Aim: To estimate the re‐hospitalization rate of extremely preterm children during infancy and associated factors after the recent improvement in survival rates. Method: The cohort included all children born before 29 wk of gestation in nine French regions in 1997. All admissions between discharge from initial hospitalization and 9 mo after birth were considered. Factors studied included the child's characteristics at birth and during neonatal hospitalization, risk factors for infection after discharge and parents' socio‐demographic characteristics. Adjusted odds ratios (aOR) for re‐hospitalization for all reasons and for respiratory disorders were obtained from logistic regression models. Results: Of the 376 children, 178 were re‐admitted at least once (47.3%; 95% CI: 42.3–52.4). Fifty‐five percent of the hospitalized children were admitted at least once for respiratory disorders. The re‐hospitalization rate was higher for children who had had chronic lung disease (aOR: 2.2; 95% CI: 1.3–3.7), those initially discharged between August and October (aOR: 2.5; 95% CI: 1.2–5.1) or between November and January (aOR: 3.2; 95% CI: 1.5–6.8), and children living with other children under six (aOR: 3.4; 95 %CI: 1.6–7.5). Re‐hospitalizations were associated with neither gestational age nor the duration of neonatal hospitalization. Adjusted odds ratios for re‐hospitalization for respiratory tract disorders were very similar to those for the overall hospitalizations. Conclusion: Infants born before 29 wk have a very high risk of re‐hospitalization. The associated factors can help define high‐risk groups at discharge from the neonatal unit who need special surveillance.

Aims The objectives of this study were to describe annual trends in patients hospitalized for heart failure (HF) and HF‐associated mortality rates in France between 2000 and 2012. Methods and results Hospital discharge data were extracted from the French National Hospitalization Database (PMSI). Mortality data were obtained from the French National Mortality Database. HF events constituting the underlying or associated cause of death were selected. Rates were age standardized using the 2010 European census population as the standard population. Time trends were tested using a Poisson regression model. In 2012, the overall age‐standardized rate of patients hospitalized for HF was 246.2 per 100 000 inhabitants. The age‐standardized rate of HF‐associated mortality was 113.8 per 100 000 inhabitants in 2010. Hospitalized patient rates remained steady between 2002 and 2012, whereas mortality decreased by 3.3% annually from 2000 to 2010. Trends in hospitalized patients and mortality differed significantly between men and women, particularly among the 45‐ to 55‐ and 65‐ to 74‐year‐old age groups, with a smaller decrease observed in women. Conclusion Among men, a slight decrease in patients hospitalized for HF and a substantial reduction in mortality were observed. Among women, only a large decrease in HF mortality was observed. HF remains one of the leading causes of death and hospitalization in France, particularly in the elderly.

ObjectiveTo investigate a new approach to calculating cause-related standardized mortality rates that involves assigning weights to each cause of death reported on death certificates.MethodsWe derived cause-related standardized mortality rates from death certificate data for France in 2010 using: (i) the classic method, which considered only the underlying cause of death; and (ii) three novel multiple-cause-of-death weighting methods, which assigned weights to multiple causes of death mentioned on death certificates: the first two multiple-cause-of-death methods assigned non-zero weights to all causes mentioned and the third assigned non-zero weights to only the underlying cause and other contributing causes that were not part of the main morbid process. As the sum of the weights for each death certificate was 1, each death had an equal influence on mortality estimates and the total number of deaths was unchanged. Mortality rates derived using the different methods were compared.FindingsOn average, 3.4 causes per death were listed on each certificate. The standardized mortality rate calculated using the third multiple-cause-of-death weighting method was more than 20% higher than that calculated using the classic method for five disease categories: skin diseases, mental disorders, endocrine and nutritional diseases, blood diseases and genitourinary diseases. Moreover, this method highlighted the mortality burden associated with certain diseases in specific age groups.ConclusionA multiple-cause-of-death weighting approach to calculating cause-related standardized mortality rates from death certificate data identified conditions that contributed more to mortality than indicated by the classic method. This new approach holds promise for identifying underrecognized contributors to mortality.

Even if pain has been identified, its assessment and management remains inadequate. The quality of care may be improved by educating the personnel in developing protocols and in evaluating pain management.

To estimate the prevalence of pain in adult patients attending an emergency department (ED) and to identify risk markers for insufficient pain relief, a cross-sectional survey was conducted for 16 days, 24 hours each day, in the ED of a Paris university hospital. A structured questionnaire was used to collect characteristics of pain and its management from patients. Pain intensity was evaluated both on arrival and before discharge using two scales (a numerical descriptor scale or a verbal pain intensity scale). On arrival, 78% of the patients complained of pain; among them, 54% complained of intense pain and 47% suffered procedural pain. Insufficient pain relief was assessed in 289 (77%) patients. We identified the following risk markers for insufficient pain relief: moderate or low pain intensity, no intervention in the ED before the medical examination, and no use of medication before arrival.

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BackgroundIn the age of big data in healthcare, automated comparison of medical diagnoses in large scale databases is a key issue. Our objectives were: 1) to formally define and identify cases of independence between last hospitalization main diagnosis (MD) and death registry underlying cause of death (UCD) for deceased subjects hospitalized in their last year of life; 2) to study their distribution according to socio-demographic and medico-administrative variables; 3) to discuss the interest of this method in the specific context of hospital quality of care assessment.Methods1) Elaboration of an algorithm comparing MD and UCD, relying on Iris, a coding system based on international standards. 2) Application to 421,460 beneficiaries of the general health insurance regime (which covers 70% of French population) hospitalized and deceased in 2008–2009.Results1) Independence, was defined as MD and UCD belonging to different trains of events leading to death 2) Among the deaths analyzed automatically (91.7%), 8.5% of in-hospital deaths and 19.5% of out-of-hospital deaths were classified as independent. Independence was more frequent in elder patients, as well as when the discharge-death time interval grew (14.3% when death occurred within 30 days after discharge and 27.7% within 6 to 12 months) and for UCDs other than neoplasms.ConclusionOur algorithm can identify cases where death can be considered independent from the pathology treated in hospital. Excluding these deaths from the ones allocated to the hospitalization process could contribute to improve post-hospital mortality indicators. More generally, this method has the potential of being developed and used for other diagnoses comparisons across time periods or databases.

Abortion is a good opportunity for intervention, but especially so for socially disadvantaged women. It is essential to draw the attention of prescribers and women to the higher risk of contraceptive failure at the start of use of a method.