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2.
MMWR Morb Mortal Wkly Rep ; 70(14): 519-522, 2021 Apr 09.
Article in English | MEDLINE | ID: covidwho-1173072

ABSTRACT

CDC's National Vital Statistics System (NVSS) collects and reports annual mortality statistics using data from U.S. death certificates. Because of the time needed to investigate certain causes of death and to process and review data, final annual mortality data for a given year are typically released 11 months after the end of the calendar year. Daily totals reported by CDC COVID-19 case surveillance are timely but can underestimate numbers of deaths because of incomplete or delayed reporting. As a result of improvements in timeliness and the pressing need for updated, quality data during the global COVID-19 pandemic, NVSS expanded provisional data releases to produce near real-time U.S. mortality data.* This report presents an overview of provisional U.S. mortality data for 2020, including the first ranking of leading causes of death. In 2020, approximately 3,358,814 deaths† occurred in the United States. From 2019 to 2020, the estimated age-adjusted death rate increased by 15.9%, from 715.2 to 828.7 deaths per 100,000 population. COVID-19 was reported as the underlying cause of death or a contributing cause of death for an estimated 377,883 (11.3%) of those deaths (91.5 deaths per 100,000). The highest age-adjusted death rates by age, race/ethnicity, and sex occurred among adults aged ≥85 years, non-Hispanic Black or African American (Black) and non-Hispanic American Indian or Alaska Native (AI/AN) persons, and males. COVID-19 death rates were highest among adults aged ≥85 years, AI/AN and Hispanic persons, and males. COVID-19 was the third leading cause of death in 2020, after heart disease and cancer. Provisional death estimates provide an early indication of shifts in mortality trends and can guide public health policies and interventions aimed at reducing numbers of deaths that are directly or indirectly associated with the COVID-19 pandemic.


Subject(s)
/mortality , Mortality/trends , Adolescent , Adult , Aged , Aged, 80 and over , Cause of Death/trends , Child , Child, Preschool , Continental Population Groups/statistics & numerical data , Ethnic Groups/statistics & numerical data , Female , Health Status Disparities , Humans , Infant , Male , Middle Aged , Mortality/ethnology , United States/epidemiology , Vital Statistics , Young Adult
3.
MMWR Morb Mortal Wkly Rep ; 70(14): 510-513, 2021 Apr 09.
Article in English | MEDLINE | ID: covidwho-1173069

ABSTRACT

Geographic differences in infectious disease mortality rates have been observed among American Indian or Alaska Native (AI/AN) persons in the United States (1), and aggregate analyses of data from selected U.S. states indicate that COVID-19 incidence and mortality are higher among AI/AN persons than they are among White persons (2,3). State-level data could be used to identify disparities and guide local efforts to reduce COVID-19-associated incidence and mortality; however, such data are limited. Reports of laboratory-confirmed COVID-19 cases and COVID-19-associated deaths reported to the Montana Department of Public Health and Human Services (MDPHHS) were analyzed to describe COVID-19 incidence, mortality, and case-fatality rates among AI/AN persons compared with those among White persons. During March-November 2020 in Montana, the estimated cumulative COVID-19 incidence among AI/AN persons (9,064 cases per 100,000) was 2.2 times that among White persons (4,033 cases per 100,000).* During the same period, the cumulative COVID-19 mortality rate among AI/AN persons (267 deaths per 100,000) was 3.8 times that among White persons (71 deaths per 100,000). The AI/AN COVID-19 case-fatality rate (29.4 deaths per 1,000 COVID-19 cases) was 1.7 times the rate in White persons (17.0 deaths per 1,000). State-level surveillance findings can help in developing state and tribal COVID-19 vaccine allocation strategies and assist in local implementation of culturally appropriate public health measures that might help reduce COVID-19 incidence and mortality in AI/AN communities.


Subject(s)
/statistics & numerical data , /ethnology , European Continental Ancestry Group/statistics & numerical data , Health Status Disparities , Adult , Aged , Aged, 80 and over , Female , Humans , Incidence , Male , Middle Aged , Montana/epidemiology , Mortality/ethnology , Young Adult
4.
Diabetes Obes Metab ; 23(4): 886-896, 2021 04.
Article in English | MEDLINE | ID: covidwho-1171152

ABSTRACT

AIMS: Coronavirus disease 2019 (COVID-19) is caused by a novel severe acute respiratory syndrome coronavirus 2. It can lead to multiorgan failure, including respiratory and cardiovascular decompensation, and kidney injury, with significant associated morbidity and mortality, particularly in patients with underlying metabolic, cardiovascular, respiratory or kidney disease. Dapagliflozin, a sodium-glucose cotransporter-2 inhibitor, has shown significant cardio- and renoprotective benefits in patients with type 2 diabetes (with and without atherosclerotic cardiovascular disease), heart failure and chronic kidney disease, and may provide similar organ protection in high-risk patients with COVID-19. MATERIALS AND METHODS: DARE-19 (NCT04350593) is an investigator-initiated, collaborative, international, multicentre, randomized, double-blind, placebo-controlled study testing the dual hypotheses that dapagliflozin can reduce the incidence of cardiovascular, kidney and/or respiratory complications or all-cause mortality, or improve clinical recovery, in adult patients hospitalized with COVID-19 but not critically ill on admission. Eligible patients will have ≥1 cardiometabolic risk factor for COVID-19 complications. Patients will be randomized 1:1 to dapagliflozin 10 mg or placebo. Primary efficacy endpoints are time to development of new or worsened organ dysfunction during index hospitalization, or all-cause mortality, and the hierarchical composite endpoint of change in clinical status through day 30 of treatment. Safety of dapagliflozin in individuals with COVID-19 will be assessed. CONCLUSIONS: DARE-19 will evaluate whether dapagliflozin can prevent COVID-19-related complications and all-cause mortality, or improve clinical recovery, and assess the safety profile of dapagliflozin in this patient population. Currently, DARE-19 is the first large randomized controlled trial investigating use of sodium-glucose cotransporter 2 inhibitors in patients with COVID-19.


Subject(s)
Benzhydryl Compounds/therapeutic use , Cardiovascular Diseases/prevention & control , Glucosides/therapeutic use , Kidney Diseases/prevention & control , Mortality , Respiratory Insufficiency/drug therapy , Sodium-Glucose Transporter 2 Inhibitors/therapeutic use , Atherosclerosis/epidemiology , /epidemiology , Cardiovascular Diseases/etiology , Cause of Death , Comorbidity , Diabetes Mellitus, Type 2/epidemiology , Disease Progression , Double-Blind Method , Heart Failure/epidemiology , Humans , Hypertension/epidemiology , Kidney Diseases/etiology , Multicenter Studies as Topic , Randomized Controlled Trials as Topic , Renal Insufficiency, Chronic/epidemiology , Respiratory Insufficiency/etiology , Treatment Outcome
5.
Rev Panam Salud Publica ; 45, mar. 2021
Article | PAHOIRIS | ID: covidwho-1168410

ABSTRACT

[RESUMEN]. Objetivos. Describir la difusión espacio-temporal de las muertes por COVID-19, y analizar sus desigualdades socio-espaciales en la Argentina. Métodos. Se analizaron las muertes por COVID-19 ocurridas en Argentina al 17 de octubre de 2020 utilizando datos referidos al día, mes y año, y el lugar de residencia. Se utilizó la técnica de escaneo espacio-temporal por permutaciones para detectar la presencia de conglomerados espacio-temporales. Se compararon el nivel de pobreza, densidad poblacional y porcentaje de población adulta mayor entre las áreas pertenecientes a conglomerados de mortalidad alta y las áreas pertenecientes a conglomerados de mortalidad baja. Resultados. Se detectaron cinco conglomerados de mortalidad alta entre el 21 de marzo y el 27 de agosto en el Aglomerado Gran Buenos Aires (AGBA) y noreste de la provincia de Buenos Aires. Los conglomerados de mortalidad baja se localizaron en la periferia del AGBA, desde mediados de septiembre a mediados de octubre, y en el centro y noroeste de la Argentina, entre fines de abril y fines de agosto. Los conglomerados de mortalidad alta se localizaron en áreas con mayor densidad poblacional y mayor porcentaje de población adulta mayor en comparación a los conglomerados de mortalidad baja. Conclusiones. No se detectaron conglomerados de mortalidad alta entre septiembre y mediados de octubre. Tampoco hemos detectado una difusión espacial de muertes hacia áreas de nivel socioeconómico bajo a nivel nacional. Nuestros resultados apoyan el modelo de difusión de la mortalidad en una primera fase, que afecta a la principal área urbana de la Argentina.


[ABSTRACT]. Objectives. Describe the space-time spread of COVID-19 deaths and analyze its socio-spatial inequalities in Argentina. Methods. COVID-19 deaths in Argentina as of October 17, 2020 were analyzed using data on day, month, and year, and place of residence. The space-time permutation scan method was used to detect the presence of space-time clusters. Poverty levels, population densities, and percentage of older adults in the population were compared for areas in high-mortality clusters and low-mortality clusters. Results. Five high-mortality clusters were detected between March 21 and August 27 in the Greater Buenos Aires conurbation and the northeast of the province of Buenos Aires. Low-mortality clusters were located on the periphery of the urban area from mid-September to mid-October and in central and northwestern Argentina between late April and late August. High-mortality clusters were located in areas with higher population densities and higher percentages of older adults in population, compared to low-mortality clusters. Conclusions. No high-mortality clusters were detected between September and mid-October. Nor have we detected a spatial spread of deaths to areas of low socioeconomic status at the national level. Our results support the first phase of the mortality spread model, affecting the largest urban area in Argentina.


[RESUMO]. Objetivo. Descrever a distribuição espaço-temporal de mortes por COVID-19 e analisar desigualdades socioespaciais na Argentina. Métodos. As mortes por COVID-19 ocorridas na Argentina até 17 de outubro de 2020 foram analisadas a partir de dados referentes ao dia, mês e ano e local de residência. A estatística scan utilizando modelo de permutação espaço-tempo foi aplicada para detectar conglomerados espaço-temporais. Realizou-se a comparação do nível de pobreza, densidade populacional e percentual de população idosa entre as áreas pertencentes aos conglomerados com alta mortalidade e as áreas pertencentes aos conglomerados com baixa mortalidade. Resultados. Cinco conglomerados com alta mortalidade foram detectados entre 21 de março e 27 de agosto na região da Grande Buenos Aires e no nordeste da província de Buenos Aires. Os conglomerados com baixa mortalidade estavam localizados na periferia da região da Grande Buenos Aires, de meados de setembro a meados de outubro, e nas regiões central e noroeste do país, entre o final de abril e final de agosto. Os conglomerados com alta mortalidade estavam localizados em áreas de maior densidade populacional e maior percentual de população idosa em comparação aos conglomerados com baixa mortalidade. Conclusão. Não foram detectados conglomerados com alta mortalidade entre setembro e meados de outubro. Também não se observou a distribuição espacial de mortes em áreas com baixo nível socioeconômico em todo o país. Os resultados deste estudo respaldam o modelo de distribuição de mortes na primeira fase, atingindo a principal área urbana da Argentina.


Subject(s)
Spatio-Temporal Analysis , Space-Time Clustering , Coronavirus Infections , Betacoronavirus , Coronavirus , Coronavirus Infections , Mortality , Argentina , Spatio-Temporal Analysis , Space-Time Clustering , Coronavirus Infections , Mortality , Spatio-Temporal Analysis , Space-Time Clustering , Coronavirus Infections , Mortality
6.
RMD Open ; 7(1)2021 03.
Article in English | MEDLINE | ID: covidwho-1166567

ABSTRACT

BACKGROUND: The CHIC study (COVID-19 High-intensity Immunosuppression in Cytokine storm syndrome) is a quasi-experimental treatment study exploring immunosuppressive treatment versus supportive treatment only in patients with COVID-19 with life-threatening hyperinflammation. Causal inference provides a means of investigating causality in non-randomised experiments. Here we report 14-day improvement as well as 30-day and 90-day mortality. PATIENTS AND METHODS: The first 86 patients (period 1) received optimal supportive care only; the second 86 patients (period 2) received methylprednisolone and (if necessary) tocilizumab, in addition to optimal supportive care. The main outcomes were 14-day clinical improvement and 30-day and 90-day survival. An 80% decline in C reactive protein (CRP) was recorded on or before day 13 (CRP >100 mg/L was an inclusion criterion). Non-linear mediation analysis was performed to decompose CRP-mediated effects of immunosuppression (defined as natural indirect effects) and non-CRP-mediated effects attributable to natural prognostic differences between periods (defined as natural direct effects). RESULTS: The natural direct (non-CRP-mediated) effects for period 2 versus period 1 showed an OR of 1.38 (38% better) for 14-day improvement and an OR of 1.16 (16% better) for 30-day and 90-day survival. The natural indirect (CRP-mediated) effects for period 2 showed an OR of 2.27 (127% better) for 14-day improvement, an OR of 1.60 (60% better) for 30-day survival and an OR of 1.49 (49% better) for 90-day survival. The number needed to treat was 5 for 14-day improvement, 9 for survival on day 30, and 10 for survival on day 90. CONCLUSION: Causal inference with non-linear mediation analysis further substantiates the claim that a brief but intensive treatment with immunosuppressants in patients with COVID-19 and systemic hyperinflammation adds to rapid recovery and saves lives. Causal inference is an alternative to conventional trial analysis, when randomised controlled trials are considered unethical, unfeasible or impracticable.


Subject(s)
Antibodies, Monoclonal, Humanized/therapeutic use , C-Reactive Protein/immunology , Cytokine Release Syndrome/drug therapy , Glucocorticoids/therapeutic use , Immunosuppressive Agents/therapeutic use , Methylprednisolone/therapeutic use , /immunology , Causality , Cytokine Release Syndrome/immunology , Historically Controlled Study , Humans , Inflammation/immunology , Mortality , Survival Rate , Treatment Outcome
7.
J Transl Med ; 19(1): 128, 2021 03 29.
Article in English | MEDLINE | ID: covidwho-1158209

ABSTRACT

BACKGROUND: Omega-3 polyunsaturated fatty acids (n3-PUFAs) may exert beneficial effects on the immune system of patients with viral infections. This paper aimed to examine the effect of n3-PUFA supplementation on inflammatory and biochemical markers in critically ill patients with COVID-19. METHODS: A double-blind, randomized clinical trial study was conducted on 128 critically ill patients infected with COVID-19 who were randomly assigned to the intervention (fortified formula with n3-PUFA) (n = 42) and control (n = 86) groups. Data on 1 month survival rate, blood glucose, sodium (Na), potassium (K), blood urea nitrogen (BUN), creatinine (Cr), albumin, hematocrit (HCT), calcium (Ca), phosphorus (P), mean arterial pressure (MAP), O2 saturation (O2sat), arterial pH, partial pressure of oxygen (PO2), partial pressure of carbon dioxide (PCO2), bicarbonate (HCO3), base excess (Be), white blood cells (WBCs), Glasgow Coma Scale (GCS), hemoglobin (Hb), platelet (Plt), and the partial thromboplastin time (PTT) were collected at baseline and after 14 days of the intervention. RESULTS: The intervention group had significantly higher 1-month survival rate and higher levels of arterial pH, HCO3, and Be and lower levels of BUN, Cr, and K compared with the control group after intervention (all P < 0.05). There were no significant differences between blood glucose, Na, HCT, Ca, P, MAP, O2sat, PO2, PCO2, WBCs, GCS, Hb, Plt, PTT, and albumin between two groups. CONCLUSION: Omega-3 supplementation improved the levels of several parameters of respiratory and renal function in critically ill patients with COVID-19. Further clinical studies are warranted. Trial registry Name of the registry: This study was registered in the Iranian Registry of Clinical Trials (IRCT); Trial registration number: IRCT20151226025699N3; Date of registration: 2020.5.20; URL of trial registry record: https://en.irct.ir/trial/48213.


Subject(s)
/diet therapy , Critical Illness/therapy , Fatty Acids, Omega-3/pharmacology , Adult , Aged , Aged, 80 and over , Biomarkers/analysis , Biomarkers/blood , Blood Gas Analysis , Blood Glucose/drug effects , Blood Glucose/metabolism , /physiopathology , Critical Illness/mortality , Dietary Supplements , Double-Blind Method , Fatty Acids, Omega-3/administration & dosage , Female , Hematocrit , Humans , Inflammation Mediators/analysis , Inflammation Mediators/blood , Iran/epidemiology , Kidney/drug effects , Kidney/physiopathology , Kidney/virology , Male , Middle Aged , Mortality , Prognosis , Respiratory System/drug effects , Respiratory System/physiopathology , Respiratory System/virology , Survival Analysis , Treatment Outcome
8.
J Infect Dev Ctries ; 15(2): 204-208, 2021 03 07.
Article in English | MEDLINE | ID: covidwho-1150799

ABSTRACT

The steadily growing COVID-19 pandemic is challenging health systems worldwide including Sudan. In Sudan, the first COVID-19 case was reported on 13th March 2020, and up to 11 November 2020 there were 14,401 confirmed cases of which 9,535 cases recovered and the rest 3,750 cases were under treatment. Additionally, 1,116 deaths were reported, indicating a relatively high case fatality rate of 7.7%. Several preventive and control measures were implemented by the government of Sudan and health partners, including the partial lockdown of the country, promoting social distancing, and suspending mass gathering such as festivals and performing religious practices in groups. However, new cases still emerging every day and this could be attributed to the noncompliance of the individuals to the advocated preventive measurements.


Subject(s)
/epidemiology , Communicable Disease Control/methods , Africa/epidemiology , /prevention & control , Communicable Disease Control/organization & administration , Humans , Mass Media , Mortality , Socioeconomic Factors , Sudan/epidemiology
9.
J Am Coll Cardiol ; 77(13): 1644-1655, 2021 04 06.
Article in English | MEDLINE | ID: covidwho-1147716

ABSTRACT

BACKGROUND: Adults with congenital heart disease (CHD) have been considered potentially high risk for novel coronavirus disease-19 (COVID-19) mortality or other complications. OBJECTIVES: This study sought to define the impact of COVID-19 in adults with CHD and to identify risk factors associated with adverse outcomes. METHODS: Adults (age 18 years or older) with CHD and with confirmed or clinically suspected COVID-19 were included from CHD centers worldwide. Data collection included anatomic diagnosis and subsequent interventions, comorbidities, medications, echocardiographic findings, presenting symptoms, course of illness, and outcomes. Predictors of death or severe infection were determined. RESULTS: From 58 adult CHD centers, the study included 1,044 infected patients (age: 35.1 ± 13.0 years; range 18 to 86 years; 51% women), 87% of whom had laboratory-confirmed coronavirus infection. The cohort included 118 (11%) patients with single ventricle and/or Fontan physiology, 87 (8%) patients with cyanosis, and 73 (7%) patients with pulmonary hypertension. There were 24 COVID-related deaths (case/fatality: 2.3%; 95% confidence interval: 1.4% to 3.2%). Factors associated with death included male sex, diabetes, cyanosis, pulmonary hypertension, renal insufficiency, and previous hospital admission for heart failure. Worse physiological stage was associated with mortality (p = 0.001), whereas anatomic complexity or defect group were not. CONCLUSIONS: COVID-19 mortality in adults with CHD is commensurate with the general population. The most vulnerable patients are those with worse physiological stage, such as cyanosis and pulmonary hypertension, whereas anatomic complexity does not appear to predict infection severity.


Subject(s)
Cardiac Surgical Procedures , Cyanosis , Heart Defects, Congenital , Hypertension, Pulmonary , Adult , /therapy , Cardiac Surgical Procedures/methods , Cardiac Surgical Procedures/statistics & numerical data , Causality , Comorbidity , Cyanosis/diagnosis , Cyanosis/etiology , Cyanosis/mortality , Female , Global Health/statistics & numerical data , Heart Defects, Congenital/classification , Heart Defects, Congenital/epidemiology , Heart Defects, Congenital/physiopathology , Heart Defects, Congenital/therapy , Hospitalization/statistics & numerical data , Humans , Hypertension, Pulmonary/diagnosis , Hypertension, Pulmonary/etiology , Hypertension, Pulmonary/mortality , Male , Mortality , Patient Acuity , Risk Factors , Symptom Assessment
10.
J Immunother Cancer ; 9(3)2021 03.
Article in English | MEDLINE | ID: covidwho-1143073

ABSTRACT

Cancer patients are highly vulnerable to SARS-CoV-2 infections due to frequent contacts with the healthcare system, immunocompromised state from cancer or its therapies, supportive medications such as steroids and most importantly their advanced age and comorbidities. Patients with lung cancer have consistently been reported to suffer from an increased risk of death compared with other cancers. This is possibly due to the combination of specific pathophysiological aspects, including underlying pulmonary compromise due to smoking history and the increased specific pressures on respiratory healthcare services caused by the related pandemic. Rationally and safely treating patients with lung cancer during the pandemic has become a continuous challenge over the last year. Deciding whether to offer, modify, postpone or even cancel treatments for this particular patient's population has become the crucial recurrent dilemma for lung cancer professionals. Chemotherapy, immunotherapy and targeted agents represent distinct risks factors in the context of COVID-19 that should be balanced with the short-term and long-term consequences of delaying cancer care. Despite the rapid and persistent trend of the pandemic, declared by WHO on March 11, 2020, and still ongoing at the time of writing (January 2021), various efforts were made by oncologists worldwide to understand the impact of COVID-19 on patients with cancer. Adapted recommendations of our evidence-based practice guidelines have been developed for all stakeholders. Different small and large-scale registries, such as the COVID-19 and Cancer Consortium (CCC19) and Thoracic Cancers International COVID-19 Collaboration quickly collected data, supporting cancer care decisions under the challenging circumstance created by the COVID-19 pandemic. Several recommendations were developed as guidance for prioritizing the various aspects of lung cancer care in order to mitigate the adverse effects of the COVID-19 healthcare crisis, potentially reducing the morbidity and mortality of our patients from COVID-19 and from cancer. These recommendations helped inform decisions about treatment of established disease, continuation of clinical research and lung cancer screening. In this review, we summarize available evidence regarding the direct and indirect impact of the COVID-19 pandemic on lung cancer care and patients.


Subject(s)
Antineoplastic Agents/therapeutic use , Carcinoma, Non-Small-Cell Lung/therapy , Lung Neoplasms/therapy , Pneumonectomy , Radiotherapy , Small Cell Lung Carcinoma/therapy , /complications , Carcinoma, Non-Small-Cell Lung/complications , China , Humans , Italy , Lung Neoplasms/complications , Mortality , Netherlands , Risk Factors , Severity of Illness Index , Small Cell Lung Carcinoma/complications , United Kingdom , United States
12.
JAMA Netw Open ; 4(3): e214149, 2021 03 01.
Article in English | MEDLINE | ID: covidwho-1141277

ABSTRACT

Importance: Significant concern has been raised that crisis standards of care policies aimed at guiding resource allocation may be biased against people based on race/ethnicity. Objective: To evaluate whether unanticipated disparities by race or ethnicity arise from a single institution's resource allocation policy. Design, Setting, and Participants: This cohort study included adults (aged ≥18 years) who were cared for on a coronavirus disease 2019 (COVID-19) ward or in a monitored unit requiring invasive or noninvasive ventilation or high-flow nasal cannula between May 26 and July 14, 2020, at 2 academic hospitals in Miami, Florida. Exposures: Race (ie, White, Black, Asian, multiracial) and ethnicity (ie, non-Hispanic, Hispanic). Main Outcomes and Measures: The primary outcome was based on a resource allocation priority score (range, 1-8, with 1 indicating highest and 8 indicating lowest priority) that was assigned daily based on both estimated short-term (using Sequential Organ Failure Assessment score) and longer-term (using comorbidities) mortality. There were 2 coprimary outcomes: maximum and minimum score for each patient over all eligible patient-days. Standard summary statistics were used to describe the cohort, and multivariable Poisson regression was used to identify associations of race and ethnicity with each outcome. Results: The cohort consisted of 5613 patient-days of data from 1127 patients (median [interquartile range {IQR}] age, 62.7 [51.7-73.7]; 607 [53.9%] men). Of these, 711 (63.1%) were White patients, 323 (28.7%) were Black patients, 8 (0.7%) were Asian patients, and 31 (2.8%) were multiracial patients; 480 (42.6%) were non-Hispanic patients, and 611 (54.2%) were Hispanic patients. The median (IQR) maximum priority score for the cohort was 3 (1-4); the median (IQR) minimum score was 2 (1-3). After adjustment, there was no association of race with maximum priority score using White patients as the reference group (Black patients: incidence rate ratio [IRR], 1.00; 95% CI, 0.89-1.12; Asian patients: IRR, 0.95; 95% CI. 0.62-1.45; multiracial patients: IRR, 0.93; 95% CI, 0.72-1.19) or of ethnicity using non-Hispanic patients as the reference group (Hispanic patients: IRR, 0.98; 95% CI, 0.88-1.10); similarly, no association was found with minimum score for race, again with White patients as the reference group (Black patients: IRR, 1.01; 95% CI, 0.90-1.14; Asian patients: IRR, 0.96; 95% CI, 0.62-1.49; multiracial patients: IRR, 0.81; 95% CI, 0.61-1.07) or ethnicity, again with non-Hispanic patients as the reference group (Hispanic patients: IRR, 1.00; 95% CI, 0.89-1.13). Conclusions and Relevance: In this cohort study of adult patients admitted to a COVID-19 unit at 2 US hospitals, there was no association of race or ethnicity with the priority score underpinning the resource allocation policy. Despite this finding, any policy to guide altered standards of care during a crisis should be monitored to ensure equitable distribution of resources.


Subject(s)
Health Care Rationing , Healthcare Disparities/ethnology , Hospitalization/statistics & numerical data , Resource Allocation , Standard of Care/statistics & numerical data , /ethnology , Cohort Studies , Ethnic Groups , Female , Florida/epidemiology , Health Care Rationing/methods , Health Care Rationing/organization & administration , Health Services Needs and Demand , Humans , Male , Middle Aged , Mortality/ethnology , Resource Allocation/methods , Resource Allocation/organization & administration
13.
BMC Infect Dis ; 21(1): 262, 2021 Mar 15.
Article in English | MEDLINE | ID: covidwho-1136209

ABSTRACT

INTRODUCTION: Renin-angiotensin system (RAS) inhibitors have been postulated to influence susceptibility to Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). This study investigated whether there is an association between their prescription and the incidence of COVID-19 and all-cause mortality. METHODS: We conducted a propensity-score matched cohort study comparing the incidence of COVID-19 among patients with hypertension prescribed angiotensin-converting enzyme I (ACE) inhibitors or angiotensin II type-1 receptor blockers (ARBs) to those treated with calcium channel blockers (CCBs) in a large UK-based primary care database (The Health Improvement Network). We estimated crude incidence rates for confirmed/suspected COVID-19 in each drug exposure group. We used Cox proportional hazards models to produce adjusted hazard ratios for COVID-19. We assessed all-cause mortality as a secondary outcome. RESULTS: The incidence rate of COVID-19 among users of ACE inhibitors and CCBs was 9.3 per 1000 person-years (83 of 18,895 users [0.44%]) and 9.5 per 1000 person-years (85 of 18,895 [0.45%]), respectively. The adjusted hazard ratio was 0.92 (95% CI 0.68 to 1.26). The incidence rate among users of ARBs was 15.8 per 1000 person-years (79 out of 10,623 users [0.74%]). The adjusted hazard ratio was 1.38 (95% CI 0.98 to 1.95). There were no significant associations between use of RAS inhibitors and all-cause mortality. CONCLUSION: Use of ACE inhibitors was not associated with the risk of COVID-19 whereas use of ARBs was associated with a statistically non-significant increase compared to the use of CCBs. However, no significant associations were observed between prescription of either ACE inhibitors or ARBs and all-cause mortality.


Subject(s)
Angiotensin Receptor Antagonists/therapeutic use , Angiotensin-Converting Enzyme Inhibitors/therapeutic use , Antihypertensive Agents/therapeutic use , Calcium Channel Blockers/therapeutic use , Hypertension/complications , Hypertension/drug therapy , Adolescent , Adult , Aged , Aged, 80 and over , Angiotensin Receptor Antagonists/adverse effects , Angiotensin-Converting Enzyme Inhibitors/adverse effects , Antihypertensive Agents/adverse effects , Calcium Channel Blockers/adverse effects , Cohort Studies , Female , Humans , Incidence , Male , Middle Aged , Mortality , Propensity Score , Proportional Hazards Models , Renin-Angiotensin System , United Kingdom , Young Adult
14.
Sci Rep ; 11(1): 5839, 2021 03 12.
Article in English | MEDLINE | ID: covidwho-1132092

ABSTRACT

Guided by a rigorous mathematical result, we have earlier introduced a numerical algorithm, which using as input the cumulative number of deaths caused by COVID-19, can estimate the effect of easing of the lockdown conditions. Applying this algorithm to data from Greece, we extend it to the case of two subpopulations, namely, those consisting of individuals below and above 40 years of age. After supplementing the Greek data for deaths with the data for the number of individuals reported to be infected by SARS-CoV-2, we estimated the effect on deaths and infections in the case that the easing of the lockdown measures is different for these two subpopulations. We found that if the lockdown measures are partially eased only for the young subpopulation, then the effect on deaths and infections is small. However, if the easing is substantial for the older population, this effect may be catastrophic.


Subject(s)
/epidemiology , Quarantine , Algorithms , /transmission , Hospitalization , Humans , Models, Theoretical , Mortality , Public Health Surveillance
15.
BMJ Open ; 11(3): e046044, 2021 03 10.
Article in English | MEDLINE | ID: covidwho-1127586

ABSTRACT

OBJECTIVES: This study describes a new strategy to reduce the impact of COVID-19 on the elderly and other clinically vulnerable subjects, where general practitioners (GPs) play an active role in managing high-risk patients, reducing adverse health outcomes. DESIGN: Retrospective cohort study. SETTING: Population-based study including subjects resident in the province of Milan and Lodi. PARTICIPANTS: 127 735 residents older than 70 years, with specific chronic conditions. INTERVENTIONS: We developed a predictive algorithm for overall mortality risk based on demographic and clinical characteristics. All residents older than 70 years were classified as being at low or high risk of death from COVID-19 infection according to the algorithm. The high-risk group was assigned to their GPs for telephone triage and consultation. The high-risk cohort was divided into two groups based on GP intervention: patients who were not contacted and patients who were contacted by their GPs. OUTCOME MEASURES: Overall mortality, COVID-19 morbidity and hospitalisation. RESULTS: Patients with increased risk of death from COVID-19 were 127 735; 495 669 patients were not at high risk and were not included in the intervention. Out of the high-risk subjects, 79 110 were included but not contacted by their GPs, while 48 625 high-risk subjects were included and contacted. Overall mortality, morbidity and hospitalisation was higher in high-risk patients compared with low-risk populations. High-risk patients contacted by their GPs had a 50% risk reduction in COVID-19 mortality, and a 70% risk reduction in morbidity and hospitalisation for COVID-19 compared with non-contacted patients. CONCLUSIONS: The study showed that, during the COVID-19 outbreak, involvement of GPs and changes in care management of high-risk groups produced a significant reduction in all adverse health outcomes.


Subject(s)
/mortality , Health Status , Outcome Assessment, Health Care , Aged , Hospitalization , Humans , Italy/epidemiology , Morbidity , Mortality , Retrospective Studies
16.
Medicine (Baltimore) ; 100(5): e23925, 2021 Feb 05.
Article in English | MEDLINE | ID: covidwho-1125827

ABSTRACT

ABSTRACT: The World Health Organization (WHO) classified the spread of COVID-19 (Coronavirus Disease 2019) as a global pandemic in March. Scholars predict that the pandemic will continue into the coming winter and will become a seasonal epidemic in the following year. Therefore, the identification of effective control measures becomes extremely important. Although many reports have been published since the COVID-19 outbreak, no studies have identified the relative effectiveness of a combination of control measures implemented in Wuhan and other areas in China. To this end, a retrospective analysis by the collection and modeling of an unprecedented number of epidemiology records in China of the early stage of the outbreaks can be valuable.In this study, we developed a new dynamic model to describe the spread of COVID-19 and to quantify the effectiveness of control measures. The transmission rate, daily close contacts, and the average time from onset to isolation were identified as crucial factors in viral spreading. Moreover, the capacity of a local health-care system is identified as a threshold to control an outbreak in its early stage. We took these factors as controlling parameters in our model. The parameters are estimated based on epidemiological reports from national and local Center for Disease Control (CDCs).A retrospective simulation showed the effectiveness of combinations of 4 major control measures implemented in Wuhan: hospital isolation, social distancing, self-protection by wearing masks, and extensive medical testing. Further analysis indicated critical intervention conditions and times required to control an outbreak in the early stage. Our simulations showed that South Korea has kept the spread of COVID-19 at a low level through extensive medical testing. Furthermore, a predictive simulation for Italy indicated that Italy would contain the outbreak in late May under strict social distancing.In our general analysis, no single measure could contain a COVID-19 outbreak once a health-care system is overloaded. Extensive medical testing could keep viral spreading at a low level. Wearing masks functions as favorably as social distancing but with much lower socioeconomic costs.


Subject(s)
Communicable Disease Control , Hospitalization/statistics & numerical data , Outcome Assessment, Health Care/methods , /isolation & purification , /economics , /prevention & control , China/epidemiology , Communicable Disease Control/methods , Communicable Disease Control/organization & administration , Communicable Disease Control/standards , Contact Tracing/statistics & numerical data , Disease Transmission, Infectious/prevention & control , Disease Transmission, Infectious/statistics & numerical data , Humans , Models, Theoretical , Mortality , Systems Analysis , Time-to-Treatment/statistics & numerical data
17.
Medicine (Baltimore) ; 100(5): e24409, 2021 Feb 05.
Article in English | MEDLINE | ID: covidwho-1125185

ABSTRACT

ABSTRACT: Infection with the SARS-CoV-2 virus seems to contribute significantly to increased postoperative complications and mortality after emergency surgical procedures. Additionally, the fear of COVID-19 contagion delays the consultation of patients, resulting in the deterioration of their acute diseases by the time of consultation. In the specific case of urgent digestive surgery patients, both factors significantly worsen the postoperative course and prognosis. Main working hypothesis: infection by COVID-19 increases postoperative 30-day-mortality for any cause in patients submitted to emergency/urgent general or gastrointestinal surgery. Likewise, hospital collapse during the first wave of the COVID-19 pandemic increased 30-day-mortality for any cause. Hence, the main objective of this study is to estimate the cumulative incidence of mortality at 30-days-after-surgery. Secondary objectives are: to estimate the cumulative incidence of postoperative complications and to develop a specific postoperative risk propensity model for COVID-19-infected patients.A multicenter, observational retrospective cohort study (COVID-CIR-study) will be carried out in consecutive patients operated on for urgent digestive pathology. Two cohorts will be defined: the "pandemic" cohort, which will include all patients (classified as COVID-19-positive or -negative) operated on for emergency digestive pathology during the months of March to June 2020; and the "control" cohort, which will include all patients operated on for emergency digestive pathology during the months of March to June 2019. Information will be gathered on demographic characteristics, clinical and analytical parameters, scores on the usual prognostic scales for quality management in a General Surgery service (POSSUM, P-POSSUM and LUCENTUM scores), prognostic factors applicable to all patients, specific prognostic factors for patients infected with SARS-CoV-2, postoperative morbidity and mortality (at 30 and 90 postoperative days). The main objective is to estimate the cumulative incidence of mortality at 30 days after surgery. As secondary objectives, to estimate the cumulative incidence of postoperative complications and to develop a specific postoperative risk propensity model for SARS-CoV-2 infected patients.The protocol (version1.0, April 20th 2020) was approved by the local Institutional Review Board (Ethic-and-Clinical-Investigation-Committee, code PR169/20, date 05/05/20). The study findings will be submitted to peer-reviewed journals and presented at relevant national and international scientific meetings.ClinicalTrials.gov Identifier: NCT04479150 (July 21, 2020).


Subject(s)
Digestive System Diseases , Digestive System Surgical Procedures , Emergency Treatment , Infection Control , Postoperative Complications , Time-to-Treatment , Adult , /prevention & control , Digestive System Diseases/diagnosis , Digestive System Diseases/epidemiology , Digestive System Diseases/mortality , Digestive System Diseases/surgery , Digestive System Surgical Procedures/adverse effects , Digestive System Surgical Procedures/methods , Digestive System Surgical Procedures/mortality , Emergencies/epidemiology , Emergency Treatment/adverse effects , Emergency Treatment/methods , Emergency Treatment/mortality , Female , Humans , Incidence , Infection Control/methods , Infection Control/statistics & numerical data , Male , Mortality , Multicenter Studies as Topic , Observational Studies as Topic , Postoperative Complications/diagnosis , Postoperative Complications/epidemiology , Postoperative Complications/etiology , Research Design , Risk Assessment/methods
18.
CMAJ Open ; 9(1): E181-E188, 2021.
Article in English | MEDLINE | ID: covidwho-1124785

ABSTRACT

BACKGROUND: Clinical data on patients admitted to hospital with coronavirus disease 2019 (COVID-19) provide clinicians and public health officials with information to guide practice and policy. The aims of this study were to describe patients with COVID-19 admitted to hospital and intensive care, and to investigate predictors of outcome to characterize severe acute respiratory infection. METHODS: This observational cohort study used Canadian data from 32 selected hospitals included in a global multisite cohort between Jan. 24 and July 7, 2020. Adult and pediatric patients with a confirmed diagnosis of COVID-19 who received care in an intensive care unit (ICU) and a sampling of up to the first 60 patients receiving care on hospital wards were included. We performed descriptive analyses of characteristics, interventions and outcomes. The primary analyses examined in-hospital mortality, with secondary analyses of the length of hospital and ICU stay. RESULTS: Between January and July 2020, among 811 patients admitted to hospital with a diagnosis of COVID-19, the median age was 64 (interquartile range [IQR] 53-75) years, 495 (61.0%) were men, 46 (5.7%) were health care workers, 9 (1.1%) were pregnant, 26 (3.2%) were younger than 18 years and 9 (1.1%) were younger than 5 years. The median time from symptom onset to hospital admission was 7 (IQR 3-10) days. The most common symptoms on admission were fever, shortness of breath, cough and malaise. Diabetes, hypertension and cardiac, kidney and respiratory disease were the most common comorbidities. Among all patients, 328 received care in an ICU, admitted a median of 0 (IQR 0-1) days after hospital admission. Critically ill patients received treatment with invasive mechanical ventilation (88.8%), renal replacement therapy (14.9%) and extracorporeal membrane oxygenation (4.0%); 26.2% died. Among those receiving mechanical ventilation, 31.2% died. Age was an influential predictor of mortality (odds ratio per additional year of life 1.06, 95% confidence interval 1.03-1.09). INTERPRETATION: Patients admitted to hospital with COVID-19 commonly had fever, respiratory symptoms and comorbid conditions. Increasing age was associated with the development of critical illness and death; however, most critically ill patients in Canada, including those requiring mechanical ventilation, survived and were discharged from hospital.


Subject(s)
/epidemiology , Critical Care , Hospitalization , Adolescent , Adult , Aged , Aged, 80 and over , /therapy , Canada/epidemiology , Comorbidity , Critical Illness , Disease Management , Disease Progression , Female , Humans , Incidence , Intensive Care Units , Male , Middle Aged , Mortality , Pandemics , Pregnancy , Public Health Surveillance , Severity of Illness Index , Young Adult
19.
Front Public Health ; 9: 579948, 2021.
Article in English | MEDLINE | ID: covidwho-1121567

ABSTRACT

Influenza viruses have caused disease outbreaks in human societies for a long time. Influenza often has rapid onset and relatively short duration, both in the individual and in the population. The case fatality rate varies for different strains of the virus, as do the effects on total mortality. Outbreaks related to coronavirus infections have recently become a global concern but much less is known about the dynamics of these outbreaks and their effects on mortality. In this work, disease outbreaks in Sweden, in the time period of 1860-2020, are characterized and compared to the currently ongoing COVID-19 outbreak. The focus is on outbreaks with a sharp increase in all-cause mortality. Outbreak onset is defined as the time point when death counts start to increase consistently for a period of at least 10 days. The duration of the outbreak is defined as the time period in which mortality rates are elevated. Excess mortality is estimated by standard methods. In total there were 15 outbreaks detected in the time period, the first 14 were likely caused by influenza virus infections, the last by SARS-CoV-2. The mortality dynamics of the SARS-CoV-2 outbreak is shown to be similar to outbreaks due to influenza virus, and in terms of the number of excess deaths, it is the worst outbreak in Sweden since the "Spanish flu" of 1918-1919.


Subject(s)
/mortality , Disease Outbreaks/history , Influenza, Human/mortality , Cause of Death , History, 19th Century , History, 20th Century , History, 21st Century , Humans , Influenza, Human/history , Mortality/history , Sweden/epidemiology
20.
BMC Med ; 19(1): 71, 2021 03 05.
Article in English | MEDLINE | ID: covidwho-1119426

ABSTRACT

BACKGROUND: To estimate excess mortality for care home residents during the COVID-19 pandemic in England, exploring associations with care home characteristics. METHODS: Daily number of deaths in all residential and nursing homes in England notified to the Care Quality Commission (CQC) from 1 January 2017 to 7 August 2020. Care home-level data linked with CQC care home register to identify home characteristics: client type (over 65s/children and adults), ownership status (for-profit/not-for-profit; branded/independent) and size (small/medium/large). Excess deaths computed as the difference between observed and predicted deaths using local authority fixed-effect Poisson regressions on pre-pandemic data. Fixed-effect logistic regressions were used to model odds of experiencing COVID-19 suspected/confirmed deaths. RESULTS: Up to 7 August 2020, there were 29,542 (95% CI 25,176 to 33,908) excess deaths in all care homes. Excess deaths represented 6.5% (95% CI 5.5 to 7.4%) of all care home beds, higher in nursing (8.4%) than residential (4.6%) homes. 64.7% (95% CI 56.4 to 76.0%) of the excess deaths were confirmed/suspected COVID-19. Almost all excess deaths were recorded in the quarter (27.4%) of homes with any COVID-19 fatalities. The odds of experiencing COVID-19 attributable deaths were higher in homes providing nursing services (OR 1.8, 95% CI 1.6 to 2.0), to older people and/or with dementia (OR 5.5, 95% CI 4.4 to 6.8), amongst larger (vs. small) homes (OR 13.3, 95% CI 11.5 to 15.4) and belonging to a large provider/brand (OR 1.2, 95% CI 1.1 to 1.3). There was no significant association with for-profit status of providers. CONCLUSIONS: To limit excess mortality, policy should be targeted at care homes to minimise the risk of ingress of disease and limit subsequent transmission. Our findings provide specific characteristic targets for further research on mechanisms and policy priority.


Subject(s)
Health Services for the Aged , Homes for the Aged/statistics & numerical data , Nursing Homes/statistics & numerical data , Quality of Health Care , Residential Facilities/statistics & numerical data , Aged , Aged, 80 and over , /prevention & control , Cohort Studies , England/epidemiology , Female , Health Services Needs and Demand , Health Services for the Aged/organization & administration , Health Services for the Aged/standards , Humans , Male , Mortality
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