Skip to main content

Table 4 Palliative/Supportive Care in Patients with Heart Failure

From: Palliative care referral criteria and outcomes in cancer and heart failure: a systematic review of literature

Study

Population

Aims

Design

Key Findings

Harding et al. (2009)

365 adult HF inpatients in tertiary teaching hospitals in the UK

1) To measure point prevalence of inpatients appropriate for PC

2) To identify patient characteristics associated with PC appropriateness to inform referral criteria

3) To propose evidence-based clinical referral criteria

Cross-sectional design, identifying chronic HF as a reason for current admission, using NYHA stage 3/4 classification, cross- referenced with existing echocardiogram data

Proposed criteria for PC referral for patients with chronic HF:

1. Symptomatic (e.g. breathless at rest or on minimal exertion) despite optimal treatment

2. On optimal therapy but with continuing or deteriorating physical or psychological symptoms

3. HF patients when hospital admission may not be the best/only/preferred option, or for whom PC (hospice, day care, hospital inpatient or community care) may be of benefit, either immediately or in the future

4. Where the family or carer(s) would benefit from support, either immediately or in the future (including bereavement)

5. Where patient has had 2 or more previous admissions for HFwithin the last 6 months

James et al. (2010)

214 patients with a discharge diagnosis of HF

To determine if SHFM can identify HF inpatients who would benefit from PC referrals

Cohort, retrospective and prospective Medical records

The SHFM13 is a Web-based tool that uses specific clinical and laboratory variables, HF medications, and devices the patient currently has or will receive as predictor variables.

Clinical variables entered into the tool include age, sex, NYHA classification, ejection fraction, ischemic cardiomyopathy, QRS duration, systolic blood pressure, and devices such as pacemakers and intraventricular conduction devices. 63% of HF patients with life expectancy ≤1.5 years would have received timely PC

consultation had the SHFM been used as a screening tool.

Ng Fat Hing et al. (2018)

612 patients with advanced NYHA HF and left ventricular ejection fraction

≤40%

To use the SHFM as a prediction of 1- year outcomes to help inform decision-making

Retrospective, chart review

SHFM showed good discrimination for outcomes including 1-year event-free survival from death, heart transplant, and ventricular assist device implant among low- to moderate-risk patients but

underestimated events in high-risk patients.

Avula et al. (2020)

689 patients with HF

To evaluate the SHFM and PRISM

score to predict 1- year mortality

Retrospective

The discriminatory ability of modified SHFM was similar to that of the PRISM score, but the models in combination significantly improved the ability

to predict 1-year mortality (P = 0.002).

Ezekowitz et al. (2011)

105 patients (mean age = 65 years, 76% male, mean ejection fraction = 28%) followed up in outpatient HF clinics

To assess the utility of PC questionnaires (NYHA, PPS, ESAS,

and KCCQ) in patients with HF

Cohort, prospective

The PPS and ESAS were each correlated to the NYHA class (P < 0.0001 for both) and the KCCQ score (PPS: R2 = 0.57; ESAS: R2 =

−0.72; both P < 0.0001). 33

patients died (10 patients) or were hospitalized (26 patients) for more than 1 year. In addition to age and sex, a higher (worse) ESAS score trended toward significance (P = 0.07) and a lower (worse) PPS was significant (P = 0.04) in predicting all-cause hospitalization or death. Given the difficulty of identifying patients with HF eligible for PC or hospice care, these tools may be

of use in clinical practice.

Greener et al. (2014)

2647 patients with HF admissions who received and did not receive PC services

To identify individual-level predictors of palliative care referral for HF patients

Chart review, retrospective

6.2% of HF patients were referred to PC during their hospitalization. Patients who were referred to PC were older (> 75 years), more likely to be married, and had longer hospital stays (19.53 days versus

9.67 days; P < 0.0001), higher risk for mortality (score of 3.31 versus 2.56; P < 0.0001), higher severity of illness (score of 3.30 versus 2.85; P < 0.0001), more days in the intensive care unit (4.96 days versus 2.01 days; P = 0.03), more prior-year HF admissions (P = 0.0004), and more hospital readmissions within 30 days (P < 0.0001). PC-referred patients were also more likely to have chronic and acute renal failure and Alzheimer disease, to be deceased at discharge or to be discharged to hospice care, and to undergo

thoracentesis.

Campbell et al. (2018)

272 patients screened for specialized PC needs

To develop a definition of specialized PC

needs and assess outcomes of those

Prospective, observational

27% of patients had specialized PC needs, and these patients were older (P = 0.041); had lower SBP (P

= 0.018), more severe NYHA class (P = 0.031), lower scores on AKPS

  

who received specialized PC

 

and NAT-PD-HF (P < 0.001 and

0.008), and higher Zarit Burden Interview severity (P < 0.001); and were more likely to have a history of myocardial infarction (P = 0.004) and a history of diabetes (P

= 0.029).

Kane et al. (2018)

372 patients screened for recruitment into PC intervention

To identify patients for recruitment into PC interventions using modified European Society of Cardiology and NYHA inclusion

criteria

Prospective, observational

NYHA II patients have PC needs and limiting referral to PC to only NYHA III/IV is not recommended. Including NYHA II patients will improve recruitment to PC treatment plans.

Roch et al. (2020)

100 patients hospitalized with HF

To evaluate an integrated PC outcome scale for assessing PC needs in patients with HF

Cross-sectional study

The integrated PC outcome scale identified clinically relevant somatic and psycho-emotional symptoms in approximately 75% of patients. Patients also found the assessment to be easy to understand (95%) and felt it was a suitable tool to assess PC needs

(91%).

Unroe et al.

229,543

To examine

Retrospective

Approximately 80% of Medicare

(2011)

Medicare

resource use in the

cohort study

beneficiary patients were

 

beneficiaries

last 180 days of life,

 

hospitalized in the last 6 months

 

with HF who died

including all-cause

 

of life; days in intensive care

 

between

hospitalizations,

 

increased from 3.5 to 4.6 days (P <

 

January 1, 2000,

intensive care unit

 

0.001). Use of hospice increased

 

and December

days, skilled

 

from 19% to nearly 40% of

 

31, 2007

nursing facility

 

patients (P < 0.001). Unadjusted

  

stays, home health,

 

mean costs to Medicare per

  

hospice, durable

 

patient rose 26% from $28,766 to

  

medical

 

$36,216 (P < 0.001). After

  

equipment,

 

adjustment for age, sex, race,

  

outpatient

 

comorbid conditions, and

  

physician visits, and

 

geographic region, costs increased

  

cardiac procedures.

 

by 11% (cost ratio, 1.11; 95% CI,

    

1.10–1.13). Increasing age was

    

strongly and independently

    

associated with lower costs. Renal

    

disease, chronic obstructive

    

pulmonary disease, and black race

    

were independent predictors of

    

higher costs.

Kheirbek et

179 hospice-

To examine the

Chart review,

30-day all-cause readmission rate

al. (2015)

referred patients

association of

retrospective

was 5% in the hospice-referred

 

matched with

discharge hospice

 

group and 41% in the hospice-

 

179 hospice-

referral with 30 day

 

eligible group, corresponding to

 

eligible patients

all cause

 

an HR of 0.12 (95% CI, 0.06–0.24)

    

for hospice referral. Hospice-

  

readmission in decompensated HF

 

referred patients were admitted later. 30-day mortality was higher in the hospice-referred group (43% versus 27%) with an HR of 1.86 (95% CI, 1.30–2.67). However,

among patients who were alive at 30 days, all-cause readmission occurred in 8% of the hospice- referred group versus 39% of the hospice-eligible group (HR = 0.17;

95% CI, 0.08–0.36).

Rogers et al. (2017)

150 patients randomized to usual care versus PC intervention

To assess for quality-of-life outcomes in patients receiving usual care versus usual care and PC intervention

Prospective, randomized

Patients with PCintervention had significant improvements in KCCQ and FACIT-Pal scores at 6 months (KCCQ difference: 9.49 points; 95% CI, 0.94–18.05; P = 0.030;

FACIT-Pal difference: 11.77 points; 95% CI, 0.84–22.71; P = 0.035).

Depression also improved in the PC intervention group (HADS- depression difference: −1.83; P = 0.048). Randomization did not affect re-hospitalization or

mortality.

Truby et al. (2020)

150 patients with HF

Secondary analysis of trial by Rogers et al. to compare quality of life between men and women

Randomized controlled trial, alternative outcome analysis

Women had lower KCCQ scores (24.5 versus 36.2, P = 0.04), but there was no significant difference in the FACIT-Pal scale (115.7 versus 120.3, P = 0.27). After referral to PC, men had significant improvement in KCCQ scores at 6 months, whereas women did not

(P = 0.047 versus P = 0.39).

Liu et al. (2020)

57,272 patients with primary hospital encounter diagnosis of HF or cancer receiving PC consultation

To evaluate outcomes of PC consultations for hospitalized patients with HF and cancer

Retrospective, Palliative Care Quality Network data set (nationwide collaborative of interdisciplinary PC teams)

Patients with HF were older (75.3 versus 65.2 years), had lower Palliative Performance Scale scores (35.6% versus 42.4%), and were more likely to be in a critical care unit (35.3% versus 12.5%) or telemetry or step-down unit (35.2% versus 19.2%) compared with patients with cancer. Patients with HF had more improvement in symptoms of dyspnea (odds ratio,

2.17) after PC referral compared with patients with cancer.

  1. HF heart failure; PC palliative care; NYHA New York Heart Association class; SHFM Seattle Heart Failure Model; PRISM Placement Resource Indicator for Systems Management; PPS Palliative Performance Scale; ESAS Edmonton Symptom Assessment System; KCCQ Kansas City Cardiomyopathy Questionnaire; NAT-PD-HF Needs Assessment Tool–Progressive Disease–Heart Failure; HR hazard ratio; FACIT-Pal Functional Assessment of Chronic Illness Therapy–Palliative Care; HADS Hospital Anxiety and Depression Scale; AKPS Australia-modified Karnofsky Performance Status