Drug utilization analysis of osteoporosis medications in seven European electronic health databases

We studied the characteristics of patients prescribed osteoporosis medication and patterns of use in European databases. Patients were mostly female, older, had hypertension. There was suboptimal persistence particularly for oral medications. Our findings would be useful to healthcare providers to focus their resources on improving persistence to specific osteoporosis treatments.

PURPOSE

To characterise the patients prescribed osteoporosis therapy and describe the drug utilization patterns.

METHODS

We investigated the treatment patterns of bisphosphonates, denosumab, teriparatide, and selective estrogen receptor modulators (SERMs) in seven European databases in the United Kingdom, Italy, the Netherlands, Denmark, Spain, and Germany. In this cohort study, we included adults aged ≥ 18 years, with ≥ 1 year of registration in the respective databases, who were new users of the osteoporosis medications. The study period was between 01 January 2018 to 31 January 2022.

RESULTS

Overall, patients were most commonly initiated on alendronate. Persistence decreased over time across all medications and databases, ranging from 52-73% at 6 months to 29-53% at 12 months for alendronate. For other oral bisphosphonates, the proportion of persistent users was 50-66% at 6 months and decreased to 30-44% at 12 months. For SERMs, the proportion of persistent users at 6 months was 40-73% and decreased to 25-59% at 12 months. For parenteral treatment groups, the proportions of persistence with denosumab were 50-85% (6 month), 30-63% (12 month) and with teriparatide 40-75% (6 month) decreasing to 21-54% (12 month). Switching occurred most frequently in the alendronate group (2.8-5.8%) and in the teriparatide group (7.1-14%). Switching typically occurred in the first 6 months and decreased over time. Patients in the alendronate group most often switched to other oral or intravenous bisphosphonates and denosumab.

CONCLUSION

Our results show suboptimal persistence to medications that varied across different databases and treatment switching was relatively rare.

Transforming the Information System for Research in Primary Care (SIDIAP) in Catalonia to the OMOP Common Data Model and Its Use for COVID-19 Research

Purpose

The primary aim of this work was to convert the Information System for Research in Primary Care (SIDIAP) from Catalonia, Spain, to the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). Our second aim was to provide a descriptive analysis of COVID-19-related outcomes among the general population.

Patients and Methods

We mapped patient-level data from SIDIAP to the OMOP CDM and we performed more than 3,400 data quality checks to assess its readiness for research. We established a general population cohort as of the 1st March 2020 and identified outpatient COVID-19 diagnoses or tested positive for, hospitalised with, admitted to intensive care units (ICU) with, died with, or vaccinated against COVID-19 up to 30th June 2022.

Results

After verifying the high quality of the transformed dataset, we included 5,870,274 individuals in the general population cohort. Of those, 604,472 had either an outpatient COVID-19 diagnosis or positive test result, 58,991 had a hospitalisation, 5,642 had an ICU admission, and 11,233 died with COVID-19. A total of 4,584,515 received a COVID-19 vaccine. People who were hospitalised or died were more commonly older, male, and with more comorbidities. Those admitted to ICU with COVID-19 were generally younger and more often male than those hospitalised and those who died.

Conclusion

We successfully transformed SIDIAP to the OMOP CDM. From this dataset, a general population cohort of 5.9 million individuals was identified and their COVID-19-related outcomes over time were described. The transformed SIDIAP database is a valuable resource that can enable distributed network research in COVID-19 and beyond.

Background rates of 41 adverse events of special interest for COVID-19 vaccines in 10 European healthcare databases - an ACCESS cohort study

BACKGROUND

In May 2020, the ACCESS (The vACCine covid-19 monitoring readinESS) project was launched to prepare real-world monitoring of COVID-19 vaccines. Within this project, this study aimed to generate background incidence rates of 41 adverse events of special interest (AESI) to contextualize potential safety signals detected following administration of COVID-19 vaccines.

METHODS

A dynamic cohort study was conducted using a distributed data network of 10 healthcare databases from 7 European countries (Italy, Spain, Denmark, The Netherlands, Germany, France and United Kingdom) over the period 2017 to 2020. A common protocol (EUPAS37273), common data model, and common analytics programs were applied for syntactic, semantic and analytical harmonization. Incidence rates (IR) for each AESI and each database were calculated by age and sex by dividing the number of incident cases by the total person-time at risk. Age-standardized rates were pooled using random effect models according to the provenance of the events.

FINDINGS

A total number of 63,456,074 individuals were included in the study, contributing to 211.7 million person-years. A clear age pattern was observed for most AESIs, rates also varied by provenance of disease diagnosis (primary care, specialist care). Thrombosis with thrombocytopenia rates were extremely low ranging from 0.06 to 4.53/100,000 person-years for cerebral venous sinus thrombosis (CVST) with thrombocytopenia (TP) and mixed venous and arterial thrombosis with TP, respectively.

INTERPRETATION

Given the nature of the AESIs and the setting (general practitioners or hospital-based databases or both), background rates from databases that show the highest level of completeness (primary care and specialist care) should be preferred, others can be used for sensitivity. The study was designed to ensure representativeness to the European population and generalizability of the background incidence rates.

FUNDING

The project has received support from the European Medicines Agency under the Framework service contract nr EMA/2018/28/PE.

Air pollution and green spaces in relation to breast cancer risk among pre and postmenopausal women: A mega cohort from Catalonia

BACKGROUND

The association between air pollution and green spaces with breast cancer risk stratified by menopausal status has not been frequently investigated despite its importance given the different impact of risk factors on breast cancer risk depending on menopausal status.

OBJECTIVES

To study the association between air pollution, green spaces and pre and postmenopausal breast cancer risk.

METHODS

We conducted a population-based cohort study using electronic primary care records in Catalonia. We included women aged 17-85 years free of cancer at study entry between 2009 and 2017. Our exposures were particulate matter <2.5 μm (PM_2.5) & <10 μm (PM₁₀), nitrogen dioxide (NO₂), normalized difference vegetation index (NDVI), and percentage of green spaces estimated at the census tract level. Breast cancer was identified with ICD-10 code C50. We estimated cause-specific hazard ratios (HR) for the relationship between each individual exposure and pre and postmenopausal breast cancer risk, using linear and non-linear models.

RESULTS

Of the 1,054,180 pre and 744,658 postmenopausal women followed for a median of 10 years, 6,126 and 17,858 developed breast cancer, respectively. Among premenopausal women, only very high levels of PM₁₀ (≥46 μg/m³) were associated with increased cancer risk (compared to lower levels) in non-linear models. Among postmenopausal women, an interquartile range increase in PM_2.5 (HR:1.03; 95%CI:1.01-1.04), PM₁₀ (1.03; 1.01-1.05), and NO₂ (1.05; 1.02-1.08) were associated with higher cancer risk. NDVI was negatively associated with decreased cancer risk only among postmenopausal women who did not change residence during follow-up (0.84; 0.71-0.99) or who were followed for at least three years (0.82; 0.69-0.98).

DISCUSSION

Living in areas with high concentrations of PM_2.5, PM₁₀, and NO₂ increases breast cancer risk in postmenopausal women while long-term exposure to green spaces may decrease this risk. Only very high concentrations of PM₁₀ increase breast cancer risk in premenopausal women.

International cohort study indicates no association between alpha-1 blockers and susceptibility to COVID-19 in benign prostatic hyperplasia patients

Purpose: Alpha-1 blockers, often used to treat benign prostatic hyperplasia (BPH), have been hypothesized to prevent COVID-19 complications by minimising cytokine storm release. The proposed treatment based on this hypothesis currently lacks support from reliable real-world evidence, however. We leverage an international network of large-scale healthcare databases to generate comprehensive evidence in a transparent and reproducible manner.

Methods: In this international cohort study, we deployed electronic health records from Spain (SIDIAP) and the United States (Department of Veterans Affairs, Columbia University Irving Medical Center, IQVIA OpenClaims, Optum DOD, Optum EHR). We assessed association between alpha-1 blocker use and risks of three COVID-19 outcomes—diagnosis, hospitalization, and hospitalization requiring intensive services—using a prevalent-user active-comparator design. We estimated hazard ratios using state-of-the-art techniques to minimize potential confounding, including large-scale propensity score matching/stratification and negative control calibration. We pooled database-specific estimates through random effects meta-analysis.

Results: Our study overall included 2.6 and 0.46 million users of alpha-1 blockers and of alternative BPH medications. We observed no significant difference in their risks for any of the COVID-19 outcomes, with our meta-analytic HR estimates being 1.02 (95% CI: 0.92–1.13) for diagnosis, 1.00 (95% CI: 0.89–1.13) for hospitalization, and 1.15 (95% CI: 0.71–1.88) for hospitalization requiring intensive services.

Conclusion: We found no evidence of the hypothesized reduction in risks of the COVID-19 outcomes from the prevalent-use of alpha-1 blockers—further research is needed to identify effective therapies for this novel disease.

Background rates of five thrombosis with thrombocytopenia syndromes of special interest for COVID-19 vaccine safety surveillance: Incidence between 2017 and 2019 and patient profiles from 38.6 million people in six European countries

Background

Thrombosis with thrombocytopenia syndrome (TTS) has been reported among individuals vaccinated with adenovirus‐vectored COVID‐19 vaccines. In this study, we describe the background incidence of non‐vaccine induced TTS in six European countries.

Methods

Electronic medical records from France, the Netherlands, Italy, Germany, Spain, and the United Kingdom informed the study. Incidence rates of cerebral venous sinus thrombosis (CVST), splanchnic vein thrombosis (SVT), deep vein thrombosis (DVT), pulmonary embolism (PE), and myocardial infarction or ischemic stroke, all with concurrent thrombocytopenia, were estimated among the general population of persons in a database between 2017 and 2019. A range of additional potential adverse events of special interest for COVID‐19 vaccinations were also studied in a similar manner.

Findings

A total of 38 611 617 individuals were included. Background rates ranged from 1.0 (95% CI: 0.7–1.4) to 8.5 (7.4–9.9) per 100 000 person‐years for DVT with thrombocytopenia, from 0.5 (0.3–0.6) to 20.8 (18.9–22.8) for PE with thrombocytopenia, from 0.1 (0.0–0.1) to 2.5 (2.2–2.7) for SVT with thrombocytopenia, and from 1.0 (0.8–1.2) to 43.4 (40.7–46.3) for myocardial infarction or ischemic stroke with thrombocytopenia. CVST with thrombocytopenia was only identified in one database, with incidence rate of 0.1 (0.1–0.2) per 100 000 person‐years. The incidence of non‐vaccine induced TTS increased with age, and was typically greater among those with more comorbidities and greater medication use than the general population. It was also more often seen in men than women. A large proportion of those affected were seen to have been taking antithrombotic and anticoagulant therapies prior to their event.

Interpretation

Although rates vary across databases, non‐vaccine induced TTS has consistently been seen to be a very rare event among the general population. While still remaining very rare, rates were typically higher among older individuals, and those affected were also seen to generally be male and have more comorbidities and greater medication use than the general population.

Cancer and the risk of coronavirus disease 2019 diagnosis, hospitalisation and death: A population-based multistate cohort study including 4 618 377 adults in Catalonia, Spain

The relationship between cancer and coronavirus disease 2019 (COVID-19) infection and severity remains poorly understood. We conducted a population-based cohort study between 1 March and 6 May 2020 describing the associations between cancer and risk of COVID-19 diagnosis, hospitalisation and COVID-19-related death. Data were obtained from the Information System for Research in Primary Care (SIDIAP) database, including primary care electronic health records from ~80% of the population in Catalonia, Spain. Cancer was defined as any primary invasive malignancy excluding non-melanoma skin cancer. We estimated adjusted hazard ratios (aHRs) for the risk of COVID-19 (outpatient) clinical diagnosis, hospitalisation (with or without a prior COVID-19 diagnosis) and COVID-19-related death using Cox proportional hazard regressions. Models were estimated for the overall cancer population and by years since cancer diagnosis (<1 year, 1-5 years and ≥5 years), sex, age and cancer type; and adjusted for age, sex, smoking status, deprivation and comorbidities. We included 4 618 377 adults, of which 260 667 (5.6%) had a history of cancer. A total of 98 951 individuals (5.5% with cancer) were diagnosed, and 6355 (16.4% with cancer) were directly hospitalised with COVID-19. Of those diagnosed, 6851 were subsequently hospitalised (10.7% with cancer), and 3227 died without being hospitalised (18.5% with cancer). Among those hospitalised, 1963 (22.5% with cancer) died. Cancer was associated with an increased risk of COVID-19 diagnosis (aHR: 1.08; 95% confidence interval [1.05-1.11]), direct COVID-19 hospitalisation (1.33 [1.24-1.43]) and death following hospitalisation (1.12 [1.01-1.25]). These associations were stronger for patients recently diagnosed with cancer, aged <70 years, and with haematological cancers. These patients should be prioritised in COVID-19 vaccination campaigns and continued non-pharmaceutical interventions.

Seek COVER: using a disease proxy to rapidly develop and validate a personalized risk calculator for COVID-19 outcomes in an international network

Background

We investigated whether we could use influenza data to develop prediction models for COVID-19 to increase the speed at which prediction models can reliably be developed and validated early in a pandemic. We developed COVID-19 Estimated Risk (COVER) scores that quantify a patient’s risk of hospital admission with pneumonia (COVER-H), hospitalization with pneumonia requiring intensive services or death (COVER-I), or fatality (COVER-F) in the 30-days following COVID-19 diagnosis using historical data from patients with influenza or flu-like symptoms and tested this in COVID-19 patients.

Methods

We analyzed a federated network of electronic medical records and administrative claims data from 14 data sources and 6 countries containing data collected on or before 4/27/2020. We used a 2-step process to develop 3 scores using historical data from patients with influenza or flu-like symptoms any time prior to 2020. The first step was to create a data-driven model using LASSO regularized logistic regression, the covariates of which were used to develop aggregate covariates for the second step where the COVER scores were developed using a smaller set of features. These 3 COVER scores were then externally validated on patients with 1) influenza or flu-like symptoms and 2) confirmed or suspected COVID-19 diagnosis across 5 databases from South Korea, Spain, and the United States. Outcomes included i) hospitalization with pneumonia, ii) hospitalization with pneumonia requiring intensive services or death, and iii) death in the 30 days after index date.

Results

Overall, 44,507 COVID-19 patients were included for model validation. We identified 7 predictors (history of cancer, chronic obstructive pulmonary disease, diabetes, heart disease, hypertension, hyperlipidemia, kidney disease) which combined with age and sex discriminated which patients would experience any of our three outcomes. The models achieved good performance in influenza and COVID-19 cohorts. For COVID-19 the AUC ranges were, COVER-H: 0.69–0.81, COVER-I: 0.73–0.91, and COVER-F: 0.72–0.90. Calibration varied across the validations with some of the COVID-19 validations being less well calibrated than the influenza validations.

Conclusions

This research demonstrated the utility of using a proxy disease to develop a prediction model. The 3 COVER models with 9-predictors that were developed using influenza data perform well for COVID-19 patients for predicting hospitalization, intensive services, and fatality. The scores showed good discriminatory performance which transferred well to the COVID-19 population. There was some miscalibration in the COVID-19 validations, which is potentially due to the difference in symptom severity between the two diseases. A possible solution for this is to recalibrate the models in each location before use.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01505-z.

From Inception to ConcePTION: Genesis of a Network to Support Better Monitoring and Communication of Medication Safety During Pregnancy and Breastfeeding

In 2019, the Innovative Medicines Initiative (IMI) funded the ConcePTION project-Building an ecosystem for better monitoring and communicating safety of medicines use in pregnancy and breastfeeding: validated and regulatory endorsed workflows for fast, optimised evidence generation-with the vision that there is a societal obligation to rapidly reduce uncertainty about the safety of medication use in pregnancy and breastfeeding. The present paper introduces the set of concepts used to describe the European data sources involved in the ConcePTION project and illustrates the ConcePTION Common Data Model (CDM), which serves as the keystone of the federated ConcePTION network. Based on data availability and content analysis of 21 European data sources, the ConcePTION CDM has been structured with six tables designed to capture data from routine healthcare, three tables for data from public health surveillance activities, three curated tables for derived data on population (e.g., observation time and mother-child linkage), plus four metadata tables. By its first anniversary, the ConcePTION CDM has enabled 13 data sources to run common scripts to contribute to major European projects, demonstrating its capacity to facilitate effective and transparent deployment of distributed analytics, and its potential to address questions about utilization, effectiveness, and safety of medicines in special populations, including during pregnancy and breastfeeding, and, more broadly, in the general population.

Implementation of the COVID-19 Vulnerability Index Across an International Network of Health Care Data Sets: Collaborative External Validation Study

Background

SARS-CoV-2 is straining health care systems globally. The burden on hospitals during the pandemic could be reduced by implementing prediction models that can discriminate patients who require hospitalization from those who do not. The COVID-19 vulnerability (C-19) index, a model that predicts which patients will be admitted to hospital for treatment of pneumonia or pneumonia proxies, has been developed and proposed as a valuable tool for decision-making during the pandemic. However, the model is at high risk of bias according to the “prediction model risk of bias assessment” criteria, and it has not been externally validated.

Objective

The aim of this study was to externally validate the C-19 index across a range of health care settings to determine how well it broadly predicts hospitalization due to pneumonia in COVID-19 cases.

Methods

We followed the Observational Health Data Sciences and Informatics (OHDSI) framework for external validation to assess the reliability of the C-19 index. We evaluated the model on two different target populations, 41,381 patients who presented with SARS-CoV-2 at an outpatient or emergency department visit and 9,429,285 patients who presented with influenza or related symptoms during an outpatient or emergency department visit, to predict their risk of hospitalization with pneumonia during the following 0-30 days. In total, we validated the model across a network of 14 databases spanning the United States, Europe, Australia, and Asia.

Results

The internal validation performance of the C-19 index had a C statistic of 0.73, and the calibration was not reported by the authors. When we externally validated it by transporting it to SARS-CoV-2 data, the model obtained C statistics of 0.36, 0.53 (0.473-0.584) and 0.56 (0.488-0.636) on Spanish, US, and South Korean data sets, respectively. The calibration was poor, with the model underestimating risk. When validated on 12 data sets containing influenza patients across the OHDSI network, the C statistics ranged between 0.40 and 0.68.

Conclusions

Our results show that the discriminative performance of the C-19 index model is low for influenza cohorts and even worse among patients with COVID-19 in the United States, Spain, and South Korea. These results suggest that C-19 should not be used to aid decision-making during the COVID-19 pandemic. Our findings highlight the importance of performing external validation across a range of settings, especially when a prediction model is being extrapolated to a different population. In the field of prediction, extensive validation is required to create appropriate trust in a model.

Alpha-1 blockers and susceptibility to COVID-19 in benign prostate hyperplasia patients : an international cohort study

Alpha-1 blockers, often used to treat benign prostate hyperplasia (BPH), have been hypothesized to prevent COVID-19 complications by minimising cytokine storms release. We conducted a prevalent-user active-comparator cohort study to assess association between alpha-1 blocker use and risks of three COVID-19 outcomes: diagnosis, hospitalization, and hospitalization requiring intensive services. Our study included 2.6 and 0.46 million users of alpha-1 blockers and of alternative BPH therapy during the period between November 2019 and January 2020, found in electronic health records from Spain (SIDIAP) and the United States (Department of Veterans Affairs, Columbia University Irving Medical Center, IQVIA OpenClaims, Optum DOD, Optum EHR). We estimated hazard ratios using state-of-the-art techniques to minimize potential confounding, including large-scale propensity score matching/stratification and negative control calibration. We found no differential risk for any of COVID-19 outcome, pointing to the need for further research on potential COVID-19 therapies.

Filling the gaps in the characterization of the clinical management of COVID-19: 30-day hospital admission and fatality rates in a cohort of 118 150 cases diagnosed in outpatient settings in Spain

BACKGROUND

Currently, there is a missing link in the natural history of COVID-19, from first (usually milder) symptoms to hospitalization and/or death. To fill in this gap, we characterized COVID-19 patients at the time at which they were diagnosed in outpatient settings and estimated 30-day hospital admission and fatality rates.

METHODS

This was a population-based cohort study.

Data were obtained from Information System for Research in Primary Care (SIDIAP)-a primary-care records database covering >6 million people (>80% of the population of Catalonia), linked to COVID-19 reverse transcriptase polymerase chain reaction (RT-PCR) tests and hospital emergency, inpatient and mortality registers. We included all patients in the database who were ≥15 years old and diagnosed with COVID-19 in outpatient settings between 15 March and 24 April 2020 (10 April for outcome studies). Baseline characteristics included socio-demographics, co-morbidity and previous drug use at the time of diagnosis, and polymerase chain reaction (PCR) testing and results.

Study outcomes included 30-day hospitalization for COVID-19 and all-cause fatality.

RESULTS

We identified 118 150 and 95 467 COVID-19 patients for characterization and outcome studies, respectively. Most were women (58.7%) and young-to-middle-aged (e.g. 21.1% were 45-54 years old). Of the 44 575 who were tested with PCR, 32 723 (73.4%) tested positive. In the month after diagnosis, 14.8% (14.6-15.0) were hospitalized, with a greater proportion of men and older people, peaking at age 75-84 years. Thirty-day fatality was 3.5% (95% confidence interval: 3.4% to 3.6%), higher in men, increasing with age and highest in those residing in nursing homes [24.5% (23.4% to 25.6%)].

CONCLUSION

COVID-19 infections were widespread in the community, including all age-sex strata. However, severe forms of the disease clustered in older men and nursing-home residents. Although initially managed in outpatient settings, 15% of cases required hospitalization and 4% died within a month of first symptoms. These data are instrumental for designing deconfinement strategies and will inform healthcare planning and hospital-bed allocation in current and future COVID-19 outbreaks.

Endothelial dysfunction is an early indicator of sepsis and neutrophil degranulation of septic shock in surgical patients

Background

Stratification of the severity of infection is currently based on the Sequential Organ Failure Assessment (SOFA) score, which is difficult to calculate outside the ICU. Biomarkers could help to stratify the severity of infection in surgical patients.

Methods

Levels of ten biomarkers indicating endothelial dysfunction, 22 indicating emergency granulopoiesis, and six denoting neutrophil degranulation were compared in three groups of patients in the first 12 h after diagnosis at three Spanish hospitals.

Results

There were 100 patients with infection, 95 with sepsis and 57 with septic shock. Seven biomarkers indicating endothelial dysfunction (mid‐regional proadrenomedullin (MR‐ProADM), syndecan 1, thrombomodulin, angiopoietin 2, endothelial cell‐specific molecule 1, vascular cell adhesion molecule 1 and E‐selectin) had stronger associations with sepsis than infection alone. MR‐ProADM had the highest odds ratio (OR) in multivariable analysis (OR 11·53, 95 per cent c.i. 4·15 to 32·08; P = 0·006) and the best area under the curve (AUC) for detecting sepsis (0·86, 95 per cent c.i. 0·80 to 0·91; P < 0·001). In a comparison of sepsis with septic shock, two biomarkers of neutrophil degranulation, proteinase 3 (OR 8·09, 1·34 to 48·91; P = 0·028) and lipocalin 2 (OR 6·62, 2·47 to 17·77; P = 0·002), had the strongest association with septic shock, but lipocalin 2 exhibited the highest AUC (0·81, 0·73 to 0·90; P < 0·001).

Conclusion

MR‐ProADM and lipocalin 2 could be alternatives to the SOFA score in the detection of sepsis and septic shock respectively in surgical patients with infection.

Viabilidad del caracol terrestre (Cantareus aspersus) durante la época de descanso

Los periodos de estivación e hibernación del caracol son periodos críticos de en la producción helicícola y su conocimiento contribuye decisivamente a la organización productiva y los resultados económicos de las granjas. El objetivo de este estudio fue determinar la evolución del peso vivo y la viabilidad del caracol terrestre (Cantareus aspersus), en condiciones semicontroladas durante el periodo de reposo. La experiencia tuvo una duración de 32 semanas, desde septiembre de 2013 hasta mayo del 2014. Los resultados obtenidos muestran una disminución del peso vivo del 13,57 % y una perdida de la viabilidad en torno al 20 %. Este estudio abre nuevas líneas de investigación orientadas al conocimiento de la fase de hibernación de los caracoles que manejados adecuadamente permite establecer distintas estrategias reproductivas y de manejo en la producción industrial del caracol terrestre C. aspersus.

Determination of N-nitrosamines and nicotine in air particulate matter samples by pressurised liquid extraction and gas chromatography-ion trap tandem mass spectrometry

N-nitrosamines are potentially hazardous pollutants, classified as probable carcinogenic and mutagenic by the U.S. Environmental Protection Agency (EPA). In this paper, the presence of these pollutants was studied in air samples taken at different locations of Tarragona (urban and harbour). As a result, a reliable method has been developed for determining N-nitrosamines and nicotine based on pressurised liquid extraction (PLE) and gas chromatography-(chemical ionisation) ion trap tandem mass spectrometry (GC-(CI)MS/MS). The chromatographic analysis enables the determination of these compounds in less than 13 min with total separation and good resolution between the compounds. Recovery values were higher than 80% for most of the compounds and the repeatability of the method was under 18% (5 ng m(-3), %RSD, n=4). MDLs were between 0.1 ng m(-3) (NMor and NPip) and 2 ng m(-3) (NMEA). NMor, NPyr, NPip and nicotine were the most frequent compounds in urban and harbour samples at concentration levels between 0.3 ng m(-3) (NPyr) and 12.5 ng m(-3) (nicotine) and between 0.13 ng m(-3) (NPyr) and 3.8 ng m(-3) (nicotine), respectively.

The nuclear poly(A) binding protein, PABP2, forms an oligomeric particle covering the length of the poly(A) tail

The mammalian nuclear poly(A) binding protein, PABP2, controls the length of the newly synthesized poly(A) tail on messenger RNAs. To gain a better understanding of the mechanism of length control, we have investigated the structure of the PABP2.poly(A) complex. Electron microscopy and scanning force microscopy studies reveal that PABP2, when bound to poly(A), forms both linear filaments and discrete-sized, compact, oligomeric particles. The maximum diameter of the filament is 7 nm; the maximum diameter of the particle is 21(+/-2) nm. Maximum particle size is realized when the PABP2. poly(A) complex is formed with poly(A) molecules 200-300 nt long, which corresponds to the average length of the newly synthesized poly(A) tail in vitro and in vivo. The equilibrium between filaments and particles is highly sensitive to ionic strength; filaments are favored at low ionic strength, while particles predominate at moderate to high ionic strength. Nitrocellulose filter binding and gel mobility shift assays indicate that the PABP2.poly(A) particle formed on A(300) is not significantly more stable than complexes formed with smaller species of poly(A). These results are discussed in the context of the proposed functions for PABP2.

Shigellosis in Mozambique: the 1993 outbreak rehabilitation--a follow-up study

In this paper we describe a dysentery outbreak in Mozambique during 1993. A total of 47,483 cases and 199 deaths were reported, with an incidence rate of 292.5/100,000 and a fatality rate of 0.25% for the whole country. Of the 144 districts in the country 123 were affected: those situated along the principal communications routes and corridors had high incidence rates, up to 3308/100,000. All the provincial capitals were affected with incidence rates between 59.6 and 4381.8/100,000. Shigella dysenteriae type 1 was identified as the aetiological agent. This strain was sensitive to nalidixic acid, cephalosporins, gentamicin and kanamycin, and resistant to tetracyclines, trimethoprim, chloramphenicol, ampicillin, sulphisoxazole, cotrimoxazol and erythromycin. This is the first dysentery epidemic caused by S. dysenteriae type 1 reported in Mozambique. The epidemic still continues. Population movements after the war, poor levels of sanitation and poverty contributed to the gravity of the outbreak.

[Cholera epidemiology in Mozambique: 1973-1992]

The results of an epidemiological analysis of cholera in Mozambique from 1973 to 1992 are described. The project sought to assess the influence of socio-economic and ecological factors the spread of cholera in a country at war. Information about the incidence of cholera and the fatality rate were related to the rainfall and the annual average growth rate of the population in the main cities. Water supply, sanitation and food hygiene were also studied. The high annual average growth rate of the population was found to have a direct linear correlation to the incidence of cholera. The drought of 1991-1992 also played an important role in the increased number of cases of the disease. Cholera has presented an endemic-epidemic pattern determined by: a) the uncontrolled growth of urban population, b) the deterioration of sanitation in urban centers, c) the unhygienic commercialization of food and d) the drought.

[Clinical, echocardiographic and hemodynamic sequence in cerebral arteriovenous fistula]

It is presented a fatal case of cerebral arteriovenous tube in which it was obtained clinical, radiological, electric, echocardiographic and haemodinamic sequencial information since the birth. Data suggested biventricular overcharge's existence initially without cardiac insufficiency. Finally appeared right ventricular expansion's data and biventricular hypertrophy, with left ventricular fluxe's diminution and cardiac insufficiency's data and shock.