Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 687
Filter
Add filters

Year range
2.
BMJ Open ; 11(4): e042042, 2021 04 07.
Article in English | MEDLINE | ID: covidwho-1172757

ABSTRACT

OBJECTIVE: To report the clinical characteristics of patients hospitalised with COVID-19 in Southeast Michigan. DESIGN: Retrospective cohort study. SETTING: Eight hospitals in Southeast Michigan. PARTICIPANTS: 3219 hospitalised patients with a positive SARS-CoV-2 infection by nasopharyngeal PCR test from 13 March 2020 until 29 April 2020. MAIN OUTCOMES MEASURES: Outcomes were discharge from the hospital or in-hospital death. Examined predictors included patient demographics, chronic diseases, home medications, mechanical ventilation, in-hospital medications and timeframe of hospital admission. Multivariable logistic regression was conducted to identify risk factors for in-hospital mortality. RESULTS: During the study period, 3219 (90.4%) patients were discharged or died in the hospital. The median age was 65.2 (IQR 52.6-77.2) years, the median length of stay in the hospital was 6.0 (IQR 3.2-10.1) days, and 51% were female. Hypertension was the most common chronic disease, occurring in 2386 (74.1%) patients. Overall mortality rate was 16.0%. Blacks represented 52.3% of patients and had a mortality rate of 13.5%. Mortality was highest at 18.5% in the prepeak hospital COVID-19 volume, decreasing to 15.3% during the peak period and to 10.8% in the postpeak period. Multivariable regression showed increasing odds of in-hospital death associated with older age (OR 1.04, 95% CI 1.03 to 1.05, p<0.001) for every increase in 1 year of age and being male (OR 1.47, 95% CI 1.21 to 1.81, p<0.001). Certain chronic diseases increased the odds of in-hospital mortality, especially chronic kidney disease. Administration of vitamin C, corticosteroids and therapeutic heparin in the hospital was associated with higher odds of death. CONCLUSION: In-hospital mortality was highest in early admissions and improved as our experience in treating patients with COVID-19 increased. Blacks were more likely to get admitted to the hospital and to receive mechanical ventilation, but less likely to die in the hospital than whites.


Subject(s)
/epidemiology , Hospital Mortality , Hospitalization/statistics & numerical data , Aged , Comorbidity , Female , Humans , Male , Michigan/epidemiology , Middle Aged , Respiration, Artificial , Retrospective Studies
3.
Neurosciences (Riyadh) ; 26(2): 158-162, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-1170592

ABSTRACT

OBJECTIVES: To assess and quantify the impact COVID-19 has had thus far on ischemic stroke admission rate and severity (National Institutes of Health Stroke Scale (NIHSS) score) at a single tertiary center in Makkah, Saudi Arabia. METHODS: This is a retrospective analysis performed on admitted cases with definitive final diagnoses of transient ischemic attack (TIA) and ischemic stroke at King Abdullah Medical City in Makkah between January 1, 2020 and July 2020. RESULTS: Sixty-nine patients were included in our study, 41 of whom presented at our facility before the pandemic and 29 during the pandemic. No statistical significance was observed between rate of admission, stroke severity, and rate of thrombolysis before the COVID-19 pandemic and after the outbreak. We observed a reduction of mean arrival time after the pandemic began, as well as a reduction of hospital stay days. CONCLUSION: A 29% reduction of admission secondary to acute ischemic stroke was noted during the pandemic. However, COVID-19 did not affect acute stroke care at our institute. The study is limited because of its small sample size, as we assessed just one medical center.


Subject(s)
Ischemic Attack, Transient/epidemiology , /epidemiology , Adult , Aged , Aged, 80 and over , Female , Hospitalization/statistics & numerical data , Humans , Intensive Care Units/statistics & numerical data , Ischemic Attack, Transient/therapy , Length of Stay/statistics & numerical data , Male , Middle Aged , Retrospective Studies , Saudi Arabia/epidemiology , Severity of Illness Index , Sex Distribution , Stroke/epidemiology , Stroke/therapy , Tertiary Care Centers , Thrombolytic Therapy/statistics & numerical data , Time-to-Treatment/statistics & numerical data , Young Adult
5.
PLoS One ; 16(3): e0248029, 2021.
Article in English | MEDLINE | ID: covidwho-1167077

ABSTRACT

Many countries have seen a two-wave pattern in reported cases of coronavirus disease-19 during the 2020 pandemic, with a first wave during spring followed by the current second wave in late summer and autumn. Empirical data show that the characteristics of the effects of the virus do vary between the two periods. Differences in age range and severity of the disease have been reported, although the comparative characteristics of the two waves still remain largely unknown. Those characteristics are compared in this study using data from two equal periods of 3 and a half months. The first period, between 15th March and 30th June, corresponding to the entire first wave, and the second, between 1st July and 15th October, corresponding to part of the second wave, still present at the time of writing this article. Two hundred and four patients were hospitalized during the first period, and 264 during the second period. Patients in the second wave were younger and the duration of hospitalization and case fatality rate were lower than those in the first wave. In the second wave, there were more children, and pregnant and post-partum women. The most frequent signs and symptoms in both waves were fever, dyspnea, pneumonia, and cough, and the most relevant comorbidities were cardiovascular diseases, type 2 diabetes mellitus, and chronic neurological diseases. Patients from the second wave more frequently presented renal and gastrointestinal symptoms, were more often treated with non-invasive mechanical ventilation and corticoids, and less often with invasive mechanical ventilation, conventional oxygen therapy and anticoagulants. Several differences in mortality risk factors were also observed. These results might help to understand the characteristics of the second wave and the behaviour and danger of SARS-CoV-2 in the Mediterranean area and in Western Europe. Further studies are needed to confirm our findings.


Subject(s)
/epidemiology , Hospitalization/statistics & numerical data , Aged , Comorbidity , Female , Humans , Male , Middle Aged , Pandemics , Spain/epidemiology , Treatment Outcome
6.
Stroke ; 52(2): 563-572, 2021 01.
Article in English | MEDLINE | ID: covidwho-1166636

ABSTRACT

BACKGROUND AND PURPOSE: The magnitude and drivers of excess cerebrovascular-specific mortality during the coronavirus disease 2019 (COVID-19) pandemic are unknown. We aim to quantify excess stroke-related deaths and characterize its association with social distancing behavior and COVID-19-related vascular pathology. METHODS: United States and state-level excess cerebrovascular deaths from January to May 2020 were quantified using National Center for Health Statistic data and Poisson regression models. Excess cerebrovascular deaths were analyzed as a function of time-varying stroke-related emergency medical service (EMS) calls and cumulative COVID-19 deaths using linear regression. A state-level regression analysis was performed to determine the association between excess cerebrovascular deaths and time spent in residences, measured by Google Community Mobility Reports, during the height of the pandemic after the first COVID-19 death (February 29). RESULTS: Forty states and New York City were included. Excess cerebrovascular mortality occurred nationally from the weeks ending March 28 to May 2, 2020, up to a 7.8% increase above expected levels during the week of April 18. Decreased stroke-related EMS calls were associated with excess stroke deaths one (70 deaths per 1000 fewer EMS calls [95% CI, 20-118]) and 2 weeks (85 deaths per 1000 fewer EMS calls [95% CI, 37-133]) later. Twenty-three states and New York City experienced excess cerebrovascular mortality during the pandemic height. A 10% increase in time spent at home was associated with a 4.3% increase in stroke deaths (incidence rate ratio, 1.043 [95% CI, 1.001-1.085]) after adjusting for COVID-19 deaths. CONCLUSIONS: Excess US cerebrovascular deaths during the COVID-19 pandemic were observed and associated with decreases in stroke-related EMS calls nationally and mobility at the state level. Public health measures are needed to identify and counter the reticence to seeking medical care for acute stroke during the COVID-19 pandemic.


Subject(s)
/epidemiology , Stroke/mortality , Stroke/virology , Emergency Medical Services/statistics & numerical data , Hospitalization/statistics & numerical data , Humans , United States
7.
BMJ ; 372: n693, 2021 03 31.
Article in English | MEDLINE | ID: covidwho-1166413

ABSTRACT

OBJECTIVE: To quantify rates of organ specific dysfunction in individuals with covid-19 after discharge from hospital compared with a matched control group from the general population. DESIGN: Retrospective cohort study. SETTING: NHS hospitals in England. PARTICIPANTS: 47 780 individuals (mean age 65, 55% men) in hospital with covid-19 and discharged alive by 31 August 2020, exactly matched to controls from a pool of about 50 million people in England for personal and clinical characteristics from 10 years of electronic health records. MAIN OUTCOME MEASURES: Rates of hospital readmission (or any admission for controls), all cause mortality, and diagnoses of respiratory, cardiovascular, metabolic, kidney, and liver diseases until 30 September 2020. Variations in rate ratios by age, sex, and ethnicity. RESULTS: Over a mean follow-up of 140 days, nearly a third of individuals who were discharged from hospital after acute covid-19 were readmitted (14 060 of 47 780) and more than 1 in 10 (5875) died after discharge, with these events occurring at rates four and eight times greater, respectively, than in the matched control group. Rates of respiratory disease (P<0.001), diabetes (P<0.001), and cardiovascular disease (P<0.001) were also significantly raised in patients with covid-19, with 770 (95% confidence interval 758 to 783), 127 (122 to 132), and 126 (121 to 131) diagnoses per 1000 person years, respectively. Rate ratios were greater for individuals aged less than 70 than for those aged 70 or older, and in ethnic minority groups compared with the white population, with the largest differences seen for respiratory disease (10.5 (95% confidence interval 9.7 to 11.4) for age less than 70 years v 4.6 (4.3 to 4.8) for age ≥70, and 11.4 (9.8 to 13.3) for non-white v 5.2 (5.0 to 5.5) for white individuals). CONCLUSIONS: Individuals discharged from hospital after covid-19 had increased rates of multiorgan dysfunction compared with the expected risk in the general population. The increase in risk was not confined to the elderly and was not uniform across ethnicities. The diagnosis, treatment, and prevention of post-covid syndrome requires integrated rather than organ or disease specific approaches, and urgent research is needed to establish the risk factors.


Subject(s)
/complications , Hospitalization/statistics & numerical data , Multiple Organ Failure/epidemiology , Patient Readmission/statistics & numerical data , Adult , Aged , /mortality , Cardiovascular Diseases/epidemiology , Case-Control Studies , Diabetes Mellitus/epidemiology , England/epidemiology , Ethnic Groups , Female , Humans , Male , Middle Aged , Patient Discharge/statistics & numerical data , Respiratory Tract Diseases/epidemiology , Retrospective Studies , Risk Factors , /isolation & purification
8.
CMAJ ; 193(12): E410-E418, 2021 03 22.
Article in English | MEDLINE | ID: covidwho-1160947

ABSTRACT

BACKGROUND: Patient characteristics, clinical care, resource use and outcomes associated with admission to hospital for coronavirus disease 2019 (COVID-19) in Canada are not well described. METHODS: We described all adults with COVID-19 or influenza discharged from inpatient medical services and medical-surgical intensive care units (ICUs) between Nov. 1, 2019, and June 30, 2020, at 7 hospitals in Toronto and Mississauga, Ontario. We compared patient outcomes using multivariable regression models, controlling for patient sociodemographic factors and comorbidity level. We validated the accuracy of 7 externally developed risk scores to predict mortality among patients with COVID-19. RESULTS: There were 1027 hospital admissions with COVID-19 (median age 65 yr, 59.1% male) and 783 with influenza (median age 68 yr, 50.8% male). Patients younger than 50 years accounted for 21.2% of all admissions for COVID-19 and 24.0% of ICU admissions. Compared with influenza, patients with COVID-19 had significantly greater in-hospital mortality (unadjusted 19.9% v. 6.1%, adjusted relative risk [RR] 3.46, 95% confidence interval [CI] 2.56-4.68), ICU use (unadjusted 26.4% v. 18.0%, adjusted RR 1.50, 95% CI 1.25-1.80) and hospital length of stay (unadjusted median 8.7 d v. 4.8 d, adjusted rate ratio 1.45, 95% CI 1.25-1.69). Thirty-day readmission was not significantly different (unadjusted 9.3% v. 9.6%, adjusted RR 0.98, 95% CI 0.70-1.39). Three points-based risk scores for predicting in-hospital mortality showed good discrimination (area under the receiver operating characteristic curve [AUC] ranging from 0.72 to 0.81) and calibration. INTERPRETATION: During the first wave of the pandemic, admission to hospital for COVID-19 was associated with significantly greater mortality, ICU use and hospital length of stay than influenza. Simple risk scores can predict in-hospital mortality in patients with COVID-19 with good accuracy.


Subject(s)
/epidemiology , Critical Care/statistics & numerical data , Hospitalization/statistics & numerical data , Influenza, Human/epidemiology , Age Factors , Aged , Aged, 80 and over , /therapy , Female , Humans , Influenza, Human/diagnosis , Influenza, Human/therapy , Male , Middle Aged , Ontario , Outcome Assessment, Health Care , Retrospective Studies , Risk Factors , Socioeconomic Factors , Survival Rate
9.
BMJ Open ; 11(3): e048391, 2021 03 30.
Article in English | MEDLINE | ID: covidwho-1159364

ABSTRACT

OBJECTIVE: To assess medium-term organ impairment in symptomatic individuals following recovery from acute SARS-CoV-2 infection. DESIGN: Baseline findings from a prospective, observational cohort study. SETTING: Community-based individuals from two UK centres between 1 April and 14 September 2020. PARTICIPANTS: Individuals ≥18 years with persistent symptoms following recovery from acute SARS-CoV-2 infection and age-matched healthy controls. INTERVENTION: Assessment of symptoms by standardised questionnaires (EQ-5D-5L, Dyspnoea-12) and organ-specific metrics by biochemical assessment and quantitative MRI. MAIN OUTCOME MEASURES: Severe post-COVID-19 syndrome defined as ongoing respiratory symptoms and/or moderate functional impairment in activities of daily living; single-organ and multiorgan impairment (heart, lungs, kidneys, liver, pancreas, spleen) by consensus definitions at baseline investigation. RESULTS: 201 individuals (mean age 45, range 21-71 years, 71% female, 88% white, 32% healthcare workers) completed the baseline assessment (median of 141 days following SARS-CoV-2 infection, IQR 110-162). The study population was at low risk of COVID-19 mortality (obesity 20%, hypertension 7%, type 2 diabetes 2%, heart disease 5%), with only 19% hospitalised with COVID-19. 42% of individuals had 10 or more symptoms and 60% had severe post-COVID-19 syndrome. Fatigue (98%), muscle aches (87%), breathlessness (88%) and headaches (83%) were most frequently reported. Mild organ impairment was present in the heart (26%), lungs (11%), kidneys (4%), liver (28%), pancreas (40%) and spleen (4%), with single-organ and multiorgan impairment in 70% and 29%, respectively. Hospitalisation was associated with older age (p=0.001), non-white ethnicity (p=0.016), increased liver volume (p<0.0001), pancreatic inflammation (p<0.01), and fat accumulation in the liver (p<0.05) and pancreas (p<0.01). Severe post-COVID-19 syndrome was associated with radiological evidence of cardiac damage (myocarditis) (p<0.05). CONCLUSIONS: In individuals at low risk of COVID-19 mortality with ongoing symptoms, 70% have impairment in one or more organs 4 months after initial COVID-19 symptoms, with implications for healthcare and public health, which have assumed low risk in young people with no comorbidities. TRIAL REGISTRATION NUMBER: NCT04369807; Pre-results.


Subject(s)
/complications , Hospitalization/statistics & numerical data , Activities of Daily Living , Adult , Aged , /physiopathology , Case-Control Studies , Community-Based Participatory Research , Diabetes Mellitus, Type 2/complications , Female , Humans , Male , Middle Aged , Prospective Studies , Severity of Illness Index
11.
J Infect Dis ; 223(6): 945-956, 2021 03 29.
Article in English | MEDLINE | ID: covidwho-1155781

ABSTRACT

BACKGROUND: The current study was performed to evaluate risk factors for severe coronavirus disease 2019 (COVID-19) outcomes among Medicare beneficiaries during the pandemic's early phase. METHODS: In a retrospective cohort study covering Medicare fee-for-service beneficiaries, we separated out elderly residents in nursing homes (NHs) and those with end-stage renal disease (ESRD) from the primary study population of individuals age ≥65 years. Outcomes included COVID-19 hospital encounters and COVID-19-associated deaths. We estimated adjusted odds ratios (ORs) using logistic regression. RESULTS: We analyzed 25 333 329 elderly non-NH beneficiaries without ESRD, 653 966 elderly NH residents, and 292 302 patients with ESRD. COVID-related death rates (per 10 000) were much higher among elderly NH residents (275.7) and patients with ESRD (60.8) than in the primary study population (5.0). Regression-adjusted clinical predictors of death among the primary population included immunocompromised status (OR, 1.43), frailty index conditions such as cognitive impairment (3.16), and other comorbid conditions, including congestive heart failure (1.30). Demographic-related risk factors included male sex (OR, 1.77), older age (3.09 for 80- vs 65-year-olds), Medicaid dual-eligibility status (2.17), and racial/ethnic minority. Compared with whites, ORs were higher for blacks (2.47), Hispanics (3.11), and Native Americans (5.82). Results for COVID-19 hospital encounters were consistent. CONCLUSIONS: Frailty, comorbid conditions, and race/ethnicity were strong risk factors for COVID-19 hospitalization and death among the US elderly.


Subject(s)
/mortality , Medicare/statistics & numerical data , Aged , Aged, 80 and over , Ethnic Groups , Female , Hospitalization/statistics & numerical data , Humans , Male , Minority Groups , Nursing Homes , Pandemics , Retrospective Studies , Risk Factors , Severity of Illness Index , United States/epidemiology
12.
J Glob Health ; 10(2): 020506, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-1154781

ABSTRACT

Background: Coronavirus disease-2019 (COVID-19), a pandemic that brought the whole world to a standstill, has led to financial and health care burden. We aimed to evaluate epidemiological characteristics, needs of resources, outcomes, and global burden of the disease. Methods: Systematic review was performed searching PubMed from December 1, 2019, to March 25, 2020, for full-text observational studies that described epidemiological characteristics, following MOOSE protocol. Global data were collected from the JHU-Corona Virus Resource Center, WHO-COVID-2019 situation reports, KFF.org, and Worldometers.info until March 31, 2020. The prevalence percentages were calculated. The global data were plotted in excel to calculate case fatality rate (CFR), predicted CFR, COVID-19 specific mortality rate, and doubling time for cases and deaths. CFR was predicted using Pearson correlation, regression models, and coefficient of determination. Results: From 21 studies of 2747 patients, 8.4% of patients died, 20.4% recovered, 15.4% were admitted to ICU and 14.9% required ventilation. COVID-19 was more prevalent in patients with hypertension (19.3%), smoking (11.3%), diabetes mellitus (10%), and cardiovascular diseases (7.4%). Common complications were pneumonia (82%), cardiac complications (26.4%), acute respiratory distress syndrome (15.7%), secondary infection (11.2%), and septic shock (4.3%). Though CFR and COVID-19 specific death rates are dynamic, they were consistently high for Italy, Spain, and Iran. Polynomial growth models were best fit for all countries for predicting CFR. Though many interventions have been implemented, stern measures like nationwide lockdown and school closure occurred after very high infection rates (>10cases per 100 000population) prevailed. Given the trend of government measures and decline of new cases in China and South Korea, most countries will reach the peak between April 1-20, if interventions are followed. Conclusions: A collective approach undertaken by a responsible government, wise strategy implementation and a receptive population may help contain the spread of COVID-19 outbreak. Close monitoring of predictive models of such indicators in the highly affected countries would help to evaluate the potential fatality if the second wave of pandemic occurs. The future studies should be focused on identifying accurate indicators to mitigate the effect of underestimation or overestimation of COVID-19 burden.


Subject(s)
Coronavirus Infections/epidemiology , Global Burden of Disease/statistics & numerical data , Hospitalization/statistics & numerical data , Models, Statistical , Pneumonia, Viral/epidemiology , Betacoronavirus , Humans , Pandemics
13.
Euro Surveill ; 26(12)2021 03.
Article in English | MEDLINE | ID: covidwho-1154192

ABSTRACT

The emergence of SARS-CoV-2 P.1 lineage coincided with a surge in hospitalisations in the North region of Brazil. In the South region's Rio Grande do Sul state, severe COVID-19 case numbers rose 3.8 fold in February 2021. During that month, at a COVID-19 referral hospital in this state, whole-genome sequencing of a subset of cases' specimens (n = 27) revealed P.1 lineage SARS-CoV-2 in most (n = 24). Findings raise concerns regarding a possible association between lineage P.1 and rapid case and hospitalisation increases.


Subject(s)
/diagnosis , /isolation & purification , Brazil/epidemiology , Hospitalization/statistics & numerical data , Humans , Whole Genome Sequencing
14.
Ann R Coll Surg Engl ; 103(3): 167-172, 2021 Mar.
Article in English | MEDLINE | ID: covidwho-1154068

ABSTRACT

INTRODUCTION: We describe a new service model, the Orthopaedic Assessment Unit (OAU), designed to provide care for trauma patients during the COVID-19 pandemic. Patients without COVID-19 symptoms and isolated musculoskeletal injuries were redirected to the OAU. METHODS: We prospectively reviewed patients throughput during the peak of the global pandemic (7 May 2020 to 7 June 2020) and compared with our historic service provision (7 May 2019 to 7 June 2019). The Mann-Whitney and Fisher Exact tests were used to test the statistical significance of data. RESULTS: A total of 1,147 patients were seen, with peak attendances between 11am and 2pm; 96% of all referrals were seen within 4h. The majority of patients were seen by orthopaedic registrars (52%) and nurse practitioners (44%). The majority of patients suffered from sprains and strains (39%), followed by fractures (22%) and wounds (20%); 73% of patients were discharged on the same day, 15% given follow up, 8% underwent surgery and 3% were admitted but did not undergo surgery. Our volume of trauma admissions and theatre cases decreased by 22% and 17%, respectively (p=0.058; 0.139). There was a significant reduction of virtual fracture clinic referrals after reconfiguration of services (p<0.001). CONCLUSIONS: Rapid implementation of a specialist OAU during a pandemic can provide early definitive trauma care while exceeding national waiting time standards. The fall in trauma attendances was lower than anticipated. The retention of orthopaedic staff in the department to staff the unit and maintain a high standard of care is imperative.


Subject(s)
Delivery of Health Care/organization & administration , Fractures, Bone/therapy , Orthopedics/organization & administration , Sprains and Strains/therapy , Adult , Aged , Ambulatory Care/statistics & numerical data , Emergency Service, Hospital , Environment Design , Female , Fractures, Bone/diagnosis , Fractures, Bone/epidemiology , Hospitalization/statistics & numerical data , Humans , Male , Middle Aged , Nurse Practitioners , Orthopedic Procedures , Orthopedic Surgeons , Scotland/epidemiology , Sprains and Strains/diagnosis , Sprains and Strains/epidemiology , Trauma Centers , Triage , Wounds and Injuries/diagnosis , Wounds and Injuries/epidemiology , Wounds and Injuries/therapy
15.
Nat Commun ; 12(1): 1904, 2021 03 26.
Article in English | MEDLINE | ID: covidwho-1152855

ABSTRACT

The spread of Coronavirus disease 19 (COVID-19) has led to many healthcare systems being overwhelmed by the rapid emergence of new cases. Here, we study the ramifications of hospital load due to COVID-19 morbidity on in-hospital mortality of patients with COVID-19 by analyzing records of all 22,636 COVID-19 patients hospitalized in Israel from mid-July 2020 to mid-January 2021. We show that even under moderately heavy patient load (>500 countrywide hospitalized severely-ill patients; the Israeli Ministry of Health defined 800 severely-ill patients as the maximum capacity allowing adequate treatment), in-hospital mortality rate of patients with COVID-19 significantly increased compared to periods of lower patient load (250-500 severely-ill patients): 14-day mortality rates were 22.1% (Standard Error 3.1%) higher (mid-September to mid-October) and 27.2% (Standard Error 3.3%) higher (mid-December to mid-January). We further show this higher mortality rate cannot be attributed to changes in the patient population during periods of heavier load.


Subject(s)
/prevention & control , Hospital Mortality/trends , Hospitals/statistics & numerical data , /isolation & purification , Adult , Aged , Aged, 80 and over , /virology , Epidemics , Female , Hospitalization/statistics & numerical data , Humans , Israel/epidemiology , Male , Middle Aged , Monte Carlo Method , /physiology
17.
Cochrane Database Syst Rev ; 3: CD013879, 2021 03 11.
Article in English | MEDLINE | ID: covidwho-1151840

ABSTRACT

BACKGROUND: A small minority of people with coronavirus disease 2019 (COVID-19) develop a severe illness, characterised by inflammation, microvascular damage and coagulopathy, potentially leading to myocardial injury, venous thromboembolism (VTE) and arterial occlusive events. People with risk factors for or pre-existing cardiovascular disease may be at greater risk. OBJECTIVES: To assess the prevalence of pre-existing cardiovascular comorbidities associated with suspected or confirmed cases of COVID-19 in a variety of settings, including the community, care homes and hospitals. We also assessed the nature and rate of subsequent cardiovascular complications and clinical events in people with suspected or confirmed COVID-19. SEARCH METHODS: We conducted an electronic search from December 2019 to 24 July 2020 in the following databases: the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, covid-19.cochrane.org, ClinicalTrials.gov and EU Clinical Trial Register. SELECTION CRITERIA: We included prospective and retrospective cohort studies, controlled before-and-after, case-control and cross-sectional studies, and randomised controlled trials (RCTs). We analysed controlled trials as cohorts, disregarding treatment allocation. We only included peer-reviewed studies with 100 or more participants, and excluded articles not written in English or only published in pre-print servers. DATA COLLECTION AND ANALYSIS: Two review authors independently screened the search results and extracted data. Given substantial variation in study designs, reported outcomes and outcome metrics, we undertook a narrative synthesis of data, without conducting a meta-analysis. We critically appraised all included studies using the Joanna Briggs Institute (JBI) checklist for prevalence studies and the JBI checklist for case series. MAIN RESULTS: We included 220 studies. Most of the studies originated from China (47.7%) or the USA (20.9%); 9.5% were from Italy. A large proportion of the studies were retrospective (89.5%), but three (1.4%) were RCTs and 20 (9.1%) were prospective. Using JBI's critical appraisal checklist tool for prevalence studies, 75 studies attained a full score of 9, 57 studies a score of 8, 31 studies a score of 7, 5 studies a score of 6, three studies a score of 5 and one a score of 3; using JBI's checklist tool for case series, 30 studies received a full score of 10, six studies a score of 9, 11 studies a score of 8, and one study a score of 5 We found that hypertension (189 studies, n = 174,414, weighted mean prevalence (WMP): 36.1%), diabetes (197 studies, n = 569,188, WMP: 22.1%) and ischaemic heart disease (94 studies, n = 100,765, WMP: 10.5%)  are highly prevalent in people hospitalised with COVID-19, and are associated with an increased risk of death. In those admitted to hospital, biomarkers of cardiac stress or injury are often abnormal, and the incidence of a wide range of cardiovascular complications is substantial, particularly arrhythmias (22 studies, n = 13,115, weighted mean incidence (WMI) 9.3%), heart failure (20 studies, n = 29,317, WMI: 6.8%) and thrombotic complications (VTE: 16 studies, n = 7700, WMI: 7.4%). AUTHORS' CONCLUSIONS: This systematic literature review indicates that cardiometabolic comorbidities are common in people who are hospitalised with a COVID-19 infection, and cardiovascular complications are frequent. We plan to update this review and to conduct a formal meta-analysis of outcomes based on a more homogeneous selected subsample of high-certainty studies.


Subject(s)
/epidemiology , Cardiovascular Diseases/epidemiology , Arrhythmias, Cardiac/epidemiology , Comorbidity , Diabetes Mellitus/epidemiology , Heart Failure/epidemiology , Hospitalization/statistics & numerical data , Humans , Hypertension/epidemiology , Incidence , Myocardial Ischemia/epidemiology , Obesity/epidemiology , Prevalence , Thrombosis/epidemiology
18.
PLoS One ; 16(3): e0248498, 2021.
Article in English | MEDLINE | ID: covidwho-1150543

ABSTRACT

We report onset, course, correlations with comorbidities, and diagnostic accuracy of nasopharyngeal swab in 539 individuals suspected to carry SARS-COV-2 admitted to the hospital of Crema, Italy. All individuals underwent clinical and laboratory exams, SARS-COV-2 reverse transcriptase-polymerase chain reaction on nasopharyngeal swab, and chest X-ray and/or computed tomography (CT). Data on onset, course, comorbidities, number of drugs including angiotensin converting enzyme (ACE) inhibitors and angiotensin-II-receptor antagonists (sartans), follow-up swab, pharmacological treatments, non-invasive respiratory support, ICU admission, and deaths were recorded. Among 411 SARS-COV-2 patients (67.7% males) median age was 70.8 years (range 5-99). Chest CT was performed in 317 (77.2%) and showed interstitial pneumonia in 304 (96%). Fatality rate was 17.5% (74% males), with 6.6% in 60-69 years old, 21.1% in 70-79 years old, 38.8% in 80-89 years old, and 83.3% above 90 years. No death occurred below 60 years. Non-invasive respiratory support rate was 27.2% and ICU admission 6.8%. Charlson comorbidity index and high C-reactive protein at admission were significantly associated with death. Use of ACE inhibitors or sartans was not associated with outcomes. Among 128 swab negative patients at admission (63.3% males) median age was 67.7 years (range 1-98). Chest CT was performed in 87 (68%) and showed interstitial pneumonia in 76 (87.3%). Follow-up swab turned positive in 13 of 32 patients. Using chest CT at admission as gold standard on the entire study population of 539 patients, nasopharyngeal swab had 80% accuracy. Comorbidity network analysis revealed a more homogenous distribution 60-40 aged SARS-COV-2 patients across diseases and a crucial different interplay of diseases in the networks of deceased and survived patients. SARS-CoV-2 caused high mortality among patients older than 60 years and correlated with pre-existing multiorgan impairment.


Subject(s)
/pathology , Comorbidity , Adolescent , Adult , Aged , Aged, 80 and over , Angiotensin-Converting Enzyme Inhibitors/therapeutic use , C-Reactive Protein/analysis , /mortality , Child , Child, Preschool , Female , Hospitalization/statistics & numerical data , Humans , Italy , Male , Middle Aged , Risk Factors , Treatment Outcome , Young Adult
19.
J Public Health Manag Pract ; 27(3): 295-298, 2021.
Article in English | MEDLINE | ID: covidwho-1150047

ABSTRACT

OBJECTIVE: To assess whether county age distribution is associated with age-specific COVID-19 infection, emergency department, hospitalization, and mortality rates. DESIGN: Florida's 2020 COVID-19 cases are summarized into age-specific county rates and supplemented with socioeconomic and demographic characteristics and 2020 presidential voting results to assess the association of population age structure and political choices with age-specific COVID-19 infection, emergency, hospitalization, and mortality rates. RESULTS: Younger counties experienced higher under-25 infection rates, as well as higher over-64 infection, emergency, and hospitalization rates. Older counties experienced reduced infection rates for all ages and decreased over-64 emergency and hospitalization rates. Trump's vote share was associated with higher infection rates for all and higher over-64 emergency, hospitalization, and mortality rates. CONCLUSIONS: Younger counties experience higher COVID-19 infection rates for all residents, with elevated morbidity risks among seniors. Older counties had lower COVID-19 infection, emergency, and hospitalization rates. Age-specific messaging may help slow pandemic spread.


Subject(s)
/mortality , Cause of Death , Hospitalization/statistics & numerical data , Pandemics/statistics & numerical data , Politics , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , Female , Florida/epidemiology , Humans , Male , Middle Aged , Socioeconomic Factors , Young Adult
20.
Medicine (Baltimore) ; 100(12): e25083, 2021 Mar 26.
Article in English | MEDLINE | ID: covidwho-1150005

ABSTRACT

ABSTRACT: The purpose of this study was to investigate the predictive value of combined clinical and imaging features, compared with the clinical or radiological risk factors only. Moreover, the expected results aimed to improve the identification of severe acute respiratory syndrome coronavirus-2 (SARS-COV-2) patients who may have critical outcomes.This retrospective study included laboratory-confirmed SARS-COV-2 cases between January 18, 2020, and February 16, 2020. The patients were divided into 2 groups with noncritical illness and critical illness regarding severity status within the hospitalization. Univariable and multivariable logistic regression models were used to explore the risk factors associated with clinical and radiological outcomes in patients with SARS-COV-2. The ROC curves were performed to compare the prediction performance of different factors.A total of 180 adult patients in this study included 20 critical patients and 160 noncritical patients. In univariate logistic regression analysis, 15 risk factors were significantly associated with critical outcomes. Of importance, C-reactive protein (1.051, 95% confidence interval 1.024-1.078), D-dimer (1.911, 95% CI, 1.050-3.478), and CT score (1.29, 95% CI, 1.053-1.529) on admission were independent risk factors in multivariate analysis. The combined model achieved a better performance in disease severity prediction (P = .05).CRP, D-dimer, and CT score on admission were independent risk factors for critical illness in adults with SARS-COV-2. The combined clinical and radiological model achieved better predictive performance than clinical or radiological factors alone.


Subject(s)
/epidemiology , Diagnostic Techniques and Procedures/statistics & numerical data , Adult , Aged , C-Reactive Protein/analysis , Female , Fibrin Fibrinogen Degradation Products/analysis , Hospitalization/statistics & numerical data , Humans , Male , Middle Aged , ROC Curve , Retrospective Studies , Risk Factors , Severity of Illness Index , Tomography, X-Ray Computed
SELECTION OF CITATIONS
SEARCH DETAIL