scholarly journals Hemogram Rates as Prognostic Markers of ICU Admission in COVID-19

2021 ◽  
Author(s):  
Sara Velazquez ◽  
Rodrigo Madurga ◽  
Jose Maria Castellano ◽  
Jesus Rodriguez-Pascual ◽  
Santiago Ruiz de Aguiar ◽  
...  
Keyword(s):  
Hospital Admission ◽  
Regression Models ◽  
Complex Model ◽  
Pathophysiological Mechanism ◽  
The Novel ◽  
Prothrombotic State ◽  
Logistic Regression Models ◽  
Lymphocyte Ratio ◽  
Icu Admission ◽  
The Moment

Abstract BackgroundSince first cases of SARS COV-2 were identified, the number of affected and dead people make necessary to identify factors related to worse evolution. Endothelial injury has been proposed as the main pathophysiological mechanism in the illness development, which provokes a hyper inflammation and prothrombotic state. Leukocytes and platelets play a role in inflammation and thrombogenesis so we propose to study if neutrophil-to-lymphocyte ratio (NLR), platelets-to-lymphocyte ratio (PLR), the novel neutrophil-to-platelet ratio (NPR), and the systemic immune-inflammation index (SII), could be useful to identify patients who will need admission at Intensive Care Units.MethodsA retrospective observational study was performed at HM Hospitales including 2245 patients with COVID-19 from March 1 to June 10, 2020. Patients were divided into two groups, admitted, and not admitted to ICU. ResultsPatients requiring ICU admission had significantly higher rates at the moment of hospital admission in NLR (6.9 [4–11.7] vs 4.1 [2.6–7.6], p<0.0001), PLR (2 [1.4–3.3] vs 1.9 [1.3–2.9], p=0.023), NPR (3 [2.1–4.2] vs 2.3 [1.6–3.2], p<0.0001) and SII (13 [6.5–25.7] vs 9 [4.9–17.5], p<0.0001) than those who did not enter ICU. After multivariable logistic regression models, the hemogram rate that better remains as a predictor of ICU admission, when adjusted for the more complex model, was NPR, OR 1.11 (95% CI: 0.98-1.22, p=0.055).ConclusionsThe four rates obtained from hemogram at hospital admission, especially the novelty NPR, have shown to be useful as predictors of unfavorable clinical evolution.

scholarly journals Hemogram-derived ratios as prognostic markers of ICU admission in COVID-19

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sara Velazquez ◽  
Rodrigo Madurga ◽  
José María Castellano ◽  
Jesús Rodriguez-Pascual ◽  
Santiago Ruiz de Aguiar Diaz Obregon ◽  
...  
Keyword(s):  
Hospital Admission ◽  
Regression Models ◽  
Prognostic Markers ◽  
Clinical Parameter ◽  
Prothrombotic State ◽  
Health Records ◽  
Logistic Regression Models ◽  
Lymphocyte Ratio ◽  
Icu Admission ◽  
The Moment

Abstract Background The vast impact of COVID-19 call for the identification of clinical parameter that can help predict a torpid evolution. Among these, endothelial injury has been proposed as one of the main pathophysiological mechanisms underlying the disease, promoting a hyperinflammatory and prothrombotic state leading to worse clinical outcomes. Leukocytes and platelets play a key role in inflammation and thrombogenesis, hence the objective of the current study was to study whether neutrophil-to-lymphocyte ratio (NLR), platelets-to-lymphocyte ratio (PLR), the systemic immune-inflammation index (SII) as well as the new parameter neutrophil-to-platelet ratio (NPR), could help identify patients who at risk of admission at Intensive Care Units. Methods A retrospective observational study was performed at HM Hospitales including electronic health records from 2245 patients admitted due to COVID-19 from March 1 to June 10, 2020. Patients were divided into two groups, admitted at ICU or not. Results Patients who were admitted at the ICU had significantly higher values in all hemogram-derived ratios at the moment of hospital admission compared to those who did not need ICU admission. Specifically, we found significant differences in NLR (6.9 [4–11.7] vs 4.1 [2.6–7.6], p <  0.0001), PLR (2 [1.4–3.3] vs 1.9 [1.3–2.9], p = 0.023), NPR (3 [2.1–4.2] vs 2.3 [1.6–3.2], p <  0.0001) and SII (13 [6.5–25.7] vs 9 [4.9–17.5], p <  0.0001) compared to those who did not require ICU admission. After multivariable logistic regression models, NPR was the hemogram-derived ratio with the highest predictive value of ICU admission, (OR 1.11 (95% CI: 0.98–1.22, p = 0.055). Conclusions Simple, hemogram-derived ratios obtained from early hemogram at hospital admission, especially the novelty NPR, have shown to be useful predictors of risk of ICU admission in patients hospitalized due to COVID-19.

Neutrophil-to-Lymphocyte Ratio Cut-Off Point for COVID-19 Mortality: A Retrospective Study

2022 ◽  
Author(s):  
Zahedin Kheyri ◽  
Sepehr Metanat ◽  
Hadiseh Hosamirudsari ◽  
Samaneh Akbarpour ◽  
Maryam Shojaei ◽  
...  
Keyword(s):  
Odds Ratio ◽  
Regression Models ◽  
Neutrophil To Lymphocyte Ratio ◽  
Rt Pcr ◽  
Multivariate Logistic Regression ◽  
Logistic Regression Models ◽  
Lymphocyte Ratio ◽  
Icu Admission ◽  
Prolonged Hospitalization ◽  
Multiple Characteristics

Several months have passed since the onset of the COVID-19 pandemic. Multiple characteristics have been proposed as prognostic factors so far. This study aims to provide evidence on the association of neutrophil-to-lymphocyte ratio (NLR) at the hospitalization time and three desired outcomes (mortality, prolonged hospitalization, and intensive care unit [ICU] admission). We designed a single-centre retrospective observational study in Baharloo Hospital (Tehran, Iran) from 20 February to 19 April 2020. Patients with confirmed COVID-19 diagnosis via rt-PCR or chest CT imaging were included. Demographic and clinical data were obtained. The sample was divided into three groups, using tertile boundaries of initial NLR. The differences in mortality, comorbidities, hospitalization duration, drug administration, and ICU admission between these three groups were investigated. The identified confounding factors were adjusted to calculate the odds ratio of death, ICU admission, and prolonged hospitalization. Nine hundred sixty-three patients were included. In total, 151 and 212 participants experienced mortality and ICU admission, respectively. In multivariate logistic regression models, the adjusted odds ratio for mortality event in the second and third tertile of initial NLR after full adjustment were 1.89 (95% CI:1.07-3.32) and 2.57 (95% CI:1.48-4.43) and for ICU admission were 1.85 (95% CI:1.14-3.01) and 2.88 (95% CI:1.79-4.61), respectively. The optimal cut-off value of the initial NLR for predicting mortality was 4.27. Initial NLR can predict mortality and ICU admission in COVID-19 patients. Further investigations for curating the calculated cut-off can propose initial NLR as an indicator of poor prognosis for COVID-19 patients.

scholarly journals Risk factors for mortality, ICU admission and bacteremia in patients suspected of sepsis at the Emergency department. A prospective cohort study

2020 ◽  
Author(s):  
Valentino D’Onofrio ◽  
Agnes Meersman ◽  
Sara Vijgen ◽  
Reinoud Cartuyvels ◽  
Peter Messiaen ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cohort Study ◽  
Regression Models ◽  
Serum Lactate ◽  
Suspected Sepsis ◽  
Logistic Regression Models ◽  
Icu Admission ◽  
Observational Cohort ◽  
Independent Risk Factors ◽  
Prediction Of Prognosis

Abstract Background There is a clear need for a better assessment of independent risk factors for in-hospital mortality, ICU admission, and bacteremia in patients presenting with suspected sepsis at the ED. Methods A prospective observational cohort study including 1690 patients was performed. Two multivariable logistic regression models were used to identify independent risk factors. Results SOFA score of ≥2 and serum lactate of ≥2mmol/L were associated with all outcomes. Other independent risk factors were individual SOFA variables and SIRS variables but varied per outcome. MAP&lt;70 mmHg negatively impacted all outcomes. Conclusion These readily available measurements can help with early risk stratification and prediction of prognosis.

scholarly journals Diabetes mellitus as a risk factor for poor early outcomes in patients hospitalized with COVID-19

2020 ◽  
Author(s):  
Jacqueline Seiglie ◽  
Jesse Platt ◽  
Sara Jane Cromer ◽  
Bridget Bunda ◽  
Andrea S. Foulkes ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Mechanical Ventilation ◽  
Logistic Regression ◽  
Risk Factor ◽  
Regression Models ◽  
Massachusetts General Hospital ◽  
Hospitalized Patients ◽  
Patient Centered ◽  
Logistic Regression Models ◽  
Icu Admission

<b>OBJECTIVE</b> <p>Diabetes mellitus and obesity are highly prevalent among hospitalized patients with COVID-19, but little is known about their contributions to early COVID-19 outcomes. We tested the hypothesis that diabetes is a risk factor for poor early outcomes, after adjustment for obesity, among a cohort of patients hospitalized with COVID-19. <b></b></p> <p><b> </b></p> <p><b>RESEARCH DESIGN AND METHODS </b>We used data from the Massachusetts General Hospital (MGH) COVID-19 Data Registry of patients hospitalized with COVID-19 between March 11, 2020 and April 30, 2020. Primary outcomes were admission to the intensive care unit (ICU), need for mechanical ventilation, and death within 14 days of presentation to care. Logistic regression models were adjusted for demographic characteristics, obesity, and relevant comorbidities. </p> <p> </p> <p><b>RESULTS</b></p> <p>Among 450 patients, 178 (39.6%) had diabetes, mostly type 2 diabetes. A higher proportion of patients with diabetes were admitted to the ICU (42.1% vs. 29.8%, p=0.007), required mechanical ventilation (37.1% vs. 23.2%, p=0.001), and died (15.9% vs. 7.9%, p=0.009), compared with patients without diabetes. In multivariable logistic regression models, diabetes was associated with greater odds of ICU admission (OR 1.59 [95% CI 1.01-2.52]), mechanical ventilation (1.97 [1.21-3.20]), and death (2.02 [1.01-4.03]) at 14-days. Obesity was associated with higher odds of ICU admission (2.16 [1.20-3.88]) and mechanical ventilation (2.13 [1.14-4.00]) but not with death. </p> <p> </p> <p><b>CONCLUSIONS</b></p> <p>Among hospitalized patients with COVID-19, diabetes was associated with poor early outcomes, after adjusting for obesity. These findings can help inform patient-centered care decision making for people with diabetes at risk of COVID-19.</p>

scholarly journals Diabetes mellitus as a risk factor for poor early outcomes in patients hospitalized with COVID-19

2020 ◽  
Author(s):  
Jacqueline Seiglie ◽  
Jesse Platt ◽  
Sara Jane Cromer ◽  
Bridget Bunda ◽  
Andrea S. Foulkes ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Mechanical Ventilation ◽  
Logistic Regression ◽  
Risk Factor ◽  
Regression Models ◽  
Massachusetts General Hospital ◽  
Hospitalized Patients ◽  
Patient Centered ◽  
Logistic Regression Models ◽  
Icu Admission

<b>OBJECTIVE</b> <p>Diabetes mellitus and obesity are highly prevalent among hospitalized patients with COVID-19, but little is known about their contributions to early COVID-19 outcomes. We tested the hypothesis that diabetes is a risk factor for poor early outcomes, after adjustment for obesity, among a cohort of patients hospitalized with COVID-19. <b></b></p> <p><b> </b></p> <p><b>RESEARCH DESIGN AND METHODS </b>We used data from the Massachusetts General Hospital (MGH) COVID-19 Data Registry of patients hospitalized with COVID-19 between March 11, 2020 and April 30, 2020. Primary outcomes were admission to the intensive care unit (ICU), need for mechanical ventilation, and death within 14 days of presentation to care. Logistic regression models were adjusted for demographic characteristics, obesity, and relevant comorbidities. </p> <p> </p> <p><b>RESULTS</b></p> <p>Among 450 patients, 178 (39.6%) had diabetes, mostly type 2 diabetes. A higher proportion of patients with diabetes were admitted to the ICU (42.1% vs. 29.8%, p=0.007), required mechanical ventilation (37.1% vs. 23.2%, p=0.001), and died (15.9% vs. 7.9%, p=0.009), compared with patients without diabetes. In multivariable logistic regression models, diabetes was associated with greater odds of ICU admission (OR 1.59 [95% CI 1.01-2.52]), mechanical ventilation (1.97 [1.21-3.20]), and death (2.02 [1.01-4.03]) at 14-days. Obesity was associated with higher odds of ICU admission (2.16 [1.20-3.88]) and mechanical ventilation (2.13 [1.14-4.00]) but not with death. </p> <p> </p> <p><b>CONCLUSIONS</b></p> <p>Among hospitalized patients with COVID-19, diabetes was associated with poor early outcomes, after adjusting for obesity. These findings can help inform patient-centered care decision making for people with diabetes at risk of COVID-19.</p>

scholarly journals Neutrophil: lymphocyte ratio is positively associated with subclinical diabetic cardiomyopathy

2020 ◽  
Author(s):  
Xiaoli Huang ◽  
Zihan Qin ◽  
Min Xu ◽  
Feifei Zhang ◽  
Xiaohong Jiang ◽  
...  
Keyword(s):  
Diabetic Cardiomyopathy ◽  
Cardiac Dysfunction ◽  
Regression Models ◽  
Clinical Trial Registry ◽  
Logistic Regression Models ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Adjusted Logistic Regression ◽  
Asymptomatic Subjects

Abstract Background: Subclinical diabetic cardiomyopathy (DCM) occurs frequently in asymptomatic subjects with Type 2 diabetes mellitus (T2DM). Previous studies have shown a direct relationship between the immune system and DCM using reliable biomarkers.Methods: 507 subjects with T2DM were recruited from April 2018 to October 2019 and divided into T2DM with cardiac dysfunction (DCM) group and T2DM without cardiac dysfunction (non-DCM) group. Adjusted logistic regression models were used to evaluate relationship between the quartiles of Neutrophil: lymphocyte ratio (NLR) and subclinical DCM (covariates: age, sex, BMI, duration of diabetes, and hyperlipidemia). Results: Blood NLR was significantly upregulated in DCM group compared to non-DCM group (P = 0.05). Then the adjusted odds ratio (95% CI) of the highest NLR quartile was 14.32 (2.92-70.31) compared to the lowest quartile of NLR after multiple adjusted (P < 0.001). However, neutrophil and lymphocyte counts did not significantly relate to the incidence of DCM in T2DM patients. Conclusions: The present study demonstrated that NLR was related to the incidence of subclinical DCM, suggesting that NLR may be an efficient and accurate prognostic biomarker for DCM. Trial registration: Chinese Clinical Trial Registry (ChiCTR1900027080). Registered 30 October 2019. Retrospectively registered: www.medresman.org

scholarly journals Role of inflammatory biomarkers in the prediction of ICU admission and mortality in patients with COVID-19

2020 ◽  
Vol 8 (12) ◽  
Author(s):  
Qamar Ahmad ◽  
Sarah DePerrior ◽  
Sunita Dodani ◽  
Joshua Edwards ◽  
Paul Marik
Keyword(s):  
Regression Models ◽  
Area Under The Curve ◽  
Inflammatory Biomarkers ◽  
Logistic Regression Models ◽  
Icu Admission ◽  
Composite Scores ◽  
Design And Methods ◽  
Improved Accuracy ◽  
D Dimer

Background: Inflammatory cytokines have been implicated in the pathophysiology and prognosis of severe COVID-19. Inflammatory biomarkers may guide the clinician in making treatment decisions as well as in the allocation of resources. Objective: This study aimed to assess how levels of inflammatory biomarkers predict disease severity and mortality in patients with COVID-19 by testing a predictive scoring model developed by Zhou et al and further refining the model in a population of patients hospitalized with COVID-19. Study Design and Methods: This retrospective study included patients with COVID-19 admitted to ten Virginia hospitals from January 1, 2020, to June 15, 2020. Inflammatory markers including CRP, D-Dimer, ferritin, N/L ratio, and procalcitonin were studied and logistic regression models were applied to ascertain the risk of ICU admission and mortality with elevated markers. Results: Data from a total of 701 patients were analyzed. In bivariate tests age, CRP, D-Dimer, and N/L ratio were associated with in-hospital mortality as well as admission to the ICU. Procalcitonin was associated with admission to the ICU but not mortality. Males and African Americans were more likely to require ICU-level care. In final models, age and CRP were significantly associated with mortality (OR 1.06, 95% CI 1.04-1.08, and OR 1.06, 95% CI 1.03-1.10 respectively) as well as ICU admissions (OR 1.02, 95% CI 1.01-1.03 and OR 1.03, 95% CI 1.01-1.06 respectively). The previously established composite scores of CRP, D-Dimer, and N/L ratio were predictive of mortality (Area under the curve [AUC] 0.69 for multiplicative score) as well as ICU admissions (AUC 0.61 for multiplicative score). However, improved accuracy was obtained with age and CRP for predicting mortality (AUC 0.77) and ICU admission (AUC 0.62). Conclusions: CRP and age appear to be the strongest predictors for ICU admission and mortality compared to D-Dimer, Ferritin, Procalcitonin, and N/L ratio in patients with COVID-19.

scholarly journals Role of Serum E-Selectin as a Biomarker of Infection Severity in Coronavirus Disease 2019

2021 ◽  
Vol 10 (17) ◽  
pp. 4018
Author(s):  
Alessandra Oliva ◽  
Emanuele Rando ◽  
Dania Al Ismail ◽  
Massimiliano De Angelis ◽  
Francesca Cancelli ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Thrombotic Event ◽  
Endothelial Activation ◽  
Multiple Logistic Regression ◽  
Logistic Regression Models ◽  
Icu Admission ◽  
Increased Risk ◽  
Single Center Study

Introduction: E-selectin is a recognized marker of endothelial activation; however, its place in Coronavirus Disease 2019 (COVID-19) has not been fully explored. Aims of the study are to compare sE-selectin values among the Intensive Care Unit (ICU)-admitted and non-admitted, survived and non-survived patients and those with or without thrombosis. Methods: A single-center study of patients with COVID-19 hospitalized at Policlinico Umberto I (Rome) from March to May 2020 was performed. Simple and multiple logistic regression models were developed. Results: One hundred patients were included, with a median age (IQR) of 65 years (58–78). Twenty-nine (29%) were admitted to ICU, twenty-eight (28%) died and nineteen (19%) had a thrombotic event. The median value (IQR) of sE-selectin was 26.1 ng/mL (18.1–35). sE-selectin values did not differ between deceased and survivors (p = 0.06) and among patients with or without a thrombotic event (p = 0.22). Compared with patients who did not receive ICU treatments, patients requiring ICU care had higher levels of sE-selectin (36.6 vs. 24.1 ng/mL; p < 0.001). In the multiple logistic regression model, sE-selectin levels > 33 ng/mL, PaO2/FiO2 < 200 and PaO2/FiO2 200–300 were significantly associated with an increased risk of ICU admission. sE-selectin values significantly correlated with a neutrophil count (R = 0.32 (p = 0.001)) and the number of days from the symptoms onset to hospitalization (R = 0.28 (p = 0.004)). Conclusions: sE-selectin levels are predictive of ICU admission in COVID-19 patients. Since data on the relation between sE-selectin and COVID-19 are scarce, this study aims to contribute toward the comprehension of the pathogenic aspects of COVID-19 disease, giving a possible clinical marker able to predict its severity.

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