Study protocol for the evaluation of the health effects of superblocks in barcelona : The "salut als carrers" (health in the streets) project

Superblocks are currently being introduced in Barcelona to respond to the city's scarcity of green spaces and high levels of air pollution, traffic injuries, and sedentariness. The aim is to calm the streets by reducing the number of square meters dedicated to private vehicles and to reclaim part of this public space for people. Salut als Carrers (Health in the Streets) is a project to evaluate the potential environmental and health effects of the superblock model with an equity perspective in Barcelona. This study aims to explain the various interventions implemented in different neighborhoods in Barcelona and the methods that will be used to evaluate them in a quasi-experimental and health impact assessment (HIA) approaches. Given the complexity of the intervention evaluated, the project employs mixed methodologies. Quantitative methods include: (a) a pre-post health survey of 1200 people randomly selected from the municipal register asked about self-perceived health and quality of life, social support, mental health, mobility, physical activity, neighborhood characteristics, and housing; (b) pre-post environmental measurements, mainly of nitrogen dioxide (NO), particulate matter of less than 10 µm (PM), and particulate matter of less than 2.5 µm (PM) and black carbon; (c) pre-post environmental walkability measures using the Microscale Audit of Pedestrian Streetscapes (MAPS) tool; (d) use of public space and physical activity levels using the System for Observing Play and Recreation in Communities (SOPARC), a validated observation tool; (e) pre-post traffic injury measures with a comparison group; and (f) the comparison and integration of pre-post assessment with previous HIAs and the improvement of future HIAs. Qualitative studies will be performed to analyze residents' perception of these effects by using: (a) various focus groups according to different participant characteristics who are more or less likely to use the superblocks; and (b) a guerrilla ethnography, which is a method that combines ethnographic observation and semi-structured interviews. This study, which evaluates the impact of an ambitious urban-renewal program on health, will help to assess the effectiveness of public policy in terms of health and health inequalities

Prospective cohort study of patients with COVID-19 hospitalized in the Internal Medicine ward of Hospital Durand: study protocol

Fil: Melendi, Santiago E. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Pérez, María M. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Salas, Cintia E. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Aguirre, Camila. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Baleta, María L. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Balsano, Facundo J. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Caldano, Mariano G. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Colignon, María G. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Oliveira Brasil, Thayana De. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Wolodimeroff, Nicolás de. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Déramo Aquino, Andrea I. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Fernández de Córdova, Ana G. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Fontan, María B. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Galvagno, Florencia I. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Haedo, Mariana F. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Iturrieta Araya, Noelia S. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Mollinedo Cruz,Volga S. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Olivero, Agustín. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Pestalardo, Ignacio. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Ricciardi, María. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Saltos Navarrete, Jandry D. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Vera Rueda, María L. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Villaverde, María C. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Xavier, Franco B. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Lauko, Marcela. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Ujeda, Carlos. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Leis, Rocío. Hospital General de Agudos Carlos G. Durand; Argentina.INTRODUCCIÓN: Conocer los predictores de mala evolución en pacientes con Enfermedad por Coronavirus 2019 (COVID-19) permite identificar de forma temprana a los pacientes con peor pronóstico, aportando mejores herramientas a la hora de tomar decisiones clínicas. Se presenta el protocolo de un estudio de cohorte cuyo objetivo principal es identificar factores de riesgo de infección severa, critica y mortalidad en pacientes con COVID-19 internados en el Servicio de Clínica Médica del Hospital Durand (Buenos Aires, Argentina). MÉTODOS: Estudio de cohorte prospectivo con base en un único centro. Se incluirá a todos los pacientes que ingresen al servicio de Clínica Médica con diagnóstico de COVID-19 durante el periodo de estudio. Se recolectarán las características epidemiológicas, clínicas, de laboratorio, radiológicas y los datos de tratamiento, al ingreso y al momento del alta o muerte hospitalaria. El evento final primario es la muerte en la internación; los eventos secundarios son el desarrollo de enfermedad grave y enfermedad crítica, la internación en unidad cerrada y el requerimiento de asistencia respiratoria mecánica

Prospective cohort study of patients with COVID-19 hospitalized in the Internal Medicine ward of Hospital Durand: study protocol

Fil: Melendi, Santiago E. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Pérez, María M. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Salas, Cintia E. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Aguirre, Camila. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Baleta, María L. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Balsano, Facundo J. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Caldano, Mariano G. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Colignon, María G. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Oliveira Brasil, Thayana De. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Wolodimeroff, Nicolás de. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Déramo Aquino, Andrea I. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Fernández de Córdova, Ana G. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Fontan, María B. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Galvagno, Florencia I. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Haedo, Mariana F. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Iturrieta Araya, Noelia S. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Mollinedo Cruz,Volga S. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Olivero, Agustín. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Pestalardo, Ignacio. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Ricciardi, María. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Saltos Navarrete, Jandry D. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Vera Rueda, María L. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Villaverde, María C. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Xavier, Franco B. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Lauko, Marcela. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Ujeda, Carlos. Hospital General de Agudos Carlos G. Durand; Argentina.Fil: Leis, Rocío. Hospital General de Agudos Carlos G. Durand; Argentina.INTRODUCCIÓN: Conocer los predictores de mala evolución en pacientes con Enfermedad por Coronavirus 2019 (COVID-19) permite identificar de forma temprana a los pacientes con peor pronóstico, aportando mejores herramientas a la hora de tomar decisiones clínicas. Se presenta el protocolo de un estudio de cohorte cuyo objetivo principal es identificar factores de riesgo de infección severa, critica y mortalidad en pacientes con COVID-19 internados en el Servicio de Clínica Médica del Hospital Durand (Buenos Aires, Argentina). MÉTODOS: Estudio de cohorte prospectivo con base en un único centro. Se incluirá a todos los pacientes que ingresen al servicio de Clínica Médica con diagnóstico de COVID-19 durante el periodo de estudio. Se recolectarán las características epidemiológicas, clínicas, de laboratorio, radiológicas y los datos de tratamiento, al ingreso y al momento del alta o muerte hospitalaria. El evento final primario es la muerte en la internación; los eventos secundarios son el desarrollo de enfermedad grave y enfermedad crítica, la internación en unidad cerrada y el requerimiento de asistencia respiratoria mecánica

Global variation in postoperative mortality and complications after cancer surgery: a multicentre, prospective cohort study in 82 countries

© 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 licenseBackground: 80% of individuals with cancer will require a surgical procedure, yet little comparative data exist on early outcomes in low-income and middle-income countries (LMICs). We compared postoperative outcomes in breast, colorectal, and gastric cancer surgery in hospitals worldwide, focusing on the effect of disease stage and complications on postoperative mortality. Methods: This was a multicentre, international prospective cohort study of consecutive adult patients undergoing surgery for primary breast, colorectal, or gastric cancer requiring a skin incision done under general or neuraxial anaesthesia. The primary outcome was death or major complication within 30 days of surgery. Multilevel logistic regression determined relationships within three-level nested models of patients within hospitals and countries. Hospital-level infrastructure effects were explored with three-way mediation analyses. This study was registered with ClinicalTrials.gov, NCT03471494. Findings: Between April 1, 2018, and Jan 31, 2019, we enrolled 15 958 patients from 428 hospitals in 82 countries (high income 9106 patients, 31 countries; upper-middle income 2721 patients, 23 countries; or lower-middle income 4131 patients, 28 countries). Patients in LMICs presented with more advanced disease compared with patients in high-income countries. 30-day mortality was higher for gastric cancer in low-income or lower-middle-income countries (adjusted odds ratio 3·72, 95% CI 1·70–8·16) and for colorectal cancer in low-income or lower-middle-income countries (4·59, 2·39–8·80) and upper-middle-income countries (2·06, 1·11–3·83). No difference in 30-day mortality was seen in breast cancer. The proportion of patients who died after a major complication was greatest in low-income or lower-middle-income countries (6·15, 3·26–11·59) and upper-middle-income countries (3·89, 2·08–7·29). Postoperative death after complications was partly explained by patient factors (60%) and partly by hospital or country (40%). The absence of consistently available postoperative care facilities was associated with seven to 10 more deaths per 100 major complications in LMICs. Cancer stage alone explained little of the early variation in mortality or postoperative complications. Interpretation: Higher levels of mortality after cancer surgery in LMICs was not fully explained by later presentation of disease. The capacity to rescue patients from surgical complications is a tangible opportunity for meaningful intervention. Early death after cancer surgery might be reduced by policies focusing on strengthening perioperative care systems to detect and intervene in common complications. Funding: National Institute for Health Research Global Health Research Unit

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licenseBackground: Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide. Methods: A multimethods analysis was performed as part of the GlobalSurg 3 study—a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital. Findings: Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3·85 [95% CI 2·58–5·75]; p<0·0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63·0% vs 82·7%; OR 0·35 [0·23–0·53]; p<0·0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer. Interpretation: Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised. Funding: National Institute for Health and Care Research