Acute Kidney Injury in Patients Hospitalized With COVID-19 in New York City: Temporal Trends From March 2020 to April 2021.
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ABSTRACT:
SUBMITTER: Dellepiane S
PROVIDER: S-EPMC8325375 | biostudies-literature | 2021 Sep-Oct
REPOSITORIES: biostudies-literature
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Acute Kidney Injury in Patients Hospitalized With COVID-19 in New York City: Temporal Trends From March 2020 to April 2021.
Dellepiane Sergio S Vaid Akhil A Jaladanki Suraj K SK Coca Steven S Fayad Zahi A ZA Charney Alexander W AW Bottinger Erwin P EP He John Cijiang JC Glicksberg Benjamin S BS Chan Lili L Nadkarni Girish G
Kidney medicine 20210731 5
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Project description:BackgroundClinical severity of coronavirus disease 2019 (COVID-19) may vary over time; trends in clinical severity at admission during the pandemic among hospitalized patients in the United States have been incompletely described, so a historical record of severity over time is lacking.MethodsWe classified 466677 hospital admissions for COVID-19 from April 2020 to April 2021 into 4 mutually exclusive severity grades based on indicators present on admission (from most to least severe): Grade 4 included intensive care unit (ICU) admission and invasive mechanical ventilation (IMV); grade 3 included non-IMV ICU and/or noninvasive positive pressure ventilation; grade 2 included diagnosis of acute respiratory failure; and grade 1 included none of the above indicators. Trends were stratified by sex, age, race/ethnicity, and comorbid conditions. We also examined severity in states with high vs low Alpha (B.1.1.7) variant burden.ResultsSeverity tended to be lower among women, younger adults, and those with fewer comorbidities compared to their counterparts. The proportion of admissions classified as grade 1 or 2 fluctuated over time, but these less-severe grades comprised a majority (75%-85%) of admissions every month. Grades 3 and 4 consistently made up a minority of admissions (15%-25%), and grade 4 showed consistent decreases in all subgroups, including states with high Alpha variant burden.ConclusionsClinical severity among hospitalized patients with COVID-19 has varied over time but has not consistently or markedly worsened over time. The proportion of admissions classified as grade 4 decreased in all subgroups. There was no consistent evidence of worsening severity in states with higher vs lower Alpha prevalence.
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Project description:BackgroundHealth care personnel (HCP) have experienced significant SARS-CoV-2 risk, but exposure settings among HCP COVID-19 cases are poorly characterized.MethodsWe assessed exposure settings among HCP COVID-19 cases in the United States from March 2020 to March 2021 with reported exposures (n = 83,775) using national COVID-19 surveillance data. Exposure setting and reported community incidence temporal trends were described using breakpoint estimation. Among cases identified before initiation of COVID-19 vaccination programs (n = 65,650), we used separate multivariable regression models to estimate adjusted prevalence ratios (aPR) for associations of community incidence with health care and household and/or community exposures.ResultsHealth care exposures were the most reported (52.0%), followed by household (30.8%) and community exposures (25.6%). Health care exposures and community COVID-19 incidence showed similar temporal trends. In adjusted analyses, HCP cases were more likely to report health care exposures (aPR = 1.31; 95% CI:1.26-1.36) and less likely to report household and/or community exposures (aPR = 0.73; 95% CI:0.70-0.76) under the highest vs lowest community incidence levels.DiscussionThese findings highlight HCP exposure setting temporal trends and workplace exposure hazards under high community incidence. Findings also underscore the need for robust collection of work-related data in infectious disease surveillance.ConclusionsMany reported HCP cases experienced occupational COVID-19 exposures, particularly during periods of higher community COVID-19 incidence.
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Project description:Excess mortality studies provide crucial information regarding the health burden of pandemics and other large-scale events. Here, we used time series approaches to separate the direct contribution of SARS-CoV-2 infections on mortality from the indirect consequences of pandemic interventions and behavior changes in the United States. We estimated deaths occurring in excess of seasonal baselines stratified by state, age, week and cause (all causes, COVID-19 and respiratory diseases, Alzheimer's disease, cancer, cerebrovascular disease, diabetes, heart disease, and external causes, including suicides, opioids, accidents) from March 1, 2020 to April 30, 2021. Our estimates of COVID-19 excess deaths were highly correlated with SARS-CoV-2 serology, lending support to our approach. Over the study period, we estimate an excess of 666,000 (95% Confidence Interval (CI) 556000, 774000) all-cause deaths, of which 90% could be attributed to the direct impact of SARS-CoV-2 infection, and 78% were reflected in official COVID-19 statistics. Mortality from all disease conditions rose during the pandemic, except for cancer. The largest direct impacts of the pandemic were seen in mortality from diabetes, Alzheimer's, and heart diseases, and in age groups over 65 years. In contrast, the largest indirect consequences of the pandemic were seen in deaths from external causes, which increased by 45,300 (95% CI 30,800, 59,500) and were statistically linked to the intensity of non-pharmaceutical interventions. Within this category, increases were most pronounced in mortality from accidents and injuries, drug overdoses, and assaults and homicides, while the rate of death from suicides remained stable. Younger age groups suffered the brunt of these indirect effects. Overall, on a national scale, the largest consequences of the COVID-19 pandemic are attributable to the direct impact of SARS-CoV-2 infections; yet, the secondary impacts dominate among younger age groups, in periods of stricter interventions, and in mortality from external causes. Further research on the drivers of indirect mortality is warranted to optimize interventions in future pandemics.
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Project description:BackgroundThough the use of coronavirus disease 2019 (COVID-19) home testing kits is increasing, individuals who use home tests are not accounted for in publicly reported COVID-19 metrics. As the pandemic and the methods for tracking cases evolve, it is critical to understand who the individuals excluded are, due to their use of home testing kits, relative to those included in the reported metrics.MethodsFive New York State databases were linked to investigate trends in home-tested COVID-19 cases vs. laboratory-confirmed cases from November 2021 to April 2022. Frequency distributions, multivariate logistic regression adjusted odds ratios (aOR), and 95% confidence intervals (CI) were used to compare the characteristics of the home-tested and laboratory-tested people.ResultsOf the 591,227 confirmed COVID-19 cases interviewed, 71,531 (12%) of them underwent home tests, 515,001 (87%) underwent laboratory tests, and 5,695 (1%) underwent both home tests and laboratory tests during this period. Home-tested COVID-19 cases increased from only 1% in November 2021 to 22% in April 2022. Children aged 5-11 years with an aOR of 3.74 (95% CI: 3.53, 3.96) and adolescents aged 12-17 years with an aOR of 3.24 (95% CI: 3.07, 3.43) were more likely to undergo only home tests compared to adults aged 65 years and above. On the one hand, those who were "boosted" (aOR 1.87, 95% CI: 1.82, 1.93), those in K-12 school settings (aOR 2.33, 95% CI: 2.27, 2.40), or those who were possibly infected by a household member (aOR 1.17, 95% CI: 1.13, 1.22) were more likely to report home testing instead of laboratory testing. On the other hand, individuals who were hospitalized (aOR 0.04, 95% CI: 0.03, 0.06), who had underlying conditions (aOR 0.85, 95% CI: 0.83, 0.87), who were pregnant (aOR 0.76, 95% CI: 0.66, 0.86), and who were Hispanic (aOR 0.50: 95% CI: 0.48, 0.53), Asian (aOR 0.31, 95% CI: 0.28, 0.34), or Black (aOR 0.45, 95% CI: 0.42, 047) were less likely to choose home testing over laboratory testing.ConclusionThe percentage of individuals with confirmed COVID-19 who used only home testing kits continues to rise. People who used only home testing were less likely to be hospitalized and were those with a lower likelihood of developing a severe disease given factors such as age, vaccination status, and underlying conditions. Thus, the official COVID-19 metrics primarily reflected individuals with severe illness or the potential for severe illness. There may be racial and ethnic differences in the use of home testing vs. laboratory testing.
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Project description:BackgroundA reduction in mortality risk of COVID-19 throughout the first wave of the pandemic has been reported, but less is known about later waves. This study aimed to describe changes in hospitalizations and mortality of patients receiving inpatient geriatric care for COVID-19 or other causes during the pandemic.MethodsPatients 70 years and older hospitalized in geriatric hospitals in Stockholm for COVID-19 or other causes between March 2020-July 2021 were included. Data on the incidence of COVID-positive cases and 30-day mortality of the total ≥ 70-year-old population, in relation to weekly hospitalizations and mortality after hospital admissions were analyzed. Findings The total number of hospitalizations was 5,320 for COVID-19 and 32,243 for non-COVID-cases. In COVID-patients, the 30-day mortality rate was highest at the beginning of the first wave (29% in March-April 2020), reached 17% at the second wave peak (November-December) followed by 11-13% in the third wave (March-July 2021). The mortality in non-COVID geriatric patients showed a similar trend, but of lower magnitude (5-10%). During the incidence peaks, COVID-19 hospitalizations displaced non-COVID geriatric patients.InterpretationHospital admissions and 30-day mortality after hospitalizations for COVID-19 increased in periods of high community transmission, albeit with decreasing mortality rates from wave 1 to 3, with a probable vaccination effect in wave 3. Thus, the healthcare system could not compensate for the high community spread of COVID-19 during the pandemic peaks, which also led to displacing care for non-COVID geriatric patients.
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Project description:BackgroundDengue is the major mosquito-borne disease in Sri Lanka. After its first detection in January 2020, COVID-19 has become the major health issue in Sri Lanka. The impact of public health measures, notably restrictions on movement of people to curb COVID-19 transmission, on the incidence of dengue during the period March 2020 to April 2021 was investigated.MethodsThe incidence of dengue and COVID-19, rainfall and the public movement restrictions implemented to contain COVID-19 transmission were obtained from Sri Lanka government sources. A Seasonal Autoregressive Integrated Moving Average (SARIMA) model was used to predict the monthly dengue incidence from March 2020 to April 2021 for each of the country's 25 districts based on five years of pre-pandemic data, and compared with the actual recorded incidence of dengue during this period. Ovitrap collections of Aedes larvae were performed in Jaffna city in the Jaffna district from August 2020 to April 2021 and the findings compared with similar collections made in the pre-pandemic period from March 2019 to December 2019.ResultsThe recorded numbers of dengue cases for every month from March 2020 to April 2021 in the whole country and for all 25 districts over the same period were lower than the numbers of dengue cases predicted from data for the five years (2015-2019) immediately preceding the COVID-19 pandemic. The number of dengue cases recorded nationwide represented a 74% reduction from the predicted number of dengue cases for the March 2020 to April 2021 period. The numbers of Aedes larvae collected from ovitraps per month were reduced by 88.6% with a lower proportion of Ae. aegypti than Ae. albopictus in Jaffna city from August 2020 until April 2021 compared with March 2019 to December 2019.ConclusionPublic health measures that restricted movement of people, closed schools, universities and offices to contain COVID-19 transmission unexpectedly led to a significant reduction in the reported numbers of dengue cases in Sri Lanka. This contrasts with findings reported from Singapore. The differences between the two tropical islands have significant implications for the epidemiology of dengue. Reduced access to blood meals and lower vector densities, particularly of Ae. aegypti, resulting from the restrictions on movement of people, are suggested to have contributed to the lower dengue incidence in Sri Lanka.
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