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Record W4387358713 · doi:10.1093/ehjacc/zuad121

None of us alone is as effective as all of us together

2023· article· en· W4387358713 on OpenAlexaff
Alexander G. Truesdell, Carolyn Rosner, Christopher B. Fordyce

Bibliographic record

VenueEuropean Heart Journal Acute Cardiovascular Care · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPsychologyHistory

Abstract

fetched live from OpenAlex

Cardiogenic shock (CS) complicating either acute myocardial infarction (AMI) or acute decompensated heart failure (ADHF) accounts for over 10% of cardiac intensive care unit (CICU) admissions and is a leading cause of in-hospital cardiovascular death—with mortality rates commonly exceeding 50% despite advances in pharmacologic and device-based therapies (with limited randomized controlled evidence for either).1,2 A volume–outcome relationship (with unfortunately highly variable inter-facility outcomes) has been observed in the management of many high-risk cardiovascular conditions to include CS—whereas patients and communities everywhere expect and deserve equity of care regardless of time of day or geography.3 Highly complex data [such as pulmonary artery catheter (PAC) derived haemodynamic parameters], technologies [to include short-term mechanical circulatory support (MCS) devices], and decision-making strategies (as required with CS) may especially benefit from multi-disciplinary multi-specialty team-based care—which already has much support for use in more stable and less time-sensitive cardiovascular conditions such as advanced coronary re-vascularization and trans-valvular therapies.4,5 Multiple contemporary single-centre non-randomized North American registry studies suggest that implementation of a standardized multi-disciplinary team-based approach to CS identification, triage, and management may help reduce high CS mortality rates within individual hospitals and even across larger regional healthcare networks.6–11 Several of these registries noted up to 50% survival improvements, which were sustained over multiple years, even with increasing shock patient volumes and expanding geographic catchment areas.6–11 Based in part on this registry data, the 2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure assigned a 2a (level of evidence B) recommendation to the management of CS patients by a multi-disciplinary team experienced in shock and a 2b (level of evidence C) recommendation for consideration of transfer of refractory patients to centres offering temporary MCS.12 However, this shock team approach has not been widely adopted outside North America. In this issue of the European Heart Journal: Acute Cardiovascular Care, Hérion et al.13 report the results of a retrospective before-and-after single-centre cohort study conducted over a 156-month period examining the outcomes of 250 consecutive adult patients with refractory CS treated with short-term MCS with (n = 166; 2013–19) and without (n = 84; 2007–2013) implementation and utilization of a shock treatment algorithm and multi-disciplinary shock team for decision-making and management. The investigators noted a higher 1-year survival in the contemporary shock team vs. historical control (no shock team) groups (59% vs. 45%, P = 0.043), and after Cox regression analysis, the shock team intervention was independently associated with a significantly improved 1-year survival rate [hazard ratio (HR): 0.592, 95% confidence interval (CI): 0.398–0.0880, P = 0.010]. The authors concluded that a multi-disciplinary shock team–based decision-making strategy for short-term MCS device implantation is associated with better 1-year survival rates (Figure 1). Independent and sequential decision-making versus collaborative, multidisciplinary, team-based decision-making in the management of cardiogenic shock. Shock team composition—which is an evolving concept—presently differs among centres in different regions dependent in part upon individual hospital and healthcare system needs and resources.14 The authors’ shock team was comprised of a cardiothoracic surgeon, an interventional cardiologist, and a cardiac-specialized anesthetist–intensivist—with delayed involvement of a heart failure specialist. This team was not activated pre-hospital by Emergency Medical Services or by the Emergency Department or by the Cardiac Catheterization Laboratory—but only by the CICU physician. All shock team conversations were conducted in-person and included the three specialist physicians who were available on-site 24 h per day every day—which contrasts with other contemporary shock teams who employ virtual telephonic or video communication platforms to ensure continuous availability of multiple medical experts often across large geographic zones.6–9,11 Allowing multiple individuals—beyond just the cardiac intensivist—to initiate shock team consultation and immediate involvement of heart failure and transplant specialists could further improve outcomes and resource utilization and should be considered when implementing a shock team process of care in other locations. As did others before them, the authors highlighted the use of standardized shock protocols, haemodynamic profiling, a selective and tailored approach to MCS use, and the employment of a multi-disciplinary shock team. Reinforcing an often-cited benefit of multi-disciplinary shock team decision-making, the ‘time to decision’ decreased by over 50% in this registry following shock team implementation (2.0 h vs. 5.2 h), and for the AMI CS cohort, there was a shorter time delay to coronary re-vascularization—which are both tremendous accomplishments considering the known impact of even brief treatment delays on CS mortality.6,15 Importantly, the investigators collected and reported CICU, in-hospital, 30-day, 3-month, 6-month, and 1-year post-discharge outcomes data. The study population only included patients with refractory CS receiving short-term MCS—which represents only a small proportion of patients in whom shock teams are activated—and data regarding CS patients treated with only inotrope or vasopressor therapy or triaged to palliation were not reported. Devices used in this centre were IABP, Impella 2.5, CP and 5.0, VA-ECMO, or combinations of these devices together. This may not reflect MCS device options available or in-use at all medical centres. Furthermore, the impact of one device over another (an area of tremendous interest) in this study is unclear and emphasizes the notion that MCS is just one component of shock team management. A weakness of the study is the small number of patients in both arms as well as the 12-year period over which the study was conducted, during which time there have been many potentially confounding clinical innovations that may have positively impacted shock care and shock survival (well beyond just the implementation of a shock team and shock protocol care strategy). Another limitation is the study’s significant selection bias. As only patients with refractory CS receiving short-term MCS were included in this analysis, there is a strong likelihood of having excluded patients who were not candidates for MCS (due to vascular access limitations, perceived futility, team discretion, or other factors) and/or patients for whom shock team consultation was not solicited or provided. Multiple different interventions were also employed by the study team during the span of this 12-year care transformation: formation of a multi-disciplinary CS team, development and implementation of a standardized protocol, increased utilization of PACs, and changes in MCS utilization and type. Parsing out the individual impact of each of these may be impossible. The promise of shock protocols, shock teams, and shock networks is that they may be able to better standardize and expedite CS diagnosis and treatment and minimize unwanted heterogeneities of care and resultant clinical outcomes both within and between medical facilities.10 Shock teams may be employed anywhere, at facilities large and small, ideally in a hub-and-spoke configuration, and should not be defined by the use (or not) of MCS, but rather by rapid, collaborative decision-making and intervention, and repeated data-driven feedback loops. This work also highlights the importance of multiple future lines of investigation in CS care: haemodynamic profiling, shock protocols, shock teams, shock centres, the role of MCS devices, and longer-term post-discharge outcomes for CS survivors. Charles Darwin purportedly stated, ‘in the long history of humankind, those who learned to collaborate most effectively have prevailed’. So, it is encouraging to see further investigations on additional continents outside North America supporting the role of multi-disciplinary team-based collaborative care for the sickest of our cardiovascular patients. None declared. No new data were generated or analysed in support of this research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.379
Threshold uncertainty score0.779

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.290
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2023
Admission routes1
Has abstractyes

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