Clinical decision rules for termination of resuscitation during in-hospital cardiac arrest: A systematic review of diagnostic test accuracy studies

Termination of Resuscitation Rules and Survival Among Patients With Out-of-Hospital Cardiac Arrest: A Systematic Review and Meta-Analysis

Importance

Termination of resuscitation (TOR) rules may help guide prehospital decisions to stop resuscitation, with potential effects on patient outcomes and health resource use. Rules with high sensitivity risk increasing inappropriate transport of nonsurvivors, while rules without excellent specificity risk missed survivors. Further examination of the performance of TOR rules in estimating survival of out-of-hospital cardiac arrest (OHCA) is needed.

Objective

To determine whether TOR rules can accurately identify patients who will not survive an OHCA.

Data Sources

For this systematic review and meta-analysis, the MEDLINE, Embase, CINAHL, Cochrane Library, and Web of Science databases were searched from database inception up to January 11, 2024. There were no restrictions on language, publication date, or time frame of the study.

Study Selection

Two reviewers independently screened records, first by title and abstract and then by full text. Randomized clinical trials, case-control studies, cohort studies, cross-sectional studies, retrospective analyses, and modeling studies were included. Systematic reviews and meta-analyses were reviewed to identify primary studies. Studies predicting outcomes other than death, in-hospital studies, animal studies, and non-peer-reviewed studies were excluded.

Data Extraction and Synthesis

Data were extracted by one reviewer and checked by a second. Two reviewers assessed risk of bias using the Revised Quality Assessment Tool for Diagnostic Accuracy Studies. Cochrane Screening and Diagnostic Tests Methods Group recommendations were followed when conducting a bivariate random-effects meta-analysis. This review followed the Preferred Reporting Items for a Systematic Review and Meta-Analysis of Diagnostic Test Accuracy Studies (PRISMA-DTA) statement and is registered with the International Prospective Register of Systematic Reviews (CRD42019131010).

Main Outcomes and Measures

Sensitivity and specificity tables with 95% CIs and bivariate summary receiver operating characteristic (SROC) curves were produced. Estimates of effects at different prevalence levels were calculated. These estimates were used to evaluate the practical implications of TOR rule use at different prevalence levels.

Results

This review included 43 nonrandomized studies published between 1993 and 2023, addressing 29 TOR rules and involving 1 125 587 cases. Fifteen studies reported the derivation of 20 TOR rules. Thirty-three studies reported external data validations of 17 TOR rules. Seven TOR rules had data to facilitate meta-analysis. One clinical study was identified. The universal termination of resuscitation rule had the best performance, with pooled sensitivity of 0.62 (95% CI, 0.54-0.71), pooled specificity of 0.88 (95% CI, 0.82-0.94), and a diagnostic odds ratio of 20.45 (95% CI, 13.15-31.83).

Conclusions and Relevance

In this review, there was insufficient robust evidence to support widespread implementation of TOR rules in clinical practice. These findings suggest that adoption of TOR rules may lead to missed survivors and increased resource utilization.

Organ Donation After Out-of-Hospital Cardiac Arrest: A Scientific Statement From the International Liaison Committee on Resuscitation

AIM OF THE REVIEW

Improving rates of organ donation among patients with out-of-hospital cardiac arrest who do not survive is an opportunity to save countless lives. The objectives of this scientific statement were to do the following: define the opportunity for organ donation among patients with out-of-hospital cardiac arrest; identify challenges and opportunities associated with organ donation by patients with cardiac arrest; identify strategies, including a generic protocol for organ donation after cardiac arrest, to increase the rate and consistency of organ donation from this population; and provide rationale for including organ donation as a key clinical outcome for all future cardiac arrest clinical trials and registries.

METHODS

The scope of this International Liaison Committee on Resuscitation scientific statement was approved by the International Liaison Committee on Resuscitation board and the American Heart Association, posted on ILCOR.org for public comment, and then assigned by section to primary and secondary authors. A unique literature search was completed and updated for each section.

RESULTS

There are a number of defining pathways for patients with out-of-hospital cardiac arrest to become organ donors; however, modifications in the Maastricht classification system need to be made to correctly identify these donors and to report outcomes with consistency. Suggested modifications to the minimum data set for reporting cardiac arrests will increase reporting of organ donation as an important resuscitation outcome. There are a number of challenges with implementing uncontrolled donation after cardiac death protocols, and the greatest impediment is the lack of legislation in most countries to mandate organ donation as the default option. Extracorporeal cardiopulmonary resuscitation has the potential to increase organ donation rates, but more research is needed to derive neuroprognostication rules to guide clinical decision-making about when to stop extracorporeal cardiopulmonary resuscitation and to evaluate cost-effectiveness.

CONCLUSIONS

All health systems should develop, implement, and evaluate protocols designed to optimize organ donation opportunities for patients who have an out-of-hospital cardiac arrest and failed attempts at resuscitation.

Organ Donation After Out-of-Hospital Cardiac Arrest: A Scientific Statement From the International Liaison Committee on Resuscitation

AIM OF THE REVIEW

Improving rates of organ donation among patients with out-of-hospital cardiac arrest who do not survive is an opportunity to save countless lives. The objectives of this scientific statement were to do the following: define the opportunity for organ donation among patients with out-of-hospital cardiac arrest; identify challenges and opportunities associated with organ donation by patients with cardiac arrest; identify strategies, including a generic protocol for organ donation after cardiac arrest, to increase the rate and consistency of organ donation from this population; and provide rationale for including organ donation as a key clinical outcome for all future cardiac arrest clinical trials and registries.

METHODS

The scope of this International Liaison Committee on Resuscitation scientific statement was approved by the International Liaison Committee on Resuscitation board and the American Heart Association, posted on ILCOR.org for public comment, and then assigned by section to primary and secondary authors. A unique literature search was completed and updated for each section.

RESULTS

There are a number of defining pathways for patients with out-of-hospital cardiac arrest to become organ donors; however, modifications in the Maastricht classification system need to be made to correctly identify these donors and to report outcomes with consistency. Suggested modifications to the minimum data set for reporting cardiac arrests will increase reporting of organ donation as an important resuscitation outcome. There are a number of challenges with implementing uncontrolled donation after cardiac death protocols, and the greatest impediment is the lack of legislation in most countries to mandate organ donation as the default option. Extracorporeal cardiopulmonary resuscitation has the potential to increase organ donation rates, but more research is needed to derive neuroprognostication rules to guide clinical decision-making about when to stop extracorporeal cardiopulmonary resuscitation and to evaluate cost-effectiveness.

CONCLUSIONS

All health systems should develop, implement, and evaluate protocols designed to optimise organ donation opportunities for patients who have an out-of-hospital cardiac arrest and failed attempts at resuscitation.

The value of a machine learning algorithm to predict adverse short-term outcome during resuscitation of patients with in-hospital cardiac arrest: a retrospective study

Background and importance Guidelines recommend that hospital emergency teams locally validate criteria for termination of cardiopulmonary resuscitation in patients with in-hospital cardiac arrest (IHCA). Objective To determine the value of a machine learning algorithm to predict failure to achieve return of spontaneous circulation (ROSC) and unfavourable functional outcome from IHCA using only data readily available at emergency team arrival. Design Retrospective cohort study. Setting and participants Adults who experienced an IHCA were attended to by the emergency team. Outcome measures and analysis Demographic and clinical data typically available at the arrival of the emergency team were extracted from the institutional IHCA database. In addition, outcome data including the Cerebral Performance Category (CPC) score count at hospital discharge were collected. A model selection procedure for random forests with a hyperparameter search was employed to develop two classification algorithms to predict failure to achieve ROSC and unfavourable (CPC 3-5) functional outcomes. Main results Six hundred thirty patients were included, of which 390 failed to achieve ROSC (61.9%). The final classification model to predict failure to achieve ROSC had an area under the receiver operating characteristic curve of 0.9 [95% confidence interval (CI), 0.89-0.9], a balanced accuracy of 0.77 (95% CI, 0.75-0.79), an F1-score of 0.78 (95% CI, 0.76-0.79), a positive predictive value of 0.88 (0.86-0.91), a negative predictive value of 0.61 (0.6-0.63), a sensitivity of 0.69 (0.66-0.72), and a specificity of 0.84 (0.8-0.88). Five hundred fifty-nine subjects experienced an unfavourable outcome (88.7%). The final classification model to predict unfavourable functional outcomes from IHCA at hospital discharge had an area under the receiver operating characteristic curve of 0.93 (95% CI, 0.92-0.93), a balanced accuracy of 0.59 (95% CI, 0.57-0.61), an F1-score of 0.94 (95% CI, 0.94-0.95), a positive predictive value of 0.91 (0.9-0.91), a negative predictive value of 0.57 (0.48-0.66), a sensitivity of 0.98 (0.97-0.99), and a specificity of 0.2 (0.16-0.24). Conclusion Using data readily available at emergency team arrival, machine learning algorithms had a high predictive power to forecast failure to achieve ROSC and unfavourable functional outcomes from IHCA while cardiopulmonary resuscitation was still ongoing; however, the positive predictive value of both models was not high enough to allow for early termination of resuscitation efforts.

Pre-arrest Prediction of Survival Following In-hospital Cardiac Arrest: A Systematic Review of Diagnostic Test Accuracy Studies

AIM

To evaluate the test accuracy of pre-arrest clinical decision tools for in-hospital cardiac arrest survival outcomes.

METHODS

We searched Medline, Embase, and Cochrane Library from inception through January 2022 for randomized and non-randomized studies. We used the Quality Assessment of Diagnostic Accuracy Studies framework to evaluate risk of bias, and Grading of Recommendations Assessment, Development and Evaluation methodology to evaluate certainty of evidence. We report sensitivity, specificity, positive predictive outcome, and negative predictive outcome for prediction of survival outcomes. PROSPERO CRD42021268005.

RESULTS

We searched 2517 studies and included 23 studies using 13 different scores: 12 studies investigating 8 different scores assessing survival outcomes and 11 studies using 5 different scores to predict neurological outcomes. All were historical cohorts/ case control designs including adults only. Test accuracy for each score varied greatly. Across the 12 studies investigating 8 different scores assessing survival to hospital discharge/ 30-day survival, the negative predictive values (NPVs) for the prediction of survival varied from 55.6% to 100%. The GO-FAR score was evaluated in 7 studies with NPVs for survival with cerebral performance category (CPC) 1 ranging from 95.0% to 99.2%. Two scores assessed survival with CPC ≤2 and these were not externally validated. Across all prediction scores, certainty of evidence was rated as very low.

CONCLUSIONS

We identified very low certainty evidence across 23 studies for 13 different pre-arrest prediction scores to outcome following IHCA. No score was sufficiently reliable to support its use in clinical practice. We identified no evidence for children.