SCANDINAVIAN JOURNAL OF PRIMARY HEALTH CARE 2020, VOL. 38, NO. 4, 473–480 https://doi.org/10.1080/02813432.2020.1844387 RESEARCH ARTICLE Precipitating factors of heart failure decompensation, short-term morbidity and mortality in patients attended in primary care Jos e Marıa Verdu-Rotellara,b,c, Helene Vaillant-Rousseld, Rosa Abellanae, Lea Gril Jevsekf, Radost Assenovag, Djurdjica Kasuba Lazich, Peter Torszai, Liam George Glynnj, Heidrun Lingnerk, Jacopo Demurtasl, Beata Borgstro€mm, Sylvaine Gibot-Boeufd and Miguel Angel Mun ~oza,b,c a Institut Catala de la Salut, Barcelona, Spain; bUnitat de Suport a la Recerca de Barcelona, Fundacio Institut Universitari per a la recerca a l’Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain; cSchool of Medicine, Universitat Autonoma de Barcelona, Bellaterra, Spain; dDepartment of General Practice, Clermont Auvergne University, Faculty of Medicine, UPU ACCePPT, Clermont-Ferrand, France; eDepartament de Fonaments Clinics, Facultat de Medicina, Universitat de Barcelona, Barcelona, Spain; f Medical Faculty, University of Maribor, Maribor, Slovenia; gSchool of Medicine, Medical University of Plovdiv, Plovdiv, Bulgaria; h Department of Family Medicine ‘Andrija Stampar’ School of Public Health, School of Medicine University of Zagreb, Zagreb, Croatia; i School of Medicine, Semmelweis University, Budapest, Hungary; jHealth Research Institute and Graduate Entry Medical School, University of Limerick, Limerick, Ireland; kHannover Medical School, Center for Public Health and Healthcare, Hannover, Germany; l Primary Care Department, Azienda Usl Toscana Sud Est, Grosseto, Italy; mDepartment of Clinical Sciences, Lund University, Malm€o, Sweden ABSTRACT ARTICLE HISTORY Objective: To evaluate the precipitating factors for heart failure decompensation in primary Received 2 February 2020 care and associations with short-term prognosis. Design Prospective cohort study with a 30-d Accepted 29 August 2020 follow-up from an index consultation. Regression models to determine independent factors KEYWORDS associated with hospitalisation or death. Heart failure; Setting: Primary care in ten European countries. Patients Patients with diagnosis of heart failure decompensation; precipitat- attended in primary care for a heart failure decompensation (increase of dyspnoea, unexplained ing factors; primary care weight gain or peripheral oedema). Main outcome measures: Potential precipitating factors for decompensation of heart failure and their association with the event of hospitalisation or mortality 30 d after a decompensation. Results: Of 692 patients 54% were women, mean age 81 (standard deviation [SD] 8.9) years; mean left ventricular ejection fraction (LVEF) 55% (SD 12%). Most frequently identified heart fail- ure precipitation factors were respiratory infections in 194 patients (28%), non-compliance of dietary recommendations in 184 (27%) and non-compliance with pharmacological treatment in 157 (23%). The two strongest precipitating factors to predict 30 d hospitalisation or death were respiratory infections (odds ratio [OR] 2.8, 95% confidence interval [CI] (2.4–3.4)) and atrial fibril- lation (AF) > 110 beats/min (OR 2.2, CI 1.5–3.2). Multivariate analysis confirmed the association between the following variables and hospitalisation/death: In relation to precipitating factors: respiratory infection (OR 1.19, 95% CI 1.14–1.25) and AF with heart rate > 110 beats/min (OR 1.22, 95% CI 1.10–1.35); and regarding patient characteristics: New York Heart Association (NYHA) III or IV (OR 1.22, 95% CI 1.15–1.29); previous hospitalisation (OR 1.15, 95% CI 1.11–1.19); and LVEF < 40% (OR 1.14, 95% CI 1.09–1.19). Conclusions: In primary care, respiratory infections and rapid AF are the most important precipi- tating factors for hospitalisation and death within 30 d following an episode of heart failure decompensation. KEY POINTS  Hospitalisation due to heart failure decompensation represents the highest share of health- care costs for this disease.  So far, no primary care studies have analysed the relationship between precipitating factors and short term prognosis of heart failure decompensation episodes.  We found that in 692 patients with heart failure decompensation in primary care, the respira- tory infection and rapid atrial fibrillation (AF) increased the risk of short-term hospital admis- sion or death.  Patients with a hospital admission the previous year and a decompensation episode caused by respiratory infection were even more likely to be hospitalized or die within 30 d. CONTACT Jose Marıa Verdu-Rotellar verdujm@gmail.com Departament de Salut, Unitat de Suport a la Recerca, Gerencia Territorial de Barcelona, Institut Catala de la Salut-IDIAP Jordi Gol, j Generalitat de Catalunya Carrer Sardenya, 375 Entlo, Barcelona 08025, Spain ß 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 474 J. M. VERDU-ROTELLAR ET AL. Introduction involved in heart failure decompensation in primary care. In addition, it aims to create a predictive prog- Heart failure is a chronic disease that affects approxi- nostic model in heart failure patients suffering from a mately 1–2% of the population [1]. Its prevalence is decompensation episode. increasing due to an aging population and therapeutic The study was originally designed in Spain where a advances, among other factors [2]. The epidemio- pilot study was carried out to test feasibility. Initially, logical dimension of heart failure, its clinical complex- 30 patients who had presented 13 events in one pri- ity and impact on patients’ quality of life all constitute mary healthcare centre were recruited. a challenge for healthcare professionals. Moreover, the The protocol was presented in a meeting of the financial burden that it represents for a health system European General Practice Research Network where with limited resources makes this disease one of the family doctors from nine countries agreed to collabor- greatest health, organisational and economic issues ate. The European investigators then gathered in order facing medical services globally [3]. Heart failure pro- to standardise the methodological procedures and gression is characterised by increasingly frequent epi- extend the study to different countries. The study sodes of decompensation that often require hospitalisation [4], the greatest contributor to health- protocol was written in English with funding for trans- care costs attributed to this disease [1,3]. There are a lations to other languages. number of precipitating factors that can cause an epi- Patients registered as having heart failure (accord- sode of heart failure decompensation. The most fre- ing to the European Society of Cardiology criteria) [11] quent are respiratory infection, transgression in dietary and attended in primary care centres, or managed by recommendations, non-compliance with pharmaco- primary care physicians in home care, because of logical treatment, hypertension and cardiac arrhyth- heart failure decompensation, were consecutively mias. Up to two thirds of these are avoidable, and recruited in ten European countries. Recruitment was timely identification could both improve disease man- performed by 117 primary care physicians and nurses agement and reduce associated costs [5,6]. On aver- in Spain (72), France (12), Ireland (1), Germany (2), Italy age, heart failure patients attend their primary care (6), Slovenia (4), Croatia (16), Bulgaria (8), Hungary (1) centres more than 25 times a year, and their decom- and Sweden (3). Heart failure decompensation was pensations are often initially treated in these units [1]. considered as such when the patient presented any of In addition, primary care patients present greater the following: increase of dyspnoea, unexplained comorbidity, the consultations and prescriptions gen- weight gain or appearance/increase of periph- erally including more than one pathology [7]. Most of eral oedema. those acutely admitted to hospital for common severe Data on the following were collected: age, sex and emergency diagnoses have been in contact with their comorbidity including hypertension, diabetes mellitus, family doctors during the month and year prior to hypercholesterolemia, ischemic heart disease, perman- admission [8]. All of the above, highlights the key role ent atrial fibrillation (AF), chronic renal failure and family doctors play in the care of such individuals. stroke. New York Heart Association (NYHA) functional There is, however, a lack of information regarding pre- class, time from commencement of symptoms until cipitating factors in the prognosis of patients treated primary care consultation, hospitalisation due to heart for heart failure decompensation in primary care. failure in the year prior to decompensation, left ven- Evidence concerning the impact of such factors on tricular ejection fraction (LVEF) and precipitating fac- decompensation episodes, mortality and hospital- tors were also assessed. admissions is largely based on data collected in hos- The following precipitating factors were taken into pital emergency rooms [9,10]. consideration if they appeared concomitantly with The objective of this study was, therefore, to iden- decompensation: tify the most frequent decompensation precipitating factors and analyse their association with short-term  Dietary transgression: if the patient reported liquid prognosis defined as hospitalisation/death within 30 d intake of more than 2.5 l a day and/or added salt from an index consultation date. to the food.  Respiratory infection. Diagnosis was made by clin- ical exploration and confirmed in the med- Methods ical records. The HEFESTOS is an international prospective cohort  Non-compliance with pharmacological treatment study focused on identifying the precipitating factors (self-reported). SCANDINAVIAN JOURNAL OF PRIMARY HEALTH CARE 475  AF with a frequency > 110 beats per minute (bpm) independent groups. Binary logistic regression analy- requiring treatment or emergency referral. ses were used to investigate the effect of the charac-  Other infections: signs and symptoms of infections teristics of patients and precipitating factors in the other than respiratory ones. primary outcome. Variables significantly (p < .05) asso-  Cardiac ischemia: clinical and electrocardiographic ciated with the primary outcome in the bivariate ana- signs of ischaemia that required changes in treat- lysis were included as potential covariates in logistic ment or emergency referral. regression models. Analyses were performed using R  Intake of drugs associated with heart failure project version 3.6.0 (R Foundation for Statistical decompensation: non-steroidal anti-inflammatory Computing, Vienna, Austria) [12]. drugs, effervescent tablets, corticosteroids, tricyclic antidepressants. Results  Other precipitants: anaemia, worsening of renal function, hypertensive crisis, changes in diur- Between August 2015 and December 2018, a total of etic treatment. 692 patients from ten countries were included. Women represented 55% of the participants and The primary outcomes were hospitalisation due to mean age was 81.2 (SD 8.90) years. Mean LVEF was cardiovascular causes and/or mortality from any cause 55% (SD 12%). The average time between consultation in the 30 d following the index consultation date. They and onset of symptoms was 9.1 d (SD 9.1). were verified through consulting medical records and/ Among the 692 patients evaluated, 195 (28%) were or by phone. hospitalised and 24 (3.5%) died during the first month following the decompensation episode. Table 1 describes the characteristics of patients according to Statistical analyses the presence/absence of primary outcome. Categorical data are expressed using frequencies and At least one precipitating factor was identified in percentages, while continuous data are expressed 156 (78%) of the 200 events, only one in 84 events using means and standard deviations (SD). A chi- (42%), two in 45 events (22%) and three or more in 27 square test was used to compare data when it was events (14%). The most frequently identified precipi- categorical. A Student’s t-test was used for tating factors were: respiratory infection (28%), Table 1. Baseline characteristics in the study population. Total No hospitalisation/death at 30 d Hospitalisation/death at 30 d N ¼ 692 N ¼ 492 N ¼ 200 N (%) N (%) N (%) p Value Sex: Men 315 (45.5) 221 (44.9) 94 (47.0) Ref. Women 377 (54.5) 271 (55.1) 106 (53.0) .437 Age, yearsa 81.2 (8.9) 81.2 (8.92) 81.2 (8.87) .818 Body mass index, kg/m2a 30.3 (6.3) 30.3 (6.35) 30.5 (6.20) .900 Diabetes mellitus 309 (44.7) 209 (42.6) 100 (50.0) <.001 Cardiac ischaemia 263 (38.2) 187 (38.2) 76 (38.0) .939 Chronic or paroxysmal atrial fibrillation 387 (56.1) 273 (55.7) 114 (57.0) .821 Stroke 96 (13.9) 71 (14.5) 25 (12.5) .296 Chronic renal disease 292 (42.3) 201 (41.0) 91 (45.5) .148 Smoker 68 (9.90) 51 (10.5) 17 (8.50) .147 Chronic obstructive pulmonary disease 204 (29.6) 135 (27.6) 69 (34.5) .013 Hypertension 584 (88.8) 413 (88.2) 171 (90.0) .056 Dyslipidaemia 373 (56.9) 255 (54.7) 118 (62.1) <.001 NHYAb <.001 I or II 188 (27.2) 163 (33.3) 25 (12.5) – III or IV 502 (72.8) 327 (66.7) 175 (87.5) – Hospital admission last year due to heart failure 175 (25.4) 105 (21.4) 70 (35.4) <.001 Ejection fraction > ¼ 50% 376 (73.4) 277 (77.2) 99 (64.7) Ref. 40–49% 58 (11.3) 38 (10.6) 20 (13.1) .109 < ¼ 39% 78 (15.2) 44 (12.3) 34 (22.2) .000 unknown 180 (26.0) 133 (27.0) 47 (23.5) .154 ACE inhibitor/ARB 513 (74.9) 351 (71.9) 162 (82.2) <.001 Betablockers 469 (68.4) 325 (66.5) 144 (73.1) .215 Aldosterone antagonist 156 (22.9) 103 (21.2) 53 (27.0) <.001 Loop diuretics 499 (73.0) 345 (71.0) 154 (77.8) .068 a Mean (standard deviation). b NHYA: New York Heart Association functional class. 476 J. M. VERDU-ROTELLAR ET AL. Table 2. Precipitating factors in the study population. Total No hospitalisation/death at 30 d Hospitalisation/death at 30 d N ¼ 692 N ¼ 492 N ¼ 200 N (%) N (%) N (%) p Value Respiratory infection one week before 194 (28.2) 106 (21.7) 88 (44.0) <.001 Non-compliance with drug treatment 157 (22.8) 116 (23.7) 41 (20.7) .261 Use of NSAIDa, corticosteroids and tricyclic antidepressants 85 (12.4) 64 (13.1) 21 (10.6) .524 Other infection one week before 49 (7.1) 31 (6.3) 18 (9.0) .234 Atrial fibrillation at rate > 110 bpm 100 (14.5) 58 (11.8) 42 (21.0) <.001 Non-compliance with dietb 184 (26.8) 148 (30.3) 36 (18.2) <.001 Other arrhythmias 22 (3.1) 16 (3.2) 6 (3.0) .984 Cardiac ischaemia 37 (5.3) 22 (4.4) 15 (7.5 ) .280 Anaemia 40 (5.8) 26 (5.3) 14 (7.0) .380 a NSAID: non-steroidal anti-inflammatory drugs. b Liquid intake of more than 2.5 l a day and/or added salt to the food. transgression of dietary recommendations (27%) and reduced the probability of an adverse event, although non-compliance with pharmacological treatment only in those who had not been previously hospital- (23%). Table 2 describes the precipitating according to ised (OR 0.40, 95% CI 0.28; 0.58) (Table 4). the presence/absence of primary outcome. In univariate analysis, patients suffering from a Discussion respiratory infection, or AF with a heart rate >110 beats/min, had a significantly higher probability of Statement of principal findings hospitalisation/death (OR 2.84, 95% CI 2.39–3.38) and Among the 692 patients from ten European countries (OR 2.17, 95% CI 1.49–3.16), respectively. In contrast, presenting an episode of heart failure decompensation patients with dietary transgression had a lower prob- in primary care, in more than three out of four cases ability of hospitalisation/death (OR 0.51, 95% CI at least one precipitating factor was identified, the 0.36–0.74). Regardless of the characteristics of patients; most frequent being respiratory infection. In addition, patients hospitalised during the previous year, pre- respiratory infection and rapid AF were associated senting a history of diabetes mellitus, chronic with a high probability hospitalisation/death within obstructive pulmonary disease (COPD), hypercholester- 30 d which occurred in 29% of the decompensa- olemia, LVEF < 40% or functional stage NYHA III or IV, treatment with ACE/or aldosterone antagonist had a tion episodes. higher probability of hospitalisation/death in the first 30 d following the episode (Table 3). Strengths and limitations A multivariate analysis including underlying patient A major strength of this study is its prospective cohort characteristics confirmed the association between the design and international perspective (patients were following variables and hospitalisation/death. With recruited from ten European countries). A selection respect to precipitating factors: respiratory infection (OR 1.19, 95% CI 1.14–1.25) and AF with heart rate bias, however, could have occurred since the more >110 beats/min (OR 1.22, 95% CI 1.10–1.35); and in severely ill subjects might have been identified. relation to patient characteristics: NYHA III or IV (OR Nevertheless, the primary care physicians responsible 1.22, 95% CI 1.15–1.29); previous hospitalisation (OR for recruitment were instructed to consecutively 1.15, 95% CI 1.11–1.19); and LVEF < 40% (OR 1.14, include any patient with decompensated heart failure. 95% CI 1.09–1.19) (Table 3). Due to the low percentage of patients who died we These variables, with and without hospitalisation could not analyse hospitalisation and death separately, for heart failure the year before the consultation, were consequently the main outcome was a combination analysed separately, including interactions in the of both. multivariate model. It was observed that hospitalisa- Some studies [13] have shown that in primary care tion in the previous year due to heart failure inter- there is up to a third of heart failure overdiagnosis. To acted with respiratory infection and dietary avoid such an issue, researchers were urged to only transgression. The probability of hospitalisation/death include patients who strictly met the clinical and echo- from an episode precipitated by respiratory infection cardiographic criteria of the current European guide- was much greater if there had been a previous hospi- lines, despite the fact that 26% presented unknown talisation (OR 7.20, 95% CI 5.61; 9.25) than if there had LVEF, a proportion very similar to other studies in pri- not (OR 2.10, 95% CI 1.75; 2.53). Dietary transgression mary care [13,14]. SCANDINAVIAN JOURNAL OF PRIMARY HEALTH CARE 477 Table 3. Patient characteristics and precipitating factors predicting hospitalisation/death at 30 d in heart failure patients after an episode of decompensation. Hospitalisation/death at 30 d Hospitalisation/death at 30 d Total N ¼ 692 Univariate odds ratio [95% Multivariate odds ratio [95% N (%) confidence interval] confidence interval] Patient characteristics Sex: Men 315 (45.5) 1 (Ref.) 1 (Ref.) Women 377 (54.5) 0.91 [0.70; 1.16] 0.99 [0.96; 1.03] Age, yearsa 81.2 (8.9) 1.00 [0.98; 1.01] 0.99 [0.99; 1.00] No diabetes mellitus 383 (55.3) 1 (Ref.) Diabetes mellitus 309 (44.7) 1.32 [1.14; 1.54] No chronic obstructive 488 (70.4) 1 (Ref.) pulmonary disease Chronic obstructive 204 (29.6) 1.37 [1.07; 1.74] pulmonary disease No dyslipidaemia 319 (43.1) 1 (Ref.) Dyslipidaemia 373 (56.9) 1.38 [1.21; 1.58] NHYA:b I or II 188 (27.2) 1 (Ref.) 1 (Ref.) III or IV 502 (72.8) 3.49 [2.36; 5.14] 1.22 [1.14; 1.29] No hospital admission last year due 517 (74.6) 1 (Ref.) 1 (Ref.) to heart failure Hospital admission last year due to 175 (25.4) 2.13 [1.76; 2.57] 1.15 [1.11; 1.19] heart failure Ejection fraction > ¼ 50% 376 (73.4) 1 (Ref.) 1 (Ref.) 40–49% 58 (11.3) 1.46 [0.92; 2.31] 1.06 [0.98; 1.15] < ¼ 39% 78 (15.2) 2.14 [1.73; 2.65] 1.14 [1.09; 1.20] Unknown 180 (26.0) 1.29 [0.91; 1.84] 1.06 [0.99; 1.14] No ACE inhibitor/ARA2 179 (25.1) 1 (Ref.) ACE inhibitor/ARA2 513 (74.9) 1.87 [1.50; 2.34] No aldosterone antagonist 179 (77.1) 1 (Ref.) Aldosterone antagonist 156 (22.9) 1.38 [1.18; 1,60] Precipitating factors No respiratory infection one 498 (71.8) 1 (Ref.) 1 (Ref.) week before Respiratory infection one 194 (28.2) 2.84 [2.39; 3.38] 1.19 [1.14; 1.25] week before No atrial fibrillation at rate > 592 (85.5) 1 (Ref.) 1 (Ref.) 110 bpm Atrial fibrillation at rate > 110 bpm 100 (14.5) 2.17 [1.49; 3.16] 1.22 [1.09; 1.35] Compliance diet 508 (73.2) 1 (Ref.) 1 (Ref.) Non-compliance dietc 184 (26.8) 0.51 [0.36; 0.74] 0.90 [0.85; 0.96] a Mean (standard deviation). b NHYA: New York Heart Association functional class. c Liquid intake of more than 2.5 l a day and/or added salt to the food. Table 4. Predictors of hospitalisation or death at 30 d in heart failure patients after an episode of decompensation and heart failure hospital admission last year. No hospital admission last year due to Hospital admission last year due to heart failure heart failure Hospitalisation/death at 30 d Hospitalisation/death at 30 d Multivariate odds ratio [95% confidence interval] Multivariate odds ratio [95% confidence interval] odds ratio odds ratio [95% confidence interval] [95% confidence interval] Sex: Men Ref. Ref. Women 0.70 [0.49; 1.00] 1.07 [0.83; 1.36] Age, yearsa 1.04 [1.01; 1.06] 0.99 [0.98; 1.00] NHYAb I or II Ref. Ref. III or IV 5.11 [2.80; 9.34] 2.83 [1.63; 4.93] Ejection fraction > ¼ 50% Ref. Ref. 40–49% 1.43 [0954; 2.15] 1.52 [0.84; 2.72] < ¼ 39% 2.19 [1.09; 4.42] 2.07 [1.84; 2.33] unknown 1.15 [0.82; 1.63] 1.00 [0.55; 1.82] Respiratory infection one week before 7.20 [5.61; 9.25] 2.10 [1.75; 2.53] Non-compliance with dietc 0.78 [0.56; 1.10] 0.40 [0.28; 0.58] a Mean (standard deviation). b NHYA: New York Heart Association functional class. c Liquid intake of more than 2.5 l a day and/or added salt to the food. 478 J. M. VERDU-ROTELLAR ET AL. A major limitation is not having determined the associated with a lack of knowledge about daily intake natriuretic peptides due to their low availability in pri- of liquids and salt, as well as the unanticipated mary care; even though NT-proBNP has a prognostic sodium content of certain foods and drugs. Real intake value in heart failure patients with an ejection fraction could be underestimated, given that its detection is  40%. Clinical use is, however, limited as a result of usually based on information received from the large SDs, many co-morbidities and greater age [15]. patients or their relatives [20]. Appropriate questioning on salt intake by primary healthcare professionals might present an opportunity to initiate educational Findings in relation to other studies and preventive measures in this regard. To the best of our knowledge, this is the first study to AF is also often related to heart failure decompen- analyse the role of precipitating factors in heart failure sation [16,17,21]. Fast and irregular heart rate, loss of decompensation in primary care. Compared to previ- atrioventricular synchrony, and decrease in the contri- ous similar studies, there was a greater proportion of bution of atrial contraction to ventricular filling make women, higher comorbidity and a larger percentage AF a frequent trigger for decompensation [21]. In our presenting preserved ejection fraction which we attri- study, AF was identified as a possible precipitating fac- bute to the higher average age of our population tor in 14% of cases, a percentage slightly lower than [13,14,16–23]. The ratio of ACE/ARB, betablockers and that described by other authors [17,21]. The propor- aldosterone-antagonist patients were similar to other tion of patients with ischemic heart disease and studies carried out in primary care [13,14]. hypertensive emergency that we observed in was also The percentage of patients with a precipitating fac- lower than in other work. This could be related to a tor is within the range described by other authors selection bias associated with patients from hospital (between 60 and 98%) [16–20,22,23]. We found more emergency rooms where a greater severity of illness is than one precipitating factors in more than one third expected than in those attended in primary care. of cases, similar to Formiga et al. [17]. Given the cur- In our study, we considered the use of non-indi- rent variability among publications [16], the identifica- cated/contraindicated medications as a possible cause tion of preventable precipitating factors should be of decompensation, an issue which was not men- systematically assessed, as recommended in the tioned in the Standardised reporting criteria [24]. Standardised reporting criteria [24]. In our case, we Only a few studies have analysed the role of precip- evaluated all the precipitating factors recommended itating factors in the prognosis of heart failure in this document, and we added those which seemed [9,10,22,23]. We observed a 30-d mortality rate of to be relevant from a primary care point of view, such 3.5%, lower than figures from hospital emergency as the use of detrimental drugs. rooms and cardiology and internal medicine hospital- The role of respiratory infection in heart failure isation units, where it ranged from 6 to 15%. The decompensation has also been identified mainly in same trend was found regarding hospitalisations, studies undertaken in hospital emergency rooms and which in our case did not arrive at 30%. Nevertheless, internal medicine units [9,10,17–19,25]. Infections can patients treated for decompensation in emergency produce a tachycardia secondary to fever which may room services reached almost 70%, possibly because shorten diastole and produce an increase in oxygen there are more hospitalisations than referrals or demand, particularly in susceptible subjects, such as because those in the emergency rooms have a more those with COPD [25]. An observation confirmed in severe condition. our study where there was a higher number of events Regarding comorbidity and decompensation short- associated with respiratory infections. term prognosis, in the univariate analysis the presence We detected that the probability of hospitalisation/ of diabetes mellitus and COPD was related to a death after a respiratory infection was even greater greater probability of admission/death. This relation- when patients had been admitted to hospital in the pre- ship however, was lost when performing the multivari- vious year, which is consistent with other authors [1]. ate analysis. The presence of these two conditions has Such finding could be explained by the fact that follow- been related to the long-term prognosis of heart fail- ing hospitalisation the previous functional level was not ure, particularly with ejection fraction [26], neverthe- fully attained, and the patients’ frailty thus increased. less, at short term other factors, such as precipitants Dietary transgression has also been commonly may play a greater role. described as a precipitating factor for heart failure One of the most striking findings of the study was decompensation [16]. Non-compliance is often that patients in whom dietary transgression had been SCANDINAVIAN JOURNAL OF PRIMARY HEALTH CARE 479 identified had a lower probability of being hospitalised References or dying. A lower probability that was not observed in [1] Farre N, Vela E, Cleries M, et al. Real world heart fail- those who had been hospitalised for heart failure in ure epidemiology and outcome: a population-based the previous year. A number of studies have reported analysis of 88,195 patients. PLoS One. 2017;12(2): that a dietary sodium restriction < 2 g/d provides ben- e0172745. efits only in more advanced stages, and is neutral or [2] Heidenreich PA, Albert NM, Allen LA, et al. Forecasting the impact of Heart Failure in the United even harmful in milder stages which could partly States: a policy statement from the American Heart explain our results [27]. Another possibility might be Association. Circ Heart Fail. 2013;6(3):606–619. that some patients could have been misdiagnosed as [3] Farre N, Vela E, Cleries M, et al. Medical resource use heart failure, and they did not follow dietary restrictive and expenditure in patients with chronic Heart Failure: a population-based analysis of 88 195 recommendations. patients. Eur J Heart Fail. 2016;18(9):1132–1140. [4] Goodlin SJ. Palliative care in congestive Heart Failure. J Am Coll Cardiol. 2009;54(5):386–396. Meaning of the study [5] Michalsen A, Ko €nig G, Thimme W. Preventable causa- tive factors leading to hospital admission with In a primary care study from 10 European countries, decompensated Heart Failure. Heart. 1998;80(5): we identified respiratory infections and rapid AF as 437–441. the most important precipitating factors for hospital- [6] Aramburu O, Conde A, Salamanca P. Insuficiencia car- diaca aguda: factores desencadenantes y prevencio n. isation and death within 30 d following an episode of Med Clin. Barc. 2014;142(1):S9–S13. heart failure decompensation. [7] Grimsmo A, Løhre A, Røsstad T, et al. Disease-specific Patients with a hospital admission the previous clinical pathways – are they feasible in primary care? year, and a decompensation episode caused by A mixed-methods study. Scand J Prim Health Care. respiratory infection, were even more likely to be hos- 2018;36(2):152–160. [8] Skarshaug LJ, Svedahl ER, Bjørngaard JH, et al. pitalised or die within 30 d. Contact with primary health care physicians before an acute hospitalisation. Scand J Prim Health Care. 2019; 37(3):283–293. Acknowledgements [9] Aguirre A, Miro O, Jacob A, et al. Papel del factor pre- cipitante de un episodio de insuficiencia cardiaca Authors are grateful to the contribution of Dr Hans aguda en relacio n al prono stico a corto plazo del Thulesius in reviewing the final version of the manuscript. paciente: estudio PAPRICA. Emergencias. 2012;24: 438–446. [10] Miro O, Aguirre A, Herrero P, et al. PAPRICA-2 study: Ethical approval role of precipitating factor of an acute heart failure episode on intermediate term prognosis]. Med Clin. The study protocol was approved by the corresponding local 2015;145(9):385–389. or regional ethics committees in each participating country. [11] Ponikowski P, Voors AA, Anker SD, et al. 2016 ESC All participating patients signed an informed consent form. guidelines for the diagnosis and treatment of acute and chronic Heart failure: the task force for the diag- nosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Disclosure statement Developed with the special contribution of the Heart No potential conflict of interest was reported by Failure Association (HFA) of the ESC. Eur J Heart Fail. the author(s). 2016;18(8):891–975. [12] R Development Core Team. R: a language and envir- onment for statistical computing. Vienna, Austria: R Funding Foundation for Statistical Computing; 2008. ISBN 3- 900051-07-0. Available from: http://www.R-project.org The project received a research grant from the Carlos III [13] Valk MJ, Mosterd A, Broekhuizen BD, et al. Institute of Health, Ministry of Economy and Overdiagnosis of heart failure in primary care: a cross- Competitiveness (Spain), awarded on the 2014 call under sectional study. Br J Gen Pract. 2016;66(649): the Health Strategy Action 2013-2016, within the National e587–e592. Research Program oriented to Societal Challenges, within [14] Giezeman M, Arne M, Theander K. Adherence to the Technical, Scientific and Innovation Research National guidelines in patients with chronic heart failure in pri- Plan 2013–2016, with reference PI14/00583, co-funded with mary health care. Scand J Prim Health Care. 2017; European Union ERDF funds. The European General Practice 35(4):336–343. Research Network (EGPRN) supported this project (ref HP/ [15] Eriksson B, W€andell P, Dahlstro €m U, et al. Limited 2015.036. Year 2015). value of NT-proBNP as a prognostic marker of 480 J. M. VERDU-ROTELLAR ET AL. all-cause mortality in patients with heart failure with [22] Dıaz A, Ciocchini C, Esperatti M, et al. Precipitating preserved and mid-range ejection fraction in primary factors leading to decompensation of chronic Heart care: a report from the Swedish heart failure register. Failure in the elderly patient in South-American com- Scand J Primary Health Care. 2019;37(4):434–443. munity hospital. J Geriatr Cardiol. 2011;8:12–14. [16] Aguirre Tejedo A, Miro O. Prevalencia de factores pre- [23] Domınguez JP, Harriague CM, Garcıa-Rojas I, et al. cipitantes de insuficiencia cardiaca aguda y su Insuficiencia cardiaca aguda en pacientes de 70 an ~os impacto prono stico: una revisio  n sistematica. o mas: factores precipitantes de descompensacio n. Emergencias. 2017;29:185–193. Rev Clin Esp. 2010;210(10):497–504. [17] Formiga F, Chivite D, Manito N, et al. Hospitalization [24] Storrow AB, Lindsell CJ, Collins SP, et al. Standardized due to acute Heart Failure. Role of the precipitating reporting criteria for studies evaluating suspected factors. Int J Cardiol. 2007;120(2):237–241. acute Heart Failure syndromes in the emergency [18] Opasich C, Rapezzi C, Lucci D, et al. Precipitating fac- department. J Am Coll Cardiol. 2012;60(9):822–832. tors and decision-making processes of short-term [25] Corrales-Medina VF, Jun KN, Rose G, et al. Cardiac worsening Heart Failure despite “optimal” treatment complications in patients with community-acquired (from the INC heart failure registry). Am J Cardiol. pneumonia: a systematic review and meta-analysis of 2001;88(4):382–387. observational studies. PLoS Med. 2011; 8(6):e1001048. [19] Nieminen MS, Brutsaert D, Dickstein K, et al. Euro [26] Eriksson B, W€andell P, Dahlstro €m U, et al. Heart Failure Survey II (EHFS II): a survey on hospital- Comorbidities, risk factors and outcomes in patients ized acute heart failure patients: description of popu- with heart failure and an ejection fraction of more lation. Eur Heart J. 2006;27(22):2725–2736. than or equal to 40% in primary care- and hospital [20] Tsuyuki RT, McKelvie RS, Arnold JM, et al. Acute pre- care-based outpatient clinics. Scand J Primary Health cipitants of congestive Heart Failure exacerbations. Care. 2018;36(2):207–215. Arch Intern Med. 2001;22:2337–2342. [27] Song EK, Moser DK, Dunbar SB, et al. Dietary sodium [21] Smit MD, Moes ML, Maass AH, et al. The importance restriction below 2 g per day predicted shorter event- of whether atrial fibrillation or Heart Failure develops free survival in patients with mild heart failure. Eur J first. Eur J Heart Fail. 2012;14(9):1030–1040. Cardiovasc Nurs. 2014;13(6):541–548.