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


10.3233/XST-200685

http://scihub22266oqcxt.onion/10.3233/XST-200685
suck pdf from google scholar
32474479!7369060!32474479
unlimited free pdf from europmc32474479    free
PDF from PMC    free
html from PMC    free

suck abstract from ncbi


Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
pmid32474479      J+Xray+Sci+Technol 2020 ; 28 (3): 383-389
Nephropedia Template TP

gab.com Text

Twit Text FOAVip

Twit Text #

English Wikipedia


  • Analysis of thin-section CT in patients with coronavirus disease (COVID-19) after hospital discharge #MMPMID32474479
  • Wei J; Yang H; Lei P; Fan B; Qiu Y; Zeng B; Yu P; Lv J; Jian Y; Wan C
  • J Xray Sci Technol 2020[]; 28 (3): 383-389 PMID32474479show ga
  • PURPOSE: To analyze clinical and thin-section computed tomographic (CT) data from the patients with coronavirus disease (COVID-19) to predict the development of pulmonary fibrosis after hospital discharge. MATERIALS AND METHODS: Fifty-nine patients (31 males and 28 females ranging from 25 to 70 years old) with confirmed COVID-19 infection performed follow-up thin-section thorax CT. After 31.5+/-7.9 days (range, 24 to 39 days) of hospital admission, the results of CT were analyzed for parenchymal abnormality (ground-glass opacification, interstitial thickening, and consolidation) and evidence of fibrosis (parenchymal band, traction bronchiectasis, and irregular interfaces). Patients were analyzed based on the evidence of fibrosis and divided into two groups namely, groups A and B (with and without CT evidence of fibrosis), respectively. Patient demographics, length of stay (LOS), rate of intensive care unit (ICU) admission, peak C-reactive protein level, and CT score were compared between the two groups. RESULTS: Among the 59 patients, 89.8% (53/59) had a typical transition from early phase to advanced phase and advanced phase to dissipating phase. Also, 39% (23/59) patients developed fibrosis (group A), whereas 61% (36/59) patients did not show definite fibrosis (group B). Patients in group A were older (mean age, 45.4+/-16.9 vs. 33.8+/-10.2 years) (P = 0.001), with longer LOS (19.1+/-5.2 vs. 15.0+/-2.5 days) (P = 0.001), higher rate of ICU admission (21.7% (5/23) vs. 5.6% (2/36)) (P = 0.061), higher peak C-reactive protein level (30.7+/-26.4 vs. 18.1+/-17.9 mg/L) (P = 0.041), and higher maximal CT score (5.2+/-4.3 vs. 4.0+/-2.2) (P = 0.06) than those in group B. CONCLUSIONS: Pulmonary fibrosis may develop early in patients with COVID-19 after hospital discharge. Older patients with severe illness during treatment were more prone to develop fibrosis according to thin-section CT results.
  • |*Betacoronavirus[MESH]
  • |*Patient Discharge[MESH]
  • |Adult[MESH]
  • |Aged[MESH]
  • |COVID-19[MESH]
  • |Coronavirus Infections/*complications[MESH]
  • |Female[MESH]
  • |Humans[MESH]
  • |Lung/*diagnostic imaging[MESH]
  • |Male[MESH]
  • |Middle Aged[MESH]
  • |Pandemics[MESH]
  • |Pneumonia, Viral/*complications[MESH]
  • |Pulmonary Fibrosis/*complications/*diagnostic imaging[MESH]
  • |Retrospective Studies[MESH]
  • |SARS-CoV-2[MESH]


  • DeepDyve
  • Pubget Overpricing
  • suck abstract from ncbi

    Linkout box