Your browser doesn't support javascript.
Mostrar: 20 | 50 | 100
Resultados 1 - 3 de 3
Filtrar
Adicionar filtros

Base de dados
Tipo de documento
Intervalo de ano
1.
Sarah Wulf Hanson; Cristiana Abbafati; Joachim G Aerts; Ziyad Al-Aly; Charlie Ashbaugh; Tala Ballouz; Oleg Blyuss; Polina Bobkova; Gouke Bonsel; Svetlana Borzakova; Danilo Buonsenso; Denis Butnaru; Austin Carter; Helen Chu; Cristina De Rose; Mohamed Mustafa Diab; Emil Ekbom; Maha El Tantawi; Victor Fomin; Robert Frithiof; Aysylu Gamirova; Petr V Glybochko; Juanita A. Haagsma; Shaghayegh Haghjooy Javanmard; Erin B Hamilton; Gabrielle Harris; Majanka H Heijenbrok-Kal; Raimund Helbok; Merel E Hellemons; David Hillus; Susanne M Huijts; Michael Hultstrom; Waasila Jassat; Florian Kurth; Ing-Marie Larsson; Miklos Lipcsey; Chelsea Liu; Callan D Loflin; Andrei Malinovschi; Wenhui Mao; Lyudmila Mazankova; Denise McCulloch; Dominik Menges; Noushin Mohammadifard; Daniel Munblit; Nikita A Nekliudov; Osondu Ogbuoji; Ismail M Osmanov; Jose L. Penalvo; Maria Skaalum Petersen; Milo A Puhan; Mujibur Rahman; Verena Rass; Nickolas Reinig; Gerard M Ribbers; Antonia Ricchiuto; Sten Rubertsson; Elmira Samitova; Nizal Sarrafzadegan; Anastasia Shikhaleva; Kyle E Simpson; Dario Sinatti; Joan B Soriano; Ekaterina Spiridonova; Fridolin Steinbeis; Andrey A Svistunov; Piero Valentini; Brittney J van de Water; Rita van den Berg-Emons; Ewa Wallin; Martin Witzenrath; Yifan Wu; Hanzhang Xu; Thomas Zoller; Christopher Adolph; James Albright; Joanne O Amlag; Aleksandr Y Aravkin; Bree L Bang-Jensen; Catherine Bisignano; Rachel Castellano; Emma Castro; Suman Chakrabarti; James K Collins; Xiaochen Dai; Farah Daoud; Carolyn Dapper; Amanda Deen; Bruce B Duncan; Megan Erickson; Samuel B Ewald; Alize J Ferrari; Abraham D. Flaxman; Nancy Fullman; Amiran Gamkrelidze; John R Giles; Gaorui Guo; Simon I Hay; Jiawei He; Monika Helak; Erin N Hulland; Maia Kereselidze; Kris J Krohn; Alice Lazzar-Atwood; Akiaja Lindstrom; Rafael Lozano; Beatrice Magistro; Deborah Carvalho Malta; Johan Mansson; Ana M Mantilla Herrera; Ali H Mokdad; Lorenzo Monasta; Shuhei Nomura; Maja Pasovic; David M Pigott; Robert C Reiner Jr.; Grace Reinke; Antonio Luiz P Ribeiro; Damian Francesco Santomauro; Aleksei Sholokhov; Emma Elizabeth Spurlock; Rebecca Walcott; Ally Walker; Charles Shey Wiysonge; Peng Zheng; Janet Prvu Bettger; Christopher JL Murray; Theo Vos.
medrxiv; 2022.
Preprint em Inglês | medRxiv | ID: ppzbmed-10.1101.2022.05.26.22275532

RESUMO

ImportanceWhile much of the attention on the COVID-19 pandemic was directed at the daily counts of cases and those with serious disease overwhelming health services, increasingly, reports have appeared of people who experience debilitating symptoms after the initial infection. This is popularly known as long COVID. ObjectiveTo estimate by country and territory of the number of patients affected by long COVID in 2020 and 2021, the severity of their symptoms and expected pattern of recovery DesignWe jointly analyzed ten ongoing cohort studies in ten countries for the occurrence of three major symptom clusters of long COVID among representative COVID cases. The defining symptoms of the three clusters (fatigue, cognitive problems, and shortness of breath) are explicitly mentioned in the WHO clinical case definition. For incidence of long COVID, we adopted the minimum duration after infection of three months from the WHO case definition. We pooled data from the contributing studies, two large medical record databases in the United States, and findings from 44 published studies using a Bayesian meta-regression tool. We separately estimated occurrence and pattern of recovery in patients with milder acute infections and those hospitalized. We estimated the incidence and prevalence of long COVID globally and by country in 2020 and 2021 as well as the severity-weighted prevalence using disability weights from the Global Burden of Disease study. ResultsAnalyses are based on detailed information for 1906 community infections and 10526 hospitalized patients from the ten collaborating cohorts, three of which included children. We added published data on 37262 community infections and 9540 hospitalized patients as well as ICD-coded medical record data concerning 1.3 million infections. Globally, in 2020 and 2021, 144.7 million (95% uncertainty interval [UI] 54.8-312.9) people suffered from any of the three symptom clusters of long COVID. This corresponds to 3.69% (1.38-7.96) of all infections. The fatigue, respiratory, and cognitive clusters occurred in 51.0% (16.9-92.4), 60.4% (18.9-89.1), and 35.4% (9.4-75.1) of long COVID cases, respectively. Those with milder acute COVID-19 cases had a quicker estimated recovery (median duration 3.99 months [IQR 3.84-4.20]) than those admitted for the acute infection (median duration 8.84 months [IQR 8.10-9.78]). At twelve months, 15.1% (10.3-21.1) continued to experience long COVID symptoms. Conclusions and relevanceThe occurrence of debilitating ongoing symptoms of COVID-19 is common. Knowing how many people are affected, and for how long, is important to plan for rehabilitative services and support to return to social activities, places of learning, and the workplace when symptoms start to wane. Key PointsO_ST_ABSQuestionC_ST_ABSWhat are the extent and nature of the most common long COVID symptoms by country in 2020 and 2021? FindingsGlobally, 144.7 million people experienced one or more of three symptom clusters (fatigue; cognitive problems; and ongoing respiratory problems) of long COVID three months after infection, in 2020 and 2021. Most cases arose from milder infections. At 12 months after infection, 15.1% of these cases had not yet recovered. MeaningThe substantial number of people with long COVID are in need of rehabilitative care and support to transition back into the workplace or education when symptoms start to wane.


Assuntos
Doença Aguda , Dispneia , COVID-19 , Fadiga , Transtornos Cognitivos , Doença
2.
medrxiv; 2021.
Preprint em Inglês | medRxiv | ID: ppzbmed-10.1101.2021.08.31.21262923

RESUMO

BackgroundThe COVID-19 pandemic has led to over 600,000 deaths in the United States and continues to disrupt lives even as effective vaccines are available. We aimed to estimate the impact and health system cost of implementing post-exposure prophylaxis against household exposure to COVID-19 with monoclonal antibodies. MethodsWe developed a decision-analytical model analysis of results from a recent randomized controlled trial with complementary data on household demographic structure, vaccine coverage, and COVID-19 confirmed case counts for the representative month of May, 2021. The model population includes individuals of all ages in the United States by sex and race/ethnicity. ResultsIn a month of similar intensity to May, 2021, in the USA, a monoclonal antibody post-exposure prophylaxis program reaching 50% of exposed unvaccinated household members aged 50+, would avert 1,813 (1,171 - 2,456) symptomatic infections, 526 (343 - 716) hospitalizations, and 83 (56 - 116) deaths. Assuming the unit cost of administering the intervention was US$ 1,264, this program would save the health system US$ 3,055,202 (-14,034,632 - 18,787,692). ConclusionsCurrently in the United States, health system and public health actors have an opportunity to improve health and reduce costs through COVID-19 post-exposure prophylaxis with monoclonal antibodies.


Assuntos
COVID-19
3.
medrxiv; 2020.
Preprint em Inglês | medRxiv | ID: ppzbmed-10.1101.2020.06.09.20126508

RESUMO

Introduction Tracking the COVID-19 pandemic using existing metrics such as confirmed cases and deaths are insufficient for understanding the trajectory of the pandemic and identifying the next wave of cases. In this study, we demonstrate the utility of monitoring the daily number of patients with COVID-like illness (CLI) who present to the Emergency Department (ED) as a tool that can guide local response efforts. Methods Using data from two hospitals in King County, WA, we examined the daily volume of CLI visits, and compare them to confirmed COVID cases and COVID deaths in the County. A linear regression model with varying lags is used to predict the number of daily COVID deaths from the number of CLI visits. Results CLI visits appear to rise and peak well in advance of both confirmed COVID cases and deaths in King County. Our regression analysis to predict daily deaths with a lagged count of CLI visits in the ED showed that the R2 value was maximized at 14 days. Conclusions ED CLI visits are a leading indicator of the pandemic. Adopting and scaling up a CLI monitoring approach at the local level will provide needed actionable evidence to policy makers and health officials struggling to confront this health challenge.


Assuntos
COVID-19 , Morte
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA