Effects of a diuretic adjustment algorithm protocol on heart failure admissions: A randomized clinical trial

Abstract

Introduction

The aim of this study was to evaluate the effectiveness of a diuretic adjustment algorithm (DAA) in maintaining clinical stability and reducing HF readmissions using telemonitoring technologies.

Methods

Randomized clinical trial of patients with an indication for furosemide dose adjustment during routine outpatient visits. In the intervention group (IG), the diuretic dose was adjusted according to the DAA and the patients received telephone calls for 30 days. In the control group (CG), the diuretic dose was adjusted by a physician at baseline only. Co-primary outcomes were hospital readmission and/or emergency department visits due to decompensated HF within 90 days, and a 2-point change in the Clinical Congestion Score and/or a deterioration in New York Heart Association functional class within 30 days.

Results

A total of 206 patients were included. Most patients were male (n=119; 58%), with a mean age of 62 (SD 13) years. Four patients (2%) in the IG and 14 (7%) in the CG were hospitalized for HF (odds ratio (OR) 0.31 (0.10–0.91); p=0.04). Multivariate analysis showed a reduction of 67% in readmissions and/or emergency department visits due to decompensated HF in the IG compared with the CG (95% CI 0.13–0.88; p=0.027). Regarding the combined outcome of HF readmission and/or emergency department visits or clinical instability, the IG had 20% fewer events than the CG within 30 days (IG: n=48 (23%), CG: n=70 (34%); OR 0.80 (0.63–0.93); p=0.03).

Discussion

Using DAA improved the combined outcome in these outpatients, with favorable and significant results that included a reduction in HF admissions and in clinical instability. (NCT02068937)

Keywords

Algorithm diuretic heart failure nursing,randomized clinical trial,remote monitoring

Introduction

The management of heart failure (HF) has improved over the years owing to optimization of medical therapy, especially by combining the pharmacological arsenal with non-pharmacological interventions.¹ Despite the advances in HF management, this syndrome affects more than 23 million people worldwide, with a 35% 5-year survival.²,³ In addition, HF prevalence, in-hospital mortality, readmissions and one year mortality continue to impact healthcare systems globally.¹,^4–7

Outpatient interventions, including comprehensive education to the patient and family, medication review, intensive follow-up and counselling on diet, medication adherence, and self-management of symptoms can be effective at maintaining patient stability and preventing hospital readmissions.^8–10 According to US data, 67.4% of hospitalized HF patients experience a readmission and approximately one-third die within one year of the index hospitalization, with the first three days after discharge bearing the highest risk. Although the risk of readmission decreases by 50% up to 38 days after hospitalization, it remains high for at least one year.¹¹ Therefore, an index HF hospitalization is a significant marker of morbidity and mortality that extends beyond 30 days, which highlights the importance of close assessment and management of HF.¹¹

Different approaches to HF management have been effective at improving outcomes, such as patient self-care, home visits, telephone calls, and more recently telemonitoring and electronic transfer of clinical data.¹²,¹³ These methods have also been effective in studies conducted in Brazil.¹⁴,¹⁵ A systematic review showed that both structured telephone and telemonitoring reduced all-cause mortality, and both also reduced HF hospitalizations.¹⁶ The same authors published a subsequent review of more articles reporting that both strategies continued to provide statistically and clinically significant benefits.¹⁷

In an effort to improve HF outcomes, we developed an algorithm for diuretic adjustment that focuses on pharmacological and non-pharmacological assessment and home management. The diuretic adjustment algorithm (DAA) protocol has been effective at preventing decompensated HF and at reducing 30-day readmission rates and HF hospitalizations by 50%.¹⁸ This algorithm was validated for use in Brazil, showing a greater reduction in the signs of congestion and body weight than conventional management.¹⁹ However, its effectiveness in reducing readmissions remains unknown in low- to middle-income settings.¹⁹

The purpose of the present study was to evaluate the effectiveness of the DAA in maintaining clinical stability and reducing hospital readmissions in patients with HF.

Methods

Trial design

This was a prospective randomized open blinded end-point (PROBE) study with a parallel design and two groups. Patients were recruited from the outpatient HF clinic of a university hospital in southern Brazil between May 2013 and December 2017. The HF clinic is staffed by a multidisciplinary team of cardiologists, nurses and nutritionists. On average, 200 patients are seen per month at the clinic, with a focus on promoting adherence to optimized pharmacological and non-pharmacological management.

The Institutional Review Board approved the study (number 100376), which adhered to the tenets of the Declaration of Helsinki and the Brazilian legal and regulatory framework for research involving human subjects. The trial is registered at ClinicalTrials.gov (NCT02068937). The detailed protocol for this trial has been published previously.²⁰

Participants

Eligible participants were all patients aged 18 years or over of either sex with a diagnosis of HF who were being followed up at the HF clinic, were using furosemide, and needed dose adjustment during an outpatient visit. Patients were required to have a weighing scale at home or ready access to one, to provide a telephone number for follow-up contact and consent to such follow-up, and to be available to return to the hospital for a 1-month reassessment visit. Patients were excluded if they had physical impairments or communication barriers (e.g., deaf persons and patients with dementia or aphasia) that would preclude body-weight monitoring, had degenerative neurological conditions (e.g., Alzheimer’s disease), were on the waiting list for heart transplant, were scheduled for surgery or had chronic kidney disease requiring renal replacement therapy.

Intervention

Patients assigned to the intervention group (IG) received four to eight telephone calls (one to two per week) for 30 days to support non-pharmacological management and to have their diuretic dose adjusted according to the DAA. Patients assigned to the control group (CG) underwent routine outpatient follow-up (no telephone calls), and their diuretic dose was adjusted only at the time of inclusion. Patients in both groups returned for clinical evaluation after 1 month.

All patients with an indication for furosemide dose adjustment were identified during regular medical or nursing consultations. Eligible patients provided written informed consent prior to participation. The diuretic dose was adjusted according to medical criteria.

All patients underwent clinical examination during the medical or nursing consultation, which routinely involves the use of the Clinical Congestion Score. This tool assesses pulmonary rales, elevated central venous pressure, jugular distension, third heart sound, orthopnea, hepatojugular reflux and peripheral oedema, in addition to estimating the New York Heart Association (NYHA) functional class. Total scores range from 1 to 22. Values ≥ 5 points indicate congestive conditions.²¹ All data were recorded by a health professional (blinded to group allocation) in the patients’ electronic medical records. A structured questionnaire was administered to all trial participants for collection of sociodemographic data and clinical parameters (age, sex, educational attainment, income, current prescriptions, comorbidities, smoking, alcohol consumption, aetiology of HF, duration of HF, prior admissions, echocardiographic findings, and serum levels of sodium, potassium, urea and creatinine).

Patients in the IG were instructed to measure their body weight daily, in the morning, after urination, wearing light clothes and before their first meal of the day. They were required to use the same scale throughout the study period.

All telephone calls were made by a HF specialist nurse. The only necessary infrastructure was a quiet environment and a telephone. Calls were made at any time of the day and did not exceed 15 minutes.

At the end of 90 days, the patients’ electronic medical records were reviewed to identify possible admissions for HF. Also, an investigator contacted the patients by telephone to identify possible admissions to other health facilities. An HF specialist physician or nurse blinded to group allocation performed all evaluations during clinical visits.

Intervention group

After inclusion and baseline assessment, individualized telephone calls were scheduled weekly and managed according to the study protocol – once to twice a week (Figure 1). During the telephone follow-up period, the DAA was used to provide guidance on the necessary treatment aspects. The calls were made after the daily body-weight check. Patients who did not have a scale could get one from the HF clinic. After 30 days, all patients were required to return for a face-to-face assessment. In all contacts made after inclusion, the DAA was used to determine the diuretic dose adjustment.¹⁹

Figure 1.

Study protocol. *Continue program: call in 7 days.

At the beginning of each telephone call, the nurse identified herself and stated the reason for calling. First, the patients were asked to provide the results of the body-weight check (in kilograms). The approach was determined based on the weight results: increased weight (≥1 kg), expected weight or decreased weight (≤1 kg). An investigation for signs and symptoms of increased or decreased blood volume was then performed.

For patients who gained weight, the medication dose and non-pharmacological guidelines were reviewed to determine treatment adherence. If adherence was confirmed, the nurse answered any questions the patient had and reinforced educational elements. A new call was made after seven days. If there were no changes in weight, a furosemide tablet was added for two days and educational elements were reinforced. If the patient reported any signs or symptoms (e.g., dyspnoea, nocturnal paroxysmal dyspnoea and oedema), a furosemide tablet was indicated, and another telephone call was made in 48 hours.

For those who remained at the expected weight and reported no symptoms, treatment remained unchanged. However, if any symptoms were reported, an extra furosemide tablet was indicated. The nurse called the patient again within 48 hours to assess the persistence of symptoms. If symptoms persisted, the patient was instructed to take an extra dose of furosemide and go to the hospital for laboratory tests (urea, sodium, potassium and creatinine).

For those who lost weight, an assessment was performed for symptoms of hypovolaemia. In the absence of symptoms, the dose and programme remained unchanged. However, in the presence of symptoms of hypovolaemia, patients were further inquired about episodes of vomiting or diarrhoea, anorexia, other current illnesses and diuretic overdose. If any of these had occurred, the diuretic was discontinued for 24 hours, after which the patient was called again. If the symptoms persisted, diuretic treatment was resumed with one less tablet and an appointment was scheduled to measure vital signs and perform laboratory tests. If the symptoms were no longer present after 24 hours, diuretic treatment was resumed with one less tablet and the programme was continued.

For patients who lost weight but reported no symptoms, every possible cause of weight loss was investigated. An appointment was scheduled for patients with rapid weight loss, whereas the dose was maintained for those without rapid weight loss.

Control group

No telephone monitoring was performed for the CG. The patients were scheduled to return for a face-to-face assessment after 30 days

Outcomes

Co-primary outcomes were hospital readmission and/or emergency department visits due to decompensated HF within 90 days, and a 2-point change in the Clinical Congestion Score and/or a deterioration in NYHA functional class (unchanged or worsening functional class III and IV) within 30 days.

Sample size

Considering a 30% hospital admission rate within 90 days¹⁸ and a 20% relative reduction in the IG, a significance level of 0.05, a power of 80% and an anticipated dropout rate of 20%, a sample size of 270 patients (135 per group) was necessary. The trial was stopped earlier than planned because of difficulties in recruiting patients due to competing studies (similar populations) conducted at the HF clinic.

Randomization

Participants were randomly allocated to the intervention or CG in a 1:1 ratio using a list of sequential numbers generated by randomization.com. The list was managed by an investigator with no involvement in the baseline assessment or telephone calls. After each inclusion, the investigator contacted the nurse for information on group allocation. The allocation sequence was concealed in sequentially numbered, opaque, sealed envelopes. This investigator, the patient and the nurse in charge of the telephone calls were not blinded.

Statistical analysis

Data were expressed as mean and standard deviation for continuous variables with normal distribution and as median and interquartile range for those with skewed distribution. Categorical variables were presented as numbers and percentages. According to the data distribution, the baseline characteristics of the groups and the effects of the intervention were compared with Student’s t-test, the Mann–Whitney test or Pearson’s chi-square test. Student’s t-test and the Mann–Whitney test were used to assess changes in the Clinical Congestion Score and in body weight in both groups from baseline to 30 days. A two-tailed p<0.05 was considered statistically significant. Statistical analysis was performed using the intention-to-treat principle for all patients with outcomes at 90 days. A Kaplan–Meier survival curve was constructed in a time-dependent manner, considering the date of first HF readmission and/or emergency department visit, and the results were compared by the log-rank test. Adjusted prevalence ratios were obtained through multiple analysis of Poisson regression with robust variance, considering independent variables that were more strongly associated in bivariate analysis (up to the level of significance <0.20). For a final analysis, a significance level of 0.05 was considered. SPSS, version 20.0, was used for data analysis.

Results

The first patient was included in May 2013 and the last one in December 2017. The last follow-up evaluation was performed in March 2018. A total of 2907 patients were assessed for eligibility; of these, 206 met the inclusion criteria and were randomized. The flow diagram of patient enrollment and participation is shown in Figure 2.

Figure 2.

CONSORT flow diagram.

Patient characteristics were similar in the two groups (Table 1). Mean patient age was 62.5 years. Most patients were male, with a left ventricular ejection fraction of 33% and NYHA functional class III. There were no significant differences in furosemide dose or laboratory test results between the groups.

Table 1.

Demographic and clinical characteristics.

Variable	Total(n = 206)	IG(n = 99)	CG(n = 107)	p
Age^a	62.5 ± 13	64 ± 12	61.5 ± 14	0.27
Sex (male)^b	119 (58)	57 (28)	62 (30)	0.53
Race (white)^b	174 (84)	82 (40)	92 (45)	0.41
Aetiology^b
Ischaemic	47 (23)	24 (12)	23 (11)	0.84
LVEF^a	33 ± 12	33 ± 12	33 ± 13	0.63
NYHA class^b
I	43 (21)	18 (9)	25 (12)	0.72
II	72 (35)	38 (18)	34 (16)
III	87 (42)	41 (20)	46 (22)
IV	4 (2)	2 (1)	2 (1)
Comorbidities^b
Systemic arterial hypertension	118 (57)	56 (27)	62 (30)	0.89
Diabetes	93 (45)	46 (22)	47 (23)	0.78
Atrial fibrillation	70 (34)	36 (17)	34 (16)	0.56
Baseline dose of ARB^c	50 (50–100)	50 (50–100)	50 (50–100)	0.75
Baseline dose of hydralazine^c	75 (75–150)	150 (75–150)	75 (41–150)	0.33
Baseline dose of isosorbide^c	60 (40–120)	60 (60–120)	60 (30–80)	0.57
Baseline dose of beta-blocker^c	100 (50–200)	100 (50–200)	100 (81–200)	0.99
Baseline dose of ACE inhibitors^c	20 (20–56)	20 (20–75)	20 (20–50)	0.89
Furosemide prior to study entry^c	80 (40–120)	80 (40–120)	80 (40–120)	0.97
Baseline furosemide^c	80 (80–120)	80 (70–120)	80 (80–150)	0.91
Baseline sodium^a	140 ± 3.5	140 ± 3.2	139 ± 3.8	0.31
Baseline potassium^c	4.6 (4.2–4.9)	4.7 (4.2-5)	4.5 (4.2–4.9)	0.36
Baseline urea^c	55 (43–79)	57 (46–80)	54 (42–79)	0.70
Baseline creatinine^a	1.27 ± 0.5	1.20 ± 0.41	1.32 ± 0.55	0.15

IG: intervention group; CG: control group; LVEF: left ventricular ejection fraction; NYHA: New York Heart Association; ARB: angiotensin receptor blocker; ACE: angiotensin converting enzyme.

^aValues presented as mean ± standard deviation, independent t-test.

^bn (%), Pearson’s chi-square test.

^cMedian and interquartile range, Mann–Whitney test.

Within 90 days, patients in the IG had 69% fewer readmissions and/or emergency department visits due to decompensated HF than controls (intervention: n=4 (2%), control: n=14 (7%); odds ratio (OR) 0.31 (0.10–0.91); p=0.04).

The analysis of the Kaplan–Meier survival curve for the occurrence of readmission and/or emergency department visits due to decompensated HF showed a log-rank value of 5.25 (p=0.02) (Figure 3). In a multivariate analysis adjusted for age, sex, left ventricular ejection fraction, NYHA functional class and allocation group, patients in the IG had a reduction of 67% in readmissions and/or emergency department visits due to decompensated HF compared with controls (95% CI 0.13–0.88; p=0.027).

Figure 3.

Kaplan–Meier survival curve (log-rank p-value = 0.02) for the occurrence of readmission and/or emergency department visits due to decompensated heart failure (HF).

Patients in the IG had 23% less clinical instability (i.e., a 2-point change in the Clinical Congestion Score and/or a deterioration in NYHA functional class) than controls within 30 days (intervention: n=46 (29%), control: n=70 (45%); OR 0.77 (0.63–0.93); p=0.006). When analysed separately, the Clinical Congestion Score differed significantly from baseline to 30 days (Table 2).

Table 2.

Changes in the Clinical Congestion Score and New York Heart Association (NYHA) functional class.

Variable	Groups		p
Clinical Congestion Score	IG (n=72)	CG (n=84)
Change <2 points^a	41 (26)	33 (21)	0.036
Change ≥2 points^a	31 (20)	51 (33)	0.036
NYHA functional class	IG (n=93)	CG (n=102)
Reduced or remained in class I or II^a	56 (28.7)	55 (28.2)	0.389
Increased or remained in class III or IV^a	37 (19)	47 (24)	0.389

IG: intervention group; CG: control group.

^an (%), Pearson’s chi-square test.

Regarding the combined outcome of HF readmission and/or emergency department visits or clinical instability, patients in the IG had 20% fewer events than controls within 30 days (intervention: n=48 (23%), control: n=70 (34%); OR 0.80 (0.63–0.93); p=0.03).

Discussion

This is the first study to provide effectiveness data on a reduction in admissions for decompensated HF in a low- to-middle income country using the DAA, the only validated algorithm available for oral diuretic dose adjustment in outpatients with HF, which was determined based on the patient’s current clinical condition rather than on previously established doses. The DAA protocol is not limited to pharmacological treatment, as overall care is likewise prioritized, including non-pharmacological treatment and medication adherence measures. The study population consisted mainly of older men with HF of ischaemic aetiology. The clinical characteristics were similar in the intervention and control groups. Patients who received the intervention had 69% fewer HF readmissions and 23% less clinical instability (i.e., a 2-point change in the Clinical Congestion Score and/or a deterioration in NYHA functional class) than controls.

The findings of the present trial, together with evidence from the literature, reinforce that clinical stability minimizes damage in patients with HF, often represented by unplanned admissions, which indicate a worse prognosis. The typical symptom responsible for readmissions, emergency department visits or unplanned admissions is pulmonary or systemic congestion, which leads to dyspnoea, rales and oedema.²²,²³ These signs and symptoms are often difficult to recognize due to their insidious onset. Once congestion is detected, it is crucial to reduce filling pressures in order to provide symptom relief. Changes in body weight over a short period of time are also used to assess fluid overload in decompensated HF. There is evidence that this weight change is correlated with the presence of symptoms and altered haemodynamic parameters, such as jugular vein pressure.²⁴ In a study of patients with HF followed up for 18 months with home weight monitoring, the most important weight changes occurred in the 7 days prior to hospitalization. The authors concluded that, in most cases, HF admissions are preceded by weight gain.²⁵ A systematic review found nine studies that examined diuretic dose adjustment in patients with HF; of these, five were randomized and only two effectively addressed dose adjustment as an important strategy.²⁶

Telemonitoring is a promising technique for early detection of deterioration in patients with HF in an attempt to avoid hospitalizations. However, clinical trials on the effectiveness of telemonitoring in HF management have produced mixed results, partly due to methodological differences (structured telephone calls and remote management systems).¹⁶

For more than 10 years, only two algorithms of different diuretic strategies have been available in the literature for evaluating readmissions and death in outpatients with HF. The first randomized clinical trial using a diuretic adjustment strategy reported a reduction in mortality and hospitalizations in the IG, as well as improved self-care.²⁷ The second trial reported fewer emergency department visits in the IG (n=1; 2.8%) than in the CG (n=7; 22%) (p=0.015). Patients who received the intervention also had fewer HF hospitalizations than controls, but with no significant difference between the groups. The rate of HF readmissions did not differ between the intervention and control groups (42% vs 61%, respectively; p=0.13), and neither did the rate of readmissions for other reasons (3% vs 6%, respectively; p=0.35).²⁸ Although the authors did not compare congestion and weight at the beginning and end of the aforementioned studies, the diuretic adjustment strategy contributed to the patients’ clinical stability.²⁸ Regarding HF hospitalizations, the IG, which was treated according to the DAA, had 69% fewer events than the control group.²⁷

Some studies have investigated intravenous diuretic dose adjustment in haemodynamically stable outpatients with HF using other interventions. These studies found the dose adjustment protocol safe, resulting in fewer hospitalizations and lower costs.^29–32

A recent meta-analysis summarized the evidence from randomized controlled trials on the impact of telemedicine on HF vs conventional healthcare. Telemedicine mainly included structured telephone support, involving interactive vocal response monitoring and telemonitoring. Telemonitoring was associated with a significant reduction in all-cause hospitalizations (OR 0.82, p=0.0004), in cardiac hospitalizations (OR 0.83, p=0.007), and in the risk of all-cause mortality (OR 0.75, p=0.003). However, telemonitoring and conventional healthcare did not differ significantly in the odds of HF-related mortality (OR 0.84, p=0.28). Structured telephone support interventions were likely to reduce all-cause hospitalizations (OR 0.86, p=0.006) and HF hospitalizations (OR 0.74, p<0.0001) compared with conventional healthcare interventions. In patients with HF receiving structured telephone support, the odds of all-cause mortality were found in a meta-analysis of eight studies (OR 0.96, p=0.55), while the odds of cardiac mortality were found in a meta-analysis of three studies (OR 0.54, p=0.009).³³ These findings highlight the importance of weight change and signs and symptoms in HF management. A state of hypervolaemia is usually present on hospital admission or readmission. Thus, early recognition and prompt management of decompensated HF provide a means of reducing poor outcomes.

We observed a lower rate of admission than expected in the present study. In fact, previous estimated rates of 30% were driven by data from early post-discharge reports, and readmissions are considerably higher after an acute decompensated HF hospitalization. Since we included outpatients mostly without recent admissions, the observed rates are compatible with the clinical scenario of this group of patients. Furthermore, the beneficial effects detected in the current analysis underscore the potential role of this intervention in clinical scenarios of lower risk.

There is broad consensus that patients with HF should receive interventions that emphasize education, and that post-discharge follow-up should begin as soon as possible (within a maximum of 10 days), including pharmacological guidance and effective communication regarding the transfer of care.³⁴

The DAA is the only available algorithm that considers adherence to pharmacological and non-pharmacological treatment prior to dose adjustment, including any physiological changes (e.g., vomiting or diarrhoea) or missed doses due to forgetfulness. In addition, the healthcare professional provides systematic guidance in each telephone call and answers the patient’s questions as soon as they are asked, which allows the identification of early signs and symptoms of worsening HF. The rapid implementation of behavioural adjustments after contact could also improve patient safety during follow-up. In addition, telemonitoring using a validated algorithm allows nurses to provide guidance with minimal variation among health professionals. This approach is a supporting alternative in the out-of-hospital follow-up of patients by allowing continuous, differentiated monitoring with time optimization and cost reduction for the healthcare system.

This study has some limitations. Although the trial is based on a protocol-driven intervention, a single HF specialist nurse made all the telephone calls, which could limit the generalization of data to nurses who are not specialists in the clinical evaluation of patients with HF. Therefore, prior training in how to approach patients remotely and in how to use the validated protocol is necessary. The knowledge that the intervention itself was conducted over the telephone without reliable clinical parameters and the concerns about the limitations of non-face-to-face assessment may lead to uncertainty about the effectiveness of the intervention. In addition, the fact that the study was conducted at a single centre may also be considered a limitation. A reduction was observed in the Clinical Congestion Score on day 30, probably because the most stable patients did not have their data collected on all variables or because the data were collected from the records of regular consultations at the HF clinic.

Another important issue was the exclusion of a large number of patients who did not have the diuretic dose adjusted due to a study with similar criteria that provided for the discontinuation of the diuretic. Patients attending the outpatient HF clinic could be recruited to only one of the studies. Moreover, the trial was stopped earlier than planned. The initial sample size calculation considered a 30% reduction in the number of readmissions and/or emergency department visits due to HF; however, a preliminary analysis indicated a reduction of more than 60% with a smaller sample size, but acknowledges that the low numbers of readmissions are a limitation of the current analysis.

Conclusions

The results of this study demonstrated that the application of a protocol for diuretic adjustment and the provision of non-pharmacological guidance by telemonitoring significantly reduced HF admissions and prevented clinical instability. Further larger studies are needed to conclusively address the effects of this strategy on hard clinical outcomes.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Financial support was provided by the Fundo de Incentivo à Pesquisa e Eventos at Hospital de Clínicas de Porto Alegre (HCPA).

ORCID iDs

Karen Brasil Ruschel

Eneida Rejane Rabelo da Silva

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