Study protocol: differential effects of diet and physical activity based interventions in pregnancy on maternal and fetal outcomes--individual patient data (IPD) meta-analysis and health economic evaluation.

© 2014 Ruifrok et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.BACKGROUND: Pregnant women who gain excess weight are at risk of complications during pregnancy and in the long term. Interventions based on diet and physical activity minimise gestational weight gain with varied effect on clinical outcomes. The effect of interventions on varied groups of women based on body mass index, age, ethnicity, socioeconomic status, parity, and underlying medical conditions is not clear. Our individual patient data (IPD) meta-analysis of randomised trials will assess the differential effect of diet- and physical activity-based interventions on maternal weight gain and pregnancy outcomes in clinically relevant subgroups of women. METHODS/DESIGN: Randomised trials on diet and physical activity in pregnancy will be identified by searching the following databases: MEDLINE, EMBASE, BIOSIS, LILACS, Pascal, Science Citation Index, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Database of Abstracts of Reviews of Effects, and Health Technology Assessment Database. Primary researchers of the identified trials are invited to join the International Weight Management in Pregnancy Collaborative Network and share their individual patient data. We will reanalyse each study separately and confirm the findings with the original authors. Then, for each intervention type and outcome, we will perform as appropriate either a one-step or a two-step IPD meta-analysis to obtain summary estimates of effects and 95% confidence intervals, for all women combined and for each subgroup of interest. The primary outcomes are gestational weight gain and composite adverse maternal and fetal outcomes. The difference in effects between subgroups will be estimated and between-study heterogeneity suitably quantified and explored. The potential for publication bias and availability bias in the IPD obtained will be investigated. We will conduct a model-based economic evaluation to assess the cost effectiveness of the interventions to manage weight gain in pregnancy and undertake a value of information analysis to inform future research. SYSTEMATIC REVIEW REGISTRATION: PROSPERO 2013: CRD42013003804.This study was funded by the National Institute for Health Research (NIHR) HTA (Health Technology Assessment) UK programme 12/01

Hospital-Acquired Infections in Critically Ill Patients With COVID-19

Background: Few small studies have described hospital-acquired infections (HAIs) occurring in patients with COVID-19. Research Question: What characteristics in critically ill patients with COVID-19 are associated with HAIs and how are HAIs associated with outcomes in these patients? Study Design and Methods: Multicenter retrospective analysis of prospectively collected data including adult patients with severe COVID-19 admitted to eight Italian hub hospitals from February 20, 2020, through May 20, 2020. Descriptive statistics and univariate and multivariate Weibull regression models were used to assess incidence, microbial cause, resistance patterns, risk factors (ie, demographics, comorbidities, exposure to medication), and impact on outcomes (ie, ICU discharge, length of ICU and hospital stays, and duration of mechanical ventilation) of microbiologically confirmed HAIs. Results: Of the 774 included patients, 359 patients (46%) demonstrated 759 HAIs (44.7 infections/1,000 ICU patient-days; 35% multidrug-resistant [MDR] bacteria). Ventilator-associated pneumonia (VAP; n = 389 [50%]), bloodstream infections (BSIs; n = 183 [34%]), and catheter-related BSIs (n = 74 [10%]) were the most frequent HAIs, with 26.0 (95% CI, 23.6-28.8) VAPs per 1,000 intubation-days, 11.7 (95% CI, 10.1-13.5) BSIs per 1,000 ICU patient-days, and 4.7 (95% CI, 3.8-5.9) catheter-related BSIs per 1,000 ICU patient-days. Gram-negative bacteria (especially Enterobacterales) and Staphylococcus aureus caused 64% and 28% of cases of VAP, respectively. Variables independently associated with infection were age, positive end expiratory pressure, and treatment with broad-spectrum antibiotics at admission. Two hundred thirty-four patients (30%) died in the ICU (15.3 deaths/1,000 ICU patient-days). Patients with HAIs complicated by septic shock showed an almost doubled mortality rate (52% vs 29%), whereas noncomplicated infections did not affect mortality. HAIs prolonged mechanical ventilation (median, 24 days [interquartile range (IQR), 14-39 days] vs 9 days [IQR, 5-13 days]; P < .001), ICU stay (24 days [IQR, 16-41 days] vs 9 days [IQR, 6-14 days]; P = .003), and hospital stay (42 days [IQR, 25-59 days] vs 23 days [IQR, 13-34 days]; P < .001). Interpretation: Critically ill patients with COVID-19 are at high risk for HAIs, especially VAPs and BSIs resulting from MDR organisms. HAIs prolong mechanical ventilation and hospitalization, and HAIs complicated by septic shock almost double mortality. Trial Registry: ClinicalTrials.gov; No.: NCT04388670; URL: www.clinicaltrials.go

Erratum to: Study protocol: differential effects of diet and physical activity based interventions in pregnancy on maternal and fetal outcomes: individual patient data (IPD) meta-analysis and health economic evaluation.

Erratum to: Study protocol: differential effects of diet and physical activity based interventions in pregnancy on maternal and fetal outcomes: individual patient data (IPD) meta-analysis and health economic evaluatio

Time course of risk factors associated with mortality of 1260 critically ill patients with COVID-19 admitted to 24 Italian intensive care units

94noopenPurpose: To evaluate the daily values and trends over time of relevant clinical, ventilatory and laboratory parameters during the intensive care unit (ICU) stay and their association with outcome in critically ill patients with coronavirus disease 19 (COVID-19). Methods: In this retrospective–prospective multicentric study, we enrolled COVID-19 patients admitted to Italian ICUs from February 22 to May 31, 2020. Clinical data were daily recorded. The time course of 18 clinical parameters was evaluated by a polynomial maximum likelihood multilevel linear regression model, while a full joint modeling was fit to study the association with ICU outcome. Results: 1260 consecutive critically ill patients with COVID-19 admitted in 24 ICUs were enrolled. 78% were male with a median age of 63 [55–69] years. At ICU admission, the median ratio of arterial oxygen partial pressure to fractional inspired oxygen (PaO2/FiO2) was 122 [89–175] mmHg. 79% of patients underwent invasive mechanical ventilation. The overall mortality was 34%. Both the daily values and trends of respiratory system compliance, PaO2/FiO2, driving pressure, arterial carbon dioxide partial pressure, creatinine, C-reactive protein, ferritin, neutrophil, neutrophil–lymphocyte ratio, and platelets were associated with survival, while for lactate, pH, bilirubin, lymphocyte, and urea only the daily values were associated with survival. The trends of PaO2/FiO2, respiratory system compliance, driving pressure, creatinine, ferritin, and C-reactive protein showed a higher association with survival compared to the daily values. Conclusion: Daily values or trends over time of parameters associated with acute organ dysfunction, acid–base derangement, coagulation impairment, or systemic inflammation were associated with patient survival.openZanella A.; Florio G.; Antonelli M.; Bellani G.; Berselli A.; Bove T.; Cabrini L.; Carlesso E.; Castelli G.P.; Cecconi M.; Citerio G.; Coloretti I.; Corti D.; Dalla Corte F.; De Robertis E.; Foti G.; Fumagalli R.; Girardis M.; Giudici R.; Guiotto L.; Langer T.; Mirabella L.; Pasero D.; Protti A.; Ranieri M.V.; Rona R.; Scudeller L.; Severgnini P.; Spadaro S.; Stocchetti N.; Vigano M.; Pesenti A.; Grasselli G.; Aspesi M.; Baccanelli F.; Bassi F.; Bet A.; Biagioni E.; Biondo A.; Bonenti C.; Bottino N.; Brazzi L.; Buquicchio I.; Busani S.; Calini A.; Calligaro P.; Cantatore L.P.; Carelli S.; Carsetti A.; Cavallini S.; Cimicchi G.; Coppadoro A.; Dall'Ara L.; Di Gravio V.; Erba M.; Evasi G.; Facchini A.; Fanelli V.; Feliciotti G.; Fusarini C.F.; Ferraro G.; Gagliardi G.; Garberi R.; Gay H.; Giacche L.; Grieco D.; Guzzardella A.; Longhini F.; Manzan A.; Maraggia D.; Milani A.; Mischi A.; Montalto C.; Mormina S.; Noseda V.; Paleari C.; Pedeferri M.; Pezzi A.; Pizzilli G.; Pozzi M.; Properzi P.; Rauseo M.; Russotto V.; Saccarelli L.; Servillo G.; Spano S.; Tagliabue P.; Tonetti T.; Tullo L.; Vetrugno L.; Vivona L.; Volta C.A.; Zambelli V.; Zanoni A.Zanella, A.; Florio, G.; Antonelli, M.; Bellani, G.; Berselli, A.; Bove, T.; Cabrini, L.; Carlesso, E.; Castelli, G. P.; Cecconi, M.; Citerio, G.; Coloretti, I.; Corti, D.; Dalla Corte, F.; De Robertis, E.; Foti, G.; Fumagalli, R.; Girardis, M.; Giudici, R.; Guiotto, L.; Langer, T.; Mirabella, L.; Pasero, D.; Protti, A.; Ranieri, M. V.; Rona, R.; Scudeller, L.; Severgnini, P.; Spadaro, S.; Stocchetti, N.; Vigano, M.; Pesenti, A.; Grasselli, G.; Aspesi, M.; Baccanelli, F.; Bassi, F.; Bet, A.; Biagioni, E.; Biondo, A.; Bonenti, C.; Bottino, N.; Brazzi, L.; Buquicchio, I.; Busani, S.; Calini, A.; Calligaro, P.; Cantatore, L. P.; Carelli, S.; Carsetti, A.; Cavallini, S.; Cimicchi, G.; Coppadoro, A.; Dall'Ara, L.; Di Gravio, V.; Erba, M.; Evasi, G.; Facchini, A.; Fanelli, V.; Feliciotti, G.; Fusarini, C. F.; Ferraro, G.; Gagliardi, G.; Garberi, R.; Gay, H.; Giacche, L.; Grieco, D.; Guzzardella, A.; Longhini, F.; Manzan, A.; Maraggia, D.; Milani, A.; Mischi, A.; Montalto, C.; Mormina, S.; Noseda, V.; Paleari, C.; Pedeferri, M.; Pezzi, A.; Pizzilli, G.; Pozzi, M.; Properzi, P.; Rauseo, M.; Russotto, V.; Saccarelli, L.; Servillo, G.; Spano, S.; Tagliabue, P.; Tonetti, T.; Tullo, L.; Vetrugno, L.; Vivona, L.; Volta, C. A.; Zambelli, V.; Zanoni, A

A one health framework to estimate the cost of antimicrobial resistance

Abstract Objectives/purpose The costs attributable to antimicrobial resistance (AMR) remain theoretical and largely unspecified. Current figures fail to capture the full health and economic burden caused by AMR across human, animal, and environmental health; historically many studies have considered only direct costs associated with human infection from a hospital perspective, primarily from high-income countries. The Global Antimicrobial Resistance Platform for ONE-Burden Estimates (GAP-ON€) network has developed a framework to help guide AMR costing exercises in any part of the world as a first step towards more comprehensive analyses for comparing AMR interventions at the local level as well as more harmonized analyses for quantifying the full economic burden attributable to AMR at the global level. Methods GAP-ON€ (funded under the JPIAMR 8th call (Virtual Research Institute) is composed of 19 international networks and institutions active in the field of AMR. For this project, the Network operated by means of Delphi rounds, teleconferences and face-to-face meetings. The resulting costing framework takes a bottom-up approach to incorporate all relevant costs imposed by an AMR bacterial microbe in a patient, in an animal, or in the environment up through to the societal level. Results The framework itemizes the epidemiological data as well as the direct and indirect cost components needed to build a realistic cost picture for AMR. While the framework lists a large number of relevant pathogens for which this framework could be used to explore the costs, the framework is sufficiently generic to facilitate the costing of other resistant pathogens, including those of other aetiologies. Conclusion In order to conduct cost-effectiveness analyses to choose amongst different AMR-related interventions at local level, the costing of AMR should be done according to local epidemiological priorities and local health service norms. Yet the use of a common framework across settings allows for the results of such studies to contribute to cumulative estimates that can serve as the basis of broader policy decisions at the international level such as how to steer R&D funding and how to prioritize AMR amongst other issues. Indeed, it is only by building a realistic cost picture that we can make informed decisions on how best to tackle major health threats

Biased-corrected richness estimates for the Amazonian tree flora

Amazonian forests are extraordinarily diverse, but the estimated species richness is very much debated. Here, we apply an ensemble of parametric estimators and a novel technique that includes conspecific spatial aggregation to an extended database of forest plots with up-to-date taxonomy. We show that the species abundance distribution of Amazonia is best approximated by a logseries with aggregated individuals, where aggregation increases with rarity. By averaging several methods to estimate total richness, we confirm that over 15,000 tree species are expected to occur in Amazonia. We also show that using ten times the number of plots would result in an increase to just ~50% of those 15,000 estimated species. To get a more complete sample of all tree species, rigorous field campaigns may be needed but the number of trees in Amazonia will remain an estimate for years to come