This review aimed to evaluate the impact of obesity on the onset, exacerbation, and mortality of coronavirus disease 2019 (COVID‐19); and compare the effects of different degrees of obesity. PubMed, ...EMBASE, and Web of Science were searched to find articles published between December 1, 2019, and July 27, 2020. Only observational studies with specific obesity definition were included. Literature screening and data extraction were conducted simultaneously by two researchers. A random‐effects model was used to merge the effect quantity. Sensitivity analysis, subgroup analysis, and meta‐regression analysis were used to deal with the heterogeneity among studies. Forty‐one studies with 219,543 subjects and 115,635 COVID‐19 patients were included. Subjects with obesity were more likely to have positive SARS‐CoV‐2 test results (OR = 1.50; 95% CI: 1.37–1.63, I2 = 69.2%); COVID‐19 patients with obesity had a higher incidence of hospitalization (OR = 1.54, 95% CI: 1.33–1.78, I2 = 60.9%); hospitalized COVID‐19 patients with obesity had a higher incidence of intensive care unit admission (OR = 1.48, 95% CI: 1.24–1.77, I2 = 67.5%), invasive mechanical ventilation (OR = 1.47, 95% CI: 1.31–1.65, I2 = 18.8%), and in‐hospital mortality (OR = 1.14, 95% CI: 1.04–1.26, I2 = 74.4%). A higher degree of obesity also indicated a higher risk of almost all of the above events. The region may be one of the causes of heterogeneity. Obesity could promote the occurrence of the whole course of COVID‐19. A higher degree of obesity may predict a higher risk. Further basic and clinical therapeutic research needs to be strengthened.
Background There is a lack of contemporary data on cardiogenic shock (CS) in‐hospital mortality trends. Methods and Results Patients with CS admitted January 1, 2004 to December 31, 2018, were ...identified from the US National Inpatient Sample. We reported the crude and adjusted trends of in‐hospital mortality among the overall population and selected subgroups. Among a total of 563 949 644 hospitalizations during the period from January 1, 2004, to December 30, 2018, 1 254 358 (0.2%) were attributed to CS. There has been a steady increase in hospitalizations attributed to CS from 122 per 100 000 hospitalizations in 2004 to 408 per 100 000 hospitalizations in 2018 ( P trend <0.001). This was associated with a steady decline in the adjusted trends of in‐hospital mortality during the study period in the overall population (from 49% in 2004 to 37% in 2018; P trend <0.001), among patients with acute myocardial infarction CS (from 43% in 2004 to 34% in 2018; P trend <0.001), and among patients with non–acute myocardial infarction CS (from 52% in 2004 to 37% in 2018; P trend <0.001). Consistent trends of reduced mortality were seen among women, men, different racial/ethnic groups, different US regions, and different hospital sizes, regardless of the hospital teaching status. Conclusions Hospitalizations attributed to CS have tripled in the period from January 2004 to December 2018. However, there has been a slow decline in CS in‐hospital mortality during the studied period. Further studies are necessary to determine if the recent adoption of treatment algorithms in treating patients with CS will further impact in‐hospital mortality.
Aims
Admission rates for acute decompensated heart failure (HF) declined during the COVID‐19 pandemic. However, the impact of this reduction on hospital mortality is unknown. We describe temporal ...trends in the presentation of patients with acute HF and their in‐hospital outcomes at two referral centres in London during the COVID‐19 pandemic.
Methods and results
A total of 1372 patients hospitalized for HF in two referral centres in South London between 7 January and 14 June 2020 were included in the study and their outcomes compared with those of equivalent patients of the same time period in 2019. The primary outcome was all‐cause in‐hospital mortality. The number of HF hospitalizations was significantly reduced during the COVID‐19 pandemic, compared with 2019 (P < 0.001). Specifically, we observed a temporary reduction in hospitalizations during the COVID‐19 peak, followed by a return to 2019 levels. Patients admitted during the COVID‐19 pandemic had demographic characteristics similar to those admitted during the equivalent period in 2019. However, in‐hospital mortality was significantly higher in 2020 than in 2019 (P = 0.015). Hospitalization in 2020 was independently associated with worse in‐hospital mortality (hazard ratio 2.23, 95% confidence interval 1.34–3.72; P = 0.002).
Conclusions
During the COVID‐19 pandemic there was a reduction in HF hospitalization and a higher rate of in‐hospital mortality. Hospitalization for HF in 2020 is independently associated with more adverse outcomes. Further studies are required to investigate the predictors of these adverse outcomes to help inform potential changes to the management of HF patients while some constraints to usual care remain.
Temporal trends in heart failure admission and adjusted Kaplan–Meier curves for in‐hospital mortality during the COVID‐19 pandemic.
COVID-19 tide had shattered on European countries with three distinct and tough waves, from March and April, 2020; October and November, 2020 and March and April, 2021 respectively. We observed a 50% ...reduction in the hazard of death during both wave II and III compared with wave I (HR 0.54, 95%CI 0.39-0.74 and HR 0.57, 95%CI 0.41-0.80, respectively). Sex and age were independent predictors of death. We compare in-hospital mortality of COVID-19 patients admitted at our Referral Hospital of Northern Italy during the different waves, discuss the reasons of the observed differences and suggest approaches to the challenges ahead.
This study sought to assess temporal trends and outcomes of percutaneous coronary intervention (PCI) in nonagenarians.
With increasing life expectancy, nonagenarians requiring PCI are increasing even ...though outcomes data are limited.
The National Inpatient Sample was used to identify all hospitalizations for PCI in patients aged ≥90 years from January 1, 2003, to December 31, 2014. The primary outcome was in-hospital mortality.
Nonagenarians (n = 69,271) constituted 0.9% of all PCI hospitalizations, increasing from 0.6% in 2003 to 2004 to 1.4% in 2013 to 2014 (p
< 0.001). From 2003-2004 to 2013-2014, the proportion of PCIs performed for ST-segment elevation myocardial infarction (STEMI) (23.1% to 30.9%) and non-ST-segment elevation acute coronary syndromes (49.6% to 52.6%) increased, whereas those for stable ischemic heart disease (SIHD) decreased (27.3% to 16.5%), respectively (p
< 0.001 for all). Overall in-hospital mortality after PCI for STEMI, non-ST-segment elevation acute coronary syndromes, and SIHD were 16.4%, 4.2%, and 1.8%, respectively. After multivariable risk adjustment for demographics, comorbidities, and hospital-level characteristics, in-hospital mortality remained unchanged in STEMI (odds ratio: 1.04; 95% confidence interval: 0.98 to 1.11; p
= 0.20) and non-ST-segment elevation acute coronary syndromes (odds ratio: 0.99; 95% confidence interval: 0.91 to 1.08; p
= 0.82), but increased in SIHD (odds ratio: 1.21; 95% confidence interval: 1.01 to 1.44; p
= 0.04) from 2003 to 2004 to 2013 to 2014. The rates of bleeding and vascular complications decreased or remained stable in all 3 subgroups, whereas risk-adjusted incidence of stroke increased in patients with STEMI or SIHD.
The rate of in-hospital mortality, major bleeding, vascular complications, and stroke after PCI in nonagenarians changed significantly from 2003 to 2014. This study provides a benchmark for discussion of PCI-related risks among physicians, patients, and families.
Aims
Considerable differences in the long‐term trends of heart failure (HF) exist between different countries. To extend the existing knowledge on HF epidemiology in Germany, we analysed trends of ...HF‐related hospitalizations, hospital days and in‐hospital deaths during a 14‐year period (2000–2013).
Methods and results
Data were derived from the official German Federal Health Monitoring System, which includes an annual and complete enumeration of inpatients at the time of discharge from the hospital. HF cases were identified by the primary diagnosis code for HF (I50). From 2000 to 2013, the absolute number of HF‐related hospitalizations increased by 65.4% (239 694–396 380 cases) and by 28.4% after age‐standardization (261–335 per 100 000 population). Accordingly, the absolute number of HF‐related hospital days increased by 22.1% (3.4–4.2 million hospital days), despite a marked decrease by 25.9% in average length of stay (14.3–10.6 days). With approximately 35 000 in‐hospital deaths (∼45 per 100 000 population), the annual number of HF‐related in‐hospital deaths remained consistently high, and in‐hospital mortality rate in HF patients constituted 9.3% in 2013. Patients aged >65 years were disproportionately affected. In 2013, HF was the leading cause of disease‐related hospitalizations and in‐hospital deaths, representing 2.1% and 8.8% of all cases, respectively.
Conclusion
In Germany, the burden of HF is growing further, and the risk of death in HF remains high. These trends can only be partly attributed to demographic developments suggesting an exigent need for increased awareness and enhanced efforts in the prevention and management of HF.
Aims
The coronavirus disease 2019 (COVID‐19) pandemic has led to changes in health care utilization for different acute cardiovascular diseases. Whether hospitalization rates and in‐hospital ...mortality were affected by the pandemic in patients with acute symptomatic heart failure (HF) was investigated in this study.
Methods and results
Administrative data provided by 67 German Helios hospitals were examined for patients with a main discharge diagnosis of HF using ICD codes. Urgent hospital admissions per day were compared for a study period (13 March–21 May 2020) with control intervals in 2020 (1 January–12 March) and 2019 (13 March–21 May), resulting in a total of 13 484 patients excluding all patients with laboratory‐proven COVID‐19 infection. Incidence rate ratios (IRR) were calculated using Poisson regression. Generalized linear mixed models were used for univariable and multivariable analysis to identify predictors of in‐hospital mortality. The number of admissions per day was lower in the study period compared to the same year IRR 0.69, 95% confidence interval (CI) 0.67–0.73, P < 0.01 and the previous year control group (IRR 0.73, 95% CI 0.70–0.76, P < 0.01). Age was similar throughout the intervals, but case severity increased in terms of distribution within New York Heart Association (NYHA) classes and comorbidities. Within the study period, 30‐day rates for urgent hospital readmissions were higher compared to the same year but not the previous year control group. In‐hospital mortality was 7.3% in the study period, 6.1% in the same year (P = 0.03) and 6.0% in the previous year control group (P = 0.02). In multivariable analysis, age, NYHA class and other predictors of fatal outcome were identified but hospitalization during the study period was not independently associated with mortality.
Conclusion
Our data showed a significant reduction of urgent hospital admissions for HF with increased case severity and concomitant in‐hospital mortality during the COVID‐19 pandemic in Germany. Identifying causes of reduced inpatient treatment rates is essential for the understanding and valuation with regard to future optimal management of patients with HF.
Data on multiple consecutive health care-associated infections (HAIs) in patients undergoing extracorporeal membrane oxygenation (ECMO) are limited. We aim to identify the characteristics and ...outcomes of multiple, consecutive HAIs.
This retrospective study included adult patients who underwent ECMO in a single cardiac ICU in China from May 2015 to December 2022. The incidence, clinical characteristics, risk factors, and impact on in-hospital mortality among patients with non-HAI, single HAI, and multiple HAIs were analyzed. Pathogens and infection sites for each new episode were compared.
Of 192 patients, 92 (47.92%) developed 141 separate infections, with 41 (21.35%) experiencing multiple infections during a single ECMO period. Respiratory tract infections (RTIs) constituted the majority (75.89%), and gram-negative bacteria were the predominant pathogens (71.63%). RTIs decreased from 86.9% in the first infection to 14.3% in the third (P < .001), while bloodstream infections increased from 10.9 % to 57.1% (P < .001). The proportion of gram-positive bacteria increased from 9.8% to 42.9% (P = .032). Prolonged ECMO duration was the only independent risk factor for multiple consecutive HAIs (odds ratio (OR)=1.220, P < .001).
Multiple consecutive HAIs during ECMO were frequent, with distinct microbiological changes between initial and subsequent HAIs.
•Infection episodes during ECMO present significant challenges to patients.•One-quarter of patients had multiple consecutive infections during ECMO support.•The microbiology of the first infection differed from subsequent ones during ECMO.•Predictors for consecutive multiple infections during ECMO were identified.
This study is done to estimаte in‐hоsрitаl mоrtаlity in раtients with severe асute resрirаtоry syndrоme соrоnаvirus 2 (SАRS‐СоV‐2) strаtified by Vitamin‐D (Vit‐D) levels. Раtients were strаtified ...ассоrding tо by serum 25‐hydroxy‐vitamin D (25(OH)Vit‐D) levels intо twо grоuрs, that is, 25(OH)Vit‐D less thаn 40 nmol/L аnd 25(OH)Vit‐D greаter thаn 40 nmol/L. А tоtаl оf 231 раtients were inсluded. Оf these, 120 (50.2%) оf the раtients hаd 25(OH)Vit‐D levels greаter thаn 40 nmol/L. The meаn аge wаs 49 ± 17 yeаrs, аnd 67% оf the раtients were mаles. The mediаn length оf оverаll hоsрitаl stаy wаs 18 6; 53 dаys. The remаining 119 (49.8%) раtients hаd а 25(OH)Vit‐D less thаn 40 nmol/L. Vitamin D levels were seen as deficient in 63% of patients, insufficient in 25% and normal in 12%. Оverаll mоrtаlity wаs 17 раtients (7.1%) but statistically not signifiсаnt among the grоuрs (p = 0.986). The Kарlаn–Meier survivаl аnаlysis shоwed no significance based on an alpha of 0.05, LL = 0.36, df = 1, p = 0.548, indicating Vitamin_D_Levels was not able to adequately predict the hazard of Mortality. In this study, serum 25(OH)Vit‐D levels were found have no significance in terms of predicting the in‐hоsрitаl mortality in раtients with SАRS‐СоV‐2.
Highlights
This is one among a very few studies which show serum Vitamin‐D levels have no role in predicting the in‐hospital mortality in раtients with SARS‐CoV‐2.
Background
Frailty, a state of vulnerability to stressors resulting from loss of physiological reserve due to multisystemic dysfunction, is common among hospitalized older adults. Hospital clinicians ...need objective and practical instruments that identify older adults with frailty. The FI‐LAB is based on laboratory values and vital signs and may capture biological changes of frailty that predispose hospitalized older adults to complications. The study's aim was to assess the association of the FI‐LAB versus VA‐FI with hospital and post‐hospital clinical outcomes in older adults.
Methods
Retrospective cohort study was conducted on Veterans aged ≥60 admitted to a VA hospital. We identified acute hospitalizations January 2011‐December‐2014 with 1‐year follow‐up. A 31‐item FI‐LAB was created from blood laboratory tests and vital signs collected within the first 48 h of admission and scores were categorized as low (<0.25), moderate (0.25–0.40), and high (>0.40). For each FI‐LAB group, we obtained odds ratio (OR) and confidence intervals (CI) for hospital and post‐hospital outcomes using multivariate binomial logistic regression. Additionally, we calculated hazard ratios (HR) and CI for all‐cause in‐hospital mortality comparing the high and moderate FI‐LAB group with the low group.
Results
Patients were 1407 Veterans, mean age 72.7 (SD = 9.0), 67.8% Caucasian, 96.1% males, 47.0% (n = 661), 41.0% (n = 577), and 12.0% (n = 169) were in the low, moderate, and high FI‐LAB groups, respectively. Moderate and high scores were associated with prolonged LOS, OR:1.62 (95% CI:1.29–2.03); and 3.36 (95% CI:2.27–4.99), ICU admission, OR:1.40 (95% CI:1.03–1.90); and OR:2.00 (95% CI:1.33–3.02), nursing home placement OR:2.36 (95% CI:1.26–4.44); and 5.99 (95% CI:2.83–12.70), 30‐day readmissions OR:1.74 (95% CI:1.20–2.52); and 2.20 (95% CI:1.30–3.74), 30‐day mortality OR: 2.51 (95% CI:1.01–6.23); and 8.97 (95% CI:3.42–23.53), 6‐month mortality OR:3.00 (95% CI:1.90–4.74); and 6.16 (95% CI:3.55–10.71), and 1‐year mortality OR: 2.66 (95% CI:1.87–3.79); and 4.76 (95% CI:3.00–7.54) respectively. The high FI‐LAB group showed higher risk of in‐hospital mortality, HR:18.17 (95% CI:4.01–80.52) with an area‐under‐the‐curve of 0.843 (95% CI:0.75–0.93).
Conclusions
High and moderate FI‐LAB scores were associated with worse in‐hospital and post‐hospital outcomes. The FI‐LAB may identify hospitalized older patients with frailty at higher risk and assist clinicians in implementing strategies to improve outcomes.
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