To evaluate whether different real-world prescribing patterns of guideline-directed medical therapy (GDMT) in patients with heart failure with reduced ejection fraction (HFrEF) or mildly reduced ejection fraction (HFmrEF) are associated with differences in patient-reported quality of life (QoL), and specifically to compare conventional triple therapy, ARNi-based therapy, SGLT2i-based therapy, and full quadruple GDMT.
This was a multicentre, cross-sectional descriptive study conducted in two tertiary care centres in Egypt and Saudi Arabia between December 2022 and March 2024. A total of 118 adult patients with LVEF <50% were enrolled at their first follow-up visit after hospital discharge. Participants were grouped according to prescribed HF regimen: conventional triple therapy, ARNi-based therapy, SGLT2i-based therapy, or quadruple GDMT. Quality of life was measured using the Minnesota Living with Heart Failure Questionnaire (MLHFQ) 7–14 days after discharge. Between-group differences were analysed using one-way ANOVA with Tukey HSD post hoc testing, and multivariable linear regression was used to identify predictors of MLHFQ score.
Quality-of-life scores differed significantly across the treatment groups. Patients receiving quadruple GDMT had the best QoL, reflected by the lowest mean MLHFQ score (42.77 ± 19.05), whereas those receiving conventional triple therapy had the worst QoL (68.06 ± 19.77). ANOVA showed a statistically significant overall difference between regimens (F(3,114) = 8.135, p < 0.001). Post hoc analysis showed significantly better QoL with quadruple GDMT versus conventional triple therapy, and versus the SGLT2i-based triple regimen. In regression analysis, higher serum creatinine and blood urea nitrogen were independently associated with worse QoL, while higher haemoglobin was associated with better QoL. The study also found that patients receiving quadruple GDMT had shorter hospital stays compared with those receiving other regimens.
The cross-sectional design limits causal inference and temporal interpretation of GDMT effects on quality of life. Residual confounding is possible due to unmeasured factors such as disease severity, medication adherence, duration of therapy, and socioeconomic status. The relatively small sample size and limited geographic scope may affect generalisability. Clinically, the findings support systematic optimisation of GDMT and routine integration of patient-reported outcomes (e.g. MLHFQ) into care. They also highlight the importance of managing renal dysfunction and anaemia to improve QoL and justify further longitudinal and interventional research. Future multicentre, longitudinal studies are warranted to validate these findings and evaluate cost-effectiveness and long-term adherence.
Clinicians should prioritise early optimisation of full GDMT, particularly incorporating ARNi and SGLT2 inhibitors, where tolerated, to enhance patient-reported quality of life. Routine use of validated tools such as the MLHFQ during follow-up can guide treatment adjustments. Multidisciplinary care – especially pharmacist-led medication reconciliation – may improve GDMT uptake and adherence. Regular monitoring and management of renal function and anaemia are essential to optimise outcomes. Shared decision-making should be emphasised to balance treatment complexity with patient preferences and improve adherence in real-world settings.
Improved optimisation of GDMT may enhance patients' functional status, independence, and ability to participate in daily, social, and occupational activities, thereby reducing caregiver burden and societal costs. Better quality of life and fewer hospitalisations can decrease healthcare resource utilisation and economic strain on health systems. Emphasising patient-reported outcomes supports more equitable, patient-centred care, particularly in diverse and resource-variable settings, helping to reduce disparities in heart failure management and long-term outcomes.
The study provides novel real-world evidence from the Middle East and Africa on the association between contemporary GDMT combinations and early patient-reported QoL after discharge. Its main value lies in moving beyond traditional clinical endpoints such as mortality and hospitalisation to examine the lived experience of patients receiving different HF regimens. The authors position it as the first multicentre post-discharge study from this region to directly compare QoL across conventional triple therapy, ARNi-based therapy, SGLT2i-based therapy, and full quadruple GDMT.
Introduction
Heart failure with reduced and mildly-reduced ejection fraction (HFrEF and HFmrEF) remains a critical global health concern with rising incidence and considerable clinical and economic burdens. (Pratley et al., 2024; El-Hadidi et al., 2026) According to the American Heart Association, approximately 6.2 million adults in the United States alone are living with HF, with projections indicating a substantial increase in prevalence in the coming decades. (Braunschweig et al., 2011) This necessitates ongoing research to refine therapeutic strategies that address validated metrics for patient-reported outcomes and lived experiences (PROMs and PREMs). (Stolfo et al., 2025; Abdin et al., 2025; Nicola et al., 2024)
Traditionally, HF management has relied on evidence-based polypharmacy targeting various aspects of the disease pathologies. (Stolfo et al., 2025; El Hadidi et al., 2020, 2021) These include angiotensin-converting enzyme inhibitors (ACEi), evidence-based beta-blockers, and mineralocorticoid receptor antagonists (MRAs), which together have been shown to reduce hospitalisations and mortality. (Yancy et al., 2017; El Hadidi et al., 2018) Recent advances have introduced novel appropriate polypharmacy and dosage forms, including angiotensin receptor–neprilysin inhibitors (ARNi) and sodium–glucose cotransporter-2 inhibitors (SGLT2i), which have substantially transformed the management of heart failure with reduced and mildly reduced ejection fraction (HFrEF and HFmrEF) and improved patient care pathways. (El-Hadidi et al., 2026; Monzo et al., 2025; El Hadidi and Rosano, 2020) Notably, the PARADIGM-HF trial demonstrated that sacubitril/valsartan (Entresto®) was superior to enalapril in reducing cardiovascular mortality and heart failure hospitalisations, representing a major advance in heart failure therapy. (McMurray et al., 2014)
Moreover, SGLT2 inhibitors, initially developed as antihyperglycemic agents, have demonstrated significant benefits in HF patients regardless of diabetes status. The DAPA-HF and EMPEROR-Reduced trials have consistently reported reductions in HF-related events and improvements in quality of life (QoL) with dapagliflozin and empagliflozin, respectively. (Docherty et al., 2020; Anker et al., 2021) These findings have expanded the therapeutic options available, providing new possibilities for smartly optimising HF management. The compelling evidence from these trials emphasises the clinical advantages of combination therapy involving ARNi and SGLT2 inhibitors to enhance patient outcomes synergistically. (Tadic et al., 2024)
Despite strong clinical trial evidence supporting contemporary guideline-directed medical therapy (GDMT), real-world data comparing the impact of the different and commonly prescribed therapeutic regimens on patient-reported quality of life and lived experiences remain limited, particularly during the early post-discharge period. (Hadidi et al., 2022; Nicola et al., 2024)
Therefore, this study was undertaken to examine whether the commonly prescribed combinations are associated with meaningful differences in patients' lived experiences outside controlled trial settings. By prioritising patient-reported outcomes rather than clinical endpoints alone, this study provides novel real-world insight into how contemporary prescribing practices are reflected in the lived experience and early recovery of patients with HFrEF and HFmrEF.
Method
Study design
A cross-sectional descriptive study was conducted at two Middle Eastern tertiary care centres in Egypt and Saudi Arabia between December 2022 and March 2024 upon their first follow-up visits after discharge. This study is reported in accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) recommendations for cross-sectional studies. (von Elm et al., 2007)
The study aimed to compare the MLHFQ total score among patients receiving the triple therapy regimens (β-blocker + MRA and ACEi or ARBs), (β-blocker + MRA and ARNi), (β-blocker + MRA and SGLT2 inhibitors), and the recommended quadruple combination of GDMT (β-blocker + MRA + ARNi and SGLT2 inhibitors)
As a real-world, cross-sectional observational study, the objective is not to test a controlled intervention but to compare naturally occurring prescribing patterns and their association with QoL in routine clinical practice. This design is methodologically appropriate for exploratory comparative effectiveness research and for capturing patient-reported outcomes outside trial settings.
Eligibility criteria
All patients ≥18 years with heart failure and left ventricular ejection fraction (LVEF) < 50% (reduced or mildly reduced EF) receiving one of four therapeutic regimens were included.
Exclusion criteria included all the following conditions: HF with preserved ejection fraction, end-stage renal disease, end-stage liver disease, cancer, and prior heart transplantation.
Study groups
Conventional Triple Therapy regimen: β-blocker + MRA + ACEi/ARB
ARNi-Based Triple regimen: β-blocker + MRA + ARNi
SGLT2i-Based Triple regimen: β-blocker + MRA + SGLT2i
Quadruple regimen (GDMT): β-blocker + MRA + ARNi + SGLT2i
Data collection
Demographic and clinical variables were extracted from electronic medical records by the research team using a standardised data-collection sheet. All laboratory results corresponded to the index hospital admission, whereas MLHFQ was administered at the first outpatient follow-up (7–14 days post-discharge) During the same visit, a trained investigator conducted a face-to-face interview to ensure the complete responses of the questionnaire.
Outcome measures
The QoL was assessed using the Minnesota Living with Heart Failure Questionnaire (MLHFQ) administered at the first cardiology outpatient follow-up, 7–14 days after discharge. (Behlouli et al., 2009) A face-to-face interview was conducted for questionnaire collecting, a validated tool specifically designed to measure the impact of HF on patients' lives. (Bilbao et al., 2016; Naveiro-Rilo et al., 2010)
Scores are judged as follows: Lower MLHFQ scores indicate better QoL. For descriptive categorisation, we classified <24 as good, 24–45 as moderate, and ≥45 as poor QoL in line with prior validation work.
Statistical analysis
All statistical analyses were performed using IBM SPSS Statistics for Windows, Version 27.0. Armonk, NY: IBM Corp., USA.
Descriptive statistics were used to summarise the baseline characteristics of the study population, including means and standard deviations for continuous variables and frequencies and percentages for categorical variables.
Inferential statistics
A one-way between-groups analysis of variance (ANOVA) was conducted to determine if there were statistically significant differences in MLHFQ total score among the four therapeutic regimen groups. The independent variable was the therapeutic regimen, and the dependent variable was the MLHFQ score.
Following a significant ANOVA result, Tukey's Honestly Significant Difference (HSD) test was performed for post hoc comparisons to identify specific group differences. A multiple linear regression analysis was conducted to assess the ability of the independent variables (platelet count, ejection fraction (EF%), haemoglobin, Serum creatinine, sex (male/female), white blood cells (WBCs), and blood urea nitrogen (BUN) to predict the value of the MLHFQ score. Statistical significance was judged at a 5% level. We screened continuous variables for implausible values and unit mismatches. Creatinine values > 15 mg/dL or <0.3 mg/dL were considered implausible and handled via predefined rules (verification against source chart; if unresolved, casewise exclusion for analyses involving creatinine). For normally distributed continuous outcomes, we report the mean (SD) and 95% CI of the mean. Group differences were assessed by one-way ANOVA with Tukey HSD for pairwise comparisons. Model assumptions were evaluated via residual diagnostics.
Ethical considerations
Written informed consent was obtained from all participants before their voluntary participation in the study. The study was approved by the two local research ethics committees of the two hospitals in the two countries, in line with the Declaration of Helsinki and adhered to good clinical practice standards.
Data management
Data were fully anonymised to ensure patient privacy and confidentiality. All data were stored in a secure, dual password-encrypted database accessible only to the research team. Regular data audits were conducted to maintain data integrity and accuracy in the two countries.
Results
Descriptive analysis
From the two countries, the study enrolled a total of 118 voluntary HFrEF/HFmrEF patients who completed the questionnaire in full. The demographic and clinical characteristics are summarised in Table 1. The mean ejection fraction (EF) was 29.8% (SD = 8.1), and the mean serum creatinine was 3.941 mg/dL (SD = 1.5). The mean blood urea nitrogen level was 49.6 mg/dL (SD = 39.2), and the mean haemoglobin was 12 g/dL (SD = 2.3). White blood cell (WBC) count averaged 7.6 × 10ˆ3/µL (SD = 2.8), and platelet count averaged 236.7 × 10ˆ3/µL (SD = 75.2) (see Table 2).
Baseline characteristics of the study population
| Variable | Mean ± SD | Minimum | Maximum |
|---|---|---|---|
| Ejection Fraction (%) | 29.8 ± 8.1 | 15 | 45 |
| Serum Creatinine (mg/dL) | 3.9 ± 1.5 | 0.3 | 6.7 |
| Urea (mg/dL) | 49.6 ± 39.2 | 5 | 236 |
| Haemoglobin (g/dL) | 12.0 ± 2.3 | 8 | 18.9 |
| White Blood Cells ( × 10ˆ3/µL) | 7.6 ± 2.8 | 3 | 18 |
| Platelets ( × 10ˆ3/µL) | 236.7 ± 75.2 | 41 | 453 |
| MLHFQ total score | 56.5 ± 22.1 | 7 | 98 |
Note(s): MLHFQ: minnesota living with heart failure questionnaire
MLHFQ scores of the four commonly prescribed therapeutic regimens
| Regimen | Mean MLHFQ total score ±SD | Minimum – Maximum range |
|---|---|---|
| Conventional Triple regimen | 68.1 ± 19.8 | 26–98 |
| ARNi-based triple regimen | 57.3 ± 19.9 | 7–87 |
| SGLT2i-based triple regimen | 56.9 ± 22.2 | 21–92 |
| Quadruple regimen (GDMT) | 42.8 ± 19.0 | 9–92 |
Note(s): ARNi: Angiotensin Receptor-Neprilysin Inhibitor; GDMT: guideline-directed medical therapy; SD: standard deviation; SGLT-2i: sodium-glucose cotransporter 2 inhibitors
The average score on the Minnesota Living with Heart Failure Quality of Life Questionnaire was 56.50 (SD = 22.113). Sex distribution showed 89 males (75.4%) and 29 females (24.6%), as in Figure 1.
The chart is a circular pie chart divided into two segments representing sex categories. The larger segment occupies most of the circle and is labeled “75.4”, corresponding to “Male”. The smaller segment occupies roughly one quarter of the circle and is labeled “24.6”, corresponding to “Female”. Below the chart, a legend identifies the two categories with labels “Male” in blue and “Female” in orange. The values are displayed directly inside each segment, centered within their respective areas.Respondents' sex distribution %
The chart is a circular pie chart divided into two segments representing sex categories. The larger segment occupies most of the circle and is labeled “75.4”, corresponding to “Male”. The smaller segment occupies roughly one quarter of the circle and is labeled “24.6”, corresponding to “Female”. Below the chart, a legend identifies the two categories with labels “Male” in blue and “Female” in orange. The values are displayed directly inside each segment, centered within their respective areas.Respondents' sex distribution %
Figure 2 shows the prescription rates of the four distinct therapeutic regimens that were commonly prescribed among the study population. Group 1: 33 (28%) patients received conventional triple therapy (β-blockers, MRA, and ACEi or ARBs). The second group comprised 22 patients (18.6%) who received a triple regimen containing a β-blocker, MRA, and ARNi (Sacubitril/Valsartan) as an ARNi-based therapy. Another group was 33 patients (28%) who were administered a β-blocker, MRA, and SGLT2i as an SGLT2i-based triple regimen. The fourth group was 30 patients (25.4%) treated with the full four pillars (β-blockers, MRA, ARNi and SGLT2i) as the quadruple GDMT.
The vertical axis ranges from 0.0 to 30.0 with an interval of 5.0. The horizontal axis lists four categories: “Conventional Triple regimen”, “S G L T 2 i-Based regimen”, “Quadruple G D M T”, and “A R N i-Based regimen”. Each category is represented by a solid vertical bar with its value labeled at the top. The first bar, “Conventional Triple regimen”, reaches a value of 28.0. The second bar, “S G L T 2 i-Based regimen”, also reaches 28.0, matching the height of the first bar. The third bar, “Quadruple G D M T”, is shorter, reaching 25.4. The fourth bar, “A R N i-Based regimen”, is the shortest, reaching 18.6. A legend on the right side reads for the bars “Percentage of Distribution of Regimens”.The prescription rates of the four distinct therapeutic regimens
The vertical axis ranges from 0.0 to 30.0 with an interval of 5.0. The horizontal axis lists four categories: “Conventional Triple regimen”, “S G L T 2 i-Based regimen”, “Quadruple G D M T”, and “A R N i-Based regimen”. Each category is represented by a solid vertical bar with its value labeled at the top. The first bar, “Conventional Triple regimen”, reaches a value of 28.0. The second bar, “S G L T 2 i-Based regimen”, also reaches 28.0, matching the height of the first bar. The third bar, “Quadruple G D M T”, is shorter, reaching 25.4. The fourth bar, “A R N i-Based regimen”, is the shortest, reaching 18.6. A legend on the right side reads for the bars “Percentage of Distribution of Regimens”.The prescription rates of the four distinct therapeutic regimens
Inferential statistics
The conventional triple therapy group had the highest mean MLHFQ score (68.06 ± 19.77), whereas the quadruple GDMT group had the lowest mean score (42.77 ± 19.05), indicating better QoL.
Applying ANOVA for comparison between the 4 regimens regarding MLHFQ score revealed a statistically significant difference between the four groups (p < 0.001), as in Table 3.
ANOVA for MLHFQ scores between different regimens
| Sum of squares | df | Mean square | F | Sig. | |
|---|---|---|---|---|---|
| Between Groups | 10087.967 | 3 | 3362.656 | 8.135 | <0.001 |
| Within Groups | 47121.533 | 114 | 413.347 | ||
| Total | 57209.500 | 117 |
Post-hoc pairwise comparison in Table 4 declared the statistically significant difference between group one, the conventional triple therapy, and group four patients who received the four pillars of GDMT (p < 0.001), also the statistically significant difference between patients' group 3 received SGLT2i with (Β-blocker and MRA) and group 4 received the 4 pillars (p = 0.036).
Post hoc pairwise multiple comparisons by Tukey HSD test between different regimens
| (I) Regimen | (J) Regimen | Mean difference (I—J) | Std. error | Sig. | 95% confidence interval | |
|---|---|---|---|---|---|---|
| Lower bound | Upper bound | |||||
| Conventional triple regimen | ARNi | 10.742 | 5.596 | 0.226 | −3.85 | 25.33 |
| SGLT2i | 11.182 | 5.005 | 0.120 | −1.87 | 24.23 | |
| Quadruple | 25.294* | 5.129 | <0.001 | 11.92 | 38.67 | |
| ARNi-based triple regimen | Conventional | −10.742 | 5.596 | 0.226 | −25.33 | 3.85 |
| SGLT2i | 0.439 | 5.596 | 1.000 | −14.15 | 15.03 | |
| Quadruple | 14.552 | 5.707 | 0.058 | −0.33 | 29.43 | |
| SGLT2i-based triple regimen | Conventional | −11.182 | 5.005 | 0.120 | −24.23 | 1.87 |
| ARNi | −0.439 | 5.596 | 1.000 | −15.03 | 14.15 | |
| Quadruple | 14.112* | 5.129 | 0.034 | 0.74 | 27.48 | |
Note(s): ARNi: Angiotensin Receptor-Neprilysin Inhibitor; GDMT: guideline-directed medical therapy; SGLT-2i: sodium-glucose cotransporter 2 inhibitors
*Statistical significance difference (P-value < 0.05)
Tables 5 and 6 show that the length of hospital stay differed significantly among regimens (one-way ANOVA, F = 5.361, p = 0.004). Tukey HSD post hoc analysis showed that patients receiving conventional triple therapy had significantly longer hospital stay than those receiving the SGLT2i-based regimen (mean difference 1.333 days, 95% CI 0.47 to 2.20, p = 0.001) and quadruple GDMT (mean difference 1.933 days, 95% CI 1.05 to 2.82, p < 0.001). In addition, patients receiving ARNi-based therapy had a longer stay than those receiving quadruple GDMT (mean difference 1.085 days, 95% CI 0.10 to 2.07, p = 0.025).
ANOVA for length of hospital stay between the different regimens
| Sum of squares | Mean square | F | Sig. | |
|---|---|---|---|---|
| Between Groups | 23.434 | 7.811 | 5.361 | 0.004 |
| Within Groups | 52.469 | 1.457 | ||
| Total | 75.902 |
Length of hospital stay
| (I) Regimen | (J) Regimen | Mean difference (I−J) | Std. error | Sig. | 95% CI lower | 95% CI upper |
|---|---|---|---|---|---|---|
| Conventional triple therapy | ARNi-based regimen | 0.848 | 0.372 | 0.108 | −0.12 | 1.82 |
| SGLT2i-based regimen | 1.333 | 0.332 | 0.001 | 0.47 | 2.20 | |
| Quadruple GDMT | 1.933 | 0.341 | <0.001 | 1.05 | 2.82 | |
| ARNi-based regimen | Conventional triple therapy | −0.848 | 0.372 | 0.108 | −1.82 | 0.12 |
| SGLT2i-based regimen | 0.485 | 0.372 | 0.562 | −0.48 | 1.45 | |
| Quadruple GDMT | 1.085 | 0.379 | 0.025 | 0.10 | 2.07 | |
| SGLT2i-based regimen | Conventional triple therapy | −1.333 | 0.332 | 0.001 | −2.20 | −0.47 |
| ARNi-based regimen | −0.485 | 0.372 | 0.562 | −1.45 | 0.48 | |
| Quadruple GDMT | 0.600 | 0.341 | 0.297 | −0.29 | 1.49 |
Note(s): ARNi: Angiotensin Receptor-Neprilysin Inhibitor; GDMT: guideline-directed medical therapy; SGLT-2i: sodium-glucose cotransporter 2 inhibitors
Table 7 showed the statistically significant difference between groups regarding the EF% (p = 0.047). Patients receiving quadruple GDMT had lower EF than those receiving conventional triple therapy (mean difference 5.27% points, 95% CI 0.10 to 10.43, p = 0.044) as seen in Table 8.
ANOVA for EF% between different regimens
| Sum of squares | df | Mean square | F | Sig. | |
|---|---|---|---|---|---|
| Between groups | 503.731 | 3 | 167.910 | 2.725 | 0.047 |
| Within groups | 7023.973 | 114 | 61.614 | ||
| Total | 7527.703 | 117 |
Post hoc pairwise comparison concerning the EF% between regimens (Tukey HSD) in the four groups
| (I) Regimen | (J) Regimen | Mean difference (I—J) | Std. error | Sig. | 95% confidence interval | |
|---|---|---|---|---|---|---|
| Lower bound | Upper bound | |||||
| Conventional | ARNi regimen | 3.864 | 2.160 | 0.284 | −1.77 | 9.50 |
| SGLT2i regimen | 4.121 | 1.932 | 0.149 | −0.92 | 9.16 | |
| Quadruple GDMT | 5.267* | 1.980 | 0.044 | 0.10 | 10.43 | |
Note(s): ARNi: Angiotensin Receptor-Neprilysin Inhibitor; GDMT: guideline-directed medical therapy; SGLT-2i: sodium-glucose cotransporter 2 inhibitors
Regression analysis
A multiple linear regression model was used to examine independent predictors of MLHFQ score. The overall model was statistically significant, F = 5.234, p < 0.001, and explained 25.0% of the variance in MLHFQ score (R2 = 0.250; adjusted R2 = 0.202), Table 9.
Regression analysis parameters for the effect of independent variables on the MLHFQ scoring
| R | R2 | Adjusted R2 | Std. Error of estimate | F | df1 | df2 | p |
|---|---|---|---|---|---|---|---|
| 0.500 | 0.250 | 0.202 | 19.752 | 5.234 | 7 | 110 | <0.001 |
Higher serum creatinine (B = 0.295, p = 0.010) and blood urea nitrogen (B = 0.157, p = 0.003) were independently associated with higher (worse) MLHFQ scores, whereas higher haemoglobin (B = −2.314, p = 0.011) was independently associated with lower (better) MLHFQ scores, Table 10.
Predictors of MLHFQ scoring
| Variable | Unstandardized coefficients | Standardized coefficients | t | Sig. | |
|---|---|---|---|---|---|
| B | Std. Error | Beta | |||
| (Constant) | 79.367 | 14.487 | 5.479 | <0.001 | |
| Sex | −4.57 | 4.511 | −0.089 | −1.013 | 0.313 |
| Ejection fraction | −0.008 | 0.234 | −0.003 | −0.032 | 0.974 |
| Serum creatinine | 0.295 | 0.113 | 0.223 | 2.619 | 0.01 |
| Blood Urea Nitrogen (BUN) | 0.157 | 0.051 | 0.279 | 3.059 | 0.003 |
| Haemoglobin (HgB) | −2.314 | 0.899 | −0.24 | −2.573 | 0.011 |
| White blood cells | −1.317 | 0.714 | −0.165 | −1.844 | 0.068 |
| Platelets | 0.031 | 0.026 | 0.105 | 1.173 | 0.243 |
For clinical interpretability, the simplified predictive relationship can be expressed as:
Discussion
This cross-sectional study examined the association between guideline-directed medical therapy regimens and health-related quality of life in patients with HFrEF/HFmrEF, reflecting real-world outpatient practice and complementing existing evidence on patient-reported outcomes in heart failure. The presented findings corroborate the supporting evidence from the latest American and European clinical practice guidelines and advocate early initiation of all four GDMT pillars at the earliest convenience. (McDonagh et al., 2021; El-Hadidi et al., 2026) Such a finding is also in line with prior landmark studies, such as the DAPA-HF and EMPEROR-Reduced trials, which highlighted the synergistic benefits of SGLT2 inhibitors alongside conventional HF treatments. (Docherty et al., 2020; Anker et al., 2021; El Hadidi et al., 2021) These benefits might stem from the complementary mechanisms of action, combining natriuretic and diuretic effects with inhibition of the renin-angiotensin system.
The high MLHFQ scores among patients on conventional triple therapy, despite previously established mortality benefits, may be attributed to residual symptomatology. Despite its comprehensive scope, the conventional triple therapy group exhibited the highest MLHFQ scores, indicating poorer QoL outcomes. Previous literature, including guidelines by Yancy et al., supports the effectiveness of beta-blockers, MRAs, and ACE inhibitors or ARBs in reducing HF hospitalisations. (Severino et al., 2024; El Hadidi et al., 2018) However, the study underscores that such benefits may not translate into improvements in QoL, potentially due to clinical inertia and fear of adverse effects or increased pill burden (Moradi et al., 2020). This finding is consistent with the hypothesis that the newer disease-modifying agents offer not only beneficial clinical stability but also enhanced patient-reported outcomes and experiences. (Shchendrygina and Saldarriaga, 2024)
Patients treated solely with ARNi or SGLT2 inhibitors demonstrated moderate improvements in QoL, consistent with evidence from pivotal trials such as PARADIGM-HF and DAPA-HF. (Kosiborod et al., 2020; El-Hadidi et al., 2026) While both therapies individually reduce cardiovascular mortality and hospitalisations, this study highlights that their effects on QoL, though significant, do not match the enhancements achieved through their combination. (Trueman et al., 2017) This finding reinforces the need for tailored therapeutic strategies tailored to patient-specific needs and experiences. (Stolfo et al., 2025; Nicola et al., 2024)
The significant reduction in hospital length of stay for patients on the ARNi and SGLT2 inhibitor combination further supports the clinical superiority of this regimen. These findings align with the international guidelines emphasising early initiation of combination therapy to optimise outcomes. Shorter hospital stays will also be translated into reduced healthcare costs and fewer disruptions to patients' daily lives, adding an economic dimension to the therapy's clinical benefits. (McEwan et al., 2021)
Regression analysis identified higher serum creatinine and blood urea nitrogen as predictors of worse QoL, whereas higher haemoglobin predicted better QoL. These markers highlight the importance of the appropriate management and correction of renal function, anaemia and any potentially inappropriate polypharmacy in HF patients. (El Hadidi et al., 2022b) The role of haemoglobin, in particular, suggests that addressing underlying anaemia could further enhance QoL outcomes. These findings corroborate prior research advocating the regular integration of renal and haematological evaluations into HF management protocols. (Oswald et al., 2024; Zhou et al., 2024)
When compared to global findings, the results resonate with trends observed in multicentre studies from Western European and Asian cohorts. (Lam et al., 2016) However, the context-specific nature of this study, involving Middle Eastern patients from Egypt as a low-income country from Africa and Saudi Arabia as a high-income country from Asia, provides unique insights into regional variations in patient outcomes and responses to therapy. (Hassanin et al., 2020; El Hadidi et al., 2020) These insights underscore the importance of conducting culturally and geographically diverse studies to refine global HF management strategies. (Dokainish et al., 2016)
The findings advocate for the early implementation of combination therapies, particularly ARNi and SGLT2 inhibitors, in clinical practice. (Cavallari et al., 2023; Tadic et al., 2024) Therefore, this study opens the room for the early inclusion of clinical pharmacy in the HF management team to achieve an appropriate medication therapy management during hospitalisation and the full prescription of the updated guideline-directed medical therapies upon discharge. (El Hadidi et al., 2020, 2022a; Alsetohy et al., 2025)
Patient-centred care models should integrate QoL systematically as a core parameter alongside clinical endpoints. Future research should prioritise multicentre, longitudinal studies to validate these results and explore cost-effectiveness over 5 and 10 years of therapy. (Halatchev et al., 2020; El Hadidi et al., 2020) Additionally, real-world data on long-term patients' adherence and patient-reported outcomes and experiences will be crucial to determining the sustainability of these benefits.
Implications for clinical practice, research, and patient-centred care
The present findings have several important implications for clinical practice, research, and patient-centred care, while remaining consistent with the cross-sectional design of the study. The observed association between more comprehensive GDMT regimens and lower (better) MLHFQ scores suggests that, in real-world outpatient settings, patients receiving a greater number of guideline-recommended therapies tend to report better health-related quality of life. Although causality cannot be inferred, these results underscore the potential value of systematic GDMT optimization and careful medication reconciliation during follow-up visits, particularly for patients with persistently poor quality-of-life scores.
From a clinical implementation perspective, the findings support the integration of routine quality-of-life assessment, such as the MLHFQ, into heart failure care pathways to help identify patients who may benefit from closer evaluation of GDMT completeness or tolerability. In practice, clinicians may use patient-reported outcomes alongside clinical and laboratory parameters to guide individualised treatment discussions, especially when balancing the benefits of GDMT intensification against comorbidities, renal function, and patient preferences.
In terms of patient-centred care, the association between GDMT intensity and quality of life highlights the importance of shared decision-making. Discussing expected symptom burden and quality-of-life outcomes with patients may enhance engagement, adherence, and satisfaction with therapy, particularly in populations where polypharmacy or adverse effects are concerns.
From a research perspective, these findings generate hypotheses for future longitudinal and interventional studies. Prospective studies are needed to determine whether stepwise GDMT optimisation leads to sustained improvements in quality of life over time and to clarify the temporal relationship between laboratory markers, treatment intensity, and patient-reported outcomes. Randomized or pragmatic trials incorporating quality-of-life endpoints would further strengthen the evidence base and inform guideline implementation strategies.
Strengths and limitations
This study offers important real-world insights into the association between contemporary GDMT regimens and patient-reported quality of life. Also, the multicentre design across two largely populated countries enhanced the outcome of the validated MLHFQ tool, the rigorous statistical analysis, and therefore, the generalisability and robustness of findings across the neighbouring countries. Additionally, by integrating biochemical and clinical predictors into regression modelling, the study provides a nuanced understanding of factors influencing QoL beyond pharmacological treatment.
However, some limitations must be acknowledged. First, the cross-sectional design precludes causal inference or determination of temporal relationships between GDMT regimens and quality-of-life outcomes; the observed associations reflect a single time point and may be influenced by reverse causality. Second, although we adjusted for selected clinical and laboratory variables, residual confounding remains possible. Important factors such as overall disease severity (including symptom burden and functional capacity), medication adherence, duration of therapy, and socioeconomic determinants of health (e.g., income, education, access to care, and social support) were not fully captured. They may independently influence patient-reported quality of life.
Conclusion
In this cross-sectional analysis, the full GDMT regimen is associated with better patient-reported quality of life among patients with HFrEF/HFmrEF. While these findings suggest potential quality-of-life benefits for patients receiving multiple guideline-recommended therapies, causal inferences cannot be drawn, and treatment decisions should be individualised based on clinical characteristics, comorbidities, and patient preferences.
Authors contribution
Idea visualization: SEH.
Design conception: SEH, MM and EA.
Egypt Data collection: MM, EA, RW, RYK, EME
KSA Data collection: FA and AAE
Writing original article drafting: SEH; MM and EA.
Critical review of final report: AAE, RW and FA.
All authors read and approved the final manuscript.
Consent for publication
All authors confirm their approval to publish this manuscript. Patients or their legally authorized relatives signed informed consent regarding publishing their data.
Ethics consideration
Approved by the local research ethics committees of Alexandria University Hospitals, Alexandria, Egypt and King Saud University Medical City, Al Diriyah, Riyadh, KSA.
The author team would like to thank RCSI CONVERGE Centre and SFI (Research Ireland) for their support.
