Laura Grisotto

Air pollution exposure, cause-specific deaths and hospitalizations in a highly polluted Italian region

BACKGROUND The Lombardy region in northern Italy ranks among the most air polluted areas of Europe. Previous studies showed air pollution short-term effects on all-cause mortality. We examine here the effects of particulate matter with aerodynamic diameter ≤10µm (PM10) and nitrogen dioxide (NO2) exposure on deaths and hospitalizations from specific causes, including cardiac, cerebrovascular and respiratory diseases. METHODS We considered air pollution, mortality and hospitalization data for a non-opportunistic sample of 18 highly polluted and most densely populated areas of the region in the years 2003-2006. We obtained area-specific effect estimates for PM10 and NO2 from a Poisson regression model on the daily number of total deaths or cause-specific hospitalizations and then combined them in a Bayesian random-effects meta-analysis. For cause-specific mortality, we applied a case-crossover analysis. Age- and season-specific analyses were also performed. Effect estimates were expressed as percent variation in mortality or hospitalizations associated with a 10µg/m(3) increase in PM10 or NO2 concentration. RESULTS Natural mortality was positively associated with both pollutants (0.30%, 90% Credibility Interval [CrI]: -0.31; 0.78 for PM10; 0.70%, 90%CrI: 0.10; 1.27 for NO2). Cardiovascular deaths showed a higher percent variation in association with NO2 (1.12%, 90% Confidence Interval [CI]: 0.14; 2.11), while the percent variation for respiratory mortality was highest in association with PM10 (1.64%, 90%CI: 0.35; 2.93). The effect of both pollutants was more evident in the summer season. Air pollution was also associated to hospitalizations, the highest variations being 0.77% (90%CrI: 0.22; 1.43) for PM10 and respiratory diseases, and 1.70% (90%CrI: 0.39; 2.84) for NO2 and cerebrovascular diseases. The effect of PM10 on respiratory hospital admissions appeared to increase with age. For both pollutants, effects on cerebrovascular hospitalizations were more evident in subjects aged less than 75 years. CONCLUSIONS Our study provided a sound characterization of air pollution exposure and its potential effects on human health in the most polluted, and also most populated and productive, Italian region, further documenting the need for effective public health policies.

Tracheobronchial obstruction: follow-up study of 100 children treated with airway stenting

OBJECTIVE We described a cohort of 100 children with a wide variety of airway obstruction who underwent stent positioning in the last 7 years. The study examined the outcomes of this treatment in the largest series of paediatric patients reported in the literature with special concern over safety and clinical effectiveness. METHODS We performed a retrospective analysis of 100 consecutive paediatric patients who underwent stent insertions between January 2005 and May 2012. Statistical analysis was performed and exact likelihood was used. RESULTS A total of 235 stents were placed for severe airway obstruction. One hundred and twelve silicone stents (cylinder, hourglass or Y-shaped), 120 metallic stents (covered Nitinol stents, expandable coronary and vascular stents) and 3 biodegradable polydioxanone (PDS) stents were used. Eighty patients presented clinical improvement after stent insertion, 17 were weaned off mechanical ventilation and 3 showed no significant clinical improvement [95% confidence interval (CI) 0.1-8.0%]. Complications were different according to stent type. In our cohort, no fatal stent-related complications have been observed. At follow-up (median 41.4 months, range 1.1-145.4) complete resolution was registered for 60 patients (66%; 95% CI 55-76%), 17 are still under treatment, 9 were lost to follow-up, 8 underwent surgery and 6 died of causes not stent related. CONCLUSION Airway stenting represents a conservative treatment before more invasive surgical procedures and can be very effective when performed in selected children and in specialized centres by physicians experienced in rigid and flexible bronchoscopy.

Commuting-adjusted short-term health impact assessment of airborne fine particles with uncertainty quantification via Monte Carlo simulation.

Background: Exposure to air pollution is associated with a short-term increase in mortality, and this field has begun to focus on health impact assessment. Objectives: Our aim was to estimate the impact of PM10 on mortality within 2 days from the exposure in the Italian region of Lombardy for the year 2007, at the municipality level, examining exposure entailed by daily intermunicipality commuting and accounting for uncertainty propagation. Methods: We combined data from different sources to derive probabilistic distributions for all input quantities used to calculate attributable deaths (mortality rates, PM10 concentrations, estimated PM10 effects, and commuting flows) and applied a Monte Carlo procedure to propagate uncertainty and sample the distribution of attributable deaths for each municipality. Results: We estimated that annual average PM10 concentrations above the World Health Organization-recommended threshold of 20 μg/m3 were responsible for 865 short-term deaths (80% credibility interval: 475, 1,401), 26% of which were attributable to PM10 above the European Union limit of 40 μg/m3. Reducing annual average PM10 concentrations > 20 μg/m3 by 20% would have reduced the number of attributable deaths by 36%. The largest estimated impacts were along the basin of the Po River and in the largest cities. Commuting contributed to the spatial distribution of the estimated impact. Conclusions: Our estimates, which incorporated uncertainty quantification, indicate that the short-term impact of PM10 on mortality in Lombardy in 2007 was notable, and that reduction in air pollution would have had a substantial beneficial effect on population health. Using commuting data helped to identify critical areas for prioritizing intervention. Citation: Baccini M, Grisotto L, Catelan D, Consonni D, Bertazzi PA, Biggeri A. 2015. Commuting-adjusted short-term health impact assessment of airborne fine particles with uncertainty quantification via Monte Carlo simulation. Environ Health Perspect 123:27–33; http://dx.doi.org/10.1289/ehp.1408218

Heptadecanoylcarnitine (C17) a novel candidate biomarker for newborn screening of propionic and methylmalonic acidemias

BACKGROUND 3-Hydroxypalmitoleoyl-carnitine (C16:1-OH) has recently been reported to be elevated in acylcarnitine profiles of patients with propionic acidemia (PA) or methylmalonic acidemia (MMA) during expanded newborn screening (NBS). High levels of C16:1-OH, combined with other hydroxylated long chain acylcarnitines are related to long-chain 3-hydroxyacyl-CoA dehydrogenase deficiency (LCHADD) and trifunctional protein (TFP) deficiency. METHODS The acylcarnitine profile of two LCHADD patients was evaluated using liquid chromatography-tandem mass spectrometric method. A specific retention time was determined for each hydroxylated long chain acylcarnitine. The same method was applied to some neonatal dried blood spots (DBSs) from PA and MMA patients presenting abnormal C16:1-OH concentrations. RESULTS The retention time of the peak corresponding to C16:1-OH in LCHADD patients differed from those in MMA and PA patients. Heptadecanoylcarnitine (C17) has been identified as the novel biomarker specific for PA and MMA patients through high resolution mass spectrometry (Orbitrap) experiments. We found that 21 out of 23 neonates (22 MMA, and 1PA) diagnosed through the Tuscany region NBS program exhibited significantly higher levels of C17 compared to controls. Twenty-three maternal deficiency (21 vitamin B12 deficiency, 1 homocystinuria and 1 gastrin deficiency) samples and 82 false positive for elevated propionylcarnitine (C3) were also analyzed. CONCLUSIONS We have characterized a novel biomarker able to detect propionate disorders during expanded newborn screening (NBS). The use of this new biomarker may improve the analytical performances of NBS programs especially in laboratories where second tier tests are not performed.

Sheep and Fasciola hepatica in Europe: the GLOWORM experience.

Fasciola hepatica infection challenges health, welfare and productivity of small ruminants throughout the world. The distribution of F. hepatica in sheep in Europe is usually scattered and studies are generally concerned with a single area making it difficult to compare results from different environments, climates and management regimes. In order to elucidate the current scenario in terms of prevalence and intensity of F. hepatica infection in sheep farms across Europe, a standardized cross-sectional survey was conducted in three pilot areas in Ireland, Switzerland and Italy, all part of the EU funded GLOWORM project. Two consecutive field surveys (in 2012 and 2013) were conducted in the three countries in the same period (August-October) in 361 sheep farms in total. Harmonized procedures (from farm to laboratory) based on pooled samples and the highly sensitive and accurate, diagnostic FLOTAC technique were used. The georeferenced parasitological results were modelled (at the pilot area level) following a Bayesian geostatistical approach with correction for preferential sampling and accounting for climatic and environmental covariates. The observed F. hepatica prevalence rates did not differ between the two study years in any of the three pilot areas, but they did vary between the countries showing high values in Ireland (61.6%) compared to Italy (7.9%) and Switzerland (4.0%). Spatial patterns of F. hepatica distribution were detected by the Bayesian geostatistical approach in Ireland with a high risk of infection in the south-western part of the pilot area there. The latent factor analysis highlighted the importance of year-to-year variation of mean temperature, rainfall and seasonality within a country, while long-term trends of temperature and rainfall dominated between countries with respect to prevalence of infection.

Clinical and genetic factors predicting Dravet syndrome in infants with SCN1A mutations

Objective: To explore the prognostic value of initial clinical and mutational findings in infants with SCN1A mutations. Methods: Combining sex, age/fever at first seizure, family history of epilepsy, EEG, and mutation type, we analyzed the accuracy of significant associations in predicting Dravet syndrome vs milder outcomes in 182 mutation carriers ascertained after seizure onset. To assess the diagnostic accuracy of all parameters, we calculated sensitivity, specificity, receiver operating characteristic (ROC) curves, diagnostic odds ratios, and positive and negative predictive values and the accuracy of combined information. We also included in the study demographic and mutational data of the healthy relatives of mutation carrier patients. Results: Ninety-seven individuals (48.5%) had Dravet syndrome, 49 (23.8%) had generalized/genetic epilepsy with febrile seizures plus, 30 (14.8%) had febrile seizures, 6 (3.5%) had focal epilepsy, and 18 (8.9%) were healthy relatives. The association study indicated that age at first seizure and frameshift mutations were associated with Dravet syndrome. The risk of Dravet syndrome was 85% in the 0- to 6-month group, 51% in the 6- to 12-month range, and 0% after the 12th month. ROC analysis identified onset within the sixth month as the diagnostic cutoff for progression to Dravet syndrome (sensitivity = 83.3%, specificity = 76.6%). Conclusions: In individuals with SCN1A mutations, age at seizure onset appears to predict outcome better than mutation type. Because outcome is not predetermined by genetic factors only, early recognition and treatment that mitigates prolonged/repeated seizures in the first year of life might also limit the progression to epileptic encephalopathy.

Daily peer review of abnormal cervical smears in the assessment of individual practice as an additional method of internal quality control

An important internal quality control system used in the Cancer Prevention and Research Institute cytopathology laboratory in Florence is the peer review procedure, based on the review of all abnormal cytological smears which routinely emerge. Peer review is an important training opportunity for all cytologists, especially for those with less experience. This article shows the results of the peer review procedure.

Inter- and intra-tumoral heterogeneity in DNA damage evaluated by comet assay in early breast cancer patients

There are no clinical tools to functionally assess degree of DNA damage in breast cancer. The comet assay is an accepted research tool for assessing DNA damage, however, most cancer studies have assessed lymphocytes as surrogate cells. The aim of this pilot study was to use the comet assay in early breast cancer directly in tumor tissue to compare DNA damage between and within traditionally defined subgroups, and to explore intra-tumoral heterogeneity. Scrapings of tumor and healthy breast tissue were obtained at primary surgery from 104 women. Comet assay was applied to quantitatively assess DNA damage, revealing substantial inter- and intra-subgroup variation. Marked intra-tumoral heterogeneity was evident across all subgroups. The degree of DNA damage for an individual could not be predicted by breast cancer subgroup. Comet assay warrants further study as a potential clinical tool for identification of tumoral DNA damage and ultimately, individualised use of DNA damaging therapy.

The syndrome of polymicrogyria, thalamic hypoplasia, and epilepsy with CSWS

Objective: We explored the long-term follow-up of continuous spike-and-wave complexes during sleep (CSWS) in polymicrogyria and the anatomic volumetric variables that influence the risk of developing this age-related epileptic encephalopathy. Methods: We performed prospective follow-up of 27 patients with polymicrogyria/CSWS (mean follow-up 14.3 years; range 2–31 years) and comparative volumetric analysis of the polymicrogyric hemispheres and ipsilateral thalami vs 3 subgroups featuring polymicrogyria without CSWS, benign rolandic epilepsy (BRE), and headache. Receiver operator characteristic analysis of the power of volumetric values was determined to predict CSWS. Results: CSWS peaked between 5 and 7 years (mean age at onset 4.7 years). Remission occurred within 2 years from onset in 21%, within 4 years in 50%, and by age 13 years in 100%. We found smaller thalamic and hemispheric volumes in polymicrogyria/CSWS with respect to polymicrogyria without CSWS (p = 0.0021 for hemispheres; p = 0.0003 for thalami), BRE, and controls with headache (p < 0.0001). Volumes of the malformed hemispheres and ipsilateral thalami reliably identified the risk of incurring CSWS, with a 68-fold increased risk for values lower than optimal diagnostic cutoffs (436,150 mm3 for malformed hemispheres or 4,616 mm3 for ipsilateral thalami; sensitivity 92.54%; specificity 84.62%). The risk increased by 2% for every 1,000 mm3 reduction of the polymicrogyric hemispheres and by 15% for every 100 mm3 reduction of ipsilateral thalami. Conclusions: The polymicrogyria/CSWS syndrome is likely caused by a cortico-thalamic malformation complex and is characterized by remission of epilepsy within early adolescence. Early assessment of hemispheric and thalamic volumes in children with polymicrogyria and epilepsy can reliably predict CSWS.

Geostatistical integration and uncertainty in pollutant concentration surface under preferential sampling

In this paper the focus is on environmental statistics, with the aim of estimating the concentration surface and related uncertainty of an air pollutant. We used air quality data recorded by a network of monitoring stations within a Bayesian framework to overcome difficulties in accounting for prediction uncertainty and to integrate information provided by deterministic models based on emissions meteorology and chemico-physical characteristics of the atmosphere. Several authors have proposed such integration, but all the proposed approaches rely on representativeness and completeness of existing air pollution monitoring networks. We considered the situation in which the spatial process of interest and the sampling locations are not independent. This is known in the literature as the preferential sampling problem, which if ignored in the analysis, can bias geostatistical inferences. We developed a Bayesian geostatistical model to account for preferential sampling with the main interest in statistical integration and uncertainty. We used PM10 data arising from the air quality network of the Environmental Protection Agency of Lombardy Region (Italy) and numerical outputs from the deterministic model. We specified an inhomogeneous Poisson process for the sampling locations intensities and a shared spatial random component model for the dependence between the spatial location of monitors and the pollution surface. We found greater predicted standard deviation differences in areas not properly covered by the air quality network. In conclusion, in this context inferences on prediction uncertainty may be misleading when geostatistical modelling does not take into account preferential sampling.