Abstract Background The serum surfactant protein D (SP-D) level is suggested to be a useful biomarker for acute lung injuries and acute respiratory distress syndrome. Whether the serum SP-D level could identify the severity of coronavirus disease 2019 (COVID-19) in the early stage has not been elucidated. Methods We performed an observational study on 39 laboratory-confirmed COVID-19 patients from The Fourth People’s Hospital of Yiyang, Hunan, China. Receiver operating characteristic (ROC) curve analysis, correlation analysis, and multivariate logistic regression model analysis were performed. Results In the acute phase, the serum levels of SP-D were elevated significantly in severe COVID-19 patients than in mild cases (mean value ± standard deviation (SD), 449.7 ± 125.8 vs 245.9 ± 90.0 ng/mL, P <0.001), while the serum levels of SP-D in the recovery period were decreased dramatically than that in the acute phase (mean value ± SD, 129.5 ± 51.7 vs 292.9 ± 130.7 ng/ml, P <0.001), and so were for the stratified patients. The chest CT imaging scores were considerably higher in the severe group compared with those in the mild group (median value, 10.0 vs 9.0, P = 0.011), while markedly lower in the recovery period than those in the acute phase (median value, 2.0 vs 9.0, P <0.001), and so were for the stratified patients. ROC curve analysis revealed that areas under the curve of lymphocyte counts (LYM), C-reaction protein (CRP), erythrocyte sedimentation rate (ESR), interleukin-6 (IL-6), and SP-D for severe COVID-19 were 0.719, 0.833, 0.817, 0.837, and 0.922, respectively. Correlation analysis showed that the SP-D levels were negatively correlated with LYM (r = − 0.320, P = 0.047), while positively correlated with CRP (r = 0.658, P <0.001), IL-6 (r = 0.471, P = 0.002), the duration of nucleic acid of throat swab turning negative (r = 0.668, P <0.001), chest CT imaging score on admission (r = 0.695, P <0.001) and length of stay (r = 0.420, P = 0.008). Multivariate logistic regression model analysis showed that age ( P = 0.041, OR = 1.093) and SP-D ( P = 0.008, OR = 1.018) were risk factors for severe COVID-19. Conclusions Elevated serum SP-D level was a potential biomarker for the severity of COVID-19; this may be useful in identifying patients whose condition worsens at an early stage.
Abstract Objectives The coronavirus disease 2019 (COVID‐19) pandemic has severely affected nursing home residents. Given the continued high incidence of COVID‐19, and the likelihood that new variants and other infectious agents may cause future outbreaks, we sought to understand the relationship of nursing home quality ratings and measures of COVID‐19 outbreak severity and persistence. Design We analyzed nursing home facility‐level data on COVID‐19 cases and deaths, county‐level COVID‐19 rates, and nursing home data from the Centers for Medicare & Medicaid Services (CMS), including ratings from the CMS Nursing Home Five‐Star Quality Rating System. We used regression analysis to examine the association between star ratings and cumulative COVID‐19 incidence and mortality as well as persistent high resident incidence. Setting All nursing homes in the CMS COVID‐19 Nursing Home Dataset reporting data that passed quality assurance checks for at least 20 weeks and that were included in the January 2021 Nursing Home Care Compare update. Participants Residents of the included nursing homes. Measurements Cumulative resident COVID‐19 incidence and mortality through January 10, 2021; number of weeks with weekly resident incidence of COVID‐19 in the top decile nationally. Results As of January 10, 2021, nearly all nursing homes (93.6%) had reported at least one case of COVID‐19 among their residents, more than three‐quarters (76.9%) had reported at least one resident death, and most (83.5%) had experienced at least 1 week in the top decile of weekly incidence. In analyses adjusted for facility and county‐level characteristics, we found generally consistent relationships between higher nursing home quality ratings and lower COVID‐19 incidence and mortality, as well as with fewer high‐incidence weeks. Conclusion Nursing home quality ratings are associated with COVID‐19 incidence, mortality, and persistence. Nursing homes receiving five‐star ratings, for overall quality as well as for each domain, had lower COVID‐19 rates among their residents.
Abstract In a retrospective study of 39 COVID-19 patients and 32 control participants in China, we collected clinical data and examined the expression of endothelial cell adhesion molecules by enzyme-linked immunosorbent assays. Serum levels of fractalkine, vascular cell adhesion molecule-1 (VCAM-1), intercellular adhesion molecule 1 (ICAM-1), and vascular adhesion protein-1 (VAP-1) were elevated in patients with mild disease, dramatically elevated in severe cases, and decreased in the convalescence phase. We conclude the increased expression of endothelial cell adhesion molecules is related to COVID-19 disease severity and may contribute to coagulation dysfunction.
Abstract CMS strives to reduce costs and improve care for nursing home (NH) residents by reducing acute care transfers. We used a national database of Medicare claims and the Minimum Data Set to build NH stays from July 2017 through June 2018 and identify dates of hospital admissions and emergency department visits without hospitalization (ED) among all residents. We calculated rates of 30-day re-hospitalization and ED among short-stay (rehabilitation) residents, and the number of hospitalizations or ED per long-stay resident day (LSRD), then examined associations with NH Five-Star ratings (data.medicare.gov) and other provider characteristics available from Medicare administrative data. We identified 1.79 million short-stays and 898,290 long-stays at 15,576 NHs. Nationally, the 30-day re-hospitalization rate is 22.6%, the short-stay ED rate is 12.0%, there was one hospitalization every 561 LSRD (1.8 per 1000 LSRD), and there was one ED every 617 LSRD (1.6 per 1000 LSRD). Median facility rates were 22.3% (IQR=17.8%, 27.1%) for 30-day re-hospitalizations, 12.0% (IQR=8.7%, 16.1%) for short-stay EDs, 1.6 hospitalizations per 1000 LSRD (IQR=1.1, 2.3), and 1.4 ED per 1000 LSRD (IQR =0.9, 2.2). Higher rates were strongly associated with lower Five-Star ratings, particularly staffing ratings, and larger, for-profit, non-hospital facilities; even after risk-adjustment. NH variation and associations with provider characteristics suggest it is possible to further reduce acute care transfers. CMS incorporated these measures into the Five-Star rating system, providing greater transparency for residents and possibly incentivizing NHs to improve through competition. Future research should monitor success or identify the need for other avenues to improve.
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Research Objective The Oncology Care Model (OCM) is a six‐year episode‐based alternative payment model for cancer care launched by the Centers for Medicare & Medicaid Services in July 2016. OCM includes several elements intended to improve end‐of‐life (EOL) care. We evaluated the impact of OCM on EOL care intensity, spending, and oncologist and patient experiences. Study Design Using 100% Medicare claims (2014–2019) we employed a Difference‐in‐Differences (DID) approach comparing changes over time in care intensity and Medicare payments at the end of life, for beneficiaries served by OCM practices and by a propensity‐score matched comparison group of non‐participating practices. We also surveyed caregivers of deceased beneficiaries about patient experiences in the last month of life, and we surveyed oncologists from OCM practices about changes in palliative and EOL care. Finally, we conducted case studies with over 40 OCM practices. Population Studied Claims‐based analyses included 256,102 Medicare beneficiaries in OCM or comparison practices who underwent chemotherapy for cancer and died during or within 90 days of their last OCM‐defined episode. Surveys were completed by family members of 5786 deceased beneficiaries (55% OCM, 45% comparison) and by 400 oncologists working in OCM practices. Principal Findings OCM led to fewer hospitalization in the last 30 days of life for deceased OCM versus comparison beneficiaries (DID:‐11 per 1000 beneficiaries (90%CI:‐19, −4). OCM had no impact on outpatient emergency department use in the last month of life, use of infused chemotherapy in the last two weeks of life, or on hospice use, duration, or timing. The average Medicare Part A payments during the last episode for deceased beneficiaries rose $440 less in the OCM group than in comparisons, a 2.4 percent relative reduction from the OCM baseline mean of $18,530 (p ≤ 0.05). OCM had no impact on average total episode payments, or on Medicare Part B or D payments, during deceased beneficiaries' last episodes. OCM did not affect caregivers' perceptions: survey respondents rated EOL care highly before OCM began, and there were no changes over time and no differences between OCM and comparison respondents. Roughly one third of oncologists reported enhancing access to palliative care (36%) and using new/enhanced standards or guidelines to trigger discussions about EOL goals and hospice (32%). Most oncologists (55%) reported that OCM improves quality of EOL care. Conclusions OCM led to a small relative reduction in hospitalizations during deceased beneficiaries' last month of life and a corresponding relative decrease in Medicare Part A payments. OCM had no impact on hospice use, duration, or timing. OCM had no impact on beneficiaries' care experiences at the end of life. Oncologists reported EOL process improvements attributable to OCM. Implications for Policy or Practice OCM emphasizes shared decision making and advance care planning to ensure that cancer beneficiaries' EOL wishes are documented and followed. The first three years of OCM suggest that these efforts led to small relative reductions in hospitalizations and Part A payments in the last month of life. The lack of impact on hospice use/timing, despite clinician‐reported EOL care process improvements, suggests ongoing areas for potential improvements. Primary Funding Source Centers for Medicare and Medicaid Services.
Abstract
BACKGROUND Coronavirus disease 2019 (COVID-19) is highly contagious and deadly and is associated with coagulopathy. Pentraxin-3(PTX3) participates in innate resistance to infections and plays a role in thrombogenesis.
PURPOSE The present study aimed to investigate the role of PTX3 in coagulopathy in patients with COVID-19.
METHODS A retrospective study including thirty-nine COVID-19 patients enrolled in Hunan, China were performed. The patients were classified into the D-dimer_L (D-dimer?1mg/L) and D-dimer_H (D-dimer?1mg/L) groups basing on the plasma D-dimer levels on admission. Serum PTX3 levels were detected by enzyme-linked immunosorbent assays and compared between those two groups, and then linear regression models were applied to analyze the association between PTX3 and D-dimer.
RESULTS Our results showed that serum PTX3 levels (median values, 10.21 vs 3.36, P < 0.001), chest computerized tomography scores (median values, 10.0 vs 9.0, P < 0.05), and length of stay (16.0±4.2 vs 10.7±3.6, P = 0.001) in the D-dimer_H group were significantly higher than that in D-dimer_L group. The coefficient of determination for PTX3 was 0.651 (P < 0.001) in the D-dimer_H group.
CONCLUSION Serum level of PTX3 was positively correlated with disease severity and coagulopathy. Detection of serum PTX3 level could assist to identify severer patients on admission and may be a potential therapeutic target for coagulopathy in patients with COVID-19.
Abstract Background The effects of cryptococcemia on patient outcomes in those with or without HIV remain unclear. Methods One hundred and seventy‐nine cryptococcemia patients were enrolled in this retrospective study. Demographic characteristics, blood test results and outcome were compared between the two groups. Results The diagnosis time of Cryptococcus infection was 2.0(0‐6.0) days for HIV‐infected patients, 5.0 (1.5‐8.0) days for HIV‐uninfected patients ( p = .008), 2.0 (1.0‐6.0) days for cryptococcal meningitis (CM) patients and 6.0 (5.0‐8.0) days for non‐CM patients ( p < .001). HIV infection [adjusted odds ratio (AOR) (95% confidence interval): 6.0(2.3‐15.9)], CRP < 15 mg/L [AOR:3.7(1.7‐8.1)) and haemoglobin > 110 g/L [AOR:2.5(1.2‐5.4)] were risk factors for CM development. Forty‐six (25.7%) patients died within 90 days. ICU stay [AOR:2.8(1.1‐7.1)], hypoalbuminemia [AOR:2.7(1.4‐5.3)], no anti‐cryptococcal treatment [AOR:4.7(1.9‐11.7)] and altered consciousness [AOR:2.4(1.0‐5.5)] were independent risk factors for 90‐day mortality in all patients. HIV infection did not increase the 90‐day mortality of cryptococcemia patients when anti‐ Cryptococcus treatment was available. Non‐Amphotericin B treatment [AOR:3.4(1.0‐11.2)] was associated with 90‐day mortality in HIV‐infected patients, but age ≥ 50.0 years old [AOR:2.7(1.0‐2.9)], predisposing disease [AOR:4.1(1.2‐14.2)] and altered consciousness [AOR:3.7(1.1‐12.9)] were associated with 90‐day mortality in HIV‐uninfected patients who accepted anti‐ Cryptococcus treatment. Conclusion HIV infection increased the incidence of CM rather than mortality in cryptococcemia patients. The predictive model was completely divergent in HIV‐infected and HIV‐uninfected patients, suggesting that novel strategies for diagnosis and treatment algorithms are urgently needed.
Two defining features of the nursing home industry are the tremendous churn in chain ownership and the perception of low-quality care at many facilities. We examined whether nursing homes that underwent chain-related transactions, such as mergers and acquisitions, experienced a larger number of health deficiency citations than nursing homes that maintained common ownership over the same period. Using facility-level data for the period 1993-2010, we found that those nursing homes that underwent chain-related transactions had more deficiency citations in the years preceding and following a transaction than those nursing homes that maintained common ownership. Thus, we did not find that these transactions led to a decline in quality. Instead, we found that chains targeted nursing homes that were already having quality problems and that these problems persisted after the transaction. Given the high frequency of nursing home chain transactions, policy makers will need to continue to invest in tracking, reporting, and overseeing these transactions. One important step would be to report more detailed data on chain ownership, transactions, and aggregate chain quality on the Nursing Home Compare website, the federal government's online report card for nursing homes.
To the Editor—Causal relationships between risk factors and outcomes are almost impossible to determine following traditional statistical analysis because the related confounding factors are difficult to identify and measure. To eliminate the influence of confounding factors, Mendelian randomization (MR) analysis uses genetic variants to infer causality [1]. With great interest, we read the recent article by Ran and colleagues [2] exploring the causal association between coronavirus disease 2019 (COVID-19) and blood constituents. In this MR analysis–based study, Ran et al determined the causal effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on platelet/endothelial cell adhesion molecule 1, which are consistent with the studies of Li and colleagues [3] and our previous studies [4], thus further supporting the role of endothelial dysfunction in the pathogenesis of COVID-19. Moreover, the findings that SARS-CoV-2 infection is causally associated with eosinophil cell count,...
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