Predicting mortality among a general practice-based sample of older people with heart failure

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.

Sex differences in long-term heart failure prognosis: a comprehensive meta-analysis

AIMS

Sex differences in the long-term prognosis of heart failure (HF) remain controversial, and there is a lack of comprehensive pooling of the sex differences in outcomes of HF. This study aims to characterize the sex differences in the long-term prognosis of HF and explore whether these differences vary by age, HF course, left ventricular ejection fraction, region, period of study, study design, and follow-up duration.

METHODS AND RESULTS

A systematic review was conducted using Medline, Embase, Web of Science, and the Cochrane Library, from 1 January 1990 to 31 March 2024. The primary outcome was all-cause mortality (ACM), and the secondary outcomes included cardiovascular mortality (CVM), hospitalization for HF (HHF), all-cause hospitalization, a composite of ACM and HHF, and a composite of CVM and HHF. Pooled hazard ratios (HRs) with corresponding 95% confidence intervals (CIs) were calculated using random-effects meta-analysis. Ninety-four studies (comprising 96 cohorts) were included in the meta-analysis, representing 706,247 participants (56.5% were men; the mean age was 71.0 years). Female HF patients had a lower risk of ACM (HR 0.83; 95% CI 0.80, 0.85; I2 = 84.9%), CVM (HR 0.84; 95% CI 0.79, 0.89; I2 = 70.7%), HHF (HR 0.94; 95% CI 0.89, 0.98; I2 = 84.0%), and composite endpoints (ACM + HHF: HR 0.89; 95% CI 0.83, 0.95; I2 = 80.0%; CVM + HHF: HR 0.85; 95% CI 0.77, 0.93; I2 = 87.9%) compared with males. Subgroup analysis revealed that the lower risk of mortality observed in women was more pronounced among individuals with long-course HF (i.e. chronic HF, follow-up duration > 2 years) or recruited in the randomized controlled trials (P for interaction < 0.05).

CONCLUSION

Female HF patients had a better prognosis compared with males, with lower risks of ACM, CVM, HHF, and composite endpoints. Despite the underrepresentation of female populations in HF clinical trials, their mortality benefits tended to be lower than in real-world settings.

REGISTRATION

PROSPERO: CRD42024526100.

The utility of the surprise question: A useful tool for identifying patients nearing the last phase of life? A systematic review and meta-analysis

BACKGROUND

The surprise question is widely used to identify patients nearing the last phase of life. Potential differences in accuracy between timeframe, patient subgroups and type of healthcare professionals answering the surprise question have been suggested. Recent studies might give new insights.

AIM

To determine the accuracy of the surprise question in predicting death, differentiating by timeframe, patient subgroup and by type of healthcare professional.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

Electronic databases PubMed, Embase, Cochrane Library, Scopus, Web of Science and CINAHL were searched from inception till 22nd January 2021. Studies were eligible if they used the surprise question prospectively and assessed mortality. Sensitivity, specificity, negative predictive value, positive predictive value and c-statistic were calculated.

RESULTS

Fifty-nine studies met the inclusion criteria, including 88.268 assessments. The meta-analysis resulted in an estimated sensitivity of 71.4% (95% CI [66.3-76.4]) and specificity of 74.0% (95% CI [69.3-78.6]). The negative predictive value varied from 98.0% (95% CI [97.7-98.3]) to 88.6% (95% CI [87.1-90.0]) with a mortality rate of 5% and 25% respectively. The positive predictive value varied from 12.6% (95% CI [11.0-14.2]) with a mortality rate of 5% to 47.8% (95% CI [44.2-51.3]) with a mortality rate of 25%. Seven studies provided detailed information on different healthcare professionals answering the surprise question.

CONCLUSION

We found overall reasonable test characteristics for the surprise question. Additionally, this study showed notable differences in performance within patient subgroups. However, we did not find an indication of notable differences between timeframe and healthcare professionals.

mHOMR: a prospective observational study of an automated mortality prediction model to identify patients with unmet palliative needs

OBJECTIVE

Identification of patients with shortened life expectancy is a major obstacle to delivering palliative/end-of-life care. We previously developed the modified Hospitalised-patient One-year Mortality Risk (mHOMR) model for the automated identification of patients with an elevated 1-year mortality risk. Our goal was to investigate whether patients identified by mHOMR at high risk for mortality in the next year also have unmet palliative needs.

METHOD

We conducted a prospective observational study at two quaternary healthcare facilities in Toronto, Canada, with patients admitted to general internal medicine service and identified by mHOMR to have an expected 1-year mortality risk of 10% or more. We measured patients' unmet palliative needs-a severe uncontrolled symptom on the Edmonton Symptom Assessment Scale or readiness to engage in advance care planning (ACP) based on Sudore's ACP Engagement Survey.

RESULTS

Of 518 patients identified by mHOMR, 403 (78%) patients consented to participate; 87% of those had either a severe uncontrolled symptom or readiness to engage in ACP, and 44% had both. Patients represented frailty (38%), cancer (28%) and organ failure (28%) trajectories were admitted for a median of 6 days, and 94% survived to discharge.

CONCLUSIONS

A large majority of hospitalised patients identified by mHOMR have unmet palliative needs, regardless of disease, and are identified early enough in their disease course that they may benefit from a palliative approach to their care. Adoption of such a model could improve the timely introduction of a palliative approach for patients, especially those with non-cancer illness.

Identifying patients who could benefit from palliative care by making use of the general practice information system: the Surprise Question versus the SPICT

OBJECTIVE

We compared the performance of two tools to help general practitioners (GPs) identify patients in need of palliative care: the Surprise Question (SQ) and the Supportive and Palliative Care Indicators Tool (SPICT).

METHODS

Prospective cohort study in two general practices in the Netherlands with a size of 3640 patients. At the start of the study the GPs selected patients by heart using the SQ. The SPICT was translated into a digital search in electronic patient records. The GPs then selected patients from the list thus created. Afterwards the GPs were interviewed about their experiences. The following year a record was kept of all the patients deceased in both practices. We analysed the characteristics of the patients selected and the deceased. We calculated the performance characteristics concerning predicting 1-year mortality.

RESULTS

The sensitivity of the SQ was 50%, of the SPICT 57%; the specificity 99% and 98%. When analysing the deceased (n = 36), 10 died relatively suddenly and arguably could not be identified. Leaving out these 10, the sensitivity of the SQ became 69%, of the SPICT 81%. The GPs found the performance of the digital search quite time consuming.

CONCLUSION

The SPICT seems to be better in identifying patients in need of palliative care than the SQ. It is also more time consuming than the SQ. However, as the digital search can be performed more easily after it has been done for the first time, initial investments can repay themselves.

Identification of patients with potential palliative care needs: A systematic review of screening tools in primary care

BACKGROUND

Despite increasing evidence of the benefits of early access to palliative care, many patients do not receive palliative care in a timely manner. A systematic approach in primary care can facilitate earlier identification of patients with potential palliative care needs and prompt further assessment.

AIM

To identify existing screening tools for identification of patients with advanced progressive diseases who are likely to have palliative care needs in primary healthcare and evaluate their accuracy.

DESIGN

Systematic review (PROSPERO registration number CRD42019111568).

DATA SOURCES

Cochrane, MEDLINE, Embase and CINAHL were searched from inception to March 2019.

RESULTS

From 4,127 unique articles screened, 25 reported the use or development of 10 screening tools. Most tools use prediction of death and/or deterioration as a proxy for the identification of people with potential palliative care needs. The tools are based on a wide range of general and disease-specific indicators. The accuracy of five tools was assessed in eight studies; these tools differed significantly in their ability to identify patients with potential palliative care needs with sensitivity ranging from 3% to 94% and specificity ranging from 26% to 99%.

CONCLUSION

The ability of current screening tools to identify patients with advanced progressive diseases who are likely to have palliative care needs in primary care is limited. Further research is needed to identify standardised screening processes that are based not only on predicting mortality and deterioration but also on anticipating the palliative care needs and predicting the rate and course of functional decline. This would prompt a comprehensive assessment to identify and meet their needs on time.

Association of Emergency Clinicians' Assessment of Mortality Risk With Actual 1-Month Mortality Among Older Adults Admitted to the Hospital

IMPORTANCE

The accuracy of mortality assessment by emergency clinicians is unknown and may affect subsequent medical decision-making.

OBJECTIVE

To determine the association of the question, "Would you be surprised if your patient died in the next one month?" (known as the surprise question) asked of emergency clinicians with actual 1-month mortality among undifferentiated older adults who visited the emergency department (ED).

DESIGN, SETTING, AND PARTICIPANTS

This prospective cohort study at a single academic medical center in Portland, Maine, included consecutive patients 65 years or older who received care in the ED and were subsequently admitted to the hospital from January 1, 2014, to December 31, 2015. Data analyses were conducted from January 2018 to March 2019.

EXPOSURES

Treating emergency clinicians were required to answer the surprise question, "Would you be surprised if your patient died in the next one month?" in the electronic medical record when placing a bed request for all patients who were being admitted to the hospital.

MAIN OUTCOMES AND MEASURES

The primary outcome was mortality at 1 month, assessed from the National Death Index. The secondary outcomes included accuracies of responses by both emergency clinicians and admitting internal medicine clinicians to the surprise question in identifying older patients with high 6-month and 12-month mortality.

RESULTS

The full cohort included 10 737 older adults (mean [SD] age, 75.9 [8.8] years; 5532 [52%] women; 10 157 [94.6%] white) in 16 223 visits treated in the ED and admitted to the hospital. There were 5132 patients (31.6%) with a Charlson Comorbidity Index score of 2 or more. Mortality rates were 8.3% at 1 month, 17.2% at 6 months, and 22.5% at 12 months. Emergency clinicians stated that they would not be surprised if the patient died in the next month for 2104 patients (19.6%). In multivariable analysis controlling for age, sex, race, admission diagnosis, and comorbid conditions, the odds of death at 1 month were higher in patients for whom clinicians answered that they would not be surprised if the patient died in the next 1 month compared with patients for whom clinicians answered that they would be surprised if the patient died in the next 1 month (odds ratio, 2.4 [95% CI, 2.2-2.7]; P < .001). However, the diagnostic test characteristics of the surprise question were poor (sensitivity, 20%; specificity, 93%; positive predictive value, 43%; negative predictive value, 82%; accuracy, 78%; area under the receiver operating curve of the multivariable model, 0.73 [95% CI, 0.72-0.74; P < .001]).

CONCLUSIONS AND RELEVANCE

This study found that asking the surprise question of emergency clinicians may be a valuable tool to identify older patients in the ED with a high risk of 1-month mortality. The effect of implementing the surprise question to improve population-level health care for older adults in the ED who are seriously ill remains to be seen.

Prioritizing Primary Care Patients for a Communication Intervention Using the "Surprise Question": a Prospective Cohort Study

BACKGROUND

Communication about priorities and goals improves the value of care for patients with serious illnesses. Resource constraints necessitate targeting interventions to patients who need them most.

OBJECTIVE

To evaluate the effectiveness of a clinician screening tool to identify patients for a communication intervention.

DESIGN

Prospective cohort study.

SETTING

Primary care clinics in Boston, MA.

PARTICIPANTS

Primary care physicians (PCPs) and nurse care coordinators (RNCCs) identified patients at high risk of dying by answering the Surprise Question (SQ): "Would you be surprised if this patient died in the next 2 years?"

MEASUREMENTS

Performance of the SQ for predicting mortality, measured by the area under receiver operating curve (AUC), sensitivity, specificity, and likelihood ratios.

RESULTS

Sensitivity of PCP response to the SQ at 2 years was 79.4% and specificity 68.6%; for RNCCs, sensitivity was 52.6% and specificity 80.6%. In univariate regression, the odds of 2-year mortality for patients identified as high risk by PCPs were 8.4 times higher than those predicted to be at low risk (95% CI 5.7-12.4, AUC 0.74) and 4.6 for RNCCs (3.4-6.2, AUC 0.67). In multivariate analysis, both PCP and RNCC prediction of high risk of death remained associated with the odds of 2-year mortality.

LIMITATIONS

This study was conducted in the context of a high-risk care management program, including an initial screening process and training, both of which affect the generalizability of the results.

CONCLUSION

When used in combination with a high-risk algorithm, the 2-year version of the SQ captured the majority of patients who died, demonstrating better than expected performance as a screening tool for a serious illness communication intervention in a heterogeneous primary care population.

mHOMR: a feasibility study of an automated system for identifying inpatients having an elevated risk of 1-year mortality

OBJECTIVE

The need for clinical staff to reliably identify patients with a shortened life expectancy is an obstacle to improving palliative and end-of-life care. We developed and evaluated the feasibility of an automated tool to identify patients with a high risk of death in the next year to prompt treating physicians to consider a palliative approach and reduce the identification burden faced by clinical staff.

METHODS

Two-phase feasibility study conducted at two quaternary healthcare facilities in Toronto, Canada. We modified the Hospitalised-patient One-year Mortality Risk (HOMR) score, which identifies patients having an elevated 1-year mortality risk, to use only data available at the time of admission. An application prompted the admitting team when patients had an elevated mortality risk and suggested a palliative approach. The incidences of goals of care discussions and/or palliative care consultation were abstracted from medical records.

RESULTS

Our model (C-statistic=0.89) was found to be similarly accurate to the original HOMR score and identified 15.8% and 12.2% of admitted patients at Sites 1 and 2, respectively. Of 400 patients included, the most common indications for admission included a frailty condition (219, 55%), chronic organ failure (91, 23%) and cancer (78, 20%). At Site 1 (integrated notification), patients with the notification were significantly more likely to have a discussion about goals of care and/or palliative care consultation (35% vs 20%, p = 0.016). At Site 2 (electronic mail), there was no significant difference (45% vs 53%, p = 0.322).

CONCLUSIONS

Our application is an accurate, feasible and timely identification tool for patients at elevated risk of death in the next year and may be effective for improving palliative and end-of-life care.

The Surprise Question Can Be Used to Identify Heart Failure Patients in the Emergency Department Who Would Benefit From Palliative Care

CONTEXT

Heart failure (HF) is associated with symptom exacerbations and risk of mortality after an emergency department (ED) visit. Although emergency physicians (EPs) treat symptoms of HF, often the opportunity to connect with palliative care is missed. The "surprise question" (SQ) "Would you be surprised if this patient died in the next 12 months?" is a simple tool to identify patients at risk for 12-month mortality.

OBJECTIVES

The objective of this study was to assess the accuracy of the SQ when used by EPs to assess patients with HF.

METHODS

We conducted a prospective cohort study in which clinicians applied the SQ to patients presenting to the ED with symptoms of HF. Chart review and review of death records were completed. The primary outcome was accuracy of the surprise question to predict 12-month mortality. A univariate analysis for potential predictors of 12-month mortality was performed.

RESULTS

During the study period, 199 patients were identified, and complete data were available for 97% of observations (n = 193). The one-year mortality was 29%. EPs reported that "they would not be surprised" if the patient died within the next 12 months in 53% of cases. 42.7% of these patients died within 12 months compared to 13.3% in the "would be surprised" group. There was a strong association with death in the "not surprised" group (odds ratio 4.85, 95% CI 2.34-9.98, P < 0.0001). The sensitivity, specificity, positive predictive value, and negative predictive value of the SQ were 78.6%, 56.9%, 42.7%, and 86.7%, respectively, with c-statistic = 0.68.

CONCLUSION

The SQ screening tool can assist ED providers in identifying HF patients that would benefit from early palliative care involvement.

Palliative care needs assessment in chronic heart failure

PURPOSE OF REVIEW

The unmet palliative care needs of patients with chronic heart failure (CHF) are well known. Palliative care needs assessment is paramount for timely provision of palliative care. The present review provides an overview of palliative care needs assessment in patients with CHF: the role of prognostic tools, the role of the surprise question, and the role of palliative care needs assessment tools.

RECENT FINDINGS

Multiple prognostic tools are available, but offer little guidance for individual patients. The surprise question is a simple tool to create awareness about a limited prognosis, but the reliability in CHF seems less than in oncology and further identification and assessment of palliative care needs is required. Several tools are available to identify palliative care needs. Data about the ability of these tools to facilitate timely initiation of palliative care in CHF are lacking.

SUMMARY

Several tools are available aiming to facilitate timely introduction of palliative care. Focus on identification of needs rather than prognosis appears to be more fitting for people with CHF. Future studies are needed to explore whether and to what extent these tools can help in addressing palliative care needs in CHF in a timely manner.

Impact of Hospice and Palliative Care Service Utilization on All-Cause 30-Day Readmission Rate for Older Adults Hospitalized with Heart Failure

BACKGROUND

Acute decompensated heart failure (HF) is the leading cause for hospital readmission. Large-scale sustainable interventions to reduce readmission rate have not been fully explored or proven effective.

OBJECTIVE

We studied the impact of hospice and palliative care service utilization on 30-day all-cause hospital readmissions for patients with HF.

METHODS AND RESULTS

Data were retrieved from the Department of Veterans Affairs Corporate Data Warehouse. The study included 238 116 HF admissions with primary diagnosis of HF belonging to 130 812 patients. Among these patients, 2592 had hospice and palliative care utilizations and 68 245 patients did not. Rehospitalization was calculated within 30 days of index hospitalization. Propensity scores were used to match hospice and nonhospice patients on demographics, Charlson comorbidity categories, and 30-day survival. In the matched group, logistic regression was used to estimate effects of hospice on readmission, controlling for any covariates that had failed to balance. The average age of the matched patients was 74 years old, 14% were African American, 75% Caucasian, 2% Asian, and 17% female. After propensity matching, the odds ratio for readmission was 1.29. The 95% confidence interval for the odds was 1.13 to 1.48, suggesting that veterans receiving services have a higher chance of readmission.

CONCLUSION

In a large cohort study of older US Veterans, utilization of hospice and palliative care services was associated with a higher 30-day all-cause readmission rate among hospitalized patients with HF. Further prospective studies should be conducted to confirm results and test generalizability outside the Veterans Affairs system of care.

Predicting one-year mortality in heart failure using the 'Surprise Question': a prospective pilot study

BACKGROUND

The Surprise Question: 'would you be surprised if this patient were to die within the next year?' has been shown to predict mortality in patients with chronic kidney disease and cancer. This prospective study aimed to determine whether the Surprise Question could identify heart failure patients with a prognosis of less than 1 year, and whether the Surprise Question can be used by different healthcare professionals.

METHODS AND RESULTS

Overall, 129 consecutive patients admitted with decompensated heart failure were included. Doctors and nurses were asked to provide a 'surprised' or 'not surprised' response to the Surprise Question for each patient. Patients were followed up until death or 1 year following study inclusion. The sensitivity, specificity, positive predictive value and negative predictive value of the Surprise Question were assessed. Cox regression was used to determine covariates significantly associated with survival. The Surprise Question showed excellent sensitivity (0.85) and negative predictive value (0.88) but only fair specificity (0.59) and positive predictive value (0.52) when asked of cardiologists. There were similar levels of accuracy between doctors and specialist nurses. The Surprise Question was significantly associated with all-cause mortality in multivariate regression analysis (hazard ratio 2.8, 95% confidence interval 1.0-7.9, P = 0.046).

CONCLUSION

This study demonstrates that the Surprise Question can identify heart failure patients within the last year of life. Despite over-classification of patients into the 'not surprised' category, the Surprise Question identified nearly all patients who were within the last year of life, whilst also accurately identifying those unlikely to die.

The "Surprise Question" Asked of Emergency Physicians May Predict 12-Month Mortality among Older Emergency Department Patients

BACKGROUND

Identification of older adults with serious illness (life expectancy less than one year) who may benefit from serious illness conversations or other palliative care interventions in the emergency department (ED) is difficult.

OBJECTIVES

To assess the performance of the "surprise question (SQ)" asked of emergency physicians to predict 12-month mortality.

DESIGN

We asked attending emergency physician "Would you be surprised whether this patient died in the next 12 months?" regarding patients ≥65 years old that they had cared for that shift. We prospectively obtained death records from Massachusetts Department of Health Vital Records.

SETTING

An urban, university-affiliated ED.

MEASUREMENT

Twelve-month mortality.

RESULTS

We approached 38 physicians to answer the SQ, and 86% participated. The mean age of our cohort was 76 years, 51% were male, and 45% had at least one serious illness. Out of 207 patients, the physicians stated that they "would not be surprised" if the patient died in the next 12 months for 102 of the patients (49%); 44 of the 207 patients (21%) died within 12 months. The SQ demonstrated sensitivity of 77%, specificity of 56%, positive predictive value of 32%, and negative predictive value of 90%. When combined with other predictors, the model sorted the patient who lived from the patient who died correctly 72% of the time (c-statistic = 0.72).

CONCLUSION

Use of the SQ by emergency physicians may predict 12-month mortality in older ED patients and may help emergency physicians identify older adults in need of palliative care interventions.

How accurate is the 'Surprise Question' at identifying patients at the end of life? A systematic review and meta-analysis

BACKGROUND

Clinicians are inaccurate at predicting survival. The 'Surprise Question' (SQ) is a screening tool that aims to identify people nearing the end of life. Potentially, its routine use could help identify patients who might benefit from palliative care services. The objective was to assess the accuracy of the SQ by time scale, clinician, and speciality.

METHODS

Searches were completed on Medline, Embase, CINAHL, AMED, Science Citation Index, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Open Grey literature (all from inception to November 2016). Studies were included if they reported the SQ and were written in English. Quality was assessed using the Newcastle-Ottawa Scale.

RESULTS

A total of 26 papers were included in the review, of which 22 reported a complete data set. There were 25,718 predictions of survival made in response to the SQ. The c-statistic of the SQ ranged from 0.512 to 0.822. In the meta-analysis, the pooled accuracy level was 74.8% (95% CI 68.6-80.5). There was a negligible difference in timescale of the SQ. Doctors appeared to be more accurate than nurses at recognising people in the last year of life (c-statistic = 0.735 vs. 0.688), and the SQ seemed more accurate in an oncology setting 76.1% (95% CI 69.7-86.3).

CONCLUSIONS

There was a wide degree of accuracy, from poor to reasonable, reported across studies using the SQ. Further work investigating how the SQ could be used alongside other prognostic tools to increase the identification of people who would benefit from palliative care is warranted.

TRIAL REGISTRATION

PROSPERO CRD42016046564 .

The "surprise question" for predicting death in seriously ill patients: a systematic review and meta-analysis

BACKGROUND

The surprise question - "Would I be surprised if this patient died in the next 12 months?" - has been used to identify patients at high risk of death who might benefit from palliative care services. Our objective was to systematically review the performance characteristics of the surprise question in predicting death.

METHODS

We searched multiple electronic databases from inception to 2016 to identify studies that prospectively screened patients with the surprise question and reported on death at 6 to 18 months. We constructed models of hierarchical summary receiver operating characteristics (sROCs) to determine prognostic performance.

RESULTS

Sixteen studies (17 cohorts, 11 621 patients) met the selection criteria. For the outcome of death at 6 to 18 months, the pooled prognostic characteristics were sensitivity 67.0% (95% confidence interval [CI] 55.7%-76.7%), specificity 80.2% (73.3%-85.6%), positive likelihood ratio 3.4 (95% CI 2.8-4.1), negative likelihood ratio 0.41 (95% CI 0.32-0.54), positive predictive value 37.1% (95% CI 30.2%-44.6%) and negative predictive value 93.1% (95% CI 91.0%-94.8%). The surprise question had worse discrimination in patients with noncancer illness (area under sROC curve 0.77 [95% CI 0.73-0.81]) than in patients with cancer (area under sROC curve 0.83 [95% CI 0.79-0.87; p = 0.02 for difference]). Most studies had a moderate to high risk of bias, often because they had a low or unknown participation rate or had missing data.

INTERPRETATION

The surprise question performs poorly to modestly as a predictive tool for death, with worse performance in noncancer illness. Further studies are needed to develop accurate tools to identify patients with palliative care needs and to assess the surprise question for this purpose.

Utility of the "Surprise" Question in Predicting Survival among Older Patients with Acute Surgical Conditions

BACKGROUND

The surprise question is a validated tool for identifying patients with increased risk of death within one year who could, therefore, benefit from palliative care. However, its utility in surgery is unknown.

OBJECTIVE

We sought to determine whether the surprise question predicted 12-month mortality in older emergency general surgery patients.

DESIGN

This was a prospective cohort study.

SETTING/SUBJECTS

Emergency general surgery attendings and surgical residents in or beyond their third year of training at a single tertiary care academic hospital from January to July 2014.

MEASUREMENTS

Surgeons responded to the surprise question within 72 hours of evaluating patients, ≥65 years, hospitalized with an acute surgical condition. Patient data, including demographic and clinical characteristics, were extracted from the medical record. Mortality within 12 months of initial evaluation was determined by using Social Security death data.

RESULTS

Ten attending surgeons and 18 surgical residents provided 163 responses to the surprise question for 119 patients: 60% of responses were "No, I would not be surprised" and 40% were "Yes, I would be surprised." A "No" response was associated with increased odds of death within 12 months in binary logistic regression (OR 4.8 [95% CI 2.1-11.1]).

CONCLUSIONS

The surprise question is a valuable tool for identifying older patients with higher risk of death, and it may be a useful screening criterion for older emergency general surgery patients who would benefit from palliative care evaluation.

Discharge Hospice Referral and Lower 30-Day All-Cause Readmission in Medicare Beneficiaries Hospitalized for Heart Failure

BACKGROUND

Heart failure (HF) is the leading cause for hospital readmission. Hospice care may help palliate HF symptoms but its association with 30-day all-cause readmission remains unknown.

METHODS AND RESULTS

Of the 8032 Medicare beneficiaries hospitalized for HF in 106 Alabama hospitals (1998-2001), 182 (2%) received discharge hospice referrals. Of the 7850 patients not receiving hospice referrals, 1608 (20%) died within 6 months post discharge (the hospice-eligible group). Propensity scores for hospice referral were estimated for each of the 1790 (182+1608) patients and were used to match 179 hospice-referral patients with 179 hospice-eligible patients who were balanced on 28 baseline characteristics (mean age, 79 years; 58% women; 18% non-white). Overall, 22% (1742/8032) died in 6 months, of whom 8% (134/1742) received hospice referrals. Among the 358 matched patients, 30-day all-cause readmission occurred in 5% and 41% of hospice-referral and hospice-eligible patients, respectively (hazard ratio associated with hospice referral, 0.12; 95% confidence interval, 0.06-0.24). Hazard ratios (95% confidence intervals) for 30-day all-cause readmission associated with hospice referral among the 126 patients who died and 232 patients who survived 30-day post discharge were 0.03 (0.04-0.21) and 0.17 (0.08-0.36), respectively. Although 30-day mortality was higher in the hospice referral group (43% versus 27%), it was similar at 90 days (64% versus 67% among hospice-eligible patients).

CONCLUSIONS

A discharge hospice referral was associated with lower 30-day all-cause readmission among hospitalized patients with HF. However, most patients with HF who died within 6 months of hospital discharge did not receive a discharge hospice referral.

[Geriatric assessment and factors associated with mortality in elderly patients with heart failure admitted to an acute geriatric unit]

INTRODUCTION AND OBJECTIVES

Heart failure (HF) is very prevalent in older adults, and is associated with a high mortality. The prediction of the outcome of HF and the identification of patients in advanced stages is difficult. The present work aims at identifying variables of the geriatric assessment and other clinical variables associated with an increased risk of death at one year in older adults with HF.

MATERIAL AND METHODS

Prospective study of 101 patients (mean age, 85.9 ± 6.3 years, 81% women) admitted during 2006 to an Acute Geriatric Unit, with principal diagnosis of HF. We recorded: demographic data, predisposing heart disease, main trigger of exacerbation, comorbidity, number of prescriptions at discharge and specific treatment of HF, average length-of-stay, readmissions, and mortality at one year after discharge. Geriatric assessment included: disability in basic (Barthel index) and instrumental (Lawton index) activities of daily living, cognitive function (Pfeiffer test), comorbidity (Charlson index), and geriatric syndromes.

RESULTS

In a multivariable logistic regression model, previous disability (lower Barthel index) (OR [95%CI]=1.03 [1.01-1.06]; P=.040) and higher number of re-admissions (OR [95%CI]=3.53 [1.19-10.44]; P=.023) were associated with 1-year mortality. Female sex had a protective effect (OR [95%CI]=0.15 [0.04-0.59]; P=.007).

CONCLUSIONS

Disability in the basic activities of daily living and re-admissions were associated with increased 1-year mortality in older adults, whereas female sex was protective. If confirmed in further studies, these data could reinforce the need for a systematic comprehensive geriatric assessment in older adults with HF.

Recognising patients who will die in the near future: a nationwide study via the Dutch Sentinel Network of GPs

BACKGROUND

Recognising patients who will die in the near future is important for adequate planning and provision of end-of-life care. GPs can play a key role in this.

AIM

To explore the following questions: How long before death do GPs recognise patients likely to die in the near future? Which patient, illness, and care-related characteristics are related to such recognition? How does recognising death in the near future, before the last week of life, relate to care in during this period?

DESIGN AND SETTING

One-year follow-back study via a surveillance GP network in the Netherlands.

METHOD

Registration of demographic and care-related characteristics.

RESULTS

Of 252 non-sudden deaths, 70% occurred in the home or care home and 30% in hospital. GP recognition of death in the near future was absent in 30%, and occurred prior to the last month in 15%, within the last month in 19%, and in the last week in 34%. Logistic regression analyses showed cancer and low functional status were positively associated with death in the near future; cancer and discussing palliative care options were positively associated with recognising death in the near future before the last week of life. Recognising death in the near future before patients' last week of life was associated with fewer hospital deaths, more GP-patient contacts in the last week, more deaths in a preferred place, and more-frequent GP-patient discussions about specific topics in the last 7 days of life.

CONCLUSION

Recognising death in the near future precedes several aspects of end-of-life care. The proportion in whom death in the near future is never recognised is large, suggesting GPs could be assisted in this process through training and implementation of care protocols that promote timely recognition of the dying phase.

End-of-life care conversations with heart failure patients: a systematic literature review and narrative synthesis

BACKGROUND

Current models of end-of-life care (EOLC) have been largely developed for cancer and may not meet the needs of heart failure patients.

AIM

To review the literature concerning conversations about EOLC between patients with heart failure and healthcare professionals, with respect to the prevalence of conversations; patients' and practitioners' preferences for their timing and content; and the facilitators and blockers to conversations.

DESIGN OF STUDY

Systematic literature review and narrative synthesis.

METHOD

Searches of Medline, PsycINFO and CINAHL databases from January 1987 to April 2010 were conducted, with citation and journal hand searches. Studies of adult patients with heart failure and/or their health professionals concerning discussions of EOLC were included: discussion and opinion pieces were excluded. Extracted data were analysed using NVivo, with a narrative synthesis of emergent themes.

RESULTS

Conversations focus largely on disease management; EOLC is rarely discussed. Some patients would welcome such conversations, but many do not realise the seriousness of their condition or do not wish to discuss end-of-life issues. Clinicians are unsure how to discuss the uncertain prognosis and risk of sudden death; fearing causing premature alarm and destroying hope, they wait for cues from patients before raising EOLC issues. Consequently, the conversations rarely take place.

CONCLUSION

Prognostic uncertainty and high risk of sudden death lead to EOLC conversations being commonly avoided. The implications for policy and practice are discussed: such conversations can be supportive if expressed as 'hoping for the best but preparing for the worst'.