Precipitating factors and decision-making processes of short-term worsening heart failure despite “optimal” treatment (from the IN-CHF Registry)

Precipitating Factors and DecisionMaking Processes of Short-Term Worsening Heart Failure Despite “Optimal” Treatment (from the IN-CHF Registry) Cristina Opasich, MD, Claudio Rapezzi, MD, Donata Lucci, MS, Marco Gorini, Francesco Pozzar, MD, Emanuela Zanelli, MD, Luigi Tavazzi, MD, and Aldo P. Maggioni, MD, on behalf of the Italian Network on Congestive Heart Failure (IN-CHF) Investigators*

MS,

This study sought to prospectively assess which factors were related to short-term worsening heart failure (HF) leading to or not to hospital admission, in long-term outpatients followed by cardiologists. The subsequent decision-making process was also analyzed. The study population consisted of 2,701 outpatients enrolled in the registry of the Italian Network on Congestive Heart Failure (IN-CHF) and followed by 133 cardiology centers (19% of all existing Italian cardiology centers). Clinical and follow-up data were collected by local trained clinicians; 215 patients (8%) had short-term decompensation (on average 2 months after the index outpatient visit). Multivariate analysis showed that previous hospitalization, long duration of symptoms, ischemic etiology, atrial fibrillation, higher functional class (New York Heart Association classification III to IV), higher heart rate, and low systolic blood pressure were independently associated with HF destabilization. Poor compli-

ance (21%) and infection (12%) were the most frequent precipitating factors, but a precipitating factor was not identified in 40% of the patients. Poor compliance was more common in women, but no other clinical characteristics emerged as being related with a specific precipitating factor. Fifty-seven percent of the patients with a short-term recurrence of worsening HF required hospital admission; infusion treatment with inotropes and/or vasodilators was necessary in 19% of them. Long-term therapy was changed in 48% of the patients. Thus, in ambulatory HF patients, short-term worsening HF can be predicted according to the clinical characteristics on an outpatient basis. Nearly 1/3 of precipitating factors can be prevented. Patient education and avoidance of inappropriate treatment may reduce the number of relapses. 䊚2001 by Excerpta Medica, Inc. (Am J Cardiol 2001;88:382–387)

ecently, there has been a focus on prevention of heart failure (HF) recurrences R and the official HF guidelines suggest comprehensive (pharmacologic

HF outpatients is actually scarce. The aims of this study were: (1) to prospectively evaluate the occurrence of short-term worsening HF, leading to or not to hospital admission, and the respective concomitant and/or precipitating factors in consecutive long-term outpatients with HF, who were closely followed by cardiologists involved in the Italian-Network on Congestive Heart Failure (IN-CHF); (2) to identify which patients are more likely to experience early decompensation; (3) to determine whether some of the concomitant factors are predictable from clinical variables, and potentially preventable; and (4) to evaluate the physician decision-making process after destabilization.

1–11

and nonpharmacologic) management programs for reducing relapses and subsequent hospital admissions.12–14 However, published studies generally recruit patients at the end of an episode of hospitalization and address only decompensations leading to a repeated hospital admission, so that information on From the S. Maugeri Foundation, Institute of Care and Scientific Research, Cardiology Division, Pavia; Institute of Cardiology, University of Bologna, Bologna; ANMCO Research Center, Florence; S. Camillo Hospital, Cardiology Department, Roma; S. Maugeri Foundation, Institute of Care and Scientific Research, Cardiology Division, Gussago; and S. Matteo Hospital, Institute of Care and Scientific Research, Department of Cardiology, Pavia, Italy. This study was supported in part by Merck Sharp & Dohme, Rome, Italy. Manuscript received December 20, 2000; revised manuscript received and accepted March 16, 2001. Address for reprints: Cristina Opasich, MD, ANMCO Research Center, Associazione Nazionale Medici Cardiologi Ospedalieri, Via La Marmora, 34-50121 Firenze, Italy. E-mail: [email protected]. *See the Appendix for a complete list of participating Centers and Investigators.

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METHODS From March 1995 to January 1999, data from 8,102 consecutive outpatients with chronic HF, who were followed by 133 cardiology centers, were collected by locally trained clinicians and entered into a national database (IN-CHF Database). Entry into this database required that the patient had a diagnosis of chronic HF based on the presence of typical symptoms, signs, and documentation of cardiac disease.15 0002-9149/01/$–see front matter PII S0002-9149(01)01683-6

FIGURE 1. Time course of HF destabilization.

The central coordination of the project was at the Research Center of the Italian Association of Hospital Cardiologists (ANMCO), Florence, Italy. Patient demographics, history, New York Heart Association (NYHA) functional class, definition of primary etiology, physical and laboratory examination results, and drug prescriptions were recorded. Among all patients, 2,701 had ⱖ1 follow-up visit within 6 months from the initial visit (3 months later on average); these patients were grouped according to whether they had experienced or not experienced ⱖ1 episode of worsening HF (either as an outpatient or an inpatient). The occurrence of an episode of worsening HF (defined as at least a worsening in NYHA class associated with an increase of diuretic dosage), any recognized concomitant factor, and the subsequent decision-making process were routinely recorded in the database. This study only considered nonfatal decompensations. Statistical analysis: Data are presented as mean values ⫾ SD unless otherwise indicated. Clinical characteristics of patients with short-term destabilization were compared by the chi-square test with those without worsening HF. Continuous variables were compared by the Student’s t test. The observed differences are expressed as p values (2-tailed). To identify the independent determinants of a short-term worsening HF, a multivariate analysis was performed using a logistic regression model. The following variables, evaluated at the baseline examination, were entered in the model: age, gender, NYHA functional class (III to IV vs I to II), ischemic versus nonischemic etiology, left ventricular ejection fraction (⬍30% vs ⱖ30% vs unavailable ejection fraction), atrial fibrillation, third heart sound, systolic blood pressure, heart rate (ⱖ100 vs ⬍100 mm Hg), ventric-

ular tachycardia (yes vs no vs missing values), serum creatinine level (⬎2.5 vs ⱕ2.5 mg/dl vs missing values), hospital admissions for HF in the previous year, duration of symptoms (⬎18 vs ⱕ18 months), symptom score (based on a graded score of dyspnea, fatigue, and angina, ⬎5 vs ⱕ5), and sodium level (⬍135 vs ⱖ135 mEq/L vs missing values). Systolic blood pressure and age were considered in the multivariate model as continuous variables. Possible predictors of specific determinants of worsening HF were also evaluated.

RESULTS

Patients’ baseline data: Two hundred fifteen patients (8%) experienced short-term decompensation, which occurred a mean of 59 ⫾ 44 days after the baseline examination (Figure 1). Table 1 shows the clinical and epidemiologic features at the baseline visit of the 215 patients with short-term destabilization compared with those without this event. Patients with subsequent short-term destabilization showed more frequently an ischemic and valvular HF etiology and a more severe clinical profile. When pharmacologic treatment was considered (Table 2), patients with subsequent short-term destabilization received significantly more digitalis, oral anticoagulants, amiodarone, and diuretics while they received ␤ blockers less frequently compared with the patients whose disease was not unstable. Notably, 85% of patients with subsequent destabilization were given angiotensin-converting enzyme (ACE) inhibitors; significant differences among patients with or without worsening HF were observed in the mean dosage of the most frequently used ACE inhibitors (lisinopril 14 ⫾ 8 vs 11 ⫾ 9 mg, p ⫽ NS; captopril

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383

TABLE 1 Clinical Characteristics at Baseline Examination No Short-Term Worsening HF (n ⫽ 2,486) (92%) Age (yrs) Mean ⫾ SD ⱖ70 Women NYHA class III–IV Heart rate (beats/min) Mean ⫾ SD ⱖ100 Ejection fraction (%) (n ⫽ 1,501) Mean ⫾ SD ⬍30% Systolic blood pressure (mm Hg) Mean ⫾ SD ⬍100 100–130 ⬎130 Etiology Coronary heart disease Dilated cardiomyopathy Hypertensive Valvular Other Third sound Ventricular tachycardia (n ⫽ 584) Atrial fibrillation/flutter (n ⫽ 2,588) Creatinine (mg/dl) (n ⫽ 1,123) Mean ⫾ SD ⬎2.5 mg/dl Na (mEq/L) (n ⫽ 1,119) Mean ⫾ SD ⬍135 mEq/L Time from symptoms onset ⬎18 mo Admissions for HF in the previous year ⱖ1 Symptoms score ⬎5

Short-Term Worsening HF (n ⫽ 215) (8%)

63 ⫾ 12 761 (30.6%) 619 (24.9%) 630 (25.3%)

63 ⫾ 12 73 (33.9%) 49 (22.8%) 97 (45.1%)

NS NS NS 0.001

77 ⫾ 15 269 (10.9%)

82 ⫾ 19 38 (17.8%)

0.001 0.003

34 ⫾ 12 467 (34.2%)

30 ⫾ 10 63 (47.0%)

0.001 0.003

132 ⫾ 21 79 (3.2%) 1,356 (54.5%) 1,051 (42.3%)

123 ⫾ 22 15 (7.0%) 141 (65.6%) 59 (27.4%)

0.001 0.001 0.001

1,001 856 260 252 117 666 143

106 61 14 25 9 79 20

(40.3%) (34.4%) (10.5%) (10.1%) (4.7%) (26.8%) (27.0%)

(49.3%) (28.4%) (6.5%) (11.6%) (4.2%) (36.7%) (37.0%)

0.046

0.002 NS

470 (19.8%)

61 (28.9%)

0.002

1.2 ⫾ 0.5 17 (1.7%)

1.3 ⫾ 0.5 16 (6.3%)

0.009 0.002

140 ⫾ 4 70 (6.9%)

139 ⫾ 4 8 (7.8%)

0.047 NS

1,203 (48.4%)

131 (60.9%)

0.001

1,381 (55.6%)

169 (78.6%)

0.001

21 (9.8%)

0.001

98 (3.9%)

TABLE 2 Drugs at the Baseline Examination in Patients With and Without Short-term Worsening Heart Failure

ACE inhibitors Digitalis Calcium channel blockers ␤ blockers Oral anticoagulants Diuretics Amiodarone Nitrates Antiplatelets Antiarrhythmics

p Value

No Short-Term Worsening HF (n ⫽ 2,486) (92%)

Short-Term Worsening HF (n ⫽ 215) (8%)

p Value

2096 (84.3) 1627 (65.4) 304 (12.3)

183 (85.1) 161 (74.9) 24 (11.2)

NS 0.005 NS

460 (18.5) 660 (26.6) 2105 (84.7) 503 (20.2) 978 (39.3) 879 (35.4) 58 (2.3)

22 (10.2) 78 (36.3) 202 (94.0) 59 (27.4) 98 (45.6) 72 (33.5) 3 (1.4)

0.002 0.002 0.001 0.012 NS NS NS

78 ⫾ 45 vs 74 ⫾ 44 mg, p ⫽ NS; enalapril 16 ⫾ 9 vs 13 ⫾ 7 mg, p ⬍0.005). Predictors of short-term destabilization: Figure 2 shows the results of the multivariate analysis per384 THE AMERICAN JOURNAL OF CARDIOLOGY姞

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formed to identify the independent predictors of short-term worsening HF. Among the considered variables, a previous hospitalization for HF, long duration of symptoms, faster heart rate, atrial fibrillation, high functional class, ischemic etiology, and low systolic blood pressure resulted as independently associated with clinical destabilization. Precipitating factors of destabilization: Table 3 shows the precipitating

factors of destabilization. Precipitating or concomitant factors were not identified in 40% of patients. No peculiar clinical characteristics emerged in those patients whose destabilization was due to poor compliance, the most frequent concomitant factor, and in those in whom a precipitating factor was not recognized. Decision-making process related to destabilization: More than half (57%)

of the patients with short-term recurrence of worsening HF were hospitalized. An intravenous infusion treatment with inotropes and/or vasodilators was required in 19%. Besides the increase of diuretic dosage, a change in drug prescription was made in 48% of the patients (Table 4).

DISCUSSION

Epidemiology of destabilization of chronic heart failure: It is well known

that chronic HF is associated with high rates of destabilization that often lead to hospital admission.1–11 The rate of hospital admission (for any reason) ranges from 31% to 61% during the first 3 to 6 months after an index episode of hospitalization1,6,7,16,17 and worsening HF is the most frequent reason for readmission. To the best of our knowledge, observational data collected by hospital cardiologists for nonhospitalized patients, which examines the frequency of clinical decompensations that do not necessarily lead to hospital admission, are lacking in the literature. Our study took into consideration all the episodes of worsening HF leading to hospitalization or diagnosed at the first clinical examination after recruitment into a large nationwide database on ⱖ2,700 consecutive stable outpatients with chronic HF. We observed that 8% of those patients had early destabilization. This is a low rate, which likely reflects some peculiarities of the IN-CHF registry. All patients were followed-up by expert cardiologists, who were involved in a national HF program and members of the Italian Working Group on Heart Failure. By comparing the prescription of drugs in the IN-CHF registry and those reported in large HF trials,18 –21 patients may be considered as treated according to the current recAUGUST 15, 2001

FIGURE 2. Independent predictors of short-term destabilization. CHD ⴝ coronary heart disease; EF ⴝ ejection fraction; Na ⴝ natriemia; SBP ⴝ systolic blood pressure.

TABLE 3 Precipitating Factors (⬎1 factor was allowed to be specified) Number (%) Poor compliance Infections Uncontrolled hypertension Myocardial ischemia Onset of atrial fibrillation Iatrogenic factors Other Unknown

45 25 11 11 11 5 32 87

(21) (12) (5) (5) (5) (2) (15) (40)

ommendations. For instance, 84% of IN-CHF registry patients and 85% of patients with short-term destabilization were treated with ACE. Dosages of ACE were less than that recommended, reflecting what usually happens in routine clinical practice, but were considered adequate.20,22 When diagnosed, worsening HF induced a hospital admission in more than half of the patients. That means that about 5% of the IN-CHF registry patients had an early admission for HF. The 1-year rate of admission for HF in the registry was reported to be 13%23; thus, a third of the HF admissions occurred early after the entry outpatient examination. Risk factors for short-term destabilization: Some independent predictors of short-term episodes of worsening HF were identified by multivariate analysis (Figure 2). Not surprisingly, they were related to a more severe clinical profile. When comparing such predictors with the independent predictors of 1-year mortality and hospital admission in the patients of the IN-CHF registry,23 ischemic etiology and previous hospitalizations for HF confirmed their relevance not only at 1 year but also in the short-term follow-up. The observation that sinus tachycardia at rest contrib-

uted to predicting the short-term risk of decompensation, with an incremental risk of 61%, further supports the role of heart rate as an important risk factor for cardiovascular morbidity and mortality reported for subjects with hypertension or other cardiovascular risk factors, during and after a coronary event and also in the general population.24 –27 Among patients with left ventricular dysfunction (ejection fraction ⬍40%) St John Sutton et al28 observed that increased heart rate was an important predictor of ventricular dilation and cardiovascular death. In the placebo arm of the Cardiac Insufficiency BIsoprolol Study-I, heart rate at the first examination was correlated with mortality at 2 years, whereas this relation was lacking among patients treated with bisoprolol.29 Precipitating factors: Concomitant precipitating factors were not identified in 40% of the cases with short-term worsening HF. Because many of these patients were very ill at the first examination, worsening HF may have occurred without evident precipitating factors. Another explanation for the high rate of nonrecognition of precipitating factors may be the still inadequate effort given to investigating them. The IN-CHF registry takes a picture of routine clinical practice. It is possible that the physician search for concomitant factors is not yet perceived as really useful and, consequently, is not pursued vigorously enough. No clinical or instrumental indicators were able to predict the occurrence of precipitating factors. It should be considered that the variety of concomitant events and the relatively small number of each event could have limited the statistical power of this analysis. Decision making: To the best of our knowledge this is the first study that takes into account physician behaviors (in terms of therapeutic changes) in case of worsening HF.

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385

Giuliano, R. Marini); Monfalcone (E. Barducci); Trieste Osp. Maggiore (F. Humar); Udine Osp. S. M. della Misericordia (M.C. Albanese, C. Fresco); Liguria New Prescription Arenzano (A. Camerini, R. Griffo); Genova Osp. Galliera (G. Derchi); Genova-Rivarolo (D. Astengo, L. 9/215 (4.2%) Fazzini); Genova-Sestri Ponente (L. Pizzorno); Sarzana 20/215 (9.3%) (D. Bertoli); Emilia Romagna Forl␮ (G. Morgagni); 17/215 (7.9%) Guastalla (G. Bruno, E. Iori); Modena Osp. Sant’Agostino (F. Melandri); Modena Policlinico (F. 8/215 (3.7%) Cionini, L. Reggianini); Piacenza (F. Passerini); Ric25/215 (11.6%) cione (P. Del Corso, L. Rusconi); Rimini (M. Marza13/215 (6.1%) loni, M. Mezzetti), Scandiano (G. P. Gambarati); To8/215 (3.7%) scana Castelnuovo Garfagnana (P. R. Mariani, C. Vol9/215 (4.2%) terrani); Empoli (F. Venturi); Firenze Osp. S. M. Nuova (G. Zambaldi); Fucecchio (A. Geri Brandinelli); Gros10/215 (4.7%) seto (G. Miracapillo); San Giovanni Valdarno (T. Tad1/215 (0.5%) dei); Viareggio (A. Dalle Luche); Umbria Citta` di Castello (G. Arcuri, R. Giannini); Foligno (U. Gasperini); Perugia Monteluce (G. Alunni, E. Bosi); Perugia Monteluce (M. Cocchieri, D. Severini); Spoleto (G. Maragoni); Marche Ancona Osp. Sestilli (C. Ferroni, G. Saccomanno); Ancona Osp. Lancisi Medicina (L. Pasetti, A. Budini); Ancona Osp. Lancisi II Cardiologia (M. Manfrin); Camerino (B. Coderoni); Macerata (A. Mori); Lazio Albano Laziale (P. Midi); Roma INRCA (D. Del Sindaco, F. Leggio); Roma Osp. Forlanini (A. Terranova); Roma Osp. San Camillo II Cardiologia (G. Pulignano); Roma Osp. San Camillo Servizio (F. Pozzar); Roma Osp. San Camillo Servizio (G. Cacciatore, M. Menichelli); Roma Osp S. F. Neri (G. Ansalone, B. Magris); Roma Osp. S. Giovanni (G. Scaffidi); Roma Osp. Sandro Pertini (C. Valtorta, A. Salustri); Roma Osp. Sant’Eugenio (F. Amaddeo, G. Barbato); Roma Osp. Santo Spirito (N. Aspromonte, M. Renzi); Abruzzo Penne (L. Mantini); Popoli (C. Frattaroli, A. Mariani); Vasto (G. Di Marco, G. Levantesi); Termoli (N. Colonna, A. Montano); Campania Caserta (O. Di Maggio, G. Toscano); Mercato S. Severino (V. Capuano); Napoli Osp. Monaldi (M. Scherillo); Napoli Osp. Monaldi Medicina (P. Sensale, V. Rullo); Napoli Osp. Cardarelli (N. Maurea); Napoli Osp. S. Gennaro (D. Miceli, A. Somelli); Nola (F. Napolitano, P. Provvisiero); Oliveto Citra (M.R. Di Muro, P. Bottiglieri); Salerno (F. Rufolo); Puglia Bari Policlinico (N. Ciriello); Brindisi (E. Angelini, C. Andriulo); Casarano (F. De Santis); Francavilla Fontana (F. Cocco); Galatina Medicina (A. Zecca); Gallipoli (A. Pennetta, F. Mariello); Lecce Osp. Fazzi (F. Magliari, A. De Giorgi); Mesagne (V. Santoro); San Pietro Vernotico (S. Pede, A. Renna); Scorrano (O. De Donno, E. De Lorenzi); Taranto Osp. SS. Annunziata (G. Polimeni, V.A. Russo); Tricase (R. Mangia); Calabria Belvedere Marittimo (F. P. Cariello); Catanzaro Policlinico Servizio (M. Affinita); Catanzaro Policlinico Divisione (F. Perticone, C. Cloro); Cosenza Osp. Dell’Annunziata (G. Misuraca, R. Caporale); Cosenza Osp. Dell’Annunziata Medicina (P. Chiappetta); Reggio Calabria Osp. Morelli (E. Tripodi, F. Tassone); Rossano (S. Salituri); Siderno (C. Errigo); Trebisacce (G. Meringolo, L. Donnangelo); Sicilia Avola (G. Canonico); Catania Osp. Cannizzaro (R. Coco, M. Franco); Messina Osp. Papardo (A. Coglitore, A. Donato); Messina Osp. Piemonte (G. Di Tano); Messina Policlinico (D. Cento, C. De Gregorio); Palermo Casa Del Sole (M. Mongiovı`); Palermo Osp. Buccheri La Ferla FBF (A. M. Schillaci); Palermo Osp. Civico (U. Mirto); Palermo Osp. Ingrassia (F. Clemenza); Palermo Villa Sofia (F. Ingrillı`); Piazza Armerina (B. Aloisi); Sardegna Cagliari Brotzu (M. Porcu); Cagliari Osp. SS. Trinita` (G. Pili, S. Piras); Nuoro (I. Maoddi).

TABLE 4 Drug Changes Made After the Episode of Worsening Heart Failure Drug ACE inhibitors Digitalis Anticoagulants Calcium antagonists Nitrates ␤ blockers Amiodarone Diuretics Antiplatelets Antiarrhythmics

Withdrawn

Confirmed

17/183 (9.3%) 8/161 (5.0%) 3/78 (3.8%) 7/24 (29.2%) 9/98 (9.2%) 7/22 (31.8%) 10/59 (17.0%) —

166/183 (90.3%) 153/161 (95.0%) 75/78 (96.2%) 17/24 (70.8%) 89/98 (90.8%) 15/22 (68.2%) 49/59 (83.0%) 202/202 (100%) (dosage increased) 64/72 (88.9%) 2/3 (66.7%)

8/72 (11.1%) 1/3 (33.3%)

Changes to the medical therapy were made by the clinicians in nearly half of the patients who experienced worsening HF (Table 4). In particular, calcium antagonists, antiarrhythmics, and ␤ blockers were frequently withdrawn, whereas therapy with nitrates and diuretics was implemented. ACE use remained unchanged in most of the cases. It is hard to understand whether or not the changes in drug prescription were appropriate. However, withdrawing calcium antagonists and class I antiarrhythmics is recommended by many guidelines in such circumstances.13,14 It is interesting to note that ␤ blockers were withdrawn from nearly 1/3 of the patients with worsening HF. This probably reflects the uncertain approach of cardiologists to this class of drugs. Decompensation of chronic HF in a patient treated with ACE is generally considered “a case of worsening despite ACE inhibitors,” whereas the same episode is frequently supposed to be a “decompensation probably due to ␤ blockers” if the patient is receiving this class of drugs. This thought process is supported by the data of the BetablockeRs IN patients with congestive heart failure: Guided Use in clinical Practice study.30 In this observational study, the rate of Italian HF patients treated with ␤ blockers increased from 25% to 50%, but cardiologists were prone to withdraw the drug as soon as destabilization occurred. Apart from these considerations, worsening HF is a well-known complication of ␤ blockers in severely ill patients, so that the physician behavior was probably appropriate in many cases.

APPENDIX Participating Centers and Investigators: Piemonte Borgomanero (A. Mezzani, M. Bielli); Cuneo (U. Milanese, G. Ugliengo); Orbassano (R. Pozzi, F. Rabajoli); Veruno (E. Bosimini); Lombardia Bergamo (M. G. Valsecchi, F. Dadda); Brescia (P. Faggiano); Cassano D’Adda (G. Castiglioni, G. Gibelli); Chiari (A.L. Turelli); Como (R. Belluschi); Cremona (C. Bianchi, C. Emanuelli); Desio (S. Gramenzi, G. Foti); Erba Medicina (D. Agnelli); Gussago (E. Zanelli, M. Volterrani); Mariano Comense (E. Moroni); Milano Fondazione Don Gnocchi (E. Gara); Milano Osp. Sacco Medicina (S. Muzzupappa, M. Turiel); Milano Osp. Niguarda II Cardiologia (F. Recalcati); Milano Pio Albergo Trivulzio (D. Valenti); Montescano (C. Opasich); Passirana (F. Rusconi, M. Palvarini); Pavia Policlinico San Matteo (A. Giusti, C. Inserra); Saronno (D. Nassiacos, S. Meloni); Seriate (T. Nicoli); Sondalo (P. Bandini); Sondrio (M. Moizi); Tradate Fondazione Maugeri (R. Pedretti, M. Paolucci); Tradate Osp. Di Circolo Galmarini (L. Amati, M. Ravetta); Varese Osp. Di Circolo (F. Morandi, S. Provasoli); Vizzolo Predabissi (E. Planca, P. Quorso); P. A. di Trento Rovereto (A. Ferro); Rovereto Medicina (C. Pedrolli); Veneto Belluno (L. Riggi, L. Tarantini); Castelfranco Veneto (G. Candelpergher); Conegliano Veneto (G. Berton); Montebelluna (M.G. Stefanini); Padova (L. Cacciavillani, G. M. Boffa); Pieve Di Cadore (L. Mario); Treviso (G. Renosto, P. Stritoni); Valeggio sul Mincio (G. Perini, C. Bonadiman); Vicenza (L. Varotto, M. Penzo); Friuli Venezia Giulia Gorizia (G.

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