The 'Surprise question' in heart failure: a prospective cohort study

The Surprise Question and clinician-predicted prognosis: systematic review and meta-analysis

BACKGROUND

The Surprise Question, 'Would you be surprised if this person died within the next year?' is a simple tool that can be used by clinicians to identify people within the last year of life. This review aimed to determine the accuracy of this assessment, across different healthcare settings, specialties, follow-up periods and respondents.

METHODS

Searches were conducted of Medline, Embase, AMED, PubMed and the Cochrane Central Register of Controlled Trials, from inception until 01 January 2024. Studies were included if they reported original data on the ability of the Surprise Question to predict survival. For each study (including subgroups), sensitivity, specificity, positive and negative predictive values and accuracy were determined.

RESULTS

Our dataset comprised 56 distinct cohorts, including 68 829 patients. In a pooled analysis, the sensitivity of the Surprise Question was 0.69 ((0.64 to 0.74) I2=97.2%), specificity 0.69 ((0.63 to 0.74) I2=99.7%), positive predictive value 0.40 ((0.35 to 0.45) I2=99.4%), negative predictive value 0.89 ((0.87 to 0.91) I2=99.7%) and accuracy 0.71 ((0.68 to 0.75) I2=99.3%). The prompt performed best in populations with high event rates, shorter timeframes and when posed to more experienced respondents.

CONCLUSIONS

The Surprise Question demonstrated modest accuracy with considerable heterogeneity across the population to which it was applied and to whom it was posed. Prospective studies should test whether the prompt can facilitate timely access to palliative care services, as originally envisioned.

PROSPERO REGISTRATION NUMBER

CRD32022298236.

Would you be surprised? Prospective multicenter study of the Surprise Question as a screening tool to predict mortality in trauma patients

BACKGROUND

The Surprise Question (SQ) ("Would I be surprised if the patient died within the next year?") is a validated tool used to identify patients with limited life expectancy. Because it may have potential to expedite palliative care interventions per American College of Surgeons Trauma Quality Improvement Program Palliative Care Best Practices Guidelines, we sought to determine if trauma team members could use the SQ to accurately predict 1-year mortality in trauma patients.

METHODS

A multicenter, prospective, cohort study collected data (August 2020 to February 2021) on trauma team members' responses to the SQ at 24 hours from admission. One-year mortality was obtained via social security death index records. Positive/negative predictive values and accuracy were calculated overall, by provider role and by patient age.

RESULTS

Ten Level I/II centers enrolled 1,172 patients (87.9% blunt). The median age was 57 years (interquartile range, 36-74 years), and the median Injury Severity Score was 10 (interquartile range, 5-14 years). Overall 1-year mortality was 13.3%. Positive predictive value was low (30.5%) regardless of role. Mortality prediction minimally improved as age increased (positive predictive value highest between 65 and 74 years old, 34.5%) but consistently trended to overprediction of death, even in younger patients.

CONCLUSION

Trauma team members' ability to forecast 1-year mortality using the SQ at 24 hours appears limited perhaps because of overestimation of injury effects, preinjury conditions, and/or team bias. This has implications for the Trauma Quality Improvement Program Guidelines and suggests that more research is needed to determine the optimal time to screen trauma patients with the SQ.

LEVEL OF EVIDENCE

Prognostic and Epidemiological; Level III.

Palliative care and COVID-19: a bibliometric analysis

OBJECTIVE

To assess the impact of COVID-19 on the palliative care (PC) publication trend in the last 10 years and the collaboration between countries and main topics that were discussed in the papers.

METHODS

We used Scopus to identify publications on PC between 2012 and 2021 and publications about PC and COVID-19 between 2020 and 2021. We used VOSviewer to assess the main topics using the keywords from the papers and to assess country collaboration.

RESULTS

1937 publications resulted. An increase in publications about PC was observed during the pandemic, only partially explained by OVID-19-related publications. Cancer-related PC publications were the ones with the most marked increase. We identified six clusters in the distribution of the keywords: bioethics, cancer, nursing home/telemedicine, public health, caring and PC following the WHO definition. The countries with higher number of publications were the United States and England.

CONCLUSION

We showed an increase in the number of PC publications in the last 2 years that was only partially explained by COVID-19-related publications. Most of the publications increase was due to cancer-related publications, since, during the time of the pandemic, publications on cancer and PC increased markedly, while those on heart failure, lung disease and dementia, remained constant.

The Surprise Question as a Trigger for Primary Palliative Care Interventions for Children with Advanced Heart Disease

There is significant uncertainty in describing prognosis and a lack of reliable entry criteria for palliative care studies in children with advanced heart disease (AHD). This study evaluates the utility of the surprise question-"Would you be surprised if this child died within the next year?"-to predict one-year mortality in children with AHD and assess its utility as entry criteria for future trials. This is a prospective cohort study of physicians and nurses caring for children (1 month-19 years) with AHD hospitalized ≥ 7 days. AHD was defined as single ventricle physiology, pulmonary vein stenosis or pulmonary hypertension, or any cardiac diagnosis with signs of advanced disease. Primary physicians were asked the surprise question and medical record review was performed. Forty-nine physicians responded to the surprise question for 152 patients. Physicians responded "No, I would not be surprised if this patient died" for 54 (36%) patients, 20 (37%) of whom died within 1 year, predicting one-year mortality with 77% sensitivity, 73% specificity, 37% positive predictive value, and 94% negative predictive value. Patients who received a "No" response had an increased 1-year risk of death (hazard ratio 7.25, p < 0.001). Physician years of experience, subspecialty, and self-rated competency were not associated with the accuracy of the surprise question. The surprise question offers promise as a bedside screening tool to identify children with AHD at high risk for mortality and help physicians identify patients who may benefit from palliative care and advance care planning discussions.

'Acute Heart Failure': Should We Abandon the Term Altogether?

PURPOSE OF REVIEW

The distinction between 'acute' and 'chronic' heart failure persists. Our review aims to explore whether reclassifying heart failure decompensation more accurately as an event within the natural history of chronic heart failure has the potential to improve outcomes.

RECENT FINDINGS

Although hospitalisation for worsening heart failure confers a poor prognosis, much of this reflects chronic disease severity. Most patients survive hospitalisation with most deaths occurring in the post-discharge 'vulnerable phase'. Current evidence supports four classes of medications proven to reduce cardiovascular mortality for those who have heart failure with a reduced ejection fraction, with recent trials suggesting worsening heart failure events are opportunities to optimise these therapies. Abandoning the term 'acute heart failure' has the potential to give greater priority to initiating proven pharmacological and device therapies during decompensation episodes, in order to improve outcomes for those who are at the greatest risk.

Enhancing Palliative Care for Patients With Advanced Heart Failure Through Simple Prognostication Tools: A Comparison of the Surprise Question, the Number of Previous Heart Failure Hospitalizations, and the Seattle Heart Failure Model for Predicting 1-Year Survival

Background

Score-based survival prediction in patients with advanced heart failure (HF) is complicated. Easy-to-use prognostication tools could inform clinical decision-making and palliative care delivery.

Objective

To compare the prognostic utility of the Seattle HF model (SHFM), the surprise question (SQ), and the number of HF hospitalizations (NoH) within the last 12 months for predicting 1-year survival in patients with advanced HF.

Methods

We retrospectively analyzed data from a cluster-randomized controlled trial of advanced HF patients, predominantly with reduced ejection fraction. Primary outcome was the prognostic discrimination of SHFM, SQ (“Would you be surprised if this patient were to die within 1 year?”) answered by HF cardiologists, and NoH, assessed by receiver operating characteristic (ROC) curve analysis. Optimal cut-offs were calculated using Youden’s index (SHFM: <86% predicted 1-year survival; NoH ≥ 2).

Results

Of 535 subjects, 82 (15.3%) had died after 1-year of follow-up. SHFM, SQ, and NoH yielded a similar area under the ROC curve [SHFM: 0.65 (0.60–0.71 95% CI); SQ: 0.58 (0.54–0.63 95% CI); NoH: 0.56 (0.50–0.62 95% CI)] and similar sensitivity [SHFM: 0.76 (0.65–0.84 95% CI); SQ: 0.84 (0.74–0.91 95% CI); NoH: 0.56 (0.45–0.67 95% CI)]. As compared to SHFM, SQ had lower specificity [SQ: 0.33 (0.28–0.37 95% CI) vs. SHFM: 0.55 (0.50–0.60 95% CI)] while NoH had similar specificity [0.56 (0.51–0.61 95% CI)]. SQ combined with NoH showed significantly higher specificity [0.68 (0.64–0.73 95% CI)].

Conclusion

SQ and NoH yielded comparable utility to SHFM for 1-year survival prediction among advanced HF patients, are easy-to-use and could inform bedside decision-making.

Patient Identification for Serious Illness Conversations: A Scoping Review

Serious illness conversations aim to align medical care and treatment with patients’ values, goals, priorities, and preferences. Timely and accurate identification of patients for serious illness conversations is essential; however, existent methods for patient identification in different settings and population groups have not been compared and contrasted. This study aimed to examine the current literature regarding patient identification for serious illness conversations within the context of the Serious Illness Care Program and/or the Serious Illness Conversation Guide. A scoping review was conducted using the Joanna Briggs Institute guidelines. A comprehensive search was undertaken in four databases for literature published between January 2014 and September 2021. In total, 39 articles met the criteria for inclusion. This review found that patients were primarily identified for serious illness conversations using clinical/diagnostic triggers, the ’surprise question’, or a combination of methods. A diverse assortment of clinicians and non-clinical resources were described in the identification process, including physicians, nurses, allied health staff, administrative staff, and automated algorithms. Facilitators and barriers to patient identification are elucidated. Future research should test the efficacy of adapted identification methods and explore how clinicians inform judgements surrounding patient identification.