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Mechanical life support algorithm developed by simulation for inpatient emergency management of recipients of implantable left ventricular assist devices.
Akhtar, Waqas; Gamble, Brigitte; Kiff, Kristine; Wypych-Zych, Agnieszka; Raj, Binu; Takata, Junko; Gil, Fernando Riesgo; Hurtado, Ana; Rosenberg, Alex; Bowles, Christopher T.
Afiliação
  • Akhtar W; Harefield Hospital, Hill End Road, Harefield, Uxbridge UB96JH, United Kingdom.
  • Gamble B; Harefield Hospital, Hill End Road, Harefield, Uxbridge UB96JH, United Kingdom.
  • Kiff K; Harefield Hospital, Hill End Road, Harefield, Uxbridge UB96JH, United Kingdom.
  • Wypych-Zych A; Harefield Hospital, Hill End Road, Harefield, Uxbridge UB96JH, United Kingdom.
  • Raj B; Harefield Hospital, Hill End Road, Harefield, Uxbridge UB96JH, United Kingdom.
  • Takata J; Harefield Hospital, Hill End Road, Harefield, Uxbridge UB96JH, United Kingdom.
  • Gil FR; Harefield Hospital, Hill End Road, Harefield, Uxbridge UB96JH, United Kingdom.
  • Hurtado A; Harefield Hospital, Hill End Road, Harefield, Uxbridge UB96JH, United Kingdom.
  • Rosenberg A; Harefield Hospital, Hill End Road, Harefield, Uxbridge UB96JH, United Kingdom.
  • Bowles CT; Harefield Hospital, Hill End Road, Harefield, Uxbridge UB96JH, United Kingdom.
Resusc Plus ; 10: 100254, 2022 Jun.
Article em En | MEDLINE | ID: mdl-35669526
Background: Published guidance concerning emergency management of left ventricular assist device (LVAD) recipients is both limited and lacking in consensus which increases the risk of delayed and/or inappropriate actions. Methods: In our specialist tertiary referral centre we developed, by iteration, a novel in-hospital resuscitation algorithm for LVAD emergencies which we validated through simulation and assessment of our multi-disciplinary team. A Mechanical Life Support course was established to provide theoretical and practical education combined with simulation to consolidate knowledge and confidence in algorithm use. We assessed these measures using confidence scoring, a key performance indicator (the time taken to restart LVAD function) and a multiple-choice question (MCQ) examination. Results: The mean baseline staff confidence score in management of LVAD emergencies was 2.4 ± 1.2 out of a maximum of 5 (n = 29). After training with simulation, mean confidence score increased to 3.5 ± 0.8 (n = 13).Clinical personnel who were provided with the novel resuscitation algorithm were able to reduce time taken to restart LVAD function from a mean value of 49 ± 8.2 seconds (pre-training) to 20.4 ± 5 seconds (post-training) (n = 42, p < 0.0001).The Mechanical Life Support course increased mean confidence from 2.5 ± 1.2 to 4 ± 0.6 (n = 44, p < 0.0001) and mean MCQ score from 18.7 ± 3.4 to 22.8 ± 2.6, out of a maximum of 28 (n = 44, p < 0.0001). Conclusion: We present a simplified LVAD Advanced Life Support algorithm to aid the crucial first minutes of resuscitation where basic interventions are likely to be critical in assuring good patient outcomes.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline / Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline / Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article