All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Machine learning determination of motivators of terminal extubation during the transition to end-of-life care in intensive care unit

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00064173%3A_____%2F23%3A43925142" target="_blank" >RIV/00064173:_____/23:43925142 - isvavai.cz</a>

  • Alternative codes found

    RIV/00216208:11120/23:43925142

  • Result on the web

    <a href="https://doi.org/10.1038/s41598-023-29042-9" target="_blank" >https://doi.org/10.1038/s41598-023-29042-9</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1038/s41598-023-29042-9" target="_blank" >10.1038/s41598-023-29042-9</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Machine learning determination of motivators of terminal extubation during the transition to end-of-life care in intensive care unit

  • Original language description

    Procedural aspects of compassionate care such as the terminal extubation are understudied. We used machine learning methods to determine factors associated with the decision to extubate the critically ill patient at the end of life, and whether the terminal extubation shortens the dying process. We performed a secondary data analysis of a large, prospective, multicentre, cohort study, death prediction and physiology after removal of therapy (DePPaRT), which collected baseline data as well as ECG, pulse oximeter and arterial waveforms from WLST until 30 min after death. We analysed a priori defined factors associated with the decision to perform terminal extubation in WLST using the random forest method and logistic regression. Cox regression was used to analyse the effect of terminal extubation on time from WLST to death. A total of 616 patients were included into the analysis, out of which 396 (64.3%) were terminally extubated. The study centre, low or no vasopressor support, and good respiratory function were factors significantly associated with the decision to extubate. Unadjusted time to death did not differ between patients with and without extubation (median survival time extubated vs. not extubated: 60 [95% CI: 46; 76] vs. 58 [95% CI: 45; 75] min). In contrast, after adjustment for confounders, time to death of extubated patients was significantly shorter (49 [95% CI: 40; 62] vs. 85 [95% CI: 61; 115] min). The decision to terminally extubate is associated with specific centres and less respiratory and/or vasopressor support. In this context, terminal extubation was associated with a shorter time to death.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    30221 - Critical care medicine and Emergency medicine

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Scientific Reports

  • ISSN

    2045-2322

  • e-ISSN

    2045-2322

  • Volume of the periodical

    13

  • Issue of the periodical within the volume

    February

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    10

  • Pages from-to

    2632

  • UT code for WoS article

    001100562500015

  • EID of the result in the Scopus database

    2-s2.0-85148081876