Claudia Marino

Lazio Regional Health Service, Roma, Latium, Italy

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Publications (21)68.02 Total impact

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    ABSTRACT: BACKGROUND: This multicenter study is aimed at estimating changes in the effect of high temperatures on elderly mortality before and after the 2003 heat waves and following the introduction of heat prevention activities. METHODS: A total of sixteen cities were included in the study. City-specific relationships between maximum apparent temperature (MAT) and elderly daily mortality before (1998-2002) and after (2006-2009) intervention were modelled through non-linear distributed lag models and estimates were combined using a random effect meta-analysis. We estimated the percentage change in daily mortality for 3degreesC variations in MAT above the 25th percentile of the June city-specific 1998-2002 distribution. A time-varying analysis was carried out to describe intra-seasonal variations in the two periods. RESULTS: We observed a reduction in high temperatures' effect post intervention; the greatest reduction was for increases in temperature from 9degreesC to 12degreesC above the 25th percentile, with a decrease from +36.7% to +13.3%. A weak effect was observed for temperatures up to 3degreesC above the 25th percentile only after. Changes were month-specific with a reduction in August and an increase in May, June and September in 2006-2010. CONCLUSIONS: A change in the temperature-mortality relationship was observed, attributable to variations in temperature distributions during summer and to the introduction of adaptation measures. The reduction in the effect of high temperature suggests that prevention programs can mitigate the impact. An effect of lower temperature remains, indicating a relevant impact of temperature at the beginning of summer when the population has not yet adapted and intervention activities are not fully operational.
    Environmental Health 09/2012; 11(1):58. · 2.71 Impact Factor
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    ABSTRACT: Since 2004, the Italian Department for Civil Protection and the Ministry of Health have implemented a national program for the prevention of heat-health effects during summer, which to-date includes 34 major cities and 93% of the residents aged 65 years and over. The Italian program represents an important example of an integrated approach to prevent the impact of heat on health, comprising Heat Health Watch Warning Systems, a mortality surveillance system and prevention activities targeted to susceptible subgroups. City-specific warning systems are based on the relationship between temperature and mortality and serve as basis for the modulation of prevention measures. Local prevention activities, based on the guidelines defined by the Ministry of Health, are constructed around the infrastructures and services available. A key component of the prevention program is the identification of susceptible individuals and the active surveillance by General Practitioners, medical personnel and social workers. The mortality surveillance system enables the timely estimation of the impact of heat, and heat waves, on mortality during summer as well as to the evaluation of warning systems and prevention programs. Considering future predictions of climate change, the implementation of effective prevention programs, targeted to high risk subjects, become a priority in the public health agenda.
    International Journal of Environmental Research and Public Health 05/2010; 7(5):2256-73. · 2.00 Impact Factor
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    ABSTRACT: 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. 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. 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. 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.
    Environmental Health 01/2010; 9:37. · 2.71 Impact Factor
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    ABSTRACT: 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. 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. 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. 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.
    Environmental Health 11/2009; 8:50. · 2.71 Impact Factor
  • Epidemiology 10/2009; 20(6):S263-S264. · 5.74 Impact Factor
  • Epidemiology. 01/2009; 20.
  • Epidemiology. 01/2009; 20.
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    ABSTRACT: Rationale: Episode analyses of heat waves have documented a com-paratively higher impact on mortality than on morbidity (hospital admissions) in European cities. The evidence from daily time series studies is scarce and inconsistent. Objectives: To evaluate the impact of high environmental temper-atures on hospital admissions during April to September in 12 Euro-pean cities participating in the Assessment and Prevention of Acute Health Effects of Weather Conditions in Europe (PHEWE) project. Methods: For each city, time series analysis was used to model the relationship between maximum apparent temperature (lag 0–3 days) and daily hospital admissions for cardiovascular, cerebrovascular, and respiratory causes by age (all ages, 65–74 age group, and 751 age group), and the city-specific estimates were pooled for two geograph-ical groupings of cities. Measurements and Main Results: For respiratory admissions, there was a positive association that was heterogeneous between cities. For a 18C increase in maximum apparent temperature above a threshold, re-spiratory admissions increased by 14.5% (95% confidence interval, 1.9–7.3) and 13.1% (95% confidence interval, 0.8–5.5) in the 751 age group in Mediterranean and North-Continental cities, respectively. In contrast, the association between temperature and cardiovascular and cerebrovascular admissions tended to be negative and did not reach statistical significance. Conclusions: High temperatures have a specific impact on respiratory admissions, particularly in the elderly population, but the underlying mechanisms are poorly understood. Why high temperature in-creases cardiovascular mortality but not cardiovascular admissions is also unclear. The impact of extreme heat events on respiratory admissions is expected to increase in European cities as a result of global warming and progressive population aging.
    American Journal of Respiratory and Critical Care Medicine 01/2009; 179:383-389. · 11.04 Impact Factor
  • Epidemiology 10/2008; 19(6):S287-S288. · 5.74 Impact Factor
  • Epidemiology 10/2008; 19(6):S286-S287. · 5.74 Impact Factor
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    ABSTRACT: The aim of the present study was to analyse the role of potential selection processes and their impact when evaluating risk factors for 30-day mortality among patients hospitalised for chronic obstructive pulmonary disease (COPD). A cohort of 26,039 patients aged > or = 35 yrs and hospitalised with COPD were enrolled. A 30-day follow-up was carried out using both the cause mortality register (CMR) and the hospital discharge register (HDR). Individual and hospital factors associated with 30-day mortality were studied using both mortality outcomes. The 30-day mortality rate was 1.21.1,000 patient-days(-1) (95% confidence interval (CI) 1.14-1.29) using the CMR, and 1.06.1,000 patient-days(-1) (95% CI 0.98-1.13) using the HDR. Male patients, the most poorly educated, those who resided outside Rome and those who had more than one hospitalisation in the previous 2 yrs were more likely to die after discharge than when hospitalised. The most frequent cause of in-hospital death was respiratory disease and after discharge, heart disease. Older age, male sex, comorbidities, previous hospitalisations for respiratory failure, and admission to a ward not appropriate to treat respiratory diseases were the most important predictors of 30-day mortality. Using in-hospital 30-day mortality provides a significantly different estimate of the role of specific risk factors.
    European Respiratory Journal 05/2008; 32(3):629-36. · 6.36 Impact Factor
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    ABSTRACT: In Lazio region (Italy), mortality data are currently available from the death cause registry (DCR), which reports only underlying causes. Mortality due to other causes, defined concurrent mortality, are need to appropriately estimate the health impact from chronic diseases. The aims of the study were to estimate concurrent mortality from chronic obstructive pulmonary disease (COPD), using hospital discharge registry (HDR), to discuss the validity and limits of this method, and to compare underlying and concurrent mortality from COPD in the Lazio region. A mortality study was carried out for residents who died in 1996-2000 with COPD listed as the underlying cause of death and those who died in the hospital with a different underlying cause of death listed but with a discharge diagnosis of COPD. Age-standardized mortality rates were obtained for males and females separately, using the direct method. A random sample of death certificates was used to validate concurrent causes of death as defined from discharge diagnoses. Age-standardised mortality for COPD as underlying cause of death was 3.68/10,000 in male and 2.29/10,000 in female residents. Mortality increased slightly in the study period for women, but no trend was evident. Age-standardised mortality for COPD as concurrent cause of death was 2.39/10,000 in male and 1.31/10,000 in female residents. The positive predictive value for concurrent COPD mortality was 54.3%. Concurrent COPD mortality contributed 62.3% to the whole mortality. The estimates of concurrent COPD mortality were comparable to those reported in other countries, though using hospital data may overestimate the real concurrent mortality as estimated from death certificates.
    Respiratory Medicine 10/2007; 101(9):1988-93. · 2.59 Impact Factor
  • Epidemiology 08/2007; 18(5):S122. · 5.74 Impact Factor
  • Epidemiology 10/2006; 17(6):S84. · 5.74 Impact Factor
  • Epidemiology. 01/2006; 17.
  • Epidemiology. 01/2006; 17.
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    ABSTRACT: The major fault with existing reimbursement systems lies in their failure to discriminate for the effectiveness of stay, both when paying per day and when paying per episode of treatment. We sought to define an average length of effective stay and recovery trends by impairment category, to design a prospective payment system that takes into account costs and expected recovery trends, and to compare the calculated reimbursement with the predicted costs estimated in a previous study (Saitto C, Marino C, Fusco D, et al. A new prospective payment system for inpatient rehabilitation. Part I: predicting resource consumption. Med Care. 2005;43:844-855). We considered all rehabilitation admissions from 5 Italian inpatient facilities during a 12-month period for which total cost of care had already been estimated and daily cost predicted through regression model. We ascertained recovery trends by impairment category through repeated MDS-PAC schedules and factorial analysis of functional status. We defined effective stay and daily resource consumption by impairment category and used these parameters to calculate reimbursement for the admission. We compared our reimbursement with predicted cost through regression analysis and evaluated the goodness of fit through residual analysis. We calculated reimbursement for 2079 admissions. The r(2) values for the reimbursement to cost correlation ranged from 0.54 in the whole population to 0.56 for "multiple trauma" to 0.85 for "other medical disorders." The best fit was found in the central quintiles of the cost and severity distributions. For each impairment category, we determined the number of days of effective hospital stay and the trends of functional gain. We demonstrated, at least within the Italian health care system, the feasibility of a reimbursement system that matches costs with functional recovery. By linking reimbursement to effective stay adjusted for trends of functional gain, we suggest it is possible to avoid both needless cuts and extensions of hospital admissions.
    Medical Care 10/2005; 43(9):856-64. · 3.23 Impact Factor
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    ABSTRACT: The measures of clinical status used to predict costs must pay the most attention possible to medical conditions and clinical complexity. Length of stay (LOS), which has been used as a proxy for resource consumption, is not a direct measure of costs. Classification and regression trees, which are used in defining iso-resource groups, can be affected by overfitting and are based on a priori choices of the splitting attributes. Finally, current approaches are mainly concerned in estimating average group costs and do not attempt to estimate individual case costs. We sought to define comprehensive measures of clinical status and detailed measures of resource consumption. We also sought to predict individual inpatient rehabilitation costs through multiple regression models. A prospective analysis was conducted of all rehabilitation cases admitted to 5 Italian inpatient facilities during a period of 12 months. All admissions underwent repeated Minimum Data Set-Post Acute Care (MDS-PAC) schedules to collect information on clinical status and treatment provided. We used factorial analysis to yield continuous variables representing clinical characteristics, and we priced treatments to obtain cost of stay. We used linear regression models to predict cost of stay and validated the model-based cost predictions by data-splitting. We collected 9720 MDS-PAC schedules from 2702 hospital admissions. The multivariate regression models fitted costs reasonably well with r(2) values of at least 0.34. On cross-validation, the ability of the regression models to predict cost was confirmed. We were able to estimate actual rehabilitation costs and define reliable regression models to predict costs from individual patient characteristics. Our approach identifies the contribution of any single patient characteristic to rehabilitation cost and tests the assumptions of the analysis.
    Medical Care 10/2005; 43(9):844-55. · 3.23 Impact Factor
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    ABSTRACT: Most studies on the effectiveness of rehabilitation consider only particular rehabilitation treatments for particular conditions, and do not give a global vision of the issue. This study evaluated the effectiveness of various types of post acute rehabilitative care in patients with different diagnoses by investigating the association between treatments and functional gain by type of impairment and severity on admission. Information on the characteristics of patients and the rehabilitative treatments was collected using an Italian version of the Minimum Data Set-Post Acute Care. The questionnaire was created and validated by the Centers for Medicare and Medicaid Services, it is divided in various section and was filled in at regular intervals throughout the hospital stay. Patients included in the study were 1918. We used factor analysis to summarize each section in a single continuous variable. The observed functional gain was calculated as the difference between functional status at the beginning and at the end of the admission. A multiple linear regression analysis was performed to evaluate the association between rehabilitation treatments and functional gain, adjusting for patient characteristics and severity at admission. The effectiveness of the treatments were obtained by calculating the difference between the overall functional gain of the hospital stay and the predicted functional gain of the stay in the absence of rehabilitation treatments. The effectiveness of treatments differs across diagnostic class and it is associated directly with severity of functional status at admission. In most cases, the positive effect of treatments combines with the spontaneous functional gain; in other cases the positive effect of treatments opposes the spontaneous deterioration of patient functional status.
    Epidemiologia e prevenzione 29(2):77-84. · 0.92 Impact Factor
  • Epidemiologia e prevenzione 35(5-6 Suppl 2):118-21. · 0.92 Impact Factor

Publication Stats

220 Citations
68.02 Total Impact Points

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Institutions

  • 2012
    • Lazio Regional Health Service
      Roma, Latium, Italy
  • 2007–2010
    • Agenzia di Sanità Pubblica della Regione Lazio
      Roma, Latium, Italy