Selected article for: "community healthcare and healthcare system"
Author: Tagliabue, Fabio; Schena, Daniele; Galassi, Luca; Magni, Matteo; Guerrazzi, Guglielmo; Acerbis, Andrea; Rinallo, Christina; Longhi, Daniel; Ronzani, Alberto; Mariani, Pierpaolo
Title: Modified National Early Warning Score as Early Predictor of Outcome in COVID-19 Pandemic
  • Cord-id: 2paw9q5s
  • Document date: 2021_6_18
    • ID: 2paw9q5s
    Snippet: COVID-19 represented an important challenge to the Italian healthcare system (IHCS). Our main aim was to obtain evidence to support the use of modified national early warning score (m-NEWS) as an interdisciplinary, common, and universal scoring scale to quickly recognize patients with a risk of clinical deterioration before admission and during hospitalization. As a secondary goal, we tried to find a score threshold that can trigger patients’ immediate medical review as a part of an optimal tr
    Document: COVID-19 represented an important challenge to the Italian healthcare system (IHCS). Our main aim was to obtain evidence to support the use of modified national early warning score (m-NEWS) as an interdisciplinary, common, and universal scoring scale to quickly recognize patients with a risk of clinical deterioration before admission and during hospitalization. As a secondary goal, we tried to find a score threshold that can trigger patients’ immediate medical review as a part of an optimal triaging protocol for an emergency setting where healthcare resources are overloaded. We performed a retrospective observational study. We included in our study all patients treated for COVID-19 infection in surgical departments between 01 March 2020 and 16 April 2020. Patients with negative test results for SARS-COV-2 were excluded. m-NEWS was obtained twice a day. Patients’ m-NEWS were analyzed in order to verify the correlation between m-NEWS (at admission and m-NEWS variation 24 h after admission) and outcome (positive outcome-survival, negative outcome-death, or intensive care unit (ICU) transfer). We included a population-based sample of 225 SARS-COV-2-infected patients. Overall, the average age at hospitalization was 71 (ranging from 40 to 95). 144 (64%) patients were males and 81 (36%) females. m-NEWS values lower or equal to 7 were associated with the majority of the “recovered” population (100/132 75.75%) and at the same time with the minority of the “non-recovered” population (25/93 26.88%). For our sample, age is statistically correlated to the outcome but a triage protocol based solely on this variable is less effective than m-NEWS, which showed to be a reliable and easy-to-use score for first patient evaluation. Our observations pave the way towards further studies aiming at optimizing territorial and community healthcare management protocols.

    Search related documents:
    Co phrase search for related documents
    • active neoplasm and logistic regression: 1
    • actual need and admission time: 1
    • acute deterioration and admission time: 1
    • acute deterioration and liver renal: 1
    • acute deterioration and liver renal function: 1
    • acute deterioration and local committee: 1
    • acute deterioration and logistic regression: 1, 2, 3, 4, 5, 6
    • acute deterioration and logistic regression analysis: 1, 2
    • admission moment and logistic regression: 1, 2, 3
    • admission news and logistic regression: 1, 2, 3, 4, 5
    • admission news and logistic regression analysis: 1, 2, 3
    • admission news and logistic regression analysis multivariate: 1
    • admission time and liver renal: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13
    • admission time and liver renal function: 1, 2, 3, 4, 5, 6
    • admission time and logistic regression: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
    • admission time and logistic regression analysis: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
    • admission time and logistic regression analysis multivariate: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12
    • admission variable and logistic regression analysis: 1, 2, 3, 4, 5
    • admission variable and logistic regression analysis multivariate: 1, 2