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Background: The present study aimed at developing a standardized heat wave definition to estimate and compare the impact on mortality by gender, age and death causes in Europe during summers 1990-2004 and 2003, separately, accounting for heat wave duration and intensity.Methods: Heat waves were defined considering both maximum apparent temperature and minimum temperature and classified by intensity, duration and timing during summer. The effect was estimated as percent increase in daily mortality during heat wave days compared to non heat wave days in people over 65 years. City specific and pooled estimates by gender, age and cause of death were calculated.Results: The effect of heat waves showed great geographical heterogeneity among cities. Considering all years, except 2003, the increase in mortality during heat wave days ranged from + 7.6% in Munich to + 33.6% in Milan. The increase was up to 3-times greater during episodes of long duration and high intensity. Pooled results showed a greater impact in Mediterranean (+ 21.8% for total mortality) than in North Continental (+ 12.4%) cities. The highest effect was observed for respiratory diseases and among women aged 75-84 years. In 2003 the highest impact was observed in cities where heat wave episode was characterized by unusual meteorological conditions.Conclusions: Climate change scenarios indicate that extreme events are expected to increase in the future even in regions where heat waves are not frequent. Considering our results prevention programs should specifically target the elderly, women and those suffering from chronic respiratory disorders, thus reducing the impact on mortality. [ABSTRACT FROM AUTHOR]

Background: Subjects living close to high traffic roads (HTR) are more likely to suffer from air-pollution related morbidity and mortality. The issue has large public health consequences but few studies have described the main socio-demographic characteristics of people exposed to traffic.Objectives: To characterise a large cohort of residents in Rome according to different measures of traffic exposure, socioeconomic position (SEP), and baseline health status.Methods: Residents of Rome in October 2001 were selected. Individual and area-based SEP indices were available. GIS was used to obtain traffic indicators at residential addresses: distance from HTR (> = 10,000 vehicles/day), length of HTR, average daily traffic count, and traffic density within 150 meters of home. Hospitalisations in the 5-year period before enrolment were used to characterise health status. Logistic and linear regression analyses estimated the association between traffic exposure and socio-demographic characteristics.Results: We selected 1,898,898 subjects with complete SEP information and GIS traffic indicators. A total of 320,913 individuals (17%) lived within 50 meters of an HTR, and 14% lived between 50 and 100 meters. These proportions were higher among 75+ year-old subjects. Overall, all traffic indicators were directly associated with SEP, with people living in high or medium SEP areas or with a university degree more likely to be exposed to traffic than people living in low SEP areas or with a low level of education. However, an effect modification by area of residence within the city was seen and the association between traffic and SEP was reversed in the city centre.Conclusions: A large section of the population is exposed to traffic in Rome. Elderly people and those living in areas of high and medium SEP tend to be more exposed. These findings are related to the historical stratification of the population within the city according to age and socioeconomic status. [ABSTRACT FROM AUTHOR]

Background: Hip fracture injuries are identified as one of the most serious healthcare problems affecting older people. Many studies have explored the associations among patient characteristics, treatment processes, time to surgery and various outcomes in patients hospitalized for hip fracture. The objective of the present study is to evaluate the difference in 1-year mortality after hip fracture between patients undergoing early surgery (within 2 days) and patients undergoing delayed surgery in Italy., Methods: Observational, retrospective study based on the Hospital Information System (HIS). This cohort study included patients aged 65 years and older who were residing in Italy and were admitted to an acute care hospital for a hip fracture between 1 January 2007 and 31 December 2012. A multivariate Cox regression analysis was used to assess the effect of early surgery on the likelihood of 1-year mortality after hip fracture, adjusting for risk factors that could affect the outcome under study. The absolute number of deaths prevented by exposure to early surgery was calculated., Results: We studied a total of 405,037 admissions for hip fracture. Patients who underwent surgery within 2 days had lower 1-year mortality compared to those who waited for surgery more than 2 days (Hazard Ratios -HR-: 0.83; 95 % CI: 0.82-0.85). The number of deaths prevented by the exposure to early surgery was 5691., Conclusions: This study is the first to evaluate the association between time to surgery and 1-year mortality for all Italian elderly patients hospitalized for hip fracture. The study confirmed the previous reports on the association between delayed surgery and increased mortality and complication rates in elderly patients admitted for hip fracture. Our data support the notion that deviating from surgical guidelines in hip fracture is costly, in terms of both human life and excess hospital stay.

Background: Hospital discharge records are an essential source of information when comparing health outcomes among hospitals; however, they contain limited information on acute clinical conditions. Doubts remain as to whether the addition of clinical and drug consumption information would improve the prediction of health outcomes and reduce confounding in inter-hospital comparisons. The objective of the study is to compare the performance of two multivariate risk adjustment models, with and without clinical data and drug prescription information, in terms of their capability to a) predict short-term outcome rates and b) compare hospitals' risk-adjusted outcome rates using two risk-adjustment procedures., Methods: Observational, retrospective study based on hospital data collected at the regional level.Two cohorts of patients discharged in 2010 from hospitals located in the Lazio Region, Italy: acute myocardial infarction (AMI) and hip fracture (HF). Multivariate logistic regression models were implemented to predict 30-day mortality (AMI) or 48-hour surgery (HF), adjusting for demographic characteristics and comorbidities plus clinical data and drug prescription information. Risk-adjusted outcome rates were derived at the hospital level., Results: The addition of clinical data and drug prescription information improved the capability of the models to predict the study outcomes for the two conditions investigated. The discriminatory power of the AMI model increases when the clinical data and drug prescription information are included (c-statistic increases from 0.761 to 0.797); for the HF model the increase was more slight (c-statistic increases from 0.555 to 0.574). Some differences were observed between the hospital-adjusted proportion estimated using the two different models. However, the estimated hospital outcome rates were weakly affected by the introduction of clinical data and drug prescription information., Conclusions: The results show that the available clinical variables and drug prescription information were important complements to the hospital discharge data for characterising the acute severity of the patients. However, when these variables were used for adjustment purposes their contribution was negligible. This conclusion might not apply at other locations, in other time periods and for other health conditions if there is heterogeneity in the clinical conditions between hospitals.

Background: Despite extensive studies on exposure and disease misclassification, few studies have investigated misclassification of confounders. This study aimed to identify differentially misclassified confounders in a comparative evaluation of hospital care quality and to quantify their impact on hospital-specific risk-adjusted estimates, focusing on the appropriateness of caesarean sections (CS)., Methods: We gathered data from the Hospital Information System in Italy for women admitted in 2005-2010. We estimated adjusted proportions of CS with logistic regression models. Among several confounders, we focused on high fetal head at term (HFH), which is seldom objectively documentable in medical records., Results: A total of 540 maternity units were compared. The median HFH prevalence was 0.9%, ranging from 0 to 70%. In some units, HFH was coded so frequently that it was unlikely to reflect a natural heterogeneity. This "over-coding" was conditional on the outcome because it occurred more frequently for women that underwent CS. This suggested an opportunistic coding to justify the choice of a CS. HFH misclassification was not randomly distributed over Italy; it had an excess in the Campania region where, in some units, the proportion of HFHs gradually increased from 2005 to 2010 (e.g., from 0 to 26%), but the national average remained constant (2.5%). The inclusion of the misclassified diagnosis in the models favored those hospitals that codified in a less-than-fair manner., Conclusions: Our findings emphasized the importance of rigorously inspecting for differential misclassification of confounders. Their validity may be subject to substantial heterogeneity over hospitals, over time and geographical areas.

Background: A tariff modulation mechanisms has been introduced in some Italian regions with the aim of reducing inappropriate admissions and improving quality of care. In response to a regional act, hospitals in Lazio adopted a clinical pathway for elderly patients with hip fracture and introduced a compensation system based on the quality of health care, as in a pay-for-performance model. The objective of the present study was to compare the proportion of surgery for hip fracture performed within 48 hours of admission among Lazio hospitals according to different payment systems, before and after the implementation of the regional act., Methods: A retrospective cohort study of patients aged 65 years and over, residing in the Lazio region and admitted to an acute care hospital for hip fracture before (1 July 2008 - 30 June 2009) and after (1 July 2010 - 30 June 2011) the pay-for-performance act. The proportion of surgeries performed within 48 h of hospital arrival was calculated. An adjusted multivariate regression analysis was applied to assess the effect of hospital payment type on the likelihood of surgery within 48 h of hospital arrival., Results: The share of patients with hip fracture that had surgery within 48 hours was 11.7% before the introduction of the pay-for-performance act and 22.2% after. The proportion of early hip fracture operations increased after the pay-for-performance act, regardless of hospital payment type. The largest increase of surgery within 48 h occurred in private hospitals (adjusted Relative Risk = 2.80, p < 0.001)., Conclusions: The introduction of a compensation system based on health care quality is associated with improved quality of care for elderly patients with hip fracture, especially in hospitals that only use the Diagnosis Related Group system.

Background: Caesarean section (CS) rate is a quality of health care indicator frequently used at national and international level. The aim of this study was to assess whether adjustment for Robson's Ten Group Classification System (TGCS), and clinical and socio-demographic variables of the mother and the fetus is necessary for inter-hospital comparisons of CS rates., Methods: The study population includes 64,423 deliveries in Emilia-Romagna between January 1, 2003 and December 31, 2004, classified according to theTGCS. Poisson regression was used to estimate crude and adjusted hospital relative risks of CS compared to a reference category. Analyses were carried out in the overall population and separately according to the Robson groups (groups I, II, III, IV and V-X combined). Adjusted relative risks (RR) of CS were estimated using two risk-adjustment models; the first (M1) including the TGCS group as the only adjustment factor; the second (M2) including in addition demographic and clinical confounders identified using a stepwise selection procedure. Percentage variations between crude and adjusted RRs by hospital were calculated to evaluate the confounding effect of covariates., Results: The percentage variations from crude to adjusted RR proved to be similar in M1 and M2 model. However, stratified analyses by Robson's classification groups showed that residual confounding for clinical and demographic variables was present in groups I (nulliparous, single, cephalic, ≥37 weeks, spontaneous labour) and III (multiparous, excluding previous CS, single, cephalic, ≥37 weeks, spontaneous labour) and IV (multiparous, excluding previous CS, single, cephalic, ≥37 weeks, induced or CS before labour) and to a minor extent in groups II (nulliparous, single, cephalic, ≥37 weeks, induced or CS before labour) and IV (multiparous, excluding previous CS, single, cephalic, ≥37 weeks, induced or CS before labour)., Conclusions: The TGCS classification is useful for inter-hospital comparison of CS section rates, but residual confounding is present in the TGCS strata.

Background: P.Re.Val.E. is the most comprehensive comparative evaluation program of healthcare outcomes in Lazio, an Italian region, and the first Italian study to make health provider performance data available to the public. The aim of this study is to describe the P.Re.Val.E. and the impact of releasing performance data to the public., Methods: P.Re.Val.E. included 54 outcome/process indicators encompassing many different clinical areas. Crude and adjusted rates were estimated for the 2006-2009 period. Multivariate regression models and direct standardization procedures were used to control for potential confounding due to individual characteristics. Variable life-adjusted display charts were developed, and 2008-2009 results were compared with those from 2006-2007., Results: Results of 54 outcome indicators were published online at http://www.epidemiologia.lazio.it/prevale10/index.php. Public disclosure of the indicators' results caused mixed reactions but finally promoted discussion and refinement of some indicators. Based on the P.Re.Val.E. experience, the Italian National Agency for Regional Health Services has launched a National Outcome Program aimed at systematically comparing outcomes in hospitals and local health units in Italy., Conclusions: P.Re.Val.E. highlighted aspects of patient care that merit further investigation and monitoring to improve healthcare services and equity.

Background: Policies on waste disposal in Europe are heterogeneous and rapidly changing, with potential health implications that are largely unknown. We conducted a health impact assessment of landfilling and incineration in three European countries: Italy, Slovakia and England., Methods: A total of 49 (Italy), 2 (Slovakia), and 11 (England) incinerators were operating in 2001 while for landfills the figures were 619, 121 and 232, respectively. The study population consisted of residents living within 3 km of an incinerator and 2 km of a landfill. Excess risk estimates from epidemiological studies were used, combined with air pollution dispersion modelling for particulate matter (PM10) and nitrogen dioxide (NO2). For incinerators, we estimated attributable cancer incidence and years of life lost (YoLL), while for landfills we estimated attributable cases of congenital anomalies and low birth weight infants., Results: About 1,000,000, 16,000, and 1,200,000 subjects lived close to incinerators in Italy, Slovakia and England, respectively. The additional contribution to NO2 levels within a 3 km radius was 0.23, 0.15, and 0.14 μg/m3, respectively. Lower values were found for PM10. Assuming that the incinerators continue to operate until 2020, we are moderately confident that the annual number of cancer cases due to exposure in 2001-2020 will reach 11, 0, and 7 in 2020 and then decline to 0 in the three countries in 2050. We are moderately confident that by 2050, the attributable impact on the 2001 cohort of residents will be 3,621 (Italy), 37 (Slovakia) and 3,966 (England) YoLL. The total exposed population to landfills was 1,350,000, 329,000, and 1,425,000 subjects, respectively. We are moderately confident that the annual additional cases of congenital anomalies up to 2030 will be approximately 2, 2, and 3 whereas there will be 42, 13, and 59 additional low-birth weight newborns, respectively., Conclusions: The current health impacts of landfilling and incineration can be characterized as moderate when compared to other sources of environmental pollution, e.g. traffic or industrial emissions, that have an impact on public health. There are several uncertainties and critical assumptions in the assessment model, but it provides insight into the relative health impact attributable to waste management.

Background: Several studies have been conducted on the possible health effects for people living close to incinerators and well-conducted reviews are available. Nevertheless, several uncertainties limit the overall interpretation of the findings. We evaluated the health effects of emissions from two incinerators in a pilot cohort study., Methods: The study area was defined as the 3.5 km radius around two incinerators located near Forlì (Italy). People who were residents in 1/1/1990, or subsequently became residents up to 31/12/2003, were enrolled in a longitudinal study (31,347 individuals). All the addresses were geocoded. Follow-up continued until 31/12/2003 by linking the mortality register, cancer registry and hospital admissions databases. Atmospheric Dispersion Model System (ADMS) software was used for exposure assessment; modelled concentration maps of heavy metals (annual average) were considered the indicators of exposure to atmospheric pollution from the incinerators, while concentration maps of nitrogen dioxide (NO2) were considered for exposure to other pollution sources. Age and area-based socioeconomic status adjusted rate ratios and 95% Confidence Intervals were estimated with Poisson regression, using the lowest exposure category to heavy metals as reference., Results: The mortality and morbidity experience of the whole cohort did not differ from the regional population. In the internal analysis, no association between pollution exposure from the incinerators and all-cause and cause-specific mortality outcomes was observed in men, with the exception of colon cancer. Exposure to the incinerators was associated with cancer mortality among women, in particular for all cancer sites (RR for the highest exposure level = 1.47, 95% CI: 1.09, 1.99), stomach, colon, liver and breast cancer. No clear trend was detected for cancer incidence. No association was found for hospitalizations related to major diseases. NO2 levels, as a proxy from other pollution sources (traffic in particular), did not exert an important confounding role., Conclusions: No increased risk of mortality and morbidity was found in the entire area. The internal analysis of the cohort based on dispersion modeling found excesses of mortality for some cancer types in the highest exposure categories, especially in women. The interpretation of the findings is limited given the pilot nature of the study.

Background: Concerns about the hepatitis C virus (HCV) are due to the high risk of chronic liver disease and poor treatment efficacy. Synthesizing evidence from multiple data sources is becoming widely used to estimate HCV-infection prevalence. This paper aims to estimate the prevalence of HCV infection, and the hepatic and extrahepatic sequelae in at-risk groups, using routinely collected data in the Lazio region, Italy., Methods: HCV laboratory surveillance and dialysis, hospital discharge, and drug-user registers were used as information sources to identify at-risk groups and to estimate HCV prevalence and sequelae.Full name and birth date were used as linkage keys for the various health registries. Prevalence was estimated as the percentage of cases within the general population and the at-risk groups, with 95% confidence intervals (95% CI) from 1997 to 2001. The risk of sequelae was estimated through a follow-up of hospital discharges up to December 31, 2004 and calculated as the prevalence ratio in HCV-positive and HCV-negative people, within each at-risk group, with 95% CI., Results: There were 65,127 HCV-infected people in the study period; the prevalence was 1.24% (95%CI = 1.23%-1.25%) in the whole population, higher in males and older adults. Drug users (35.1%; 95%CI = 34.6-35.7) and dialysis patients (21.1%; 95%CI = 20.2%-22.0%) showed the highest values. Medical procedures with little exposure to blood resulted in higher estimates, ranging between 1.3% and 3.4%, which was not conclusively attributable to the surgical procedures. Cirrhosis, hepatocellular carcinoma and encephalopathy were the most frequent hepatic sequelae; cryoglobulinaemia and non-Hodgkin's lymphoma were the most frequent extrahepatic sequelae., Conclusions: Synthesising data from multiple routine sources improved estimates of HCV prevalence and sequelae in dialysis patients and drug users, although prevalence validity should be assessed in survey and sequelae need a well-defined longitudinal approach.

Background: Management of solid waste (mainly landfills and incineration) releases a number of toxic substances, most in small quantities and at extremely low levels. Because of the wide range of pollutants, the different pathways of exposure, long-term low-level exposure, and the potential for synergism among the pollutants, concerns remain about potential health effects but there are many uncertainties involved in the assessment. Our aim was to systematically review the available epidemiological literature on the health effects in the vicinity of landfills and incinerators and among workers at waste processing plants to derive usable excess risk estimates for health impact assessment., Methods: We examined the published, peer-reviewed literature addressing health effects of waste management between 1983 and 2008. For each paper, we examined the study design and assessed potential biases in the effect estimates. We evaluated the overall evidence and graded the associated uncertainties., Results: In most cases the overall evidence was inadequate to establish a relationship between a specific waste process and health effects; the evidence from occupational studies was not sufficient to make an overall assessment. For community studies, at least for some processes, there was limited evidence of a causal relationship and a few studies were selected for a quantitative evaluation. In particular, for populations living within two kilometres of landfills there was limited evidence of congenital anomalies and low birth weight with excess risk of 2 percent and 6 percent, respectively. The excess risk tended to be higher when sites dealing with toxic wastes were considered. For populations living within three kilometres of old incinerators, there was limited evidence of an increased risk of cancer, with an estimated excess risk of 3.5 percent. The confidence in the evaluation and in the estimated excess risk tended to be higher for specific cancer forms such as non-Hodgkin's lymphoma and soft tissue sarcoma than for other cancers., Conclusions: The studies we have reviewed suffer from many limitations due to poor exposure assessment, ecological level of analysis, and lack of information on relevant confounders. With a moderate level confidence, however, we have derived some effect estimates that could be used for health impact assessment of old landfill and incineration plants. The uncertainties surrounding these numbers should be considered carefully when health effects are estimated. It is clear that future research into the health risks of waste management needs to overcome current limitations.

Background: A relationship between quality of primary health care and preventable hospitalizations has been described in the US, especially among the elderly. In Europe, there has been a recent increase in the evaluation of Ambulatory Care Sensitive Conditions (ACSC) as an indicator of health care quality, but evidence is still limited. The aim of this study was to determine whether income level is associated with higher hospitalization rates for ACSC in adults in a country with universal health care coverage., Methods: From the hospital registries in four Italian cities (Turin, Milan, Bologna, Rome), we identified 9384 hospital admissions for six chronic conditions (diabetes, hypertension, congestive heart failure, angina pectoris, chronic obstructive pulmonary disease, and asthma) among 20-64 year-olds in 2000. Case definition was based on the ICD-9-CM coding algorithm suggested by the Agency for Health Research and Quality - Prevention Quality Indicators. An area-based (census block) income index was used for each individual. All hospitalization rates were directly standardised for gender and age using the Italian population. Poisson regression analysis was performed to assess the relationship between income level (quintiles) and hospitalization rates (RR, 95% CI) separately for the selected conditions controlling for age, gender and city of residence., Results: Overall, the ACSC age-standardized rate was 26.1 per 10.000 inhabitants. All conditions showed a statistically significant socioeconomic gradient, with low income people being more likely to be hospitalized than their well off counterparts. The association was particularly strong for chronic obstructive pulmonary disease (level V low income vs. level I high income RR = 4.23 95%CI 3.37-5.31) and for congestive heart failure (RR = 3.78, 95% CI = 3.09-4.62). With the exception of asthma, males were more vulnerable to ACSC hospitalizations than females. The risks were higher among 45-64 year olds than in younger people., Conclusions: The socioeconomic gradient in ACSC hospitalization rates confirms the gap in health status between social groups in our country. Insufficient or ineffective primary care is suggested as a plausible additional factor aggravating inequality. This finding highlights the need for improving outpatient care programmes to reduce the excess of unnecessary hospitalizations among poor people.

Background: Few studies have identified specific factors that increase mortality during heat waves. This study investigated socio-demographic characteristics and pre-existing medical conditions as effect modifiers of the risk of dying during heat waves in a cohort of elderly residents in Rome., Methods: A cohort of 651,195 residents aged 65 yrs or older was followed from 2005 to 2007. During summer, heat wave days were defined according to month-specific thresholds of maximum apparent temperature. The adjusted relative risk of dying during heat waves was estimated using a Poisson regression model including all the considered covariates. Risk differences were also calculated. All analyses were run separately for the 65-74 and 75+ age groups., Results: In the 65-74 age group the risk of dying during heat waves was higher among unmarried subjects and those with a previous hospitalization for chronic pulmonary disease or psychiatric disorders. In the 75+ age group, women, and unmarried subjects were more susceptible to heat. Furthermore, a higher susceptibility to heat among those with previous hospitalization for diabetes, diseases of the central nervous system (CNS), psychiatric disorders and cerebrovascular diseases resulted from risk differences., Discussion: Results showed a higher susceptibility to heat among those older than seventy-five years, females and unmarried. Pre-existing health conditions play a different role among the two considered age groups. Moreover, compared with previous studies the pattern of susceptibility factors have slightly changed over time. For the purposes of public health programmes, susceptibility should be considered as time, space and population specific.

Background: The inverse association between socioeconomic position (SEP) and health has been extensively explored in Italy; however few studies have been carried out on the relationship between income inequalities and health status or health services utilisation, particularly at a local level.The objective of this study is to test the association between the demand for hospital care and a small area indicator based on income in four Italian cities, over a four-year period (1997-2000), in the adult population., Methods: Census Block (median 260 residents) Median per capita Income (CBMI) was computed through record linkage between 1998 national tax and local population registries in the cities of Rome, Turin, Milan and Bologna (total population approximately 5.5 million). CBMI was linked to acute hospital discharges among residents, based on patient's residence.Age-standardized gender-specific hospitalisation rates were computed by CBMI quintiles (first quintile indicating lowest income), overall, and by city and year. Heterogeneity of the association between income level and hospitalisation was analysed through a Poisson model., Results: We found an inverse association between small area income level and hospitalisation rates, which decreased continuously from 153 per 1000 inhabitants in the first quintile to 107 per 1000 inhabitants in the fifth quintile. Income differences in hospitalisation were confirmed in each city and year. However, the magnitude of the association and the absolute level of hospitalisation rates were quite different in each city and tended to slightly decrease over time in all cities considered, except Bologna., Conclusion: Our study confirms an inverse association between income level and the use of hospitalization in four Italian cities, using a small area economic indicator, based on population tax data. Further analysis of the association between income and cause-specific hospitalization rates will allow to better understand the capability of the Italian National Health System to compel with socio-economic inequalities in health needs.Furthermore the SEP indicator we propose can represent a contribution to the improvement of tools for monitoring inequalities in health and in health services utilization.

Background: Data from scientific literature show that about 63% of abstracts presented at biomedical conferences will be published in full. Some studies have indicated that full publication is associated with the direction of results (publication bias). No study has looked into the occurrence of publication bias in the field of addiction., Objectives: To investigate whether the significance or direction of results of abstracts presented at the major international scientific conference on addiction is associated with full publication, Methods: The conference proceedings of the US Annual Meeting of the College on Problems of Drug Dependence (CPDD), were handsearched for abstracts of randomized controlled trials and controlled clinical trials that evaluated interventions for prevention, rehabilitation and treatment of drug addiction in humans (years searched 1993-2002). Data regarding the study designs and outcomes reported were extracted. Subsequent publication in peer reviewed journals was searched in MEDLINE and EMBASE databases, as of March 2006., Results: Out of 5919 abstracts presented, 581 met the inclusion criteria; 359 (62%) conference abstracts had been published in a broad variety of peer reviewed journals (average time of publication 2.6 years, SD +/- 1.78). The proportion of published studies was almost the same for randomized controlled trials (62.4%) and controlled clinical trials (59.5%) while studies that reported positive results were significantly more likely to be published (74.5%) than those that did not report statistical results (60.9%.), negative or null results (47.1%) and no results (38.6%), Abstracts reporting positive results had a significantly higher probability of being published in full, while abstracts reporting null or negative results were half as likely to be published compared with positive ones (HR = 0.48; 95%CI 0.30-0.74), Conclusion: Clinical trials were the minority of abstracts presented at the CPDD; we found evidence of possible publication bias in the field of addiction, with negative or null results having half the likelihood of being published than positive ones.

Background: Socioeconomic status could affect the demand for hospital care. The aim of the present study was to assess the role of age, socioeconomic status and comorbidity on acute hospital admissions among elderly., Methods: We retrospectively examined the discharge abstracts data of acute care hospital admissions of residents in Rome aged 75 or more years in the period 1997-2000. We used the Hospital Information System of Rome, the Tax Register, and the Population Register of Rome for socio-economic data. The rate of hospitalization, modified Charlson's index of comorbidity, and level of income in the census tract of residence were obtained. Rate ratios and 95% confidence limits were computed to assess the relationship between income deciles and rate of hospitalization. Cross-tabulation was used to explore the distribution of the index of comorbidity by deciles of income. Analyses were repeated for patients grouped according to selected diseases., Results: Age was associated with a marginal increase in the rate of hospitalization. However, the hospitalization rate was inversely related to income in both sexes. Higher income was associated with lower comorbidity. The same associations were observed in patients admitted with a principal diagnosis of chronic condition (diabetes mellitus, heart failure, chronic obstructive pulmonary disease) or stroke, but not hip fracture., Conclusion: Lower social status and associated comorbidity, more than age per se, are associated with a higher rate of hospitalization in very old patients.

Background: Hierarchical modelling represents a statistical method used to analyze nested data, as those concerning patients afferent to different hospitals. Aim of this paper is to build a hierarchical regression model using data from the "Italian CABG outcome study" in order to evaluate the amount of differences in adjusted mortality rates attributable to differences between centres., Methods: The study population consists of all adult patients undergoing an isolated CABG between 2002-2004 in the 64 participating cardiac surgery centres.A risk adjustment model was developed using a classical single-level regression. In the multilevel approach, the variable "clinical-centre" was employed as a group-level identifier. The intraclass correlation coefficient was used to estimate the proportion of variability in mortality between groups. Group-level residuals were adopted to evaluate the effect of clinical centre on mortality and to compare hospitals performance. Spearman correlation coefficient of ranks (rho) was used to compare results from classical and hierarchical model., Results: The study population was made of 34,310 subjects (mortality rate = 2.61%; range 0.33-7.63). The multilevel model estimated that 10.1% of total variability in mortality was explained by differences between centres. The analysis of group-level residuals highlighted 3 centres (VS 8 in the classical methodology) with estimated mortality rates lower than the mean and 11 centres (VS 7) with rates significantly higher. Results from the two methodologies were comparable (rho = 0.99)., Conclusion: Despite known individual risk-factors were accounted for in the single-level model, the high variability explained by the variable "clinical-centre" states its importance in predicting 30-day mortality after CABG.

Background: While socioeconomic inequalities in mortality have widened in many countries, evidence of social differentials is scarce in Southern Europe. We studied temporal changes in premature mortality across socioeconomic groups in Rome between 1990 and 2001., Methods: We analysed all 126,511 death certificates of residents of Rome aged 0-74 years registered between 1990-2001. A 4-level census block index based on the 1991 census was used as an indicator of socioeconomic position (SEP). Using routine mortality data, standardised mortality rates (per 100,000 inhabitants) were calculated by SEP and gender for four time periods. Rate ratios were used to compare mortality by gender and age., Results: Overall premature mortality decreased in both genders and in all socioeconomic groups; the change was greater in the highest socio-economic group. In both men and women, inequalities in mortality strengthened during the 1990s and appeared to stabilise at the end of the 20th century. However, for 60-74 year old women the gap continued to widen., Conclusion: Socioeconomic inequalities in health in Rome are still present at the beginning of the 21st century. Strategies to monitor the impact of SEP on mortality over time in different populations should be implemented to direct health policies.

Background: Cesarean section rates is often used as an indicator of quality of care in maternity hospitals. The assumption is that lower rates reflect in developed countries more appropriate clinical practice and general better performances. Hospitals are thus often ranked on the basis of caesarean section rates. The aim of this study is to assess whether the adjustment for clinical and sociodemographic variables of the mother and the fetus is necessary for inter-hospital comparisons of cesarean section (c-section) rates and to assess whether a risk adjustment model based on a limited number of variables could be identified and used., Methods: Discharge abstracts of labouring women without prior cesarean were linked with abstracts of newborns discharged from 29 hospitals of the Emilia-Romagna Region (Italy) from 2003 to 2004. Adjusted ORs of cesarean by hospital were estimated by using two logistic regression models: 1) a full model including the potential confounders selected by a backward procedure; 2) a parsimonious model including only actual confounders identified by the "change-in-estimate" procedure. Hospital rankings, based on ORs were examined., Results: 24 risk factors for c-section were included in the full model and 7 (marital status, maternal age, infant weight, fetopelvic disproportion, eclampsia or pre-eclampsia, placenta previa/abruptio placentae, malposition/malpresentation) in the parsimonious model. Hospital ranking using the adjusted ORs from both models was different from that obtained using the crude ORs. The correlation between the rankings of the two models was 0.92. The crude ORs were smaller than ORs adjusted by both models, with the parsimonious ones producing more precise estimates., Conclusion: Risk adjustment is necessary to compare hospital c-section rates, it shows differences in rankings and highlights inappropriateness of some hospitals. By adjusting for only actual confounders valid and more precise estimates could be obtained.

Background: Short-term fluctuations of ambient air pollution have been associated with exacerbation of cardiovascular disease. A multi-city study was designed to assess the probability of recurrent hospitalization in a cohort of incident myocardial infarction survivors in five European cities. The objective of this paper is to discuss the methods for analyzing short-term health effects in a cohort study based on a case-series., Methods: Three methods were considered for the analyses of the cohort data: Poisson regression approach, case-crossover analyses and extended Cox regression analyses. The major challenge of these analyses is to appropriately consider changes within the cohort over time due to changes in the underlying risk following a myocardial infarction, slow time trends in risk factors within the population, dynamic cohort size and seasonal variation., Results: Poisson regression analyses, case-crossover analyses and Extended Cox regression analyses gave similar results. Application of smoothing methods showed the capability to adequately model the complex time trends., Conclusion: From a practical point of view, Poisson regression analyses are less time-consuming, and therefore might be used for confounder selection and most of the analyses. However, replication of the results with Cox models is desirable to assure that the results are independent of the analytical approach used. In addition, extended Cox regression analyses would allow a joint estimation of long-term and short-term health effects of time-varying exposures.

Background: Administrative data can serve as an easily available source for epidemiological and evaluation studies. The aim of this study is to evaluate the use of hospital administrative data to determine breast cancer severity and the appropriateness of surgical treatment., Methods: the study population consisted of 398 patients randomly selected from a cohort of women hospitalized for first-time breast cancer surgery in the Lazio Region, Italy. Tumor severity was defined in three different ways: 1) tumor size; 2) clinical stage (TNM); 3) severity indicator based on HIS data (SI). Sensitivity, specificity, and positive predictive value (PPV) of the severity indicator in evaluating appropriateness of surgery were calculated. The accuracy of HIS data was measured using Kappa statistic., Results: Most of 387 cases were classified as T1 and T2 (tumor size), more than 70% were in stage I or II and the SI classified 60% of cases in medium-low category. Variation from guidelines indications identified under and over treatments. The accuracy of the SI to predict under-treatment was relatively good (58% of all procedures classified as under-treatment using pT where also classified as such using SI), and even greater predicting over-treatment (88.2% of all procedures classified as over treatment using pT where also classified as such using SI). Agreement between clinical chart and hospital discharge reports was K = 0.35., Conclusion: Our findings suggest that administrative data need to be used with caution when evaluating surgical appropriateness, mainly because of the limited ability of SI to predict tumor size and the questionable quality of HIS data as observed in other studies.

Background: Direct admission to Coronary Care Unit (CCU) on hospital arrival can be considered as a good proxy for adequate management in patients with acute myocardial infarction (AMI), as it has been associated with better prognosis. We analyzed a cohort of patients with AMI hospitalized in Rome (Italy) in 1997-2000 to assess the proportion directly admitted to CCU and to investigate the effect of patient characteristics such as gender, age, illness severity on admission, and socio-economic status (SES) on CCU admission practices., Methods: Using discharge data, we analyzed a cohort of 9127 AMI patients. Illness severity on admission was determined using the Deyo's adaptation of the Charlson's comorbidity index, and each patient was assigned to one to four SES groups (level I referring to the highest SES) defined by a socioeconomic index, derived by the characteristics of the census tract of residence. The effect of gender, age, illness severity and SES, on risk of non-admission to CCU was investigated using a logistic regression model (OR, CI 95%)., Results: Only 53.9% of patients were directly admitted to CCU, and access to optimal care was more frequently offered to younger patients (OR = 0.35; 95%CI = 0.25-0.48 when comparing 85+ to >=50 years), those with less severe illness (OR = 0.48; 95%CI = 0.37-0.61 when comparing Charlson index 3+ to 0) and the socially advantaged (OR = 0.81; 95%CI = 0.66-0.99 when comparing low to high SES)., Conclusion: In Rome, Italy, standard optimal coronary care is underprovided. It seems to be granted preferentially to the better off, even after controversial clinical criteria, such as age and severity of illness, are taken into account.