scholarly journals Busto COVID-19 Score Identify Low Risk Patients. External Validation.

2021 ◽  
Author(s):  
Foieni Fabrizio ◽  
Beltrami Laura Maria Giovanna ◽  
Sala Girolamo ◽  
Ughi Nicola ◽  
Del Gaudio Francesca ◽  
...  
Keyword(s):  
Hospital Admission ◽  
Retrospective Cohort ◽  
Clinical Laboratory ◽  
External Validation ◽  
White Blood Cells ◽  
Area Under The Curve ◽  
Low Risk ◽  
Reactive Protein ◽  
Risk Patients ◽  
Admission Variables

Abstract Background: Coronavirus disease of 2019 (COVID-19) is associated with severe acute respiratory failure. Early identifcation of low-risk COVID-19 patients is crucial, discharging safely patients to home and optimizing the use of available resources. Methods: We aimed to external validate a simple score for the prediction of low-risk outcomes. A retrospective cohort study of patients hospitalized for COVID-19 was carried out by the Busto Hospital and Niguarda hospital. Epidemiological, clinical, laboratory, and treatment variables were collected at hospital admission. Variables included in this retrospective cohort were analized to validate the Busto COVID-19 score as a Clinical Risk Score able to individuate low risk COVID-19 patients. Among COVID-19 patients admitted to the hospital, severe outcome was defned as the composite of the admission to the Intensive Care Unit or death. Results: The development cohort included 427 consecutive patients. The mean (SD) age of patients among the cohort was 60.5 years; 273 (63%) were men. As potential predictors, Busto COVID-19 score variables include: lung ultrasound abnormality, age, total white blood cells count , C-reactive protein value, pO2/FiO2 ratio, lactates value, arterial hypertension and fever from 5 days or more and resulted in the best performing score with an area under the curve in the derivation sample of 0.88 and 0.71 in the external sample. Conclusions: The proposed score can identify patients at low risk for severe outcome who can be safely managed in a low-intensity setting after hospital admission for COVID-19.

scholarly journals Clinical risk scores for the early prediction of severe outcomes in patients hospitalized for COVID-19

2021 ◽  
Author(s):  
Walter Ageno ◽  
◽  
Chiara Cogliati ◽  
Martina Perego ◽  
Domenico Girelli ◽  
...  
Keyword(s):  
Hospital Admission ◽  
Predictive Value ◽  
Clinical Laboratory ◽  
Area Under The Curve ◽  
Orotracheal Intubation ◽  
Risk Scores ◽  
Algorithm Selection ◽  
Derivation Cohort ◽  
Neutrophil Lymphocyte Ratio ◽  
Predictive Risk

AbstractCoronavirus disease of 2019 (COVID-19) is associated with severe acute respiratory failure. Early identification of high-risk COVID-19 patients is crucial. We aimed to derive and validate a simple score for the prediction of severe outcomes. A retrospective cohort study of patients hospitalized for COVID-19 was carried out by the Italian Society of Internal Medicine. Epidemiological, clinical, laboratory, and treatment variables were collected at hospital admission at five hospitals. Three algorithm selection models were used to construct a predictive risk score: backward Selection, Least Absolute Shrinkage and Selection Operator (LASSO), and Random Forest. Severe outcome was defined as the composite of need for non-invasive ventilation, need for orotracheal intubation, or death. A total of 610 patients were included in the analysis, 313 had a severe outcome. The subset for the derivation analysis included 335 patients, the subset for the validation analysis 275 patients. The LASSO selection identified 6 variables (age, history of coronary heart disease, CRP, AST, D-dimer, and neutrophil/lymphocyte ratio) and resulted in the best performing score with an area under the curve of 0.79 in the derivation cohort and 0.80 in the validation cohort. Using a cut-off of 7 out of 13 points, sensitivity was 0.93, specificity 0.34, positive predictive value 0.59, and negative predictive value 0.82. The proposed score can identify patients at low risk for severe outcome who can be safely managed in a low-intensity setting after hospital admission for COVID-19.

scholarly journals Predictive Modeling of Poor Outcome in Severe COVID-19: A Single-Center Observational Study Based on Clinical, Cytokine and Laboratory Profiles

2021 ◽  
Vol 10 (22) ◽  
pp. 5431
Author(s):  
Óscar Gorgojo-Galindo ◽  
Marta Martín-Fernández ◽  
María Jesús Peñarrubia-Ponce ◽  
Francisco Javier Álvarez ◽  
Christian Ortega-Loubon ◽  
...  
Keyword(s):  
Hospital Admission ◽  
Predictive Model ◽  
Blood Group ◽  
Clinical Laboratory ◽  
Area Under The Curve ◽  
Abo Blood Group ◽  
Poor Outcome ◽  
Emergency Room Admission ◽  
Poor Outcomes

Pneumonia is the main cause of hospital admission in COVID-19 patients. We aimed to perform an extensive characterization of clinical, laboratory, and cytokine profiles in order to identify poor outcomes in COVID-19 patients. Methods: A prospective and consecutive study involving 108 COVID-19 patients was conducted between March and April 2020 at Hospital Clínico Universitario de Valladolid (Spain). Plasma samples from each patient were collected after emergency room admission. Forty-five serum cytokines were measured in duplicate, and clinical data were analyzed using SPPS version 25.0. Results: A multivariate predictive model showed high hepatocyte growth factor (HGF) plasma levels as the only cytokine related to intubation or death risk at hospital admission (OR = 7.38, 95%CI—(1.28–42.4), p = 0.025). There were no comorbidities included in the model except for the ABO blood group, in which the O blood group was associated with a 14-fold lower risk of a poor outcome. Other clinical variables were also included in the predictive model. The predictive model was internally validated by the receiver operating characteristic (ROC) curve with an area under the curve (AUC) of 0.94, a sensitivity of 91.7% and a specificity of 95%. The use of a bootstrapping method confirmed these results. Conclusions: A simple, robust, and quick predictive model, based on the ABO blood group, four common laboratory values, and one specific cytokine (HGF), could be used in order to predict poor outcomes in COVID-19 patients.

scholarly journals Sex differences in a cohort of COVID-19 Italian patients hospitalized during the first and second pandemic waves

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Virginia Quaresima ◽  
Cristina Scarpazza ◽  
Alessandra Sottini ◽  
Chiara Fiorini ◽  
Simona Signorini ◽  
...  
Keyword(s):  
Hospital Admission ◽  
Disease Duration ◽  
Elderly Women ◽  
White Blood Cells ◽  
Laboratory Data ◽  
List Type ◽  
Disease Evolution ◽  
Reactive Protein ◽  
Second Wave ◽  
Older Males

Abstract Background Coronavirus disease 2019 (COVID-19) severity seems to be influenced by genetic background, sex, age, and presence of specific comorbidities. So far, little attention has been paid to sex-specific variations of demographic, clinical, and laboratory features of COVID-19 patients referred to the same hospital in the two consecutive pandemic waves. Methods Demographic, clinical, and laboratory data were collected in 1000 COVID-19 patients (367 females and 633 males), 500 hospitalized in the first wave and 500 in the second one, at the ASST Spedali Civili of Brescia from March to December 2020. Statistical analyses have been employed to compare data obtained in females and males, taking into account their age, and during the first and second COVID-19 waves. Results The mean age at the time of hospitalization was similar in females and males but was significantly higher for both in the second wave; the time elapsed from symptom onset to hospital admission did not differ between sexes in the two waves, and no correlation was observed between delayed hospital admission and length of hospitalization. The number of multi-symptomatic males was higher than that of females, and patients with a higher number of comorbidities were more frequently admitted to intensive care unit (ICU) and more frequently died. Older males remained in the ICU longer than females and showed a longer disease duration, mainly the first wave. The highest levels of white blood cells, neutrophils, C-reactive protein, and fibrinogen were significantly higher in males and in the first, and along with higher levels of D-dimer, ferritin, lactate dehydrogenase, and procalcitonin which were preferentially documented in patients requiring ICU or died. While the rate of death in ICU was higher in males, the overall death rate did not differ between the sexes; however, the deceased women were older. Conclusions These data indicate that once patients were hospitalized, the risk of dying was similar between females and males. Therefore, future studies should aim at understanding the reasons why, for a given number of SARS-CoV-2 infections, fewer females develop the disease requiring hospitalization. Highlights Although the hospitalized males were significantly more, the similar number of hospitalizations of the > 75-year-old females and males could be due to the fact that in Brescia province, elderly women are about twice as many as men. Although males spent more days in the hospital, had a longer disease duration, developed a critical illness more frequently, and were admitted and died in the ICU more than females, the total rate of deaths among patients was not significantly different between sexes. Overall, the most frequent comorbidities were cardiovascular diseases, which were preferentially seen among patients hospitalized in the second wave; it is possible that the knowledge gained in the first wave concerning the association between certain comorbidities and worse disease evolution has guided the preferential hospitalization of patients with these predominant comorbidities.

External validation of the Glasgow prognostic score (mGPS) for renal cancer.

2012 ◽  
Vol 30 (5_suppl) ◽  
pp. 378-378
Author(s):  
Viraj A. Master ◽  
Timothy V. Johnson ◽  
Omer Kucuk ◽  
Daniel Canter ◽  
John Pattaras ◽  
...  
Keyword(s):  
High Risk ◽  
Cox Regression ◽  
Inflammatory Responses ◽  
Prognostic Score ◽  
External Validation ◽  
Glasgow Prognostic Score ◽  
Low Risk ◽  
High Risk Patients ◽  
Increased Risk ◽  
Risk Patients

378 Background: Inflammation has been termed the 7th hallmark of cancer (Hanahan and Weinberg Cell 2011). Measurement of systemic inflammatory responses in malignancy is possible using a selective combination of two commonly available, cost-effective serum assays. The combination of these two serum markers, C-reactive protein (CRP) and albumin, is termed the modified Glasgow prognostic score (mGPS), and is strongly correlated with outcome in a variety of cancers, including mRCC. Recently, mGPS has been shown to be predictive of outcome in localized RCC (ASCO GU 2010 #390). We sought to externally validate these results. Methods: Nephrectomized patients with clinically localized (T1-T4N0M0) clear cell RCC with negative surgical margins were followed for a mean of 25 months (range: 1-81 months). Relapse and survival was identified through routine follow-up. Patients were categorized by mGPS score as Low Risk (mGPS = 0 points), Intermediate Risk (mGPS = 1 point), and High Risk (mGPS = 2 points). One point was assigned to patients for an elevated CRP (>10 mg/L) and hypoalbuminemia (<3.5 mg/dL). Patients with normal CRP and hypoalbuminemia were assigned 0 points. Kaplan-Meier and multivariate Cox regression analyses examined relapse-free survival (RFS) and overall survival (OS) across patient and disease characteristics. Results: Of 248 patients, 17.9% relapsed and 18.6% died. Of Low, Intermediate, and High Risk patients, 7.2%, 7.7%, and 45.5%, respectively relapsed and 5.2%, 15.4%, and 39.4%, respectively died during the study. In multivariate analysis including stage and grade, mGPS was significantly associated with RFS and OS. Compared to Low-Risk patients, High-Risk patients experienced a 3-fold (OR: 2.906, 95% CI: 1.055-8.001) increased risk of relapse and 4-fold (HR: 3.722, 95% CI: 1.046-13.245) increased risk of mortality. AUC is 0.813, which compares very favorably to existing prognostic algorithms. Conclusions: In this external validation cohort of US patients, mGPS continues to be a predictor of relapse and overall mortality following nephrectomy for localized RCC. Clinicians may consider using mGPS as an adjunct to identify high-risk patients for possible enrollment into clinical trials, or for patient counseling.

scholarly journals Codetection ofTrichomonas vaginalisandCandida albicansby PCR in Urine Samples in a Low-Risk Population Attended in a Clinic First Level in Central Veracruz, Mexico

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
A. López-Monteon ◽  
F. S. Gómez-Figueroa ◽  
G. Ramos-Poceros ◽  
D. Guzmán-Gómez ◽  
A. Ramos-Ligonio
Keyword(s):  
Trichomonas Vaginalis ◽  
Clinical Laboratory ◽  
Cross Sectional Study ◽  
Low Risk ◽  
Urine Samples ◽  
Cross Sectional ◽  
Primary Health ◽  
Risk Patients ◽  
June July ◽  
The City

The aim of this study is to estimate the prevalence ofTrichomonas vaginalisandCandida albicansin low-risk patients treated at a first level clinic (primary health care represents the first level of contact of individuals, families, and the community with the system national health). Using a cross-sectional study in patients treated in clinical laboratory of the Sanitary District no. 7 of the city of Orizaba during the months June-July, 252 urine samples were collected for the identification ofT. vaginalisandC. albicansby PCR. Furthermore, we analyzed the sociodemographic characteristics of the studied population. We observed an overall prevalence of 23.41% (95% CI 22.10–24.72) forT. vaginalisand 38.88% (95% CI 37.73–40.03) forC. albicans. There was also presence of coinfection in 14.28% (95% CI 13.10–15.46), which was associated with the presence of pain. Most of the positive cases were observed in women house-maker (80%, 95% CI 50.36–48.98). The results of this study provide evidence that the majority of positive cases observed in the studied population are presented in an asymptomatic form and usually are not associated with any risk factor.

scholarly journals Routine use of chest x-ray for low-risk patients undergoing a periodic health examination: a retrospective cohort study

CMAJ Open ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. E322-E329 ◽  
Author(s):  
Zachary Bouck ◽  
Graham Mecredy ◽  
Noah M. Ivers ◽  
Ciara Pendrith ◽  
Ben Fine ◽  
...  
Keyword(s):  
Cohort Study ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Low Risk ◽  
Health Examination ◽  
Periodic Health Examination ◽  
X Ray ◽  
Risk Patients ◽  
Chest X Ray

Factors associated with a delayed diagnosis of pulmonary embolism

Diagnosis ◽  
2016 ◽  
Vol 3 (1) ◽  
pp. 37-41
Author(s):  
Sho Nishiguchi ◽  
Haruka Inada ◽  
Izumi Kitagawa ◽  
Yasuharu Tokuda
Keyword(s):  
Pulmonary Embolism ◽  
Diagnostic Delay ◽  
Delayed Diagnosis ◽  
Low Risk ◽  
Factors Associated ◽  
Reactive Protein ◽  
Time To Diagnosis ◽  
Wells Score ◽  
Risk Patients ◽  
Serum Crp

AbstractAcute pulmonary embolism (PE) is frequently a fatal disease. The clinical presentation of PE is variable and frequently nonspecific, and there is commonly a diagnostic delay. We aimed to investigate factors associated with the delay in the diagnosis of PE.Data from patients with PE were collected from January 2011 to December 2013 in an acute care teaching hospital. Time-to-diagnosis, evaluated by obtaining a diagnostic computed tomography scan, was then analyzed by the Cox proportional hazard model for examining factors associated with time to the diagnosis of PE. Independent variables included age, gender, activities of daily living, means of transport to the hospital, body temperature, hypoxemia, typical symptoms for PE, serum C-reactive protein (CRP) concentrations, infiltration on chest radiograph, Wells score, classification of patients with PE based on early mortality risk, patients referred from other specialties, daytime versus nighttime arrival, diagnosed by an emergency physician, and diagnosed by a medical resident.Sixty patients were included. The time to diagnosis was significantly delayed in low-risk patients (hazard ratio [HR], 2.2; 95% CI, 1.2–4.1) and in patients who did not use an ambulance (HR, 1.9; 95% CI, 1.0–3.7). In an analysis of the latter subgroup, higher serum CRP concentrations were associated with a delayed diagnosis (HR, 1.1; 95% CI, 1.0–1.2).The time to the diagnosis of PE was delayed in low-risk patients and in patients who attended the hospital by means other than an ambulance. In such patients, a delayed diagnosis was associated with higher serum CRP concentrations.

scholarly journals A descriptive and validation study of a predictive model of severity of SARS-COV-2 infection

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Yolanda Villena-Ortiz ◽  
Marina Giralt ◽  
Laura Castellote-Bellés ◽  
Rosa M. Lopez-Martínez ◽  
Luisa Martinez-Sanchez ◽  
...  
Keyword(s):  
Emergency Department ◽  
Predictive Model ◽  
Clinical Laboratory ◽  
Demographic Data ◽  
Severe Disease ◽  
External Validation ◽  
Predictive Values ◽  
Reactive Protein ◽  
Predictive Variables ◽  
Moderate Disease

Abstract Objectives The strain the SARS-COV-2 pandemic is putting on hospitals requires that predictive values are identified for a rapid triage and management of patients at a higher risk of developing severe COVID-19. We developed and validated a prognostic model of COVID-19 severity. Methods A descriptive, comparative study of patients with positive vs. negative PCR-RT for SARS-COV-2 and of patients who developed moderate vs. severe COVID-19 was conducted. The model was built based on analytical and demographic data and comorbidities of patients seen in an Emergency Department with symptoms consistent with COVID-19. A logistic regression model was designed from data of the COVID-19-positive cohort. Results The sample was composed of 410 COVID-positive patients (303 with moderate disease and 107 with severe disease) and 81 COVID-negative patients. The predictive variables identified included lactate dehydrogenase, C-reactive protein, total proteins, urea, and platelets. Internal calibration showed an area under the ROC curve (AUC) of 0.88 (CI 95%: 0.85–0.92), with a rate of correct classifications of 85.2% for a cut-off value of 0.5. External validation (100 patients) yielded an AUC of 0.79 (95% CI: 0.71–0.89), with a rate of correct classifications of 73%. Conclusions The predictive model identifies patients at a higher risk of developing severe COVID-19 at Emergency Department, with a first blood test and common parameters used in a clinical laboratory. This model may be a valuable tool for clinical planning and decision-making.

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