scholarly journals Predictors of severity and mortality among patients hospitalized with COVID-19 in Rhode Island

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252411
Author(s):  
Aakriti Pandita ◽  
Fizza S. Gillani ◽  
Yiyun Shi ◽  
Anna Hardesty ◽  
Meghan McCarthy ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Rhode Island ◽  
Severe Disease ◽  
Patient Characteristics ◽  
Clinical Predictors ◽  
Nursing Facility ◽  
Black Race ◽  
Presenting Symptoms ◽  
Risk Patients ◽  
Baseline Characteristics

Background In order for healthcare systems to prepare for future waves of COVID-19, an in-depth understanding of clinical predictors is essential for efficient triage of hospitalized patients. Methods We performed a retrospective cohort study of 259 patients admitted to our hospitals in Rhode Island to examine differences in baseline characteristics (demographics and comorbidities) as well as presenting symptoms, signs, labs, and imaging findings that predicted disease progression and in-hospital mortality. Results Patients with severe COVID-19 were more likely to be older (p = 0.02), Black (47.2% vs. 32.0%, p = 0.04), admitted from a nursing facility (33.0% vs. 17.9%, p = 0.006), have diabetes (53.9% vs. 30.4%, p<0.001), or have COPD (15.4% vs. 6.6%, p = 0.02). In multivariate regression, Black race (adjusted odds ratio [aOR] 2.0, 95% confidence interval [CI]: 1.1–3.9) and diabetes (aOR 2.2, 95%CI: 1.3–3.9) were independent predictors of severe disease, while older age (aOR 1.04, 95% CI: 1.01–1.07), admission from a nursing facility (aOR 2.7, 95% CI 1.1–6.7), and hematological co-morbidities predicted mortality (aOR 3.4, 95% CI 1.1–10.0). In the first 24 hours, respiratory symptoms (aOR 7.0, 95% CI: 1.4–34.1), hypoxia (aOR 19.9, 95% CI: 2.6–152.5), and hypotension (aOR 2.7, 95% CI) predicted progression to severe disease, while tachypnea (aOR 8.7, 95% CI: 1.1–71.7) and hypotension (aOR 9.0, 95% CI: 3.1–26.1) were associated with increased in-hospital mortality. Conclusions Certain patient characteristics and clinical features can help clinicians with early identification and triage of high-risk patients during subsequent waves of COVID-19.

scholarly journals 518. Factors Associated with Severe COVID-19 among Patients Hospitalized in Rhode Island

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S324-S325
Author(s):  
Aakriti Pandita ◽  
Fizza S Gillani ◽  
Yiyun Shi ◽  
Anna hardesty ◽  
Jad Aridi ◽  
...  
Keyword(s):  
Rhode Island ◽  
Clinical Data ◽  
Severe Disease ◽  
Academic Medical Center ◽  
Invasive Mechanical Ventilation ◽  
Low Flow ◽  
Categorical Variables ◽  
Nursing Facility ◽  
Presenting Symptoms ◽  
Severe Group

Abstract Background To better understand patient factors that impact clinical outcomes in COVID-19, we performed a retrospective cohort study of patients hospitalized with COVID-19 in Rhode Island to identify patient and clinical characteristics associated with severe disease. Methods We analyzed 259 patients admitted to our academic medical center during a three month period with confirmed COVID-19. Clinical data was extracted via chart review and lab results within the first 24 hours of admission were extracted directly from electronic medical records. Patients were divided in two groups based upon the highest level of supplemental oxygen (O2) required during hospitalization: severe COVID-19 (high flow O2, non-invasive, or invasive mechanical ventilation) and non-severe COVID-19 (low flow O2 or no supplemental O2). SAS 9.4 (Cary, NC) was used for statistical analyses. Chi-square or Fisher’s exact tests for categorical variables and the Student’s t-test for continuous variables were used to compare demographics, baseline comorbidities, and clinical data between the severe and non-severe groups. Table 1: Demographics Results Of 259 patients, 166 (64%) had non-severe disease, and 93 (36%) severe disease; median age [IQR] was 62 [51,73]. There were 138(53%) males and 75 (29%) Hispanics. Among non-Hispanics,124(48%) were White, 48(19%) African Americans, and 12(5%) other races. Sixty (23%) were admitted from a nursing facility and the in-hospital mortality rate was 15% (38/259). Severe COVID-19 was associated with older age (p=0.02), admission from nursing facility (p=0.009), increased BMI (p=0.03), diabetes mellitus (p=0.0002), and COPD (p=0.03). At the time of presentation, severe COVID-19 was associated with tachypnea, hypoxia, hypotension (all p&lt; 0.0001), elevated BUN (p=0.002) and AST (p=0.001), and acute or chronic kidney injury (p=0.01). Median hospital stay [IQR] was 11 days [7,18] in the severe vs. 6 days [3,11] in the non-severe group. In the severe group, 72% required ICU admission and 39% died. Table 2: Medical comorbidities Table 3: Presenting symptoms and signs in the first 48 hours of admission Table 4: Basic labs in the first 24 hours Conclusion In this cohort of patients with COVID-19, specific comorbidities, and vital signs at presentation were associated with severe COVID-19. These findings help clinicians with early identification and triage of high risk patients. Disclosures All Authors: No reported disclosures

Abstract P94: Stroke Etiologies in Patients With Covid-19: The Svin Covid-19 Multinational Registry

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Maria Esther Ramos-Araque ◽  
James E Siegler ◽  
Marc Ribo ◽  
Manuel Requena ◽  
Cristina López ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Severe Disease ◽  
Cryptogenic Stroke ◽  
Significant Risk ◽  
C Reactive Protein ◽  
Clinical Predictors ◽  
Short Term ◽  
Reactive Protein ◽  
Clinically Significant ◽  
Stroke Mechanism

Background and purpose: Coronavirus disease 2019 (COVID-19) is associated with a small but clinically significant risk of stroke, the cause of which is frequently cryptogenic. In a large multinational cohort of consecutive COVID-19 patients with stroke, we evaluated clinical predictors of cryptogenic stroke, short-term functional outcomes and in-hospital mortality among patients according to stroke etiology. Methods: We explored clinical characteristics and short-term outcomes of consecutively evaluated patients 18 years of age or older with acute ischemic stroke (AIS) and laboratory-confirmed COVID-19 from 31 hospitals in 4 countries (3/1/20-6/16/20). Results: Of the 14.483 laboratory-confirmed patients with COVID-19, 156 (1.1%) were diagnosed with AIS. Sixty-one (39.4%) were female, 84 (67.2%) white, and 88 (61.5%) were between 60-79 years of age. The most frequently reported etiology of AIS was cryptogenic (55/129, 42.6%), which was associated with significantly higher white blood cell count, c-reactive protein, and D-dimer levels than non-cryptogenic AIS patients (p</=0.05 for all comparisons). In a multivariable backward stepwise regression model estimating the odds of in-hospital mortality, cryptogenic stroke mechanism was associated with a fivefold greater odds in-hospital mortality than strokes due to any other mechanism (adjusted OR 5.16, 95%CI 1.41-18.87, p=0.01). In that model, older age (aOR 2.05 per decade, 95%CI 1.35-3.11, p<0.01) and higher baseline NIHSS (aOR 1.12, 95%CI 1.02-1.21, p=0.01) were also independently predictive of mortality. Conclusions: Our findings suggest that cryptogenic stroke among COVID-19 patients may be related to more severe disease and carries a significant risk of early mortality.

Clinical predictors of disease severity during the 2009–2010 A(HIN1) influenza virus pandemic in a paediatric population

2015 ◽  
Vol 143 (14) ◽  
pp. 2939-2949 ◽  
Author(s):  
M. N. GARCIA ◽  
D. C. PHILPOTT ◽  
K. O. MURRAY ◽  
A. ONTIVEROS ◽  
P. A. REVELL ◽  
...  
Keyword(s):  
Influenza Virus ◽  
Disease Severity ◽  
Influenza A ◽  
Severe Disease ◽  
Paediatric Population ◽  
The United States ◽  
Clinical Predictors ◽  
Presenting Symptoms ◽  
Severe Influenza ◽  
Influenza A H1n1

SUMMARYA novel influenza virus emerged in the United States in spring 2009, rapidly becoming a global pandemic. Children were disproportionally affected by the novel influenza A(H1N1) pandemic virus [A(H1N1)pdm]. This retrospective electronic medical record review study aimed to identify clinical predictors of disease severity of influenza A(HIN1)pdm infection in paediatric patients. Disease severity was defined on an increasing three-level scale from non-hospitalized, hospitalized, and admitted to the intensive care unit (ICU). From April 2009 to June 2010, 696 children presented to Texas Children's Hospital's emergency department, 38% were hospitalized, and 17% were admitted to the ICU. Presenting symptoms associated with severe influenza were dyspnoea [odds ratio (OR) 5·82], tachycardia (OR 2·61) and fatigue (OR 1·96). Pre-existing health conditions associated with disease severity included seizure disorder (OR 4·71), obesity (OR 3·28), lung disease (OR 2·84), premature birth (OR 2·53), haematological disease (OR 2·22), and developmental delay (OR 2·20). According to model fitness tests, presenting symptoms were more likely to predict severe influenza than underlying medical conditions. However, both are important risk factors. Recognition of clinical characteristics associated with severe disease can be used for triaging case management of children during future influenza outbreaks.

scholarly journals Patient Characteristics and Clinical Course of COVID-19 Patients Treated at a German Tertiary Center during the First and Second Waves in the Year 2020

2021 ◽  
Vol 10 (11) ◽  
pp. 2274
Author(s):  
Thomas Theo Brehm ◽  
Andreas Heyer ◽  
Kevin Roedl ◽  
Dominik Jarczak ◽  
Axel Nierhaus ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Severe Disease ◽  
Treatment Strategies ◽  
Patient Characteristics ◽  
Novel Treatment ◽  
Tertiary Center ◽  
Duration Of Hospitalization ◽  
Comorbidity Index ◽  
Novel Treatment Strategies ◽  
High Level

In this study, we directly compared coronavirus disease 2019 (COVID-19) patients hospitalized during the first (27 February–28 July 2020) and second (29 July–31 December 2020) wave of the pandemic at a large tertiary center in northern Germany. Patients who presented during the first (n = 174) and second (n = 331) wave did not differ in age (median [IQR], 59 years [46, 71] vs. 58 years [42, 73]; p = 0.82) or age-adjusted Charlson Comorbidity Index (median [IQR], 2 [1, 4] vs. 2 [0, 4]; p = 0.50). During the second wave, a higher proportion of patients were treated as outpatients (11% [n = 20] vs. 20% [n = 67]), fewer patients were admitted to the intensive care unit (43% [n = 75] vs. 29% [n = 96]), and duration of hospitalization was significantly shorter (median days [IQR], 14 [8, 34] vs. 11 [5, 19]; p < 0.001). However, in-hospital mortality was high throughout the pandemic and did not differ between the two periods (16% [n = 27] vs. 16% [n = 54]; p = 0.89). While novel treatment strategies and increased knowledge about the clinical management of COVID-19 may have resulted in a less severe disease course in some patients, in-hospital mortality remained unaltered at a high level. These findings highlight the unabated need for efforts to hamper severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) transmission, to increase vaccination coverage, and to develop novel treatment strategies to prevent mortality and decrease morbidity.

scholarly journals LINC-28. EPIDEMIOLOGICAL CHARACTERISTICS AND SURVIVAL OUTCOMES OF CHILDREN WITH MEDULLOBLASTOMA TREATED AT THE NATIONAL CANCER INSTITUTE (INCA) IN RIO DE JANEIRO, BRAZIL

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii383-iii384
Author(s):  
Gabriela Oigman ◽  
Diana Osorio ◽  
Joseph Stanek ◽  
Jonathan Finlay ◽  
Denizar Vianna ◽  
...  
Keyword(s):  
High Risk ◽  
Maternal Education ◽  
Survival Outcomes ◽  
Middle Income ◽  
Female Ratio ◽  
High Risk Patients ◽  
Presenting Symptoms ◽  
Risk Patients ◽  
Epidemiological Characteristics ◽  
Standard Risk

Abstract BACKGROUND Medulloblastoma (MB), the most malignant brain tumor of childhood has survival outcomes exceeding 80% for standard risk and 60% for high risk patients in high-income countries (HIC). These results have not been replicated in low-to-middle income countries (LMIC), where 80% of children with cancer live. Brazil is an upper-middle income country according to World Bank, with features of LMIC and HIC. METHODS We conducted a retrospective review of 126 children (0–18 years) diagnosed with MB from 1997 to 2016 at INCA. Data on patients, disease characteristics and treatment information were retrieved from the charts and summarized descriptively; overall survival (OS) and event-free survival (EFS) were calculated using the Kaplan-Meier Method. RESULTS The male/female ratio was 1.42 and the median age at diagnosis was 7.9 years. Headache (79%) and nausea/vomiting (75%) were the most common presenting symptoms. The median time from onset of symptoms to surgery was 50 days. The OS for standard-risk patients was 69% and 53% for high-risk patients. Patients initiating radiation therapy within 42 days after surgery (70.6% versus 59.6% p=0.016) experienced better OS. Forty-five patients (35%) had metastatic disease at admission. Lower maternal education correlated with lower OS (71.3% versus 49% p=0.025). Patients who lived &gt;40km from INCA fared better (OS= 68.2% versus 51.1% p=0.032). Almost 20% of families lived below the Brazilian minimum wage. CONCLUSIONS These findings suggest that socioeconomic factors, education, early diagnosis and continuous data collection, besides oncological treatment must be adressed to improve the survival of children with MB.

Hospitalized with stroke at the weekend: Higher cost and risk of early death?

2021 ◽  
pp. 174749302199259
Author(s):  
Marco Ghiani ◽  
Sabrina Mueller ◽  
Ulf Maywald ◽  
Thomas Wilke
Keyword(s):  
Propensity Score ◽  
Cerebral Infarction ◽  
Propensity Score Matching ◽  
Disease Severity ◽  
Patient Characteristics ◽  
Weekend Effect ◽  
Health Claims ◽  
Hospital Death ◽  
Stroke Severity ◽  
Baseline Characteristics

Objectives Previous studies have shown that weekend hospitalizations are associated with poorer health outcomes and higher mortality (“weekend effect”). However, few of these studies have adjusted for disease severity and little is known about the effect on costs. This work investigates the weekend effect and its costs for patients with cerebral infarction in Germany, adjusting for patient characteristics and proxies of stroke severity. Methods Adult patients with a cerebral infarction hospitalization 10th revision of the International statistical classification of diseases and related health problems (ICD-10: I63) between 01 January 2014 and 30 June 2017 were included from German health claims (AOK PLUS dataset). Propensity score matching was used to match patients hospitalized on weekends or on public holidays (weekend group) with patients hospitalized during the working week (workday group), based on baseline characteristics and proxies for disease severity such as concomitant diagnoses of aphasia, ataxia, and coma, or peg tube at index hospitalization. Matched cohorts were compared in terms of in-hospital, 7-day, and 30-day mortality, as well as risk and costs of stroke and rehabilitation stays in the year after first stroke. Results Of 32,311 patients hospitalized with cerebral infarction between 01 January 2014 and 30 June 2017, 8409 were in the weekend group and 23,902 in the workday group. After propensity score matching, 16,730 patients were included in our study (8365 per group). Matched cohorts did not differ in baseline characteristics or stroke severity. In the weekend group, the risk of in-hospital death (11.2%) and the seven-day mortality rate (6.8%) were 13.1% and 17.2% higher than in the workday group, respectively (both p < 0.01). The hazard ratio for death in the weekend group was 1.1 ( p = 0.043). The risks of subsequent stroke hospitalization and rehabilitation stays for a stroke were 8.4% higher and 5.5% higher in the weekend group (both p = 0.02). As a result, the stroke-related hospitalization and rehabilitation costs per patient year were, respectively, 5.6% and 8.0% higher in the weekend group (both p = 0.01). Conclusions A significant weekend effect emerged after controlling for observable patient characteristics and proxies of stroke severity. This effect also resulted in higher costs for patients admitted on weekends.

scholarly journals Baseline T-lymphocyte subset absolute counts can predict both outcome and severity in SARS-CoV-2 infected patients: a single center study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Marco Iannetta ◽  
Francesco Buccisano ◽  
Daniela Fraboni ◽  
Vincenzo Malagnino ◽  
Laura Campogiani ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
T Lymphocyte ◽  
Lymphocyte Subsets ◽  
Severe Disease ◽  
Laboratory Data ◽  
Lymphocyte Subset ◽  
Multivariable Logistic Regression Analysis ◽  
Double Positive ◽  
Increased Risk ◽  
T Lymphocyte Subset

AbstractThe aim of this study was to evaluate the role of baseline lymphocyte subset counts in predicting the outcome and severity of COVID-19 patients. Hospitalized patients confirmed to be infected with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) were included and classified according to in-hospital mortality (survivors/nonsurvivors) and the maximal oxygen support/ventilation supply required (nonsevere/severe). Demographics, clinical and laboratory data, and peripheral blood lymphocyte subsets were retrospectively analyzed. Overall, 160 patients were retrospectively included in the study. T-lymphocyte subset (total CD3+, CD3+ CD4+, CD3+ CD8+, CD3+ CD4+ CD8+ double positive [DP] and CD3+ CD4− CD8− double negative [DN]) absolute counts were decreased in nonsurvivors and in patients with severe disease compared to survivors and nonsevere patients (p < 0.001). Multivariable logistic regression analysis showed that absolute counts of CD3+ T-lymphocytes < 524 cells/µl, CD3+ CD4+ < 369 cells/µl, and the number of T-lymphocyte subsets below the cutoff (T-lymphocyte subset index [TLSI]) were independent predictors of in-hospital mortality. Baseline T-lymphocyte subset counts and TLSI were also predictive of disease severity (CD3+  < 733 cells/µl; CD3+ CD4+ < 426 cells/µl; CD3+ CD8+ < 262 cells/µl; CD3+ DP < 4.5 cells/µl; CD3+ DN < 18.5 cells/µl). The evaluation of peripheral T-lymphocyte absolute counts in the early stages of COVID-19 might represent a useful tool for identifying patients at increased risk of unfavorable outcomes.

scholarly journals Candida infective endocarditis: A retrospective study of patient characteristics and risk factors for death in 703 U.S. cases, 2015-2019

2020 ◽  
Author(s):  
Jonathan P Huggins ◽  
Samuel Hohmann ◽  
Michael Z David
Keyword(s):  
Risk Factors ◽  
Hospital Mortality ◽  
Liver Failure ◽  
Patient Characteristics ◽  
Medication Administration ◽  
Small Sample ◽  
Risk Of Death ◽  
Opiate Abuse ◽  
Small Sample Sizes ◽  
Valve Pathology

Abstract Background Candida endocarditis is a rare, sometimes fatal complication of candidemia. Past investigations of this condition are limited by small sample sizes. We used the Vizient clinical database to report on characteristics of patients with Candida endocarditis and to examine risk factors for in-hospital mortality. Methods This was a multicenter, retrospective cohort study of 703 inpatients admitted to 179 United States hospitals between October 2015 and April 2019. We reviewed demographic, diagnostic, medication administration, and procedural data from each patient’s initial encounter. Univariate and multivariate logistic regression analyses were used to identify predictors of in-hospital mortality. Results Of 703 patients, 114 (16.2%) died during the index encounter. One hundred and fifty-eight (22.5%) underwent an intervention on a cardiac valve. On multivariate analysis, acute and subacute liver failure was the strongest predictor of death (OR 9.2, 95% CI 4.8 –17.7). Female sex (OR 1.9, 95% CI 1.2 – 3.0), transfer from an outside medical facility (OR 1.8, 95% CI 1.1 – 2.8), aortic valve pathology (OR 2.7, 95% CI 1.5 – 4.9), hemodialysis (OR 2.1, 95% CI 1.1 – 4.0), cerebrovascular disease (OR 2.2, 95% CI 1.2 – 3.8), neutropenia (OR 2.5, 95% CI 1.3 – 4.8), and alcohol abuse (OR 2.9, 95% CI 1.3 – 6.7) were also associated with death on adjusted analysis, whereas opiate abuse was associated with a lower odds of death (OR 0.5, 95% CI 0.2 – 0.9). Conclusions We found that the inpatient mortality rate was 16.2% among patients with Candida endocarditis. Acute and subacute liver failure was associated with a high risk of death while opiate abuse was associated with a lower risk of death.

scholarly journals 365. Characteristics and outcomes of COVID-19 patients admitted to a regional health system in the southeast

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S251-S253
Author(s):  
Charles Teixeira ◽  
Henry Shiflett ◽  
Deeksha Jandhyala ◽  
Jessica Lewis ◽  
Scott R Curry ◽  
...  
Keyword(s):  
Renal Failure ◽  
Health System ◽  
Patient Characteristics ◽  
Supplemental Oxygen ◽  
Regional Health ◽  
Cancer Symptoms ◽  
Presenting Symptoms ◽  
Global Pandemic ◽  
Male Sex ◽  
Previous Admission

Abstract Background COVID-19, first described in Wuhan, China, is now a global pandemic. We describe a cohort of patients (pts) admitted to our academic health system (HS) in the southeast, where demographics and comorbidities differ significantly from other regions in the U.S. Methods This was a retrospective review of 161 consecutive pts admitted with COVID-19 from 3/12/20 to 6/1/20. We assessed demographics, comorbidities, presenting symptoms, treatments and outcomes and compared pts who died during hospitalization to those who survived to discharge (EpiInfo 7.2, Atlanta, GA). Results Mean age was 60.5 years, 51.6% were female, 72% African American (AA) and 69.6% admitted from home. 54.5% had a BMI &gt;30, 72% had HTN, 47.2% diabetes, and 33.6% COPD or asthma. The majority (68.8%) presented with fever (&gt;38.0) and required supplemental oxygen within 8 hours of admission (63.4%). Cough (65.6%), dyspnea (57.5%), myalgias (30.6%) and diarrhea (23.8%) were also common. 40.4% received hydroxychloroquine, 23.6% steroids and 19.9% convalescent plasma. 42.9% required ICU care, 27.3% were intubated, and 19.3% died. Characteristics associated with death included older age, male sex, HTN, ESRD on HD, and cancer. Symptoms associated with death included absence of cough, absence of myalgias, previous admission for COVID-19, tachypnea, need for supplemental oxygen, elevated BUN and creatinine, and elevated ferritin. Interventions associated with death included use of steroids, receipt of ICU care, intubation, delay to intubation, and use of vasopressors or inotropes. Complications associated with death included development of a new arrhythmia, bacteremia, pneumonia, ARDS, thrombosis, and new renal failure requiring HD (Table). Table 1. Patient Characteristics by Death Table 2. Patient Characteristics by Death Table 3. Patient Characteristics by Death Conclusion COVID-19 pts admitted to our southeast U.S. HS had significant comorbidities, most commonly obesity, HTN, and diabetes. Additionally, AA comprised a disproportionate share (72%) of our cohort compared to the general population of our state (30%), those tested in our region (32.9%), and those found to be positive for COVID-19 (35.8%). In-hospital mortality was 19.3% and intubation, particularly if delayed, was associated with death as were several complications, most notably arrhythmia, ARDS, and renal failure with HD. Disclosures All Authors: No reported disclosures

Sign in / Sign up

Export Citation Format

Share Document