Reducing gap in pre-hospital delay between women and men presenting with ST-elevation myocardial infarction

Abstract

Aims

This study aimed to analyse changes in pre-hospital delay over time in women and men presenting with ST-elevation myocardial infarction (STEMI) in Switzerland.

Methods and results

AMIS Plus registry data of patients admitted for STEMI between 2002 and 2019 were analysed using multivariable quantile regression including the following covariates: interaction between sex and admission year, age, diabetes, pain at presentation, myocardial infarction (MI) history, heart failure history, hypertension, and renal disease. Among the 15,350 patients included (74.5% men), the median (interquartile range) delay between 2002 and 2019 was 150 (84; 345) min for men and 180 (100; 414) min for women. The unadjusted median pre-hospital delay significantly decreased over time for both sexes but the decreasing trend was stronger for women. Specifically, the unadjusted sex differences in delay decreased from 60 min in 2002 (P = 0.0042) to 40.5 min in 2019 (P = 0.165). The multivariable model revealed a significant interaction between sex and admission year (P = 0.038) indicating that the decrease in delay was stronger for women (−3.3 min per year) than for men (−1.6 min per year) even after adjustment. The adjusted difference between men and women decreased from 26.93 min in 2002 to −1.97 min for women in 2019.

Conclusion

Over two decades, delay between symptom onset and hospital admission in STEMI decreased significantly for men and women. The decline was more pronounced in women, leading to the sex gap disappearing in the adjusted analysis for 2019.

Lay Summary

Because the delay between onset of heart attack symptoms and hospital admission was higher in women in the past, this study analysed whether pre-hospital delay has shortened in general since 2002 as well as in women and men separately.

• Our study showed that the pre-hospital delay steadily decreased for both sexes but the decrease was greater in women

• After considering differences in patient characteristics, such as higher age and less previous heart attacks in women, by 2019 the delay was nearly the same for women and men.

Pre-hospital delay, STEMI, Sex gap

See the editorial comment for this article ‘Have we reached equality in pre-hospital management for women and men with STEMI?’, by J. Stehli, https://doi.org/10.1093/eurjpc/zwad015.

Introduction

Early reperfusion therapy is critical for improving survival in ST-elevation myocardial infarction (STEMI) patients.¹ Time from symptom onset to reperfusion is the sum of patient delay and system delay. Patient delay is influenced by symptom awareness and the ability/willingness to seek medical attention, whereas system delay is determined by factors such as the ambulance and emergency medical system and catheterization laboratory availability. Pre-hospital delay therefore includes the full patient delay and part of the system delay such as pre-hospital decision times of the first medical contact and transportation-related delays.

Multiple characteristics have been associated with longer pre-hospital delays at both patient^2,3,4,5 and system levels,^2,3,5,6 including older age,^2,4,5 female sex^2,4,6,3 and diabetes.^4,5 In patients with previous myocardial infarction (MI), pre-hospital delay is known to be reduced⁷ mainly driven by faster symptom recognition and shorter decision times not only by the patient but also by the local emergency service or general practitioner.⁸ In general, patients with characteristics that are related to a reduced symptom recognition and symptom perception such as female sex and diabetes are more likely to have increased decision times and therefore longer pre-hospital delay.

However, little is known about temporal trends in pre-hospital delay in STEMI patients and how the impact of characteristics, such as female sex, on pre-hospital delay has changed over time. The present study aimed to identify predictors of pre-hospital delay in STEMI patients and to analyse how the delay changed over almost two decades in women and men in Switzerland.

Methods

Acute Myocardial Infarction (AMIS) Plus is an ongoing nationwide prospective registry of patients admitted to Swiss hospitals for an acute coronary syndrome, as previously detailed.^9,10 Data are collected using a standardized questionnaire which is filled out by the treating physician or a trained study nurse in the treating hospital. The data collection comprises clinical presentation, medical treatment, in-hospital outcomes and complications. Since 1997, 84 hospitals of all sizes have continuously or temporarily collected data for AMIS Plus. This study is in accordance with the Declaration of Helsinki regarding investigations on humans and was approved by the Swiss National Ethical Committee for Clinical Studies, the Board for Data Security and all cantonal ethic committees approved the registry.

This analysis included STEMI patients admitted between 2002 and 2019 to Swiss hospitals with data on pre-hospital delay. STEMI was defined as typical ischemic symptoms, a significant rise and decrease in biomarkers in relation to the individual hospital cut-off level for MI and ST-segment elevation and/or new left bundle branch block on the initial ECG. Diagnoses conform to the prevailing guidelines in use at the time of inclusion. Patients with resuscitation prior to arrival at hospital, symptom onset in hospital or who were transferred from another hospital were excluded. Primary outcome was pre-hospital delay in minutes which was defined as difference between symptom onset time and hospital admission time. To gain an overview over the changes in patient characteristics and delay over time, the first 3 years (2002–04) and the lasts 3 years (2017–19) were summarized and compared. Possible covariates were selected based on literature review and clinical experiences. Delay and age were used as a continuous variable. The other variables were binary. Pain and dyspnoea were considered according to patients’ presentation at admission. Hypertension was assumed to be present if the patient had previously been treated and/or diagnosed by a physician. For diabetes, patients with a new diagnosis during hospitalization were also considered. A patient was defined as a current smoker if he had smoked at least 100 cigarettes in his life and was currently smoking at the time of the MI. Co-morbidities were assessed using the Charlson Comorbidity Index.^11,12

Statistical analysis

Binary variables were presented as frequencies and the χ² test was used for group comparison. Normally distributed continuous variables were presented as means with standard deviation (SD) and the T-test was applied for comparison between groups. Non-normally distributed continuous variables were presented as medians with the interquartile range, and univariable quantile regression was used for group comparison.

Multivariable quantile regression was used to assess the adjusted impact of sex on pre-hospital delay. Pre-selection of covariates for the multivariable model was performed using univariate quantile regression between the covariates and pre-hospital delay. Covariates were considered for multivariable quantile regression if the P-value was < 0.2 in the univariable analysis. In the multivariable analysis, covariates with a P-value higher than 0.2 were excluded from the model. To evaluate if there was a steeper decline in delay for women than men, we added an interaction term between sex and admission year to the model to statistically assess different trends in delay over time in men and women.

Statistical analysis was performed in R (Version 1.4.1106) and a P-value of <0.05 was considered statistically significant.

Results

Patients

This analysis included 15 350 STEMI patients admitted between 2002 and 2019. Table 1 shows the comparison of patient characteristics for women and men for the whole time period and for the first 3 years of the observation period vs. the last 3 years. In both time periods, women were older, less often smokers and had a higher rate of history of heart failure and hypertension. Women presented less often with chest pain but more often with dyspnoea. In the first observation period, women had a higher prevalence of diabetes while in the last observation period, they had a higher prevalence of renal and cerebrovascular disease but less frequently a history of MI.

Table 1

Patient characteristics according to time period and gender

	Whole period (2002–19)			2002–04			2017–19
	Men (n = 11 439)	Women (n = 3911)	P-value	Men (n = 1944)	Women (n = 676)	P-value	Men (n = 1636)	Women (n = 505)	P-value
Age	62.75 (12.79)	71.32 (12.73)	<0.001	62.93 (13.25)	71.27 (12.36)	<0.001	63.14 (12.29)	71.05 (12.55)	<0.001
Symptoms at admission
Pain	10 776/11 365 (94.8)	3567/3878 (92.0)	<0.001	1723/1930 (89.3)	578/672 (86.0)	0.025	1589/1625 (97.8)**	470/497 (94.6)++	0.001
Dyspnoea	2790/10 543 (26.5)	1194/3598 (33.2)	<0.001	382/1902 (20.1)	208/666 (31.2)	<0.001	458/1494 (30.7)**	172/464 (37.1)+	0.010
Risk factors
Diabetes	1866/11 025 (16.9)	746/3717 (20.1)	<0.001	331/1882 (17.6)	154/659 (23.4)	0.002	308/1569 (19.6)	109/477 (22.9)	0.135
Hypertension	5746/10 855 (52.9)	2482/3729 (66.6)	<0.001	907/1854 (48.9)	404/651 (62.1)	<0.001	949/1552 (61.1)**	344/484 (71.1)+	<0.001
Obesity (BMI > 30)	2035/10 378 (19.6)	664/3383 (19.6)	0.981	297/1713 (17.3)	105/562 (18.7)	0.483	319/1568 (20.3)*	102/482 (21.2)	0.699
Smoking	4799/10 607 (45.2)	1143/3489 (32.8)	<0.001	888/1874 (47.4)	182/631 (28.5)	<0.001	624/1439 (43.4)*	154/419 (36.8)+	0.018
Co-morbidities
Past history of MI	1653/11 125 (14.9)	428/3801 (11.3)	<0.001	276/1799 (15.3)	91/643 (14.2)	0.520	244/1603 (15.2)	43/494 (8.7)+	<0.001
Cerebrovascular disease	454/11 119 (4.1)	216/3801 (5.7)	<0.001	100/1799 (5.6)	39/643 (6.1)	0.621	42/1601 (2.6)**	24/494 (4.9)	0.018
History of heart failure	213/11 119 (1.9)	143/3801 (3.8)	<0.001	51/1799 (2.8)	30/643 (4.7)	0.029	38/1601 (2.4)	26/494 (5.3)	0.002
Cancer	534/11 119 (4.8)	197/3801 (5.2)	0.348	78/1799 (4.3)	39/643 (6.1)	0.085	72/1601 (4.5)	22/494 (4.5)	1.000
Renal disease (moderate, severe)	497/11 119 (4.5)	280/3801 (7.4)	<0.001	71/1799 (3.9)	33/643 (5.1)	0.211	82/1601 (5.1)	45/494 (9.1)+	0.002
Delay (symptom to hospital) in minutes	150.0 (84.0; 345.0)	180.0 (100.0; 414.0)	<0.001	166.0 (90.0; 393.8)	200.0 (105.0; 540.0)	0.005	140.0 (82.0; 309.3)**	168.0 (92.0; 346.0)+	0.004

*P < 0.05, **P < 0.001 for difference in men between 2002–04 and 2017–19, ⁺P < 0.05, ⁺⁺P < 0.001 for difference in women between 2002–04 and 2017–19.

When looking only at women, the rate of pain and dyspnoea at admission, hypertension, current smoking and renal disease was higher in 2017–19 compared with 2002–04 but the rate of a history of MI was lower. In men, the comparison of the periods 2002–04 and 2017–19 showed higher rates of pain and dyspnoea at admission, hypertension and obesity in 2017–19 but the rate of current smoking and cerebrovascular disease was lower.

Unadjusted temporal trends of pre-hospital delay in women and men

Over the whole time period, pre-hospital delay was more pronounced in women than in men (180 (100; 414) min vs. 150 (84; 345) min; P < 0.001).

Figure 1 shows the unadjusted median delay in women and men from 2002 to 2019. Median pre-hospital delay decreased from 240 (118.8; 698.8) min in 2002 to 180 (93.5; 447.0) min (P < 0.001) in 2019 for women, while the delay decreased from 180 (90.0; 405.0) min to 139.5 (80.5; 320.0) min (P < 0.001) for men. The trend in delay decrease was more pronounced in women than men: the unadjusted difference in pre-hospital delay between women and men decreased from 60 min in 2002 (P = 0.042) to 40.5 min in 2019 (P = 0.165) (Figure 1). When comparing the first 3 years with the last 3 years, the median delay decreased by 32 min for women (P = 0.001) and by 26 min for men (P < 0.001) (Table 1). The unadjusted pre-hospital delay difference between women and men decreased from 34 min in 2002–04 (P = 0.005) to 28 min in 2017–19 (P = 0.004).

Figure 1

Unadjusted trends of median delay for women and men.

Adjusted temporal trends of pre-hospital delay in women and men

In model 1, female sex was identified as a significant predictor of pre-hospital delay independent of admission year and other confounders (b = 13.53 P = 0.003) (Table 2, Model 1). However, in model 2, a significant interaction between sex and admission year was found (b = −1.71 (−2.71; −0.28), P = 0.038, Table 2). This interaction revealed that after correction for the factors age, previous MI, diabetes, pain at presentation, history of heart failure, renal disease and hypertension, the decrease in pre-hospital delay was more pronounced in women than in men. According to the model, the adjusted reduction in delay was −3.29 min [−1.59 + (−1.7)] per year of enrolment in women and −1.59 min in men. This resulted in an adjusted difference between women and men of 26.93 min in 2002 and −1.97 min in 2019 (Figure 2).

Figure 2

Adjusted differences in pre-hospital delay between women and men in 2002 and 2019. The differences were adjusted for age, pain at admission, diabetes, history of myocardial infarction, history of heart failure, moderate to severe renal disease and hypertension.

Table 2

Multivariable models to analyse the adjusted effect of sex on pre-hospital delay

Predictor	Model 1: without interaction term			Model 2: with interaction term
	Coefficient	P-value	95% CI	Coefficient	P-value	95% CI
Female sex	13.53	0.003	5.92; 19.90	26.93	0.003	12.29; 38.89
Admission year (in men)	−1.86	<0.001	−2.32; −1.41	−1.59	<0.001	−2.04; −0.99
Female sex × admission year	—	—	—	−1.71	0.038	−2.71; −0.28
Age	1.41	<0.001	1.19; 1.61	1.42	<0.001	1.20; 1.63
Pain	−39.42	0.001	−59.07; −19.00	−41.32	<0.001	−59.91; −18.31
Diabetes	26.30	<0.001	18.23; 35.13	24.66	<0.001	18.28; 36.01
History of myocardial infarction	−39.90	<0.001	−45.35; −34.33	−40.33	<0.001	−44.87; −33.65
History of heart failure	32.74	0.032	7.42; 60.83	32.71	0.036	10.18; 62.27
Moderate to severe renal disease	24.55	0.039	8.48; 46.19	21.81	0.047	8.95; 47.58
Hypertension	12.04	<0.001	7.74; 17.55	12.67	<0.001	6.98; 17.61
(Intercept)	111.83	<0.001	88.60; 134.70	110.53	<0.001	82.03; 133.59

In the model with interaction term, the coefficient of female sex represents the adjusted difference between men and women in the reference year 2002. The coefficient of admission year represents the reduction of delay per additional year in men. The interaction term female sex × admission year represents the additional reduction in delay per additional year in women compared with men.

The covariates age (+1.42 min per year), diabetes (+24.66 min), history of heart failure (+32.71 min) and renal disease (+21.81 min) were independently associated with a longer pre-hospital delay whereas chest pain at presentation (−41.32 min) and history of MI (−40.33 min) were independently associated with a reduction in pre-hospital delay.

Discussion

This study showed that the median delay between onset of MI symptoms and hospital admission steadily decreased for men and women in Switzerland over the last 18 years. While overall female sex was a powerful independent predictor of prolonged pre-hospital delay, the reduction in delay over time was more pronounced in women than in men, leading to a reduction in the sex gap in pre-hospital delay between 2002 and 2019. Multivariable analysis confirmed the observation and showed comparable delays between women and men in 2019.

Whereas several studies also showed a decline in delay for men and women, most of them reported the persistence of a longer delay for women. The impact of sex on pre-hospital delay in STEMI was for example analysed in a study that compared two STEMI cohorts with 753 and 885 patients for the time periods 2000–02 and 2006–08. They found significant reductions in patient and system delay, with a stronger decrease among women, although their patient and treatment delay remained more pronounced than in men.¹³ Two additional studies also showed a persistently higher patient delay for women compared with men with STEMI for the time periods 2000–16¹⁴ and 2005–12,¹⁵ respectively. A further study showed higher pre-hospital delay for women in the two time periods 1998–2000 and 2004–06.¹⁶ In contrast to these studies, we found no essential difference in delay in 2019 after correction for patient characteristics in line with two other studies.^5,17 Possible explanations for the divergent findings are that the other studies analysed the trends only up to the year 2016,^18,3,19,20 or analysed the delay only cross-sectionally^3,21 or did not correct for patient characteristics.²² Additionally, the selection of the regression method can produce different results. As time variables often show a skewed distribution, it is recommended to use quantile regression, as we performed, rather than linear regression.²³

Although the delay decreased over time and sex discrepancies narrowed, it is important to emphasise that the median pre-hospital delay for women and men combined was still 150 min in 2019, resulting in a total ischaemic time of >120 min for many patients. A total ischaemic time of >120 min was shown to increase the transmural extent of infarction and infarct size²⁴ and mortality was also shown to decrease if the time from first medical contact to PCI decreases.²⁵ Therefore, a further reduction of the delay remains crucial.

Pre-hospital delay may be driven by both patient level and system level variables. A key factor for a shorter patient delay is the patient awareness of MI symptoms. A study published in 2018 showed that awareness of MI in women is lower for both female patients and health care providers.²⁶ A meta-analysis on global awareness of MI symptoms in the general population found a high prevalence of awareness of the symptom chest pain but limited knowledge of different symptoms such as jaw, back and neck pain.²⁷ Although some recent studies showed that the rate of chest pain is similar in women and men with STEMI,^26,28,29 women were more likely to present with additional less known symptoms such as weakness or back, shoulder, or neck pain, which may influence the awareness in women and physicians especially if the non-chest pain symptoms are the most dominant symptoms.²⁶ In our study, women suffered more often from dyspnoea and less often from pain compared with men, which might be driven by the higher rates of diabetes and heart failure. Not having chest pain or not perceived chest pain as the most emphasized symptom is a major disadvantage in terms of rapid action in the event of MI as also reflected in our regression results. In particular, the covariates pain on admission and history of MI resulted in the greatest reduction in delay, likely due to a higher awareness in these patients compared with patients without pain and MI history. These results suggest that equal treatment of women and men in the pre-hospital period is only possible if women are well informed about the differences in symptoms and symptom perception.

Another factor that led to a longer pre-hospital delay in our results was older age. Older age might be an important factor contributing to the observed unadjusted differences in delay between women and men. As women were older at the time of AMI, it is likely that more women were living alone and that a larger proportion was no longer involved in a daily work routine. Indirectly, higher age might therefore impact if and how quickly help is sought by third parties such as family members or co-workers, thereby resulting in longer delays. Indeed, previous studies showed slightly longer pre-hospital delays if patients were at home when symptoms started.³⁰ One way to address the lack of awareness of symptoms in the general populations is through public campaigns. In Switzerland, a nationwide multimedia campaign (HELP) was launched in 2007 by the Swiss Heart Foundation to raise the awareness of the symptoms of heart attacks. The campaign has been shown to effectively reduce the pre-hospital delay with a pronounced effect among men.³¹ A systematic review of the impact of educational interventions to reduce pre-hospital delay in AMI patients concluded that mass media and personalized educational interventions can reduce delay and should also address perceptual and psychological barriers such as atypical symptom onset, denial of the cardiac origin of symptoms or fear of triggering a false alarm.³²

At the system level, improved pre-hospital diagnosis might have brought a reduction in pre-hospital delay, especially in women. However, studies that focused on this question found female sex to still be a predictor of emergency medical service delay in patients with suspected STEMI³³ and of longer pre-hospital system delays.²¹ A Swedish study on 539 STEMI patients from 2015 showed for example that women have longer delay times to the acquisition of a pre-hospital ECG than men.³⁴ Therefore, pre-hospital diagnosis is likely to be an important target in order to improve delay.

Strength and limitations

The strengths of this study are the large number of patients and the long observation period of 18 years. In addition, the extensive collection of clinical data and patient characteristics allowed us to consider many covariates as potential confounders. However, we were unable to quantify the impact of sociodemographic factors on delay or the impact of living in an urban vs. rural area. Additionally, we could not differentiate between sex vs. gender-related patient characteristics that also might have an impact on delay.³⁵ As data on first medical contact were only collected since 2005, we were not able to further differentiate between patient and system delay in our analysis.

The AMIS Plus registry has some limitations: the weaknesses of AMIS Plus are common to all observational studies particularly long-lasting studies over decades. Participation in the AMIS Plus registry is voluntary, the number of hospitals varied over the years and therefore might not be entirely representative for all-comers to all hospitals in Switzerland despite the permanent involvement of more than 70% of all hospitals treating AMI.

Conclusions

This analysis of a large STEMI population shows that female sex is an independent predictor of increased time between symptom onset to hospital admission. However, over the course of almost two decades, this delay narrowed for both sexes and especially for women, so that the sex differences in adjusted pre-hospital delay no longer exists.

Authors’ contributions

F.F.: conception and design, analysis and interpretation of data and drafting of the manuscript. D.R.: conception and design, interpretation of data, revising the manuscript for important intellectual content and final approval of the manuscript submitted. H.R., M.R., G.P., F.E., A.F., R.J., S.F., P.E.: acquisition of the data, revising the manuscript for important intellectual content, gave final approval and agreed to be accountable for all aspects of work ensuring integrity and accuracy.

Acknowledgements

AMIS Plus Participants 2002–19. The authors would like to express their gratitude to the teams of the following hospitals (listed in alphabetical order with the names of the local principal investigators): Aarau, Kantonsspital (P Lessing); Affoltern am Albis, Spital (F Hess); Altdorf, Kantonsspital Uri (R Simon/S Gisler); Altstätten, Spital (PJ Hangartner); Baden, Kantonsspital (U Hufschmid); Basel, St. Claraspital (L Altwegg); Basel, Universitätsspital (R Jeger); Bern, Beau-Site Klinik (S Trummler); Bern, Inselspital (S Windecker); Bern, Tiefenauspital (P Loretan); Biel, Spitalzentrum (C Roethlisberger); Brig-Glis, Oberwalliser Kreisspital (D Evéquoz); Bülach, Spital (G Mang); Burgdorf, Regionalspital Emmental (D Ryser); Davos, Spital (W Kistler); Dornach, Spital (A. Droll); Einsiedeln, Regionalspital (S Stäuble); Flawil, Spital (G Freiwald); Frauenfeld Kantonsspital (HP Schmid); Fribourg, Hôpital cantonal (JC Stauffer/S Cook); Frutigen, Spital (K Bietenhard); Genève, Hôpitaux universitaires (M Roffi); Glarus, Kantonsspital (W Wojtyna); Grenchen, Spital (R Schönenberger); Herisau, Kantonales Spital (M Bötschi); Horgen, See Spital (B Federspiel); Interlaken, Spital (EM Weiss); Kreuzlingen, Herzzentrum Bodensee (K Weber); La Chaux-de-Fonds, Hôpital (H Zender); Lachen, Regionalspital (I Poepping); Langnau im Emmental, Regionalspital (A Hugi); Laufenburg, Gesundheitszentrum Fricktal (E Koltai); Lausanne, Centre hospitalier universitaire vaudois (JF Iglesias/S Fournier); Lugano, Cardiocentro Ticino (G Pedrazzini); Luzern, Luzerner Kantonsspital (P Erne/F Cuculi); Männedorf, Kreisspital (T Heimes); Mendrisio, Ospedale regionale (A Pagnamenta); Meyrin, Hôpital de la Tour (P Urban/A Fassa); Moutier, Hôpital du Jura bernois (C Stettler); Münsingen, Spital (F Repond); Münsterlingen, Kantonsspital (F Widmer); Muri, Kreisspital für das Freiamt (C Heimgartner); Nyon, Group. Hosp. Ouest lémanique (R Polikar); Olten, Kantonsspital (S Bassetti/S Ernst); Rheinfelden, Gesundheitszentrum Fricktal (HU Iselin); Rorschach, Spital (M Giger); Samedan, Spital Oberengadin (P Egger); Sarnen, Kantonsspital Obwalden (T Kaeslin); Schaffhausen, Kantonsspital (A Fischer); Schlieren, Spital Limmattal (T Herren); Schwyz, Spital (P Eichhorn); Scuol, Ospidal d’Engiadina Bassa (C Neumeier/G Flury); Sion, Hôpital du Valais (G Girod); Solothurn, Bürgerspital (R Vogel); Stans, Kantonsspital Nidwalden (B Niggli); St. Gallen, Kantonsspital (H Rickli); Sursee, Luzerner Kantonsspital (J Nossen); Thun, Spital (U Stoller); Uster, Spital (E Bächli/J Debrunner); Walenstadt, Kantonales Spital (D Schmidt/J Hellermann); Wetzikon, GZO Spital (U Eriksson); Winterthur, Kantonsspital (T Fischer); Wolhusen, Luzerner Kantonsspital (M Peter/Y Suter); Zofingen, Spital (S Gasser); Zollikerberg, Spital (R Fatio); Zürich, Hirslanden Klinik (C Wyss); Zürich, Hirslanden Klinik im Park (O Bertel); Zürich, Universitätsspital, Intensivmedizin (M Maggiorini); Zürich, Universitätsspital, Kardiologie (B Stähli); Zürich, Stadtspital Triemli (F Eberli); Zürich, Stadtspital Waid (S Christen).

Funding

The AMIS Plus Registry is funded by unrestricted grants from the Swiss Heart Foundation and from Abbott Medical (Schweiz) AG, Amgen AG, AstraZeneca AG, Bayer (Schweiz) AG, Biotronik Schweiz AG, Boston Scientific, B. Braun Medical AG, Cordis Medical GmbH, Daiichi Sankyo (Schweiz) AG, Medtronic (Schweiz) AG, Novartis Pharma Schweiz AG, Sanofi-Aventis (Suisse) SA, Servier (Suisse) SA, SIS Medical AG, Terumo (Deutschland) GmbH, Vascular Medical GmbH and Swiss Working Group for Interventional Cardiology. The sponsors did not play any role in the design, data collection, analysis, or interpretation of the registry.

Data availability

Individual data used for the construction of the AMIS Plus registry are the property of the hospitals participating in the AMIS Plus registry and may only be made available by each hospital’s PI and the AMIS Plus Steering Committee. Due to data protection regulations related to the different hospitals involved in this study, the authors do not have authorization to provide unrestricted data access. However, after approval of the AMIS Plus Steering Committee and subsequent negotiation of an individual AMIS Plus module contract with the AMIS Plus Steering Committee, analysis files can be provided to other researchers. Requests must be submitted to Prof. Dr Hans Rickli, President of the AMIS Plus Steering Committee ([email protected]) and Dr Dragana Radovanovic (Head of the AMIS Plus Data Center, [email protected]).

Author notes

Previous presentations: Abstract was presented at the ESC congress 2020 and at the Congress of the Swiss Society of Cardiology (SCC) 2020.

Conflict of interest: None declared