution image given a small set of low-resolution images. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has considered several regularization terms s.a. Dirichlet/Laplacian energy, Total Variation (TV)- based energies and more recently non-local means. Although TV energies are quite attractive because of their ability in edge preservation, standard explicit steepest gradient techniques have been applied to optimize fetal-based TV energies. The main contribution of this work lies in the introduction of a well-posed TV algorithm from the point of view of convex optimization. Specifically, our proposed TV optimization algorithm or fetal reconstruction is optimal w.r.t. the asymptotic and iterative convergence speeds O(1/n2) and O(1/√ε), while existing techniques are in O(1/n2) and O(1/√ε). We apply our algorithm to (1) clinical newborn data, considered as ground truth, and (2) clinical fetal acquisitions. Our algorithm compares favorably with the literature in terms of speed and accuracy.

MRI of coronary vessel walls using radial k-space sampling and steady-state free precession imaging.

OBJECTIVE: The objective of our study was to investigate the impact of radial k-space sampling and steady-state free precession (SSFP) imaging on image quality in MRI of coronary vessel walls. SUBJECTS AND METHODS: Eleven subjects were examined on a 1.5-T MR system using three high-resolution navigator-gated and cardiac-triggered 3D black blood sequences (cartesian gradient-echo [GRE], radial GRE, and radial SSFP) with identical spatial resolution (0.9 x 0.9 x 2.4 mm3). The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), vessel wall sharpness, and motion artifacts were analyzed. RESULTS: The mean SNR and CNR of the coronary vessel wall were improved using radial imaging and were best using radial k-space sampling combined with SSFP imaging. Vessel border definition was similar for all three sequences. Radial k-space sampling was found to be less sensitive to motion. Consistently good image quality was seen with the radial GRE sequence. CONCLUSION: Radial k-space sampling in MRI of coronary vessel walls resulted in fewer motion artifacts and improved SNR and CNR. The use of SSFP imaging, however, did not result in improved coronary vessel wall visualization.

Prospective sampling based on model ensembles improves the detection of rare species

Identifying the geographic distribution of populations is a basic, yet crucial step in many fundamental and applied ecological projects, as it provides key information on which many subsequent analyses depend. However, this task is often costly and time consuming, especially where rare species are concerned and where most sampling designs generally prove inefficient. At the same time, rare species are those for which distribution data are most needed for their conservation to be effective. To enhance fieldwork sampling, model-based sampling (MBS) uses predictions from species distribution models: when looking for the species in areas of high habitat suitability, chances should be higher to find them. We thoroughly tested the efficiency of MBS by conducting an important survey in the Swiss Alps, assessing the detection rate of three rare and five common plant species. For each species, habitat suitability maps were produced following an ensemble modeling framework combining two spatial resolutions and two modeling techniques. We tested the efficiency of MBS and the accuracy of our models by sampling 240 sites in the field (30 sitesx8 species). Across all species, the MBS approach proved to be effective. In particular, the MBS design strictly led to the discovery of six sites of presence of one rare plant, increasing chances to find this species from 0 to 50%. For common species, MBS doubled the new population discovery rates as compared to random sampling. Habitat suitability maps coming from the combination of four individual modeling methods predicted well the species' distribution and more accurately than the individual models. As a conclusion, using MBS for fieldwork could efficiently help in increasing our knowledge of rare species distribution. More generally, we recommend using habitat suitability models to support conservation plans.

Predictive analysis and mapping of indoor radon concentrations in Switzerland

It is estimated that around 230 people die each year due to radon (222Rn) exposure in Switzerland. 222Rn occurs mainly in closed environments like buildings and originates primarily from the subjacent ground. Therefore it depends strongly on geology and shows substantial regional variations. Correct identification of these regional variations would lead to substantial reduction of 222Rn exposure of the population based on appropriate construction of new and mitigation of already existing buildings. Prediction of indoor 222Rn concentrations (IRC) and identification of 222Rn prone areas is however difficult since IRC depend on a variety of different variables like building characteristics, meteorology, geology and anthropogenic factors. The present work aims at the development of predictive models and the understanding of IRC in Switzerland, taking into account a maximum of information in order to minimize the prediction uncertainty. The predictive maps will be used as a decision-support tool for 222Rn risk management. The construction of these models is based on different data-driven statistical methods, in combination with geographical information systems (GIS). In a first phase we performed univariate analysis of IRC for different variables, namely the detector type, building category, foundation, year of construction, the average outdoor temperature during measurement, altitude and lithology. All variables showed significant associations to IRC. Buildings constructed after 1900 showed significantly lower IRC compared to earlier constructions. We observed a further drop of IRC after 1970. In addition to that, we found an association of IRC with altitude. With regard to lithology, we observed the lowest IRC in sedimentary rocks (excluding carbonates) and sediments and the highest IRC in the Jura carbonates and igneous rock. The IRC data was systematically analyzed for potential bias due to spatially unbalanced sampling of measurements. In order to facilitate the modeling and the interpretation of the influence of geology on IRC, we developed an algorithm based on k-medoids clustering which permits to define coherent geological classes in terms of IRC. We performed a soil gas 222Rn concentration (SRC) measurement campaign in order to determine the predictive power of SRC with respect to IRC. We found that the use of SRC is limited for IRC prediction. The second part of the project was dedicated to predictive mapping of IRC using models which take into account the multidimensionality of the process of 222Rn entry into buildings. We used kernel regression and ensemble regression tree for this purpose. We could explain up to 33% of the variance of the log transformed IRC all over Switzerland. This is a good performance compared to former attempts of IRC modeling in Switzerland. As predictor variables we considered geographical coordinates, altitude, outdoor temperature, building type, foundation, year of construction and detector type. Ensemble regression trees like random forests allow to determine the role of each IRC predictor in a multidimensional setting. We found spatial information like geology, altitude and coordinates to have stronger influences on IRC than building related variables like foundation type, building type and year of construction. Based on kernel estimation we developed an approach to determine the local probability of IRC to exceed 300 Bq/m3. In addition to that we developed a confidence index in order to provide an estimate of uncertainty of the map. All methods allow an easy creation of tailor-made maps for different building characteristics. Our work is an essential step towards a 222Rn risk assessment which accounts at the same time for different architectural situations as well as geological and geographical conditions. For the communication of 222Rn hazard to the population we recommend to make use of the probability map based on kernel estimation. The communication of 222Rn hazard could for example be implemented via a web interface where the users specify the characteristics and coordinates of their home in order to obtain the probability to be above a given IRC with a corresponding index of confidence. Taking into account the health effects of 222Rn, our results have the potential to substantially improve the estimation of the effective dose from 222Rn delivered to the Swiss population.

Solid-phase microextraction as short-term sampling technique for BTEX occupational exposure

Solid phase microextraction (SPME) has been widely used for many years in various applications, such as environmental and water samples, food and fragrance analysis, or biological fluids. The aim of this study was to suggest the SPME method as an alternative to conventional techniques used in the evaluation of worker exposure to benzene, toluene, ethylbenzene, and xylene (BTEX). Polymethylsiloxane-carboxen (PDMS/CAR) showed as the most effective stationary phase material for sorbing BTEX among other materials (polyacrylate, PDMS, PDMS/divinylbenzene, Carbowax/divinylbenzene). Various experimental conditions were studied to apply SPME to BTEX quantitation in field situations. The uptake rate of the selected fiber (75 μm PDMS/CAR) was determined for each analyte at various concentrations, relative humidities, and airflow velocities from static (calm air) to dynamic (>200 cm/s) conditions. The SPME method also was compared with the National Institute of Occupational Safety and Health method 1501. Unlike the latter, the SPME approach fulfills the new requirement for the threshold limit value-short term exposure limit (TLV-STEL) of 2.5 ppm for benzene (8 mg/m3).

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.

Limited sampling strategies for monitoring tacrolimus in paediatric liver transplant recipients

Ce travail de recherche a été réalisé dans le laboratoire de pharmacologie clinique, au Centre Hospitalier Universitaire Sainte-Justine, à Montréal. C'est une étude rétrospective basée sur le suivi thérapeutique du Tacrolimus prescrit chez les enfants après transplantation hépatique. Ce suivi est nécessaire car le Tacrolimus possède une importante variabilité pharmacocinétique inter et intra-individuelle ainsi qu'un index thérapeutique très étroit. Actuellement, l'individualisation des doses prescrites est basée sur la mesure de la concentration de base - du médicament dans le sang (C0), mais des études récentes montrent que cette mesure ne reflète pas précisément l'exposition du Tacrolimus dans l'organisme chez les enfants. Le meilleur reflet de cette exposition est la mesure de l'aire sous la courbe (AUC). Cependant, cette dernière implique la mesure de multiples concentrations tout au long de l'intervalle entre 2 doses de médicament (Tacrolimus: 12 heures) ce qui est long, cher et impraticable en ambulatoire. De nouvelles méthodes utilisant un nombre limité de prélèvements ont donc été développées pour prédire au mieux cette AUC. Ce sont les "Limited sampling strategies" ou LSS. La plupart de ces LSS pour le Tacrolimus ont été développées et validées chez des patients transplantés adultes et leur application directe chez les transplantés pédiatriques n'est pas possible en raison de différences importantes au niveau des paramètres pharmacocinétiques du médicament entre ces deux populations. Aussi, le but de ce travail était de développer et valider, pour la première fois, des LSS chez les enfants transplantés hépatiques. Pour cela, une analyse de 36 profils pharmacocinétiques de 28 patients transplantés hépatiques âgés de 0.4- 18.5 ans a été effectuée. Tous les profils ont été réalisés au Centre Hospitalier Universitaire Sainte-Justine entre janvier 2007 et janvier 2009. Les LSS comportant au maximum 4 mesures de concentration ont été développées en utilisant une analyse de régression multiple. Parmi tous les modèles obtenus, cinq ont été sélectionnés sur la base de critères précis puis validés selon la méthode décrite par Sheiner et Beal.¦Les résultats montrent que ces cinq modèles peuvent prédire l'AUC du Tacrolimus avec une précision cliniquement acceptable de ± 15% alors que la C0 présente la plus faible corrélation avec l'AUC.¦En conclusion, cette étude confirme que la C0 ne permet pas de prédire de manière efficace l'exposition du Tacrolimus dans l'organisme dans notre population de patients pédiatriques contrairement aux LSS analysées qui offrent une méthode pratique et fiable. Par ailleurs, en permettant d'obtenir une estimation précise et simplifiée de l'AUC complète du Tacrolimus chez les patients, ces LSS ouvrent la porte à de futures études prospectives visant à mieux définir l'AUC cible du médicament et à déterminer si le suivi basé sur la mesure de l'AUC est plus efficace et plus sûr que celui basé sur la mesure de la C0.

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.

Interpolating and sampling sequences in finite Riemann surfaces

We provide a description of the interpolating and sampling sequences on a space of holomorphic functions on a finite Riemann surface, where a uniform growth restriction is imposed on the holomorphic functions.