Coronavirus Disease 2019 In-hospital Mortality Research Articles

Impact of Diabetes Mellitus On In-Hospital Mortality of COVID-19 Patients in Japan Since COVID-19 Became a Common Infectious Disease.

The number of severe cases of coronavirus disease 2019 (COVID-19) has been decreasing since the emergence of the Omicron variant at the end of 2021. COVID-19 has become a common infectious disease in Japan and was downgraded to a category five infectious disease on May 8, 2023. This study aimed to compare the impact of diabetes mellitus on in-hospital mortality in COVID-19 patients since COVID-19 became a common infectious disease. We conducted a retrospective observational study using data from an advanced critical care center in Osaka, Japan. The study included 1,381 patients of COVID-19 admitted to the center between March 1, 2020, and May 7, 2023, before COVID-19 became a category five infectious disease in Japan. Individuals younger than 18 years and pregnant women were excluded. We divided the patients into two groups: pre- and post-Omicron epidemic groups. The primary endpoint of the study was the in-hospital mortality, and the prognostic impact of diabetes mellitus was compared between the groups. The Kaplan-Meier curve showed a significantly lower rate of in-hospital mortality in the post-Omicron epidemic group than in the pre-Omicron epidemic group. The hazard ratio (HR) was 1.83 (95% CI, 1.36-2.50; p < 0.0001). Patients with diabetes mellitus had higher in-hospital mortality in both the pre- and post-Omicron epidemic groups; their HRs were 1.39 (95% CI, 1.21-1.59; p < 0.0001) and 1.45 (95% CI, 1.15-1.83; p = 0.0012), respectively. Diabetes mellitus had no significant interaction effect on the association between the post-Omicron epidemic and in-hospital mortality (p for interaction = 0.2154). Diabetes mellitus may continue contributing to COVID-19 in-hospital mortality in the future, as the Omicron sub-strain may still be prevalent.

Management of immunosuppression in lung transplant recipients and COVID-19 outcomes: an observational retrospective cohort-study

BackgroundThe aim of this study was to assess the impact of immunosuppression management on coronavirus disease 2019 (COVID-19) outcomes.MethodsWe performed a single-center retrospective study in a cohort of 358 lung transplant recipients (LTx) over the period from March 2020 to April 2022. All included symptomatic patients had at least one positive SARS-CoV-2 rt-PCR. We used a composite primary outcome for COVID-19 including increased need for oxygen since the hospital admission, ICU transfer, and in-hospital mortality. We assessed by univariate and multivariate analyses the risk factors for poor outcomes.ResultsOverall, we included 91 LTx who contracted COVID-19. The COVID-19 in-hospital mortality rate reached 4.4%. By hierarchical clustering, we found a strong and independent association between the composite poor outcome and the discontinuation of at least one immunosuppressive molecule among tacrolimus, cyclosporine, mycophenolate mofetil, and everolimus. Obesity (OR = 16, 95%CI (1.96; 167), p = 0.01) and chronic renal failure (OR = 4.6, 95%CI (1.4; 18), p = 0.01) were also independently associated with the composite poor outcome. Conversely, full vaccination was protective (OR = 0.23, 95%CI (0.046; 0.89), p = 0.047).ConclusionThe administration of immunosuppressive drugs such as tacrolimus, cyclocporine or everolimus can have a protective effect in LTx with COVID-19, probably related to their intrinsic antiviral capacity.

COVID-19 severity and in-hospital mortality in an area with high HIV prevalence.

HIV infection causes immune dysregulation affecting T-cell and monocyte function, which may alter coronavirus disease 2019 (COVID-19) pathophysiology. We investigated the associations among clinical phenotypes, laboratory biomarkers, and hospitalisation outcomes in a cohort of people hospitalised with COVID-19 in a high HIV prevalence area. We conducted a prospective observational cohort study in Tshwane, South Africa. Respiratory disease severity was quantified using the respiratory oxygenation score. Analysed biomarkers included inflammatory and coagulation biomarkers, CD4 T-cell counts, and HIV-1 viral loads (HIVVL). The analysis included 558 patients, of whom 21.7% died during admission. The mean age was 54 years. A total of 82 participants were HIV-positive. People living with HIV (PLWH) were younger (mean age 46 years) than HIV-negative people; most were on antiretroviral treatment with a suppressed HIVVL (72%) and the median CD4 count was 159 (interquartile range: 66-397) cells/µL. After adjusting for age, HIV was not associated with increased risk of mortality during hospitalisation (age-adjusted hazard ratio = 1.1, 95% confidence interval: 0.6-2.0). Inflammatory biomarker levels were similar in PLWH and HIV-negative patients. Detectable HIVVL was associated with less severe respiratory disease. In PLWH, mortality was associated with higher levels of inflammatory biomarkers. Opportunistic infections, and other risk factors for severe COVID-19, were common in PLWH who died. PLWH were not at increased risk of mortality and those with detectable HIVVL had less severe respiratory disease than those with suppressed HIVVL. This study advances our understanding of severe COVID-19 in PLWH.

Validation of the T-Lymphocyte Subset Index (TLSI) as a Score to Predict Mortality in Unvaccinated Hospitalized COVID-19 Patients.

Lymphopenia has been consistently reported as associated with severe coronavirus disease 2019 (COVID-19). Several studies have described a profound decline in all T-cell subtypes in hospitalized patients with severe and critical COVID-19. The aim of this study was to assess the role of T-lymphocyte subset absolute counts measured at ward admission in predicting 30-day mortality in COVID-19 hospitalized patients, validating a new prognostic score, the T-Lymphocyte Subset Index (TLSI, range 0-2), based on the number of T-cell subset (CD4+ and CD8+) absolute counts that are below prespecified cutoffs. These cutoff values derive from a previously published work of our research group at Policlinico Tor Vergata, Rome, Italy: CD3+CD4+ &lt; 369 cells/μL, CD3+CD8+ &lt; 194 cells/μL. In the present single-center retrospective study, T-cell subsets were assessed on admission to the infectious diseases ward. Statistical analysis was performed using JASP (Version 0.16.2. JASP Team, 2022, Amsterdam, The Netherlands) and Prism8 (version 8.2.1. GraphPad Software, San Diego, CA, USA). Clinical and laboratory parameters of 296 adult patients hospitalized because of COVID-19 were analyzed. The overall mortality rate was 22.3% (66/296). Survivors (S) had a statistically significant lower TLSI score compared to non-survivors (NS) (p &lt; 0.001). Patients with increasing TLSI scores had proportionally higher rates of 30-day mortality (p &lt; 0.0001). In the multivariable logistic analysis, the TLSI was an independent predictor of in-hospital 30-day mortality (OR: 1.893, p = 0.003). Survival analysis showed that patients with a TLSI &gt; 0 had an increased risk of death compared to patients with a TLSI = 0 (hazard ratio: 2.83, p &lt; 0.0001). The TLSI was confirmed as an early and independent predictor of COVID-19 in-hospital 30-day mortality.

Characteristics of hospitalised COVID-19 patients during the first two pandemic waves, Gauteng.

BackgroundGauteng province (GP) was one of the most affected provinces in the country during the first two pandemic waves in South Africa. We aimed to describe the characteristics of coronavirus disease 2019 (COVID-19) patients admitted in one of the largest quaternary hospitals in GP during the first two waves.ObjectivesStudy objectives were to determine factors associated with hospital admission during the second wave and to describe factors associated with in-hospital COVID-19 mortality.MethodData from a national hospital-based surveillance system of COVID-19 hospitalisations were used. Multivariable logistic regression models were conducted to compare patients hospitalised during wave 1 and wave 2, and to determine factors associated with in-hospital mortality.ResultsThe case fatality ratio was the highest (39.95%) during wave 2. Factors associated with hospitalisation included age groups 40–59 years (adjusted odds ratio [aOR]: 2.14, 95% confidence interval [CI]: 1.08–4.27), 60–79 years (aOR: 2.49, 95% CI: 1.23–5.02) and ≥ 80 years (aOR: 3.39, 95% CI: 1.35–8.49). Factors associated with in–hospital mortality included age groups 60–79 years (aOR: 2.55, 95% CI: 1.11–5.84) and ≥ 80 years (aOR: 5.66, 95% CI: 2.12–15.08); male sex (aOR: 1.56, 95% CI: 1.22–1.99); presence of an underlying comorbidity (aOR: 1.76, 95% CI: 1.37–2.26), as well as being admitted during post–wave 2 (aOR: 2.42, 95% CI: 1.33–4.42).ConclusionCompared to the recent omicron-driven pandemic waves characterised by lower admission rates and less disease severity among younger patients, COVID-19 in-hospital mortality during the earlier waves was associated with older age, being male and having an underlying comorbidity.ContributionThis study showed how an active surveillance system can contribute towards identifying changes in disease trends.

Impact of cardiac and acute kidney injury on COVID-19 in-hospital mortality

Background and aimThe severity of Coronavirus Disease 2019 (COVID-19) is a multifactorial condition. Cardiac and acute kidney injury (AKI) are two complications commonly reported in severe forms of COVID-19. We aimed to investigate the effect of these tow complications on the COVID-19 in-hospital mortality.Materials and methodsThis is a prospective study, including 120 severe cases of COVID-19, admitted at the university hospital of Blida. Troponin was assessed by an immuno-fluoroassay method. AKI was defined according to the KDIGO-2012 guidelines. The association with in-hospital mortality was assessed using the Kaplan–Meier survival curve, proportional Cox regression analyses and the receiver operating characteristic curve.ResultsCardiac and acute kidney injury were very common, occurring in 19% and 25% of patients. When analyzing survival, both were significantly associated with in-hospital mortality (pLogRank < 0.0001). A cutoff value of 9.6 ng/mL for troponin and 13.9 mg/L for creatinine could predict poor prognosis with a sensitivity of 73% and 67%, and a specificity of 62% and 64%, respectively. Hazard ratios were (HR = 3.5, 95% CI [1.7–7.3], P = 0.001 and HR = 3.14, 95% CI [1.6–6.1], P = 0.001) for troponin cutoff and AKI respectively.ConclusionThis study demonstrates the high frequency of cardiac and acute kidney injury in severe COVID-19 patients and provides further evidence of their potential link to poor short-term prognosis.

Disseminated Intravascular Coagulation Score and Sepsis-induced Coagulopathy Score in Prediction of COVID-19 Severity: A Retrospective Analysis.

BackgroundThe novel disseminated intravascular coagulation (DIC) score (platelet count, prolonged prothrombin time, D-dimer, and fibrinogen) and sepsis-induced coagulopathy (SIC) score (platelet count, international normalized ratio, and sequential organ failure assessment score) are markers of coagulopathy, which, for the first time, are explored in line with the coronavirus disease-2019 (COVID-19) disease outcomes. The correlation of D-dimer with these findings is also studied.Materials and methodsA retrospective analysis of hospital-based records of 168 COVID-19 patients was done. Data including D-dimer, routine investigations, DIC, and SIC scorings (all within 3 days of admission) were collected and correlated with the outcomes. The study was conducted in a tertiary care center catering to North India's population.ResultsHigher DIC score (1.59 ± 1.18 vs 0.96 ± 1.18), SIC score (1.60 ± 0.89 vs 0.63 ± 0.99), and D-dimer titers (1321.33 ± 1627.89 vs 583·66 ± 777.71 ng/mL) were significantly associated with severe COVID-19 disease (p <0.05). DIC score and SIC score ≥1, and D-dimer ≥1315 ng/mL for severe disease; DIC score ≥1, SIC score ≥2, and D-dimer ≥600 ng/mL for pulmonary embolism (PE); and DIC score and SIC score ≥1, and D-dimer level ≥990 ng/mL for mortality were the respective cutoff values we found from our study.ConclusionHigher DIC scores, SIC scores, and D-dimer values are associated with severe COVID-19 disease, inhospital mortality, and PE risk. They can serve as easily accessible early markers of severe disease and prioritize hospital admissions in the presently overburdened scenario and may be used to develop prognostic prediction models.How to cite this articleKapoor M, Panda PK, Saini LK, Bahurupi Y. Disseminated Intravascular Coagulation Score and Sepsis-induced Coagulopathy Score in Prediction of COVID-19 Severity: A Retrospective Analysis. Indian J Crit Care Med 2021;25(12):1357–1363.

Lung Ultrasound Severity Index: Development and Usefulness in Patients with Suspected SARS-Cov-2 Pneumonia-A Prospective Study.

Coronavirus disease 2019 (COVID-19) has spread across the world with a strong impact on populations and health systems. Lung ultrasound is increasingly employed in clinical practice but a standard approach and data on the accuracy of lung ultrasound are still needed. Our study's objective was to evaluate lung ultrasound diagnostic and prognostic characteristics in patients with suspected COVID-19. We conducted a monocentric, prospective, observational study. Patients with respiratory distress and suspected COVID-19 consecutively admitted to the Emergency Medicine Unit were enrolled. Lung ultrasound examinations were performed blindly to clinical data. Outcomes were diagnosis of COVID-19 pneumonia and in-hospital mortality. One hundred fifty-nine patients were included in our study; 66% were males and 63.5% had a final diagnosis of COVID-19. COVID-19 patients had a higher mortality rate (18.8% vs. 6.9%, p = 0.04) and Lung Ultrasound Severity Index (16.14 [8.71] vs. 10.08 [8.92], p < 0.001) compared with non-COVID-19 patients. This model proved able to distinguish between positive and negative cases with an area under the receiver operating characteristic (AUROC) equal to 0.72 (95% confidence interval [CI]: 0.64–0.78) and to predict in-hospital mortality with an AUROC equal to 0.81 (95% CI: 0.74–0.86) in the whole population and an AUROC equal to 0.76 (95% CI: 0.66–0.84) in COVID-19 patients. The Lung Ultrasound Severity Index can be a useful tool in diagnosing COVID-19 in patients with a high pretest probability of having the disease and to identify, among them, those with a worse prognosis.

Race, Ethnicity, Neighborhood Characteristics, and In-Hospital Coronavirus Disease-2019 Mortality.

Despite many studies reporting disparities in coronavirus disease-2019 (COVID-19) incidence and outcomes in Black and Hispanic/Latino populations, mechanisms are not fully understood to inform mitigation strategies. The aim was to test whether neighborhood factors beyond individual patient-level factors are associated with in-hospital mortality from COVID-19. We hypothesized that the Area Deprivation Index (ADI), a neighborhood census-block-level composite measure, was associated with COVID-19 mortality independently of race, ethnicity, and other patient factors. Multicenter retrospective cohort study examining COVID-19 in-hospital mortality. Inclusion required hospitalization with positive SARS-CoV-2 test or COVID-19 diagnosis at three large Midwestern academic centers. The primary study outcome was COVID-19 in-hospital mortality. Patient-level predictors included age, sex, race, insurance, body mass index, comorbidities, and ventilation. Neighborhoods were examined through the national ADI neighborhood deprivation rank comparing in-hospital mortality across ADI quintiles. Analyses used multivariable logistic regression with fixed site effects. Among 5999 COVID-19 patients median age was 61 (interquartile range: 44-73), 48% were male, 30% Black, and 10.8% died. Among patients who died, 32% lived in the most disadvantaged quintile while 11% lived in the least disadvantaged quintile; 52% of Black, 24% of Hispanic/Latino, and 8.5% of White patients lived in the most disadvantaged neighborhoods.Living in the most disadvantaged neighborhood quintile predicted higher mortality (adjusted odds ratio: 1.74; 95% confidence interval: 1.13-2.67) independent of race. Age, male sex, Medicare coverage, and ventilation also predicted mortality. Neighborhood disadvantage independently predicted in-hospital COVID-19 mortality. Findings support calls to consider neighborhood measures for vaccine distribution and policies to mitigate disparities.

Sex Differences on Clinical Characteristics, Severity, and Mortality in Adult Patients With COVID-19: A Multicentre Retrospective Study.

Background: Coronavirus disease-2019 (COVID-19) epidemic is spreading globally. Sex differences in the severity and mortality of COVID-19 emerged. This study aims to describe the impact of sex on outcomes in COVOD-19 with a special focus on the effect of estrogen.Methods: We performed a retrospective cohort study which included 413 patients (230 males and 183 females) with COVID-19 from three designated hospitals in China with a follow up time from January 31, 2020, to April 17, 2020. Women over 55 were considered as postmenopausal patients according to the previous epidemiological data from China. The interaction between age and sex on in-hospital mortality was determined through Cox regression analysis. In addition, multivariate Cox regression models were performed to explore risk factors associated with in-hospital mortality of COVID-19.Results: Age and sex had significant interaction for the in-hospital mortality (P < 0.001). Multivariate Cox regression showed that age (HR 1.041, 95% CI 1.009–1.073, P = 0.012), male sex (HR 2.033, 95% CI 1.007–2.098, P = 0.010), the interaction between age and sex (HR 1.118, 95% CI 1.003–1.232, P = 0.018), and comorbidities (HR 9.845, 95% CI 2.280–42.520, P = 0.002) were independently associated with in-hospital mortality of COVID-19 patients. In this multicentre study, female experienced a lower fatality for COVID-19 than male (4.4 vs. 10.0%, P = 0.031). Interestingly, stratification by age group revealed no difference in-hospital mortality was noted in women under 55 compared with women over 55 (3.8 vs. 5.2%, P = 0.144), as well as in women under 55 compared with the same age men (3.8 vs. 4.0%, P = 0.918). However, there was significantly difference in women over 55 with men of the same age group (5.2 vs. 21.0%, P = 0.007). Compared with male patients, female patients had higher lymphocyte (P < 0.001) and high-density lipoprotein (P < 0.001), lower high sensitive c reaction protein level (P < 0.001), and lower incidence rate of acute cardiac injury (6.6 vs. 13.5%, P = 0.022).Conclusion: Male sex is an independent risk factor for COVID-19 in-hospital mortality. Although female mortality in COVID-19 is lower than male, it might not be directly related to the effect of estrogen. Further study is warranted to identify the sex difference in COVID-19 and mechanisms involved.

Sociodemographic factors associated with COVID-19 in-hospital mortality in Brazil

ObjectivesThe coronavirus disease 2019 (COVID-19) pandemic has highlighted inequalities in access to healthcare systems, increasing racial disparities and worsening health outcomes in these populations. This study analysed the association between sociodemographic characteristics and COVID-19 in-hospital mortality in Brazil. Study designA retrospective analysis was conducted on quantitative reverse transcription polymerase chain reaction–confirmed hospitalised adult patients with COVID-19 with a defined outcome (i.e. hospital discharge or death) in Brazil. Data were retrieved from the national surveillance system database (SIVEP-Gripe) between February 16 and August 8, 2020. MethodsClinical characteristics, sociodemographic variables, use of hospital resources and outcomes of hospitalised adult patients with COVID-19, stratified by self-reported race, were investigated. The primary outcome was in-hospital mortality. The association between self-reported race and in-hospital mortality, after adjusting for clinical characteristics and comorbidities, was evaluated using a logistic regression model. ResultsDuring the study period, Brazil had 3,018,397 confirmed COVID-19 cases and 100,648 deaths. The study population included 228,196 COVID-19–positive adult in-hospital patients with a defined outcome; the median age was 61 years, 57% were men, 35% (79,914) self-reported as Black/Brown and 35.4% (80,853) self-reported as White. The total in-hospital mortality was 37% (85,171/228,196). Black/Brown patients showed higher in-hospital mortality than White patients (42% vs 37%, respectively), were admitted less frequently to the intensive care unit (ICU) (32% vs 36%, respectively) and used more invasive mechanical ventilation (21% vs 19%, respectively), especially outside the ICU (17% vs 11%, respectively). Black/Brown race was independently associated with high in-hospital mortality after adjusting for sex, age, level of education, region of residence and comorbidities (odds ratio = 1.15; 95% confidence interval = 1.09–1.22). ConclusionsAmong hospitalised Brazilian adults with COVID-19, Black/Brown patients showed higher in-hospital mortality, less frequently used hospital resources and had potentially more severe conditions than White patients. Racial disparities in health outcomes and access to health care highlight the need to actively implement strategies to reduce inequities caused by the wider health determinants, ultimately leading to a sustainable change in the health system.

Circulating Von Willebrand factor and high molecular weight multimers as markers of endothelial injury predict COVID-19 in-hospital mortality.

BackgroundCoronavirus disease 2019 (COVID-19) is a respiratory disease associated with endotheliitis and microthrombosis.ObjectivesTo correlate endothelial dysfunction to in-hospital mortality in a bi-centric cohort of COVID-19 adult patients.MethodsConsecutive ambulatory and hospitalized patients with laboratory-confirmed COVID-19 were enrolled. A panel of endothelial biomarkers and von Willebrand factor (VWF) multimers were measured in each patient ≤ 48 h following admission.ResultsStudy enrolled 208 COVID-19 patients of whom 23 were mild outpatients and 189 patients hospitalized after admission. Most of endothelial biomarkers tested were found increased in the 89 critical patients transferred to intensive care unit. However, only von Willebrand factor antigen (VWF:Ag) scaled according to clinical severity, with levels significantly higher in critical patients (median 507%, IQR 428–596) compared to non-critical patients (288%, 230–350, p < 0.0001) or COVID-19 outpatients (144%, 133–198, p = 0.007). Moreover, VWF high molecular weight multimers (HMWM) were significantly higher in critical patients (median ratio 1.18, IQR 0.86–1.09) compared to non-critical patients (0.96, 1.04–1.39, p < 0.001). Among all endothelial biomarkers measured, ROC curve analysis identified a VWF:Ag cut-off of 423% as the best predictor for in-hospital mortality. The accuracy of VWF:Ag was further confirmed in a Kaplan–Meier estimator analysis and a Cox proportional Hazard model adjusted on age, BMI, C-reactive protein and d-dimer levels.ConclusionVWF:Ag is a relevant predictive factor for in-hospital mortality in COVID-19 patients. More than a biomarker, we hypothesize that VWF, including excess of HMWM forms, drives microthrombosis in COVID-19.

COVID-19 in-hospital mortality and mode of death in a dynamic and non-restricted tertiary care model in Germany.

Reported mortality of hospitalised Coronavirus Disease-2019 (COVID-19) patients varies substantially, particularly in critically ill patients. So far COVID-19 in-hospital mortality and modes of death under state of the art care have not been systematically studied. This retrospective observational monocenter cohort study was performed after implementation of a non-restricted, dynamic tertiary care model at the University Medical Center Freiburg, an experienced acute respiratory distress syndrome (ARDS) and extracorporeal membrane-oxygenation (ECMO) referral center. All hospitalised patients with PCR-confirmed SARS-CoV-2 infection were included. The primary endpoint was in-hospital mortality, secondary endpoints included major complications and modes of death. A multistate analysis and a Cox regression analysis for competing risk models were performed. Modes of death were determined by two independent reviewers. Between February 25, and May 8, 213 patients were included in the analysis. The median age was 65 years, 129 patients (61%) were male. 70 patients (33%) were admitted to the intensive care unit (ICU), of which 57 patients (81%) received mechanical ventilation and 23 patients (33%) ECMO support. Using multistate methodology, the estimated probability to die within 90 days after COVID-19 onset was 24% in the whole cohort. If the levels of care at time of study entry were accounted for, the probabilities to die were 16% if the patient was initially on a regular ward, 47% if in the intensive care unit (ICU) and 57% if mechanical ventilation was required at study entry. Age ≥65 years and male sex were predictors for in-hospital death. Predominant complications-as judged by two independent reviewers-determining modes of death were multi-organ failure, septic shock and thromboembolic and hemorrhagic complications. In a dynamic care model COVID-19-related in-hospital mortality remained very high. In the absence of potent antiviral agents, strategies to alleviate or prevent the identified complications should be investigated. In this context, multistate analyses enable comparison of models-of-care and treatment strategies and allow estimation and allocation of health care resources.

Cytokines and their relationship with the severity and prognosis of coronavirus disease 2019 (COVID-19): a retrospective cohort study

ObjectiveTo delineate the characteristics and clinical significance of plasma inflammatory cytokines altered in COVID-19.DesignRetrospective, single-centre cohort study.SettingTongji Hospital in Wuhan, China.ParticipantsAmong a cohort of 308 patients with a diagnosis of...

Racial Disparities in COVID-19 Hospitalization and In-hospital Mortality at the Height of the New York City Pandemic.

ObjectivesInvestigate whether or not race is associated with differences in hospitalization and survival to discharge among patients with coronavirus disease-2019 (COVID-19) at the height of the pandemic in New York City (NYC).MethodsSingle-center retrospective cohort study of COVID-19 patients hospitalized at our university-affiliated NYC hospital from 3/10/20 through 4/13/20 with follow-up to 5/1/20. Our primary endpoint was hospitalization rate among patients with confirmed COVID-19 compared with the regional population based on race. Our secondary endpoint survival to discharge among hospitalized COVID-19 patients. NYC Department of Health data were used to calculate hospitalization odds ratios. Chi-square and t tests were used to compare categorial and continuous variables, respectively. Cox proportional hazards regression and predictive analysis were used to investigate our endpoints further.ResultsOur cohort of 734 patients included 355 women (48.4%), 372 Blacks (50.7%), 214 Whites (29.2%), and 92 Hispanics (12.5%) in our analysis. Blacks were nearly twice as likely as Whites to require hospitalization for COVID-19 (OR 1.89, 95% CI, 1.59–2.24, p < 0.001). Hispanics were also more likely to suffer in-hospital mortality from COVID-19 compared with Whites (HR 1.84; 95% CI 1.21–2.80; p = 0.005). There was a non-significant increased hazard of in-hospital mortality among Blacks when compared with Whites (HR, 1.30; 95% CI, 0.95–1.78; p = 0.09).Conclusions and RelevanceBlacks were more likely than Whites to require hospitalization for COVID-19 while Hispanics were more likely to experience in-hospital mortality. Further investigation into the socioeconomic factors underlying racial disparities in COVID-19 survival and severity requiring hospitalization is needed on a national scale.

New NICE guidelines for UTI management: what will change?

<h3>Abstract</h3> <h3>Background</h3> In coronavirus disease 2019 (COVID-19), finding sensitive biomarkers is critical for detecting severe cases early and intervening effectively. <h3>Objectives</h3> To compare and evaluate the predictive value of C-reactive...