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


10.1002/cnr2.1358

http://scihub22266oqcxt.onion/10.1002/cnr2.1358
suck pdf from google scholar
33656801!7994963!33656801
unlimited free pdf from europmc33656801    free
PDF from PMC    free
html from PMC    free

Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=33656801&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215

suck abstract from ncbi

pmid33656801      Cancer+Rep+(Hoboken) 2021 ; 4 (4): e1358
Nephropedia Template TP

gab.com Text

Twit Text FOAVip

Twit Text #

English Wikipedia


  • The direct and indirect effects of COVID-19 pandemic in a real-life hematological setting #MMPMID33656801
  • Condom M; Mussetti A; Maluquer C; Parody R; Gonzalez-Barca E; Arnan M; Albasanz-Puig A; Pomares H; Salas MQ; Carro I; Pena M; Clapes V; Baca Cano C; Oliveira Ramos AC; Sanz-Linares G; Moreno-Gonzalez G; Mercadal S; Boque C; Gudiol C; Domingo-Domenech E; Sureda A
  • Cancer Rep (Hoboken) 2021[Aug]; 4 (4): e1358 PMID33656801show ga
  • BACKGROUND: Clinical outcomes of novel coronavirus 2019 disease (COVID-19) in onco-hematological patients are unknown. When compared to non-immunocompromised patients, onco-hematological patients seem to have higher mortality rates. AIMS: We describe the characteristics and outcomes of a consecutive cohort of 24 onco-hematological patients with COVID-19 during the first month of the pandemic. We also describe variations in healthcare resource utilization within our hematology department. METHODS AND RESULTS: Data from patients between the first month of the pandemic were retrospectively collected. Clinical and logistic data were also collected and compared with the average values from the prior 3 months of activity. Prevalence of COVID-19 in our hematological population was 0.4%. Baseline characteristics were as follows: male sex: 83%, lymphoid diseases: 46%, median age: 69 (22-82) years. Median follow-up in survivors was 14 (9-28) days and inpatient mortality rate was 46%. Average time to moderate/severe respiratory insufficiency and death were 3 (1-10) and 10 (3-18) days, respectively. Only 1 out of every 12 patients who developed moderate to severe respiratory insufficiency recovered. Upon univariate analysis, the following factors were associated with higher mortality: age >/= 70 years (P = .01) and D-dimer >/=900 mcg/L (P = .04). With respect to indirect effects during the COVID-19 pandemic, and when compared with the prior 3 months of activity, inpatient mortality (excluding patients with COVID-19 included in the study) increased by 56%. This was associated with a more frequent use of vasoactive drugs (+300%) and advanced respiratory support (+133%) in the hematology ward. In the outpatient setting, there was a reduction in initial visits (-55%) and chemotherapy sessions (-19%). A significant increase in phone visits was reported (+581%). CONCLUSION: COVID-19 pandemic is associated with elevated mortality in hematological patients. Negative indirect effects are also evident within this setting.
  • |Adult[MESH]
  • |Aged[MESH]
  • |Aged, 80 and over[MESH]
  • |Antineoplastic Agents/*therapeutic use[MESH]
  • |Antiviral Agents/*therapeutic use[MESH]
  • |COVID-19 Drug Treatment[MESH]
  • |COVID-19/*complications/transmission/virology[MESH]
  • |Drug Therapy, Combination[MESH]
  • |Female[MESH]
  • |Hematologic Neoplasms/drug therapy/epidemiology/*mortality/virology[MESH]
  • |Humans[MESH]
  • |Male[MESH]
  • |Middle Aged[MESH]
  • |Prognosis[MESH]
  • |Retrospective Studies[MESH]
  • |SARS-CoV-2/*isolation & purification[MESH]
  • |Spain/epidemiology[MESH]
  • |Survival Rate[MESH]


  • DeepDyve
  • Pubget Overpricing
  • suck abstract from ncbi

    Linkout box