Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText.
Kick-your-searchterm to multiple Engines kick-your-query now !>
A dictionary by aggregated review articles of nephrology, medicine and the life sciences
Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

suck abstract from ncbi


suck pdf from google scholar
unlimited free pdf from europmc32367765    free
PDF from PMC    free
html from PMC    free
PDF vom PMID32367765  :  Publisher

suck abstract from ncbi

Nephropedia Template TP Text

Twit Text FOAVip

Twit Text #

English Wikipedia

  • Prediction of severe illness due to COVID-19 based on an analysis of initial Fibrinogen to Albumin Ratio and Platelet count #MMPMID32367765
  • Bi X; Su Z; Yan H; Du J; Wang J; Chen L; Peng M; Chen S; Shen B; Li J
  • Platelets 2020[Jul]; 31 (5): 674-679 PMID32367765show ga
  • Concomitant coagulation disorder can occur in severe patients withCOVID-19, but in-depth studies are limited. This study aimed to describe the parameters of coagulation function of patients with COVID-19 and reveal the risk factors of developing severe disease. This study retrospectively analyzed 113patients with SARS-CoV-2 infection in Taizhou Public Health Center. Clinical characteristics and indexes of coagulation function were collected. A multivariate Cox analysis was performed to identify potential biomarkers for predicting disease progression. Based on the results of multivariate Cox analysis, a Nomogram was built and the predictive accuracy was evaluated through the calibration curve, decision curve, clinical impact curve, and Kaplan-Meier analysis. Sensitivity, specificity, predictive values were calculated to assess the clinical value. The data showed that Fibrinogen, FAR, and D-dimer were higher in the severe patients, while PLTcount, Alb were much lower. Multivariate Cox analysis revealed that FAR and PLT count were independent risk factors for disease progression. The optimal cutoff values for FAR and PLT count were 0.0883 and 135*10(9)/L, respectively. The C-index [0.712 (95% CI = 0.610-0.814)], decision curve, clinical impact curve showed that Nomogram could be used to predict the disease progression. In addition, the Kaplan-Meier analysis revealed that potential risk decreased in patients with FAR<0.0883 and PLT count>135*10(9)/L.The model showed a good negative predictive value [(0.9474 (95%CI = 0.845-0.986)].This study revealed that FAR and PLT count were independent risk factors for severe illness and the severity of COVID-19 might be excluded when FAR<0.0883 and PLT count>135*10(9)/L.
  • |*Betacoronavirus[MESH]
  • |*Nomograms[MESH]
  • |*Pandemics[MESH]
  • |*Platelet Count[MESH]
  • |Adult[MESH]
  • |Area Under Curve[MESH]
  • |Biomarkers/blood[MESH]
  • |Blood Coagulation Tests[MESH]
  • |China/epidemiology[MESH]
  • |Coronavirus Infections/*blood/epidemiology[MESH]
  • |Disease Progression[MESH]
  • |Female[MESH]
  • |Fibrin Fibrinogen Degradation Products/analysis[MESH]
  • |Fibrinogen/*analysis[MESH]
  • |Humans[MESH]
  • |Kaplan-Meier Estimate[MESH]
  • |Male[MESH]
  • |Middle Aged[MESH]
  • |Pneumonia, Viral/*blood/epidemiology[MESH]
  • |Predictive Value of Tests[MESH]
  • |Prognosis[MESH]
  • |Proportional Hazards Models[MESH]
  • |ROC Curve[MESH]
  • |Retrospective Studies[MESH]
  • |Risk Factors[MESH]
  • |Serum Albumin, Human/*analysis[MESH]
  • |Symptom Assessment[MESH]

  • DeepDyve
  • Pubget Overpricing
  • suck abstract from ncbi

    674 5.31 2020