To describe sociodemographic and clinical characteristics, treatments, and incidence of hospital admission and all-cause mortality within a cohort of patients diagnosed with heart failure with reduced ejection fraction (HFrEF) followed up in Primary Care.
DesignPopulation-based cohort study.
SiteThe data source is the Information System for the Development of Research in Primary Care (SIDIAP), which captures information from the Electronic Health Records of Primary Health Care of the Catalan Institute of Health (approximately 80% of the Catalan population).
ParticipantsAdults with a diagnostic code of HFrEF in 2018–2022.
InterventionsNot applicable.
Main measurementsSocio-demographic and clinical characteristics, drug exposure, hospitalizations due to heart failure and all-cause mortality.
ResultsWe included 17,169 patients; 59.5% men and 40.5% women. We found differences between men and women in clinical characteristics and in drug combinations, and suboptimal use to recommended therapies, being better for men than for women. Women had higher hospitalization (44.6% vs 42.1%) and all-cause mortality rates (27.2% vs 25.3%). Hazard ratio of hospitalization was higher in older than 60, with increasing NYHA, diabetic patients and in previously hospitalized.
ConclusionsWe observed sex disparities in baseline characteristics, in drug use for heart failure, and in adherence to treatment recommendations. Women had higher rates of hospital admissions and all-cause mortality, although the hazard ratio for hospitalization risk was similar between sexes. Age over 60, increasing NHYA, diabetes and prior heart-failure hospitalization resulted in higher risk of hospital admission. These findings highlight the importance of tailoring treatment strategies according to clinical conditions.
Describir las características sociodemográficas y clínicas, los tratamientos y la incidencia de ingresos hospitalarios y mortalidad por todas las causas en una cohorte de pacientes diagnosticados con insuficiencia cardíaca con fracción de eyección reducida (ICFEr) seguidos en Atención Primaria.
DiseñoEstudio de cohorte de base poblacional.
EmplazamientoLa fuente de datos es el Sistema de Información para el Desarrollo de la Investigación en Atención Primaria (SIDIAP), que recoge información de las historias clínicas electrónicas de la Atención Primaria del Instituto Catalán de la Salud (aproximadamente el 80% de la población catalana).
ParticipantesAdultos con un código de diagnóstico de ICFEr en 2018-2022.
IntervencionesNo aplicable.
Mediciones principalesCaracterísticas sociodemográficas y clínicas, exposición a fármacos, hospitalizaciones por insuficiencia cardíaca y mortalidad por todas las causas.
ResultadosSe incluyeron 17 169 pacientes; 59,5% hombres y 40,5% mujeres. Encontramos diferencias entre hombres y mujeres en las características clínicas y en las combinaciones de fármacos, así como un uso subóptimo de las terapias recomendadas, siendo superior para los hombres que para las mujeres. Las mujeres tuvieron mayores tasas de hospitalización (44,6% frente a 42,1%) y mortalidad por todas las causas (27,2% frente a 25,3%). La razón de riesgo de hospitalización fue mayor en los mayores de 60 años, con un aumento de la NYHA, en los pacientes diabéticos y en los que habían sido hospitalizados anteriormente.
ConclusionesObservamos disparidades entre sexos en las características basales, en el uso de medicamentos para la ICFEr y en el cumplimiento de las recomendaciones terapéuticas. Las mujeres presentaron tasas más elevadas de ingresos hospitalarios y mortalidad por todas las causas, aunque la razón de riesgos para el riesgo de hospitalización fue similar entre ambos sexos. La edad superior a 60 años, el aumento de la NHYA, la diabetes y los ingresos hospitalarios previos por insuficiencia cardíaca se asociaron con un mayor riesgo de ingreso hospitalario. Estos hallazgos ponen de relieve la importancia de adaptar las estrategias terapéuticas en función de las condiciones clínicas.
Heart failure (HF) is characterized by the reduced ability of the heart to pump and/or fill with blood,1,2 being the sixth most frequent cause of death in Spain3 and causing high expenditure of health resources.4,5
Identification of etiology of the underlying cardiac dysfunction is mandatory in the diagnosis, being the most common causes ischemic heart disease (IHD), hypertension, valve diseases or arrhythmias. Diagnosis requires clinical signs/symptoms and objective evidence of cardiac dysfunction, measured by the left ventricular ejection fraction (LVEF).6 Then, HF is classified into 3 categories: HF with reduced ejection fraction (HFrEF) – LVEF ≤40%, HF with preserved ejection fraction (HFpEF) – LVEF ≥50%, and HF with mildly reduced ejection fraction (HFmrEF) – LVEF 41–49%.6,7 Approximately 50% of people with HF are HFrEF.2 Different baseline characteristics and outcomes between patients in the three subgroups have been shown, as higher proportion of men with HFrEF.4,8–10 HF is also classified according to the New York Heart Association (NYHA) functional classification, relying on symptoms, consisting in four categories of worsening of functional status: I, II, III, and IV.6
HF treatment objectives are reducing mortality and risk of hospitalization and improving symptoms.6 Four pharmacological groups have demonstrated these objectives: modulation of the renin–angiotensin–aldosterone system (RAS) with angiotensin-converting enzyme inhibitors (ACEi) or angiotensin-receptor blockers (ARB), or with the angiotensin receptor-neprilysin inhibitor sacubitril/valsartan (SAC/VAL); beta-blockers (BB); mineralocorticoid receptor antagonists (MRA); and the sodium-glucose co-transporter 2 inhibitors (SGLT2i). They represent the evidence-based first-line treatment, known as guideline-directed medical therapies (GDMT).2,6,7 Other drugs can be added in some patients, such as diuretics, ivabradine, hydralazine with isosorbide dinitrate, or digoxin.6
While HFrEF is prevalent and substantially impacts public health, its management in our Primary Health Care (PHC) setting remains under-explored. To address these gaps, we aimed to describe sociodemographic and clinical characteristics and pharmacological treatments prescribed in a cohort of patients diagnosed with HFrEF followed up in PHC, analyzing sex differences. We also assessed the incidence of hospital admission and all-cause mortality.
Material and methodsStudy designThis observational study follows the RECORD-PE reporting guidelines.11 The study design is a population-based cohort study including adults with HFrEF diagnosis in PHC in Catalonia, Spain, from January 2018 to December 2022.
Population includedWe included all ≥18 years-old individuals with an active diagnosis of HFrEF (10th International Classification of Diseases, clinical modification [ICD-10-MC] codes: I50.1; left ventricular failure, unspecified, and I50.2; systolic [congestive] heart failure)12 in the PHC electronic records in Catalonia, Spain, between 2018 to 2022. All individuals with diagnoses registered before 2018 were included at date January 1st, 2018 (prevalent diagnoses) and all individuals with a new diagnosis during the study period were included at date of diagnosis (incident diagnoses). All patients were followed up from cohort entry up to end of study period, lost to follow-up or death.
Population excludedPatients with HF diagnoses other than HFrEF were excluded (ICD-10-MC codes: I50.3, I50.4, I50.8, I50.9). They have been recently described in another paper.10
Data sourceThe data source is the Information System for the Development of Research in Primary Care (SIDIAP),13,14 capturing clinical information of approximately 6 million people from Catalonia, Spain (around 80% of the Catalan population). This information is pseudonymized, originated from different data sources: ECAP, the Electronic health records (EHR) in PHC in Catalonia, including socio-demographics, anthropometrics, comorbidities registered as ICD-10-CM,12 specialist referrals, clinical parameters, toxic habits, sickness leave, date of death, laboratory test data, vaccinations and drug prescriptions issued in PHC, registered as Anatomical, Therapeutic, Chemical classification system (ATC) codes.15 Additionally, pharmacy invoice data corresponding to these prescriptions, also by ATC, were also utilized. Lastly, we also captured information from the database of diagnoses at hospital discharge (CMBD-HA).16
Study variablesBaseline variables: socio-demographics, anthropometrics, toxic habits, comorbidities, prior hospital admissions by HF, laboratory test data, and comedications, all of them assessed at cohort entry. NYHA recorded at diagnosis or up to 3 months after diagnosis for newly diagnosed, or after the cohort entry for those diagnosed before January 2018, and the first recorded value of LVEF.
Exposure to drugs for HF treatment: we focused on the drugs prescribed during the last trimester of the study period (October-December 2022) to HFrEF patients active in the database, including drugs recommended for all patients with HFrEF according to guidelines: (1) RAS drugs, including ACEi, ARB, and SAC-VAL, (2) BB, (3) MRA, and (4) SGLT2i; and additionally other drugs used for selected patients with HFrEF: diuretics, digoxin, ivabradine, hydralazine, vericiguat, or other drugs acting on the RAS. We reported percentage of patients treated with each group, frequency of the most frequent drug combinations, and frequency of use of 4, 3, 2, 1 or none of the GDMT (RAS agents, BB, MRA and SGLT2i). Descriptives of drug exposure are reported separated by sex and by NYHA.
Study outcomes: hospital admission due to HF (1st and 2nd diagnoses in CMBD-HA) and all-cause mortality throughout the study period.
Potential confounding variables: age, sex, NYHA, previous hospitalization for HF, comorbidities.
ICD-10-CM and ATC codes extracted from SIDIAP and CMBD-HA are detailed in Supplementary Table S1.
Statistical analysisPopulation characteristics were described by absolute frequency and percentage for categorical variables and by mean and standard deviation (SD) for continuous variables. A Cox Proportional-Hazard Model was performed to estimate the risk of hospital admission due to HF event. The variables posing higher risk for new HF complications were introduced in the model: age, sex, NYHA, previous hospitalization for HF, diabetes and IHD.17,18 The findings are presented comprehensively for the entire population, as well as stratified by sex and by NYHA. All analyses have been conducted with R software version 4.2.
ResultsThere were 17,169 individuals with an active diagnosis of HFrEF in the PHC records from 2018 to 2022 (Fig. 1), 59.5% were men and 40.5% women. Baseline characteristics are described in Table 1. Women were older than men (78.6 vs 72.2 years, 51.9% of women older than 80), had obesity more frequently than men (37.9% vs 31.2%), and glomerular filtration rate (GFR) lower than 60mL/min/1.73m2 in a higher proportion than men (50.4% vs 41%). Prevalence of smoking was higher in men (17.4% vs 6.1%). NYHA was registered in 58.5% patients and LVEF, in 33.4%. They also differed by sex, with more men in NYHA I (24.8% vs 16.3%) and more women in NYHA II–IV categories, or higher frequency of registered reduced LVEF in men (56.7% vs 42.0%).
Flow diagram of patients included in the study. Flow diagram of the population included and excluded in the study. SIDIAP: Information System for the Development of Research in Primary Care. HF: heart failure. HFpEF: heart failure with preserved ejection fraction. HFrEF: heart failure with reduced ejection fraction.
Socio-demographic and clinical baseline characteristics of patients with heart failure with reduced ejection fraction.
| N (%) | Overall population | Women | Men | p-Value |
|---|---|---|---|---|
| N=17,169 | N=6962 (40.5%) | N=10,207 (59.5%) | ||
| Age in years, mean (SD) | 74.8 (12.5) | 78.6 (11.2) | 72.2 (12.7) | <0.001 |
| >80 | 6730 (39.2) | 3616 (51.9) | 3114 (30.5) | <0.001 |
| MEDEA socioeconomic index (21.4% missing) | ||||
| Rural | 2400 (17.8) | 932 (17.4) | 1468 (18.0) | 0.627 |
| Urban | 11,098 (82.2) | 4430 (82.6) | 6668 (81.9) | |
| U4-U5 | 4491 (33.2) | 1812 (33.8) | 2679 (32.9) | |
| BMI≥30kg/m2 (10.8% missing) | 5196 (33.9) | 2345 (37.9) | 2851 (31.2) | <0.001 |
| GFR, mL/min/1.73m2 (10.8% missing) | ||||
| <15 | 212 (1.3) | 76 (1.1) | 136 (1.4) | <0.001 |
| 15–29 | 1150 (7.0) | 544 (8.2) | 606 (6.2) | |
| 30–44 | 2476 (15.1) | 1198 (18.0) | 1278 (13.1) | |
| 45–59 | 3515 (21.4) | 1541 (23.1) | 1974 (20.3) | |
| 60–89 | 6951 (42.4) | 2764 (41.4) | 4187 (43.1) | |
| ≥90 | 2089 (12.7) | 551 (8.3) | 1538 (15.8) | |
| Smoking habit (1.2% missing) | ||||
| Smoker | 2176 (12.8) | 420 (6.1) | 1756 (17.4) | <0.001 |
| Non-smoker | 7672 (45.2) | 5036 (73.0) | 2636 (26.2) | |
| Former smoker | 7115 (41.9) | 1439 (20.9) | 5676 (56.4) | |
| NYHA at diagnosis (41.5% missing) | ||||
| I | 2147 (21.4) | 665 (16.3) | 1482 (24.8) | <0.001 |
| II | 5476 (54.5) | 2257 (55.3) | 3219 (54.0) | |
| III | 2260 (22.5) | 1070 (26.2) | 1190 (20.0) | |
| IV | 160 (1.6) | 87 (2.1) | 73 (1.2) | |
| LVEF, 1st registereda (66.6% missing) | ||||
| ≤40% | 2959 (51.6) | 834 (42.0) | 2125 (56.7) | <0.001 |
| 41–49% | 1262 (22.0) | 427 (21.5) | 835 (22.3) | |
| ≥50% | 1516 (26.4) | 725 (36.5) | 791 (21.1) | |
| Comorbidities | ||||
| Anemias | 1930 (11.2) | 969 (13.9) | 961 (9.4) | <0.001 |
| Atrial fibrillation | 7164 (41.7) | 3025 (43.5) | 4139 (40.6) | <0.001 |
| COPD | 2859 (16.7) | 607 (8.7) | 2252 (22.1) | <0.001 |
| Diabetes | 6593 (38.4) | 2381 (34.2) | 4212 (41.3) | <0.001 |
| Dyslipidemia | 8763 (51.0) | 3740 (53.7) | 5023 (49.2) | <0.001 |
| Hypertension | 12,294 (71.6) | 5316 (76.4) | 6978 (68.4) | <0.001 |
| IHD | 5672 (33.0) | 1482 (21.3) | 4190 (41.1) | <0.001 |
| Previously admitted to hospital for HF | 4120 (24.0) | 1689 (24.2) | 2431 (23.8) | 0.555 |
| Comedications | ||||
| Antiarrhythmic drugs | 1284 (7.5) | 474 (6.8) | 810 (7.9) | 0.006 |
| Drugs for diabetes | 5548 (32.3) | 1972 (28.3) | 3576 (35.0) | <0.001 |
| Iron (oral) | 2809 (16.4) | 1338 (19.2) | 1471 (14.4) | <0.001 |
| Lipid modifying agents | 9734 (56.7) | 3318 (47.7) | 6416 (62.9) | <0.001 |
| Oral anticoagulants | 7123 (41.5) | 2906 (41.7) | 4217 (41.3) | 0.589 |
| Platelet aggregation inhibitors | 6444 (37.5) | 2043 (29.3) | 4401 (43.1) | <0.001 |
SD: standard deviation. MEDEA: 5 urban quintiles from least to most deprived and 1 rural quintile.40 BMI: body mass index. GFR: glomerular filtration rate as CKD-EPI. NYHA: New York Heart Association. LVEF: left ventricular ejection fraction, 1st value registered regardless of diagnosis date.
All comorbidities showed sex differences, being chronic obstructive pulmonary disease (COPD), IHD, and diabetes more frequent in men. Hypertension remained the most prevalent condition regardless of sex. There were no significant sex differences in the rates of previous hospitalization for HF (24.2% in women vs 23.8% in men, p=0.555). Comedications were more frequently used in men, except for iron supplements, mostly used in women, and oral anticoagulants, non-different by sex (Table 1).
During the last trimester of the study period, 12,760 individuals (74.3%) were active in the database, comprising 7649 (59.9%) men and 5111 (40.1%) women (Fig. 1). Utilization rates of HF drugs are detailed in Table 2. We found 75.3% of patients treated with drugs acting on the RAS, either ACEi, ARB or SAC/VAL. More women used ACEi or ARB (48.8% vs 42%), while the use of SAC/VAL was higher in men (36.9% vs 21.1%). Conversely, the use of BB, MRA, SGLT2i and ivabradine was more prevalent in men than in women. Only diuretics and digoxin were more frequently prescribed for women.
Pharmacological groups prescribed for heart failure treatment during October–December 2022.
| N (%) | Overall populationN=12,760 | WomenN=5111 (40.1%) | MenN=7649 (59.9%) | p-Value |
|---|---|---|---|---|
| ACEi or ARB | 5704 (44.7) | 2494 (48.8) | 3210 (42.0) | <0.001 |
| ACEi | 3534 (27.7) | 1440 (28.2) | 2094 (27.4) | 0.333 |
| ARB | 2174 (17.0) | 1055 (20.6) | 1119 (14.6) | <0.001 |
| SAC/VAL | 3905 (30.6) | 1079 (21.1) | 2826 (36.9) | <0.001 |
| BB | 9672 (75.9) | 3687 (72.1) | 5985 (78.2) | <0.001 |
| MRA | 5368 (42.1) | 1679 (32.9) | 3689 (48.2) | <0.001 |
| SGLT2i | 4287 (33.6) | 1276 (25.0) | 3011 (39.4) | <0.001 |
| Diuretics | 8002 (62.8) | 3514 (68.8) | 4488 (58.7) | <0.001 |
| Digoxin | 884 (6.9) | 450 (8.8) | 434 (5.7) | <0.001 |
| Ivabradine | 670 (5.3) | 221 (4.3) | 449 (5.9) | <0.001 |
ACEi: angiotensin-converting enzyme inhibitors. ARB: angiotensin-receptor blockers. SAC/VAL: sacubitril/valsartan. BB: beta-blockers. MRA: mineralocorticoid receptor antagonists. SGLT2i: sodium-glucose co-transporter 2 inhibitors.
We found sex differences in the combination of different drugs. The most prevalent combination for women involved ACEi, ARB, BB and diuretics (13.3%) and for men, SAC/VAL, BB, MRA, SGLT2i and diuretics (8%). Fig. 2a and b shows the 20 most frequent HF treatment combinations prescribed by sex.
Drugs used for heart failure with reduced ejection fraction during October–December 2022. These figures depict the drugs alone and in combination in order of frequency, showing the 20 most frequent treatments; (a) in women and (b) in men. Pharmacological groups are shown on the left and the vertical bars show the frequency of unique or combined drugs. ACEi: angiotensin-converting enzyme inhibitors. ARB: angiotensin-receptor blockers. SAC/VAL: sacubitril/valsartan. BB: beta-blockers. MRA: mineralocorticoid receptor antagonists. SGLT2i: sodium-glucose co-transporter 2 inhibitors.
We also analyzed drug combinations by sex and NYHA in the population with registries (58.5%), grouping patients with NYHA I–II and III–IV, finding that the first most frequent one both in women and men and regardless of NYHA was ACEi or ARB with BB and diuretics. In men the second most frequent was all GDMT drugs along with diuretics, while in women they were BB with diuretics (Supplementary Figs. S1a–S1d).
When we analyzed the indicated drugs in the HF guidelines, sex differences emerged in the frequency of use of 4, 3, 2 or 1 drugs, as men received a higher number (Fig. 3a, b). Specifically, the combination of the four recommended drugs (SAC/VAL or ACEi or ARB+BB+MRA+SGLT2i) was prescribed in 11.9% of women vs 23% of men, whereas 25.2% of women received only one drug in comparison to 16.2% of the men, or 9% of women and 6.2% of men were not receiving any HF treatment. Further details on the possible drug combinations are described in Supplementary Table S2.
Use of the guideline-directed medical therapies for heart failure with reduced ejection fraction in women and men. These figures describe the percentage of use of 4, 3, 2 or 1 drug of those indicated per guidelines in HFrEF; (a) in women and (b) in men. ACEi: angiotensin-converting enzyme inhibitors. ARB: angiotensin-receptor blockers. SAC/VAL: sacubitril/valsartan. BB: beta-blockers. MRA: mineralocorticoid receptor antagonists. SGLT2i: sodium-glucose co-transporter 2 inhibitors.
Mean time of follow-up of the cohort was 2.7 years (mean 9829 days [SD 622.1]). During this time, the results of the Cox Proportional-Hazard model showed that women were more frequently admitted to hospital for HF (44.6% vs 42.1%, p=0.004). They also showed a higher rate of all-cause mortality (27.2% vs 25.3%, p=0.005).
When we estimated the HR of hospital admission (Fig. 4) we found an increasing risk with age for all age groups>60, a significantly increased risk for patients with NYHA II, III and IV, for those with previous HF-related hospitalization (HR 1.44, 95% CI 1.30–1.60) and for diabetic patients (HR 1.35, 95% CI 1.23–1.48).
Hazard ratios of hospital admission during the study period. This forest plot describes the HR for all the variables included in the model of hospital admission during the study period. NYHA: New York Heart Association functional classification. Model statistics: Concordance=0.601 (se=0.007). Likelihood ratio test=270.5 on 10 df, p=<2e−16. Wald test=278.5 on 10 df, p=<2e−16. Score (logrank) test=285.1 on 10 df, p=<2e−16.
We analyzed 17,169 patients with HFrEF in PHC over 5 years. We identified sex differences in sociodemographic and clinical variables and suboptimal GDMT use. Patients over 60, with advanced cardiac dysfunction, diabetes, or prior HF hospitalizations had a higher risk of HF-related hospitalizations.
Consistent with existing literature, our study reveals a predominantly male population, with women being older and more comorbid.4,8,9,17–20 IHD in men and hypertension both in women and men were frequent, aligning with established and predominant factors to HF etiology.21
Men received all HF drugs more frequently than women, except for digoxin and diuretics. This aligns with recent studies reporting lower use of key medications in women.19,22,23 In our study, more than half of women were over 80 years (vs. to one third of men) and consequently had more comorbidities and worst NYHA, and thus, they might present greater symptom burden, enforcing the chronic prescription of symptom-relief drugs such as diuretics.
As the cornerstone therapy for HFrEF includes the RAS modulation, BB, MRA, and SGLT2i,6 we would have expected most patients receiving all four drugs. Nevertheless, only 11.9% of women and 23% of men were receiving this quadruple therapy in our cohort, meaning that the use of the 4-drugs GDMT was not the most common treatment and women received it less frequently than men. A recent review reported underuse of GDMT in clinical practice, despite the strong evidence available.24 Also Sumarsono et al. and Celik et al. reported lower GDMT use in women than in men.19,23
Another study analyzed impact of GDMT on mortality, where 70% initiated GDMT during the first six months after diagnosis. Differences in the healthcare system or in the cohort composition should be considered.25 Stolfo et al. focused on SGLT2i, with a similar proportion to ours (37% vs 33.6%), increasing overtime (from 20.5% in 2021 to 59% in 2022, coinciding with the release of the European6 and American7 guidelines), and with sex differences.26
We could not determine why prescribers discontinued recommended drugs. Possible reasons could include age, adverse events, e.g. hypotension, contraindications, or some non-registered factors in the EHR.27,28 We did not know if the first election therapy were all four GDMT and if any of them had been discontinued due to any of these reasons, as we have analyzed HF treatment during the last trimester of the follow-up but not at diagnosis or longitudinally, also considering that we included patients at different stages of disease progression.
We also found different drug choices by sex when we analyzed drug combinations (Fig. 2a, b, and Supplementary Table S2). These results were similar when the analysis was restricted to patients with NYHA registers (Supplementary Figs. S1a–S1d). Underuse of drugs and lower adherence to recommendations in women have been previously described in HF29,30 and other cardiovascular conditions.31–37The observed sex disparities in hospitalization rates and all-cause mortality underscore the nuanced impact of HF management in our population. Celik et al. found higher rates of all-cause mortality and HF hospitalization in men and reduction of all-cause mortality with the four different drug combinations which included SGLT2i.23 Walli-Attaei et al. found higher all-cause mortality rates in men than in women, confirmed in the regression analysis, while found higher rates of HF hospitalization in women, although non-significant in the Cox regression,22 as in our study. Caution is needed when comparing these results due to population and follow-up differences. The less frequent use of GDMT in women coincides with a higher hospitalization rate, although the design of our study does not allow us to confirm this relationship and it is only a hypothesis that would need to be tested in future studies. Sex-specific differences prompt a deeper exploration into the underlying factors contributing to these outcomes.
Some limitations must be considered. Although HF diagnosis requires objective evidence of cardiac dysfunction, LVEF or NYHA were not routinely registered in all HF patients, hindering classification according to functionality and the assessment of treatment adequacy. This limitation has been previously described in our setting8,10 and other studies,27,28,38 as both measures are usually stored in the EHR non-structured data and are difficult to be captured by automated databases. Also the first LVEF registered showed disparities with the diagnoses of HFrEF coded, but we must consider that, apart from being stored in a non-structured manner, the time of both registers was not always coincident, with a mean of 1.1 year (386.6 days, SD 910.0) between LVEF register and HFrEF diagnosis.
The study also places some limitations due to the observational design, such as the potential unexamined confounding factors, missing values, missing variables or laboratory tests conducted in hospitals and thus not collected in our PHC-based database, like the plasma concentrations of natriuretic peptides, which are recommended as initial diagnostic tests in patients with symptoms suggestive of HF.6 Other limitations lack of registry of mortality causes and the treatment analysis focused on the last quarter of the study period. This can reflect the most current clinical updates, and these results would be put into context in the upcoming updated guidelines in Catalonia.39
We only have registers of sex in the database, but the decisions on treatment are usually gender-based. Sex and gender disparities in drug utilization patterns highlight potential areas for improvement in treatment equity, emphasizing the underuse of GDMT, particularly in women. Our findings underscore the importance of tailoring treatment strategies based on clinical conditions and of not making decisions on prescription based on gender.
Some strengths include long follow-up and the number of patients in real-world conditions in SIDIAP, which have previously demonstrated to be representative of the Catalan population.14
Our results should be considered hypothesis-generating due to their observational nature although they give us an insight into how treatment for HFrEF is used, helping clinicians in prescribing decision-making.
In conclusion, our study provides valuable insights into the real-world drug treatment of HFrEF. The predominant male proportion, coupled with older age and higher comorbidity rates among women, reflects the diverse clinical spectrum of HFrEF patients who are followed up in our PHC setting. Challenges related to non-routine registration of key cardiac function variables in EHR underscore the need for standardized data collection.
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Heart failure with reduced ejection fraction causes substantial morbidity and mortality, yet guideline-directed medical therapies remain underused in routine practice.
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Evidence suggests sex differences in heart failure with reduced ejection fraction presentation and management, but data from real-world Primary Care settings are scarce.
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In a large Primary Care cohort of 17,169 patients with heart failure with reduced ejection fraction, men were more frequently prescribed all four guideline-directed medical therapies, while women received fewer recommended therapies and had higher hospitalization and mortality rates.
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These findings reveal persistent sex disparities in heart failure with reduced ejection fraction management and highlight the need for personalized, equity-oriented treatment strategies in routine clinical practice.
The study protocol was approved by the Research Ethics Committee of IDIAPJGol (December 2022, project number 22/260-EOm).
This is a database research study which has been conducted according to the guidelines of the Declaration of Helsinki (Helsinki, Finland 2024) and does not require consent from the people included to participate.
The need for consent was waived by the Research Ethics Committee of IDIAPJGol as it is deemed unnecessary according to European legislation (Regulation [EU] 2016/679) and Spanish legislation (Ley Orgánica 3/2018, dated 6 December 2018, de Protección de Datos Personales y garantía de los derechos digitales).
AuthorshipConceptualization: MGS, RV, SFG, AV, RM. Data acquisition: MGS, RM. Data curation: RMon. Formal analysis: RMon. Funding acquisition: AV, RM. Investigation: all authors. Methodology: all authors. Project administration: MGS. Software: RMon. Resources: all authors. Supervision: MGS, AV, RM. Validation: all authors. Visualization: RMon. Writing – original draft: MGS. Writing – review and editing: all authors.
Use of AINo AI tools were used in the drafting of this manuscript.
FundingData were obtained by request of the Pharmacotherapeutic Harmonization Program of the Catalan Health Service, in the context of the agreement between IDIAPJGol and the Catalan Health Department for the Rational Use of Medicines’ Funding (FURM).
Conflict of interestThe authors have no relevant financial or non-financial interests to disclose.
Availability of data and materialsThe datasets generated and/or analyzed during the current study are not publicly available due to patient privacy and data protection concerns, but they are available from the corresponding author on reasonable request. All data generated or analyzed during this study are included in this published article and its supplementary information files.
The authors want to thank SIDIAP team for their work in maintaining the database and for their help in the data acquisition.
The followings are the supplementary data to this article:
