Management of pregnant women in tertiary maternity hospitals in the Paris area referred to the intensive care unit for acute hypoxaemic respiratory failure related to SARS-CoV-2: which practices for which outcomes?

BACKGROUND: Evidence for the management of pregnant women with acute hypoxaemic respiratory failure (AHRF) is currently lacking. The likelihood of avoiding intubation and the risks of continuing the pregnancy under invasive ventilation remain undetermined. We report the management and outcome of pregnant women with pneumonia related to SARS-CoV-2 admitted to the ICU of tertiary maternity hospitals of the Paris area. METHODS: We studied a retrospective cohort of pregnant women admitted to 15 ICUs with AHRF related to SARS-CoV-2 defined by the need for O2 ≥ 6 L/min, high-flow nasal oxygen (HFNO), non-invasive or invasive ventilation. Trajectories were assessed to determine the need for intubation and the possibility of continuing the pregnancy on invasive ventilation. RESULTS: One hundred and seven pregnant women, 34 (IQR: 30-38) years old, at a gestational age of 27 (IQR: 25-30) weeks were included. Obesity was present in 37/107. Intubation was required in 47/107 (44%). Intubation rate according to respiratory support was 14/19 (74%) for standard O2, 17/36 (47%) for non-invasive ventilation and 16/52 (31%) for HFNO. Factors significantly associated with intubation were pulmonary co-infection: adjusted OR: 3.38 (95% CI 1.31-9.21), HFNO: 0.11 (0.02-0.41) and non-invasive ventilation: 0.20 (0.04-0.80). Forty-six (43%) women were delivered during ICU stay, 39/46 (85%) for maternal pulmonary worsening, 41/46 (89%) at a preterm stage. Fourteen non-intubated women were delivered under regional anaesthesia; 9/14 ultimately required emergency intubation. Four different trajectories were identified: 19 women were delivered within 2 days after ICU admission while not intubated (12 required prolonged intubation), 23 women were delivered within 2 days after intubation, in 11 intubated women pregnancy was continued allowing delivery after ICU discharge in 8/11, 54 women were never intubated (53 were delivered after discharge). Timing of delivery after intubation was mainly dictated by gestational age. One maternal death and one foetal death were recorded. CONCLUSION: In pregnant women with AHRF related to SARS-CoV-2, HFNO and non-invasive mechanical ventilation were associated with a reduced rate of intubation, while pulmonary co-infection was associated with an increased rate. Pregnancy was continued on invasive mechanical ventilation in one-third of intubated women. Study registration retrospectively registered in ClinicalTrials (NCT05193526).

Cardiovascular disease healthcare trajectories: descriptions, similarities, mortality rates of heart failure in France.

AIMS: The primary objectives of this study were to analyse the nationwide healthcare trajectories of heart failure (HF) patients in France, 2 years after their first hospitalization, and to measure sequence similarities. Secondary objectives were to identify the association between trajectories and the risk of mortality. METHODS AND RESULTS: A retrospective, observational study was conducted using data extracted from the Echantillon Généraliste des Bénéficiaires database, covering the period from 1 January 2008 to 31 December 2018. Follow-up concluded upon death or at the end of the study. We developed a methodology specific to healthcare data by extracting frequent healthcare trajectories and measuring their similarity for use in a survival machine learning analysis. In total, 11 488 HF patients were included and followed up for an average of 2.9 ± 1.3 years. The mean age of the patients was 78.0 ± 13.2 years. The first-year mortality rate was 31.7% and increased to 78.8% at 5 years. Fifty per cent of patients experienced re-hospitalization for reasons related to cardiovascular diseases. We identified 1707 hospitalization sequences, and 21 sequences were associated with survival, while 15 sequences were linked to mortality. In all our models, age and gender emerged as the most significant predictors of mortality (permutation feature importance: 0.099 ± 0.00078 and 0.0087 ± 0.00018, respectively; weights could be interpreted in relative terms). Specifically, the age at initial hospitalization for HF was positively associated with mortality. Gender (male: 49.5%) was associated with poorer prognoses. Healthcare trajectories, including non-surgical device treatments, valve replacements, and atrial fibrillation ablation, were associated with a better prognosis (permutation feature importance: 0.0047 ± 0.00011, 0.0014 ± 0.000073, and 0.00095 ± 0.000097, respectively), except in cases where these invasive treatments preceded or followed hospitalization for cardiac decompensation. The predominant negative prognosis sequences were mostly those that included HF-related hospitalizations before or after other-related hospitalizations (permutation feature importance: 0.0007 ± 0.000091 and 0.00011 ± 0.000045, respectively). CONCLUSIONS: We highlight the value of healthcare trajectories on frequent hospitalization sequences, mortality, and prognosis and indicate the necessary prognostic value of HF re-hospitalization. Our work may be an essential tool for better identification of at-risk patients in order to increase and improve personalized care in the future.

Gastroenteritis Forecasting Assessing the Use of Web and Electronic Health Record Data With a Linear and a Nonlinear Approach: Comparison Study.

BACKGROUND: Disease surveillance systems capable of producing accurate real-time and short-term forecasts can help public health officials design timely public health interventions to mitigate the effects of disease outbreaks in affected populations. In France, existing clinic-based disease surveillance systems produce gastroenteritis activity information that lags real time by 1 to 3 weeks. This temporal data gap prevents public health officials from having a timely epidemiological characterization of this disease at any point in time and thus leads to the design of interventions that do not take into consideration the most recent changes in dynamics. OBJECTIVE: The goal of this study was to evaluate the feasibility of using internet search query trends and electronic health records to predict acute gastroenteritis (AG) incidence rates in near real time, at the national and regional scales, and for long-term forecasts (up to 10 weeks). METHODS: We present 2 different approaches (linear and nonlinear) that produce real-time estimates, short-term forecasts, and long-term forecasts of AG activity at 2 different spatial scales in France (national and regional). Both approaches leverage disparate data sources that include disease-related internet search activity, electronic health record data, and historical disease activity. RESULTS: Our results suggest that all data sources contribute to improving gastroenteritis surveillance for long-term forecasts with the prominent predictive power of historical data owing to the strong seasonal dynamics of this disease. CONCLUSIONS: The methods we developed could help reduce the impact of the AG peak by making it possible to anticipate increased activity by up to 10 weeks.

Influenza forecasting for French regions combining EHR, web and climatic data sources with a machine learning ensemble approach.

Effective and timely disease surveillance systems have the potential to help public health officials design interventions to mitigate the effects of disease outbreaks. Currently, healthcare-based disease monitoring systems in France offer influenza activity information that lags real-time by one to three weeks. This temporal data gap introduces uncertainty that prevents public health officials from having a timely perspective on the population-level disease activity. Here, we present a machine-learning modeling approach that produces real-time estimates and short-term forecasts of influenza activity for the twelve continental regions of France by leveraging multiple disparate data sources that include, Google search activity, real-time and local weather information, flu-related Twitter micro-blogs, electronic health records data, and historical disease activity synchronicities across regions. Our results show that all data sources contribute to improving influenza surveillance and that machine-learning ensembles that combine all data sources lead to accurate and timely predictions.

New Perspectives on Difficult Asthma; Sex and Age of Asthma-Onset Based Phenotypes.

BACKGROUND: Asthma is a diverse condition that differs with age and sex. However, it remains unclear how sex, age of asthma onset, and/or their interaction influence clinical expression of more problematic adult "difficult" asthma. OBJECTIVES: To better understand the clinical features of difficult asthma within a real-world clinical setting using novel phenotypic classification, stratifying subjects by sex and age of asthma onset. METHODS: Participants in a longitudinal difficult asthma clinical cohort study (Wessex AsThma CoHort of difficult asthma; WATCH), United Kingdom (n = 501), were stratified into 4 difficult asthma phenotypes based on sex and age of asthma onset (early <18 years or adult ≥18 years) and characterized in relation to clinical and pathophysiological features. RESULTS: The cohort had more female participants (65%) but had similar proportions of participants with early- or adult-onset disease. Early-onset female disease was commonest (35%), highly atopic, with good spirometry and strong associations with some physical comorbidities but highest psychophysiologic comorbidities. Adult-onset females also had considerable psychophysiologic comorbidities and highest obesity, and were least atopic. Amongst male subjects, proportionately more had adult-onset disease. Early-onset male disease was rarest (14%) but associated with worst lung function, high smoking, atopy, and fungal sensitization. Despite shortest disease duration, adult-onset males had highest use of maintenance oral corticosteroid, poor lung function, and highest fractional exhaled nitrogen oxide in spite of highest smoking prevalence. CONCLUSIONS: This study shows that sex, age of asthma onset, and their interactions influence different clinical manifestations of difficult asthma and identifies a greater risk for lung function loss and oral corticosteroid dependence associated with smoking in adult-onset male subjects.

Comparison of the effect of direct-acting antiviral with and without ribavirin on cyclosporine and tacrolimus clearance values: results from the ANRS CO23 CUPILT cohort.

PURPOSE: Direct-acting antiviral agents have demonstrated their efficacy in treating HCV recurrence after liver transplantation and particularly the sofosbuvir/daclatasvir combination. Pharmacokinetic data on both calcineurin inhibitors and direct-acting antiviral exposure in liver transplant recipients remain sparse. METHODS: Patients were enrolled from the ANRS CO23 CUPILT cohort. All patients treated with sofosbuvir/daclatasvir with or without ribavirin were included in this study when blood samples were available to estimate the clearance of immunosuppressive therapy before direct-acting antiviral initiation and during follow-up. Apparent tacrolimus and cyclosporine clearances were estimated from trough concentrations measured using validated quality control assays. RESULTS: Sixty-seven mainly male patients (79%) were included, with a mean age of 57 years and mean MELD score of 8.2; 50 were on tacrolimus, 17 on cyclosporine. Ribavirin was combined with sofosbuvir/daclatasvir in 52% of patients. Cyclosporine clearance remained unchanged as well as tacrolimus clearance under the ribavirin-free regimen. Tacrolimus clearance increased 4 weeks after direct-acting antivirals and ribavirin initiation versus baseline (geometric mean ratio 1.81; 90% CI 1.30-2.52). Patients under ribavirin had a significantly higher fibrosis stage (> 2) (p = 0.02) and lower haemoglobin during direct-acting antiviral treatment (p = 0.02) which impacted tacrolimus measurements. Direct-acting antiviral exposure was within the expected range. CONCLUSION: Our study demonstrated that liver transplant patients with a recurrence of hepatitis C who are initiating ribavirin combined with a sofosbuvir-daclatasvir direct-acting antiviral regimen may be at risk of lower tacrolimus concentrations because of probable ribavirin-induced anaemia and higher fibrosis score, although there are no effects on cyclosporine levels. TRIAL REGISTRATION: NCT01944527.

Real Time Influenza Monitoring Using Hospital Big Data in Combination with Machine Learning Methods: Comparison Study.

BACKGROUND: Traditional surveillance systems produce estimates of influenza-like illness (ILI) incidence rates, but with 1- to 3-week delay. Accurate real-time monitoring systems for influenza outbreaks could be useful for making public health decisions. Several studies have investigated the possibility of using internet users' activity data and different statistical models to predict influenza epidemics in near real time. However, very few studies have investigated hospital big data. OBJECTIVE: Here, we compared internet and electronic health records (EHRs) data and different statistical models to identify the best approach (data type and statistical model) for ILI estimates in real time. METHODS: We used Google data for internet data and the clinical data warehouse eHOP, which included all EHRs from Rennes University Hospital (France), for hospital data. We compared 3 statistical models-random forest, elastic net, and support vector machine (SVM). RESULTS: For national ILI incidence rate, the best correlation was 0.98 and the mean squared error (MSE) was 866 obtained with hospital data and the SVM model. For the Brittany region, the best correlation was 0.923 and MSE was 2364 obtained with hospital data and the SVM model. CONCLUSIONS: We found that EHR data together with historical epidemiological information (French Sentinelles network) allowed for accurately predicting ILI incidence rates for the entire France as well as for the Brittany region and outperformed the internet data whatever was the statistical model used. Moreover, the performance of the two statistical models, elastic net and SVM, was comparable.

Leveraging hospital big data to monitor flu epidemics.

BACKGROUND AND OBJECTIVE: Influenza epidemics are a major public health concern and require a costly and time-consuming surveillance system at different geographical scales. The main challenge is being able to predict epidemics. Besides traditional surveillance systems, such as the French Sentinel network, several studies proposed prediction models based on internet-user activity. Here, we assessed the potential of hospital big data to monitor influenza epidemics. METHODS: We used the clinical data warehouse of the Academic Hospital of Rennes (France) and then built different queries to retrieve relevant information from electronic health records to gather weekly influenza-like illness activity. RESULTS: We found that the query most highly correlated with Sentinel network estimates was based on emergency reports concerning discharged patients with a final diagnosis of influenza (Pearson's correlation coefficient (PCC) of 0.931). The other tested queries were based on structured data (ICD-10 codes of influenza in Diagnosis-related Groups, and influenza PCR tests) and performed best (PCC of 0.981 and 0.953, respectively) during the flu season 2014-15. This suggests that both ICD-10 codes and PCR results are associated with severe epidemics. Finally, our approach allowed us to obtain additional patients' characteristics, such as the sex ratio or age groups, comparable with those from the Sentinel network. CONCLUSIONS: Conclusions: Hospital big data seem to have a great potential for monitoring influenza epidemics in near real-time. Such a method could constitute a complementary tool to standard surveillance systems by providing additional characteristics on the concerned population or by providing information earlier. This system could also be easily extended to other diseases with possible activity changes. Additional work is needed to assess the real efficacy of predictive models based on hospital big data to predict flu epidemics.

Clinical validation of the CE-IVD marked Therascreen MGMT kit in a cohort of glioblastoma patients.

BACKGROUND: Pyrosequencing is recognized as a strong technique to analyze the MGMT status of glioblastoma patients. The most commonly used assay, quantifies the methylation levels of CpGs 74 to 78. A more recent CE-marked In Vitro Diagnostic Medical Device (CE-IVD) assay, Therascreen, analyzes CpGs 76-79. METHODS: We performed a comparison of these two assays to evaluate the potential impact of this shift in analyzed CpGs. Therascreen analysis was centrally performed for 102 glioblastoma patients, who were part of a prospective multicenter trial. RESULTS: A strong correlation was observed for the mean values of the 4 or 5 analyzed CpGs, with lower values recorded using the Therascreen assay, especially for values greater than 20%. When considering a classification in 3 categories (> 12%: methylated; ⩽ 8%: unmethylated; 9-12%: grey zone), 93% of patients were identically classified between the two assays. Using a binary classification, 95% and 97% of patients were identically classified with cut-offs of 8% and 12%, respectively. A strong prognostic significance was observed for both assays: median overall survival were 15.9 months and 34.9 months for respectively unmethylated and methylated patients with either test. CONCLUSION: The results demonstrate that these assays may be used interchangeably.

Validation of the high-performance of pyrosequencing for clinical MGMT testing on a cohort of glioblastoma patients from a prospective dedicated multicentric trial.

BACKGROUND: The goal of this prospective multicentric trial was to validate a technique that allowed for MGMT promoter methylation analysis in routine clinical practice. METHODS: The MGMT status of 139 glioblastoma patients, whom had received standard first line treatment, was determined using pyrosequencing (PSQ) and a semi-quantitative Methylation-specific PCR (sqMS-PCR) method, using both frozen and formalin-fixed paraffin-embedded FFPE samples. Eight participating centers locally performed the analysis, including external quality controls. RESULTS: There was a strong correlation between results from FFPE and frozen samples. With cut-offs of 12% and 13%, 98% and 91% of samples were identically classified with PSQ and sqMS-PCR respectively. In 12% of cases frozen samples were excluded because they had a low percentage of tumor cells. In 5-6% of cases the analysis was not feasible on FFPE samples. The optimized risk cut-offs were higher in both techniques when using FFPE samples, in comparison to frozen samples. For sqMS-PCR, we validated a cut-off between 13-15% to dichotomize patients. For PSQ, patients with a low level of methylation (<= 8%) had a median progression-free survival under 9 months, as compared with more than 15.5 months for those with a level above 12%. For intermediate values (9-12%), more discordant results between FFPE and frozen samples were observed and there was not a clear benefit of temozolomide treatment, which indicated a "grey zone". CONCLUSIONS: MGMT status can reliably be investigated in local laboratories. PSQ is the ideal choice as proven by strong interlaboratory reproducibility, along with threshold agreements across independent studies.

Predicting metabolic rate during level and uphill outdoor walking using a low-cost GPS receiver.

The objective of this study was to assess the accuracy of using speed and grade data obtained from a low-cost global positioning system (GPS) receiver to estimate metabolic rate (MR) during level and uphill outdoor walking. Thirty young, healthy adults performed randomized outdoor walking for 6-min periods at 2.0, 3.5, and 5.0 km/h and on three different grades: 1) level walking, 2) uphill walking on a 3.7% mean grade, and 3) uphill walking on a 10.8% mean grade. The reference MR [metabolic equivalents (METs) and oxygen uptake (V̇o2)] values were obtained using a portable metabolic system. The speed and grade were obtained using a low-cost GPS receiver (1-Hz recording). The GPS grade (Δ altitude/distance walked) was calculated using both uncorrected GPS altitude data and GPS altitude data corrected with map projection software. The accuracy of predictions using reference speed and grade (actual[SPEED/GRADE]) data was high [R(2) = 0.85, root-mean-square error (RMSE) = 0.68 MET]. The accuracy decreased when GPS speed and uncorrected grade (GPS[UNCORRECTED]) data were used, although it remained substantial (R(2) = 0.66, RMSE = 1.00 MET). The accuracy was greatly improved when the GPS speed and corrected grade (GPS[CORRECTED]) data were used (R(2) = 0.82, RMSE = 0.79 MET). Published predictive equations for walking MR were also cross-validated using actual or GPS speed and grade data when appropriate. The prediction accuracy was very close when either actual[SPEED/GRADE] values or GPS[CORRECTED] values (for level and uphill combined) or GPS speed values (for level walking only) were used. These results offer promising research and clinical applications related to the assessment of energy expenditure during free-living walking.

Joint Model of Iron and Hepcidin During the Menstrual Cycle in Healthy Women.

Hepcidin regulates serum iron levels, and its dosage is used in differential diagnostic of iron-related pathologies. We used the data collected in the HEPMEN (named after HEPcidin during MENses) study to investigate the joint dynamics of serum hepcidin and iron during the menstrual cycle in healthy women. Ninety menstruating women were recruited after a screening visit. Six fasting blood samples for determination of iron-status variables were taken in the morning throughout the cycle, starting on the second day of the period. Non-linear mixed effect models were used to describe the evolution of iron and hepcidin. Demographic and medical covariates were tested for their effect on model parameters. Parameter estimation was performed using the SAEM algorithm implemented in the Monolix software. A general pattern was observed for both hepcidin and iron, consisting of an initial decrease during menstruation, followed by a rebound and stabilising during the second half of the cycle. We developed a joint model including a menstruation-induced decrease of both molecules at the beginning of the menses and a rebound effect after menses. Iron stimulated the release of hepcidin. Several covariates, including contraception, amount of blood loss and ferritin, were found to influence the parameters. The joint model of iron and hepcidin was able to describe the fluctuations induced by blood loss from menstruation in healthy non-menopausal women and the subsequent regulation. The HEPMEN study showed fluctuations of iron-status variables during the menstrual cycle, which should be considered when using hepcidin measurements for diagnostic purposes in women of child-bearing potential.

Sunitinib combined with angiotensin-2 type-1 receptor antagonists induces more necrosis: a murine xenograft model of renal cell carcinoma.

BACKGROUND: Angiotensin-2 type-1 receptor antagonists not are only antihypertensive drugs but also can inhibit VEGF production. We hypothesised that adding telmisartan to sunitinib could potentiate the antiangiogenic effects. MATERIAL AND METHODS: 786-O cell lines were injected in nude mice. After tumor development, mice were divided into 4 groups: the first was the control group (DMSO), the second group was treated with sunitinib alone, the third group was treated with telmisartan alone, and the fourth group was treated with the combination. Drugs were orally administered every day for four weeks. Animals were sacrificed after treatment. Blood and tumor tissues were collected for analysis by immunohistochemistry, Western Blot, and ELISA methods. RESULTS: All animals developed a ccRCC and ten in each group were treated. Using a kinetic model, tumors tended to grow slower in the combination group compared to others (P = 0.06). Compared to sunitinib alone, the addition of telmisartan significantly increased tissue necrosis (P = 0.038). Central microvascular density decreased (P = 0.0038) as well as circulating VEGF (P = 0.003). There was no significant variation in proliferation or apoptosis markers. CONCLUSION: The combination of sunitinib and telmisartan revealed an enhancement of the blockage of the VEGF pathway on renal tumor resulting in a decrease in neoangiogenesis and an increase in necrosis.

Outcome-based determination of optimal pyrosequencing assay for MGMT methylation detection in glioblastoma patients.

The methylation of O(6)-methylguanine DNA methyltransferase (MGMT) gene promoter is a key biological marker in clinical neuro-oncology. Nevertheless, there is no consensus concerning the best technique for its assessment. In a recent study comparing five methods to analyze MGMT status, we found that the best prediction of survival was obtained with a pyrosequencing (PSQ) test assessing methylation of 5 CpGs (CpGs 74-78). In the present study we extended our PSQ analysis to 16 CpGs (CpGs 74-89) identified as critical for transcriptional control of the gene. The predictive value of the methylation levels at each CpG, as well as the mean methylation levels of selected sets of consecutive CpGs was tested in a cohort of 89 de novo glioblastoma patients who had received standard of care treatment (Stupp protocol). Using an optimal risk cut-off, each CpG or combination of CpGs, was associated with overall survival (OS) and progression free survival. The best predictive models for OS after stratification on performance score and age were obtained with CpG 89, CpG 84 and mean methylation of CpG 84-88 (Hazard ratio (HR), 0.31; p < 0.0001). The improvement compared to the predictive value of the test analyzing average methylation of CpG 74-78 (HR, 0.32; p < 0.0001) was however marginal. We recommend to test CpGs 74-78 when analyzing MGMT methylation status by PSQ because a commercial kit that has successfully been used in several studies is available, allowing reproducible and comparable results from one laboratory to another.

Comparative assessment of 5 methods (methylation-specific polymerase chain reaction, MethyLight, pyrosequencing, methylation-sensitive high-resolution melting, and immunohistochemistry) to analyze O6-methylguanine-DNA-methyltranferase in a series of 100 glioblastoma patients.

BACKGROUND: There is a strong need to determine the best technique for O(6) -methylguanine-DNA-methyltranferase (MGMT) analysis, because MGMT status is currently used in clinical trials and occasionally in routine clinical practice for glioblastoma patients. METHODS: The authors compared analytical performances and predictive values of 5 techniques in a series of 100 glioblastoma patients who received standard of care treatment (Stupp protocol). RESULTS: MGMT promoter was considered methylated in 33%, 33%, 42%, and 60% of patients by methylation-sensitive high-resolution melting, MethyLight, pyrosequencing (with an optimal risk cutoff at 8% for the average percentage of the 5 CpGs tested), and methylation-specific polymerase chain reaction (MS-PCR), respectively. Fifty-nine percent of the samples had <23% (the optimal risk cutoff) of MGMT-positive tumor cells. The best predictive values for overall survival (OS), after adjustment for age and performance status, were obtained by pyrosequencing (hazard ratio [HR], 0.32; P < .0001), MS-PCR (HR, 0.37; P < .0001), and immunohistochemistry (HR, 0.43; P = .0005) as compared with methylation-sensitive high-resolution melting (HR, 0.52 P = .02) and MethyLight (HR, 0.6; P = .05). For progression-free survival (PFS), the best predictive values were obtained with pyrosequencing (HR, 0.35; P < .0001), methylation-sensitive high-resolution melting (HR, 0.46; P = .002), and MS-PCR (HR, 0.49; P = .002). Combining pyrosequencing and immunohistochemistry slightly improved predictive power for OS, but not for PFS. Poor reproducibility and interobserver variability were, however, observed for immunohistochemistry. CONCLUSIONS: Good prediction of survival in addition to high reproducibility and sensitivity made pyrosequencing the best among the 5 techniques tested in this study.

Meta-analysis of interstitial pneumonia in studies evaluating iodine-131-labeled lipiodol for hepatocellular carcinoma using exact likelihood approach.

PURPOSE: Iodine-131-labeled lipiodol is currently licensed for unresectable hepatocellular carcinoma with portal thrombosis. It is thought to be well tolerated. Cases of interstitial pneumonia have been reported, but their frequency (≈2%) has not been well estimated. Quantifying adverse drug event frequency requires an appropriate statistical approach because standard methods are biased. METHODS: To estimate the frequency of interstitial pneumonia in patients with hepatocellular carcinoma receiving iodine-131-labeled lipiodol, we conducted a systematic review of English articles using MEDLINE and EMBASE. All types of articles were considered except case reports. Primary outcome measure was symptomatic interstitial pneumonia based on investigators' judgment. All pooled analyses were based on a random effects meta-analysis model using an exact likelihood approach based on the binomial within-study distribution. RESULTS: Ten studies, including 142 patients, used low activity per dose, ranging from 0.3 to 1.1 GBq. No respiratory adverse event was noticed in these studies. Eighteen studies, including 542 patients, evaluated higher activity per dose, around 2.2 GBq; 24 cases of interstitial pneumonia were reported in these studies. Estimated frequency of interstitial pneumonia was 1.6% (95%CI, 0.4-6.4%) after one high dose and 4.1% (95%CI, 1.0-16.0%) after two or more high doses. CONCLUSIONS: The frequency of interstitial pneumonia appears higher and more precise than previously estimated. The risk appears to be related to the number of injections and the dose level per injection. Generalized linear mixed models using the exact binomial within-study distribution initially described to summarize data on diagnostic evaluation could be relevant for drug-related adverse reaction frequency assessment.

Hemodynamic and histomorphometric characteristics of heart failure induced by aortic stenosis in the guinea pig: comparison of two constriction sizes.

Heart failure induced by aortic stenosis in young guinea pigs could constitute an interesting model for pharmacology, but its natural history needs to be characterized. One hundred five guinea pigs (3-4 weeks old) underwent thoracic aortic banding with 12- (B12G) or 14-gauge (B14G) needles or similar sham operations (S12G, S14G). Animals alive at 7 d (S12G, n = 16; B12G, n = 28; S14G, n = 19; B14G, n = 27) were assessed at 60 or 120 d. At 60 d, compared with sham groups, left ventricular (LV) mass and wall thickness increased in operated groups, but LV systolic pressure and right ventricular (RV) wall thickness only increased in the B14G group. At 120 d, B12G animals still showed signs of compensated hypertrophy with LV and RV wall thickening (+8%, +21%) and LV dilation (+20%), whereas B14G animals showed signs of decompensation with LV end-diastolic pressure increase (+167%) and mean arterial pressure decrease (-28%) associated with LV and RV hypertrophy (+77%, + 51%) and greater increases of LV and RV wall thickening (+19%, + 57%), as well as LV dilation (+43%). A 12G stenosis results in compensated hypertrophy at 60 and 120 d; a 14G stenosis leads to compensated hypertrophy at 60 d and heart failure at 120 d.

Risk factors of influenza transmission in households.

BACKGROUND: Influenza transmission in households is a subject of renewed interest, as the vaccination of children is currently under debate and antiviral treatments have been approved for prophylactic use. AIMS: To quantify the risk factors of influenza transmission in households. DESIGN OF STUDY: A prospective study conducted during the 1999 to 2000 winter season in France. SETTING: Nine hundred and forty-six households where a member, the index patient, had visited their general practitioner (GP) because of an influenza-like illness were enrolled in the study. Five hundred and ten of the index patients tested positive for influenza A (subtype H3N2). A standardised daily questionnaire allowed for identification of secondary cases of influenza among their household contacts, who were followed-up for 15 days. Of the 395 (77%) households that completed the questionnaire, we selected 279 where no additional cases had occurred on the day of the index patient's visit to the GP. METHODS: Secondary cases of influenza were those household contacts who had developed clinical influenza within 5 days of the disease onset in the index patient. Hazard ratios for individual clinical and demographic characteristics of the contact and their index patient were derived from a Cox regression model. RESULTS: Overall in the 279 households, 131 (24.1%) secondary cases occurred among the 543 household contacts. There was an increased risk of influenza transmission in preschool contacts (hazard ratio [HR] = 1.85, 95% confidence interval [CI] = 1.09 to 3.26) as compared with school-age and adult contacts. There was also an increased risk in contacts exposed to preschool index patients (HR = 1.93, 95% CI = 1.09 to 3.42) and school-age index patients (HR = 1.68, 95% CI = 1.07 to 2.65), compared with those exposed to adult index cases. No other factor was associated with transmission of the disease. CONCLUSION: Our results support the major role of children in the dissemination of influenza in households. Vaccination of children or prophylaxis with neuraminidase inhibitors would prevent, respectively, 32-38% and 21-41% of secondary cases caused by exposure to a sick child in the household.