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


10.1080/07853890.2020.1828616

http://scihub22266oqcxt.onion/10.1080/07853890.2020.1828616
suck pdf from google scholar
32997542!7877986!32997542
unlimited free pdf from europmc32997542    free
PDF from PMC    free
html from PMC    free

suck abstract from ncbi


Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 251.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 251.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
pmid32997542      Ann+Med 2021 ; 53 (1): 78-86
Nephropedia Template TP

gab.com Text

Twit Text FOAVip

Twit Text #

English Wikipedia


  • External validation of a clinical risk score to predict hospital admission and in-hospital mortality in COVID-19 patients #MMPMID32997542
  • Halalau A; Imam Z; Karabon P; Mankuzhy N; Shaheen A; Tu J; Carpenter C
  • Ann Med 2021[Dec]; 53 (1): 78-86 PMID32997542show ga
  • BACKGROUND: Identification of patients with novel coronavirus disease 2019 (COVID-19) requiring hospital admission or at high-risk of in-hospital mortality is essential to guide patient triage and to provide timely treatment for higher risk hospitalized patients. METHODS: A retrospective multi-centre (8 hospital) cohort at Beaumont Health, Michigan, USA, reporting on COVID-19 patients diagnosed between 1 March and 1 April 2020 was used for score validation. The COVID-19 Risk of Complications Score was automatically computed by the EHR. Multivariate logistic regression models were built to predict hospital admission and in-hospital mortality using individual variables constituting the score. Validation was performed using both discrimination and calibration. RESULTS: Compared to Green scores, Yellow Scores (OR: 5.72) and Red Scores (OR: 19.1) had significantly higher odds of admission (both p < .0001). Similarly, Yellow Scores (OR: 4.73) and Red Scores (OR: 13.3) had significantly higher odds of in-hospital mortality than Green Scores (both p < .0001). The cross-validated C-Statistics for the external validation cohort showed good discrimination for both hospital admission (C = 0.79 (95% CI: 0.77-0.81)) and in-hospital mortality (C = 0.75 (95% CI: 0.71-0.78)). CONCLUSIONS: The COVID-19 Risk of Complications Score predicts the need for hospital admission and in-hospital mortality patients with COVID-19. Key points: Can an electronic health record generated risk score predict the risk of hospital admission and in-hospital mortality in patients diagnosed with coronavirus disease 2019 (COVID-19)? In both validation cohorts of 2,025 and 1,290 COVID-19, the cross-validated C-Statistics showed good discrimination for both hospital admission (C = 0.79 (95% CI: 0.77-0.81)) and in-hospital mortality (C = 0.75 (95% CI: 0.71-0.78)), respectively. The COVID-19 Risk of Complications Score may help predict the need for hospital admission if a patient contracts SARS-CoV-2 infection and in-hospital mortality for a hospitalized patient with COVID-19.
  • |*Betacoronavirus[MESH]
  • |*Hospital Mortality[MESH]
  • |Adult[MESH]
  • |Aged[MESH]
  • |COVID-19[MESH]
  • |Cohort Studies[MESH]
  • |Coronavirus Infections/*mortality/therapy[MESH]
  • |Critical Illness/*mortality/therapy[MESH]
  • |Databases, Factual[MESH]
  • |Female[MESH]
  • |Humans[MESH]
  • |Male[MESH]
  • |Middle Aged[MESH]
  • |Pandemics[MESH]
  • |Pneumonia, Viral/*mortality/therapy[MESH]
  • |Retrospective Studies[MESH]
  • |Risk Assessment[MESH]
  • |Risk Factors[MESH]


  • DeepDyve
  • Pubget Overpricing
  • suck abstract from ncbi

    Linkout box