Analysis of 12-lead electrocardiograms shared on Twitter

Year 2022, Volume: 12 Issue: 3, 460 - 464, 30.05.2022

Hasan Sultanoğlu Mustafa Boğan Mehmet Cihat Demir Tuba Erdem Sultanoğlu

https://doi.org/10.16899/jcm.1001344

Abstract

Introduction: A large number of electrocardiograms (ECG) are shared on Twitter every day. Some of them aim to provide information to the readers, and some of them aim to provide training with a mini quiz. This study aimed to discuss the evaluability of ECG images shared on Twitter.
Methods: The study sample consisted of 12-lead ECG images shared on Twitter. ECG images shared on 08/01/2020 - 01/31/2021 were manually scanned.
Results: A total of 286 tweets matching the criteria were included in the study on the specified dates. The majority of them (n = 231. 80.5%) asked the reader about the ECG. The average number of the tweets' interactions was 70.42 ± 112.17, and the interaction was mainly in the form of "likes" (50.49 ± 80.64). 83.5% of ECGs had a rhythm strip. Total interaction numbers and other parameters were compared. ECGs from which small squares could be selected collected more interactions (p = 0.015). ECGs explained the case or whose diagnosis was clearly stated collected more interactions (p <0.001). Also, it was observed that ECGs without a rhythm strip contained more interaction (p <0.001).
Conclusions: We concluded that 12-derivation ECGs shared on Twitter are highly evaluable. There was also a moderate correlation between the number of followers and the number of interactions. For this reason, it is important for accounts with a high number of followers to following that are experts in their field to prevent information pollution.

Keywords

Electrocardiography, Social Media, Twitter messaging

Twitter'da Paylaşılan 12 Derivasyonlu Elektrokardiyogramların Analizi

Abstract

Giriş: Twitter'da her gün çok sayıda elektrokardiyogram (EKG) paylaşılmaktadır. Bazıları okuyuculara bilgi vermeyi, bazıları ise mini bir quiz ile eğitim vermeyi amaçlıyor. Bu çalışma Twitter'da paylaşılan EKG görüntülerinin değerlendirilebilirliğini tartışmayı amaçlamıştır.
Yöntemler: Çalışma örneklemi Twitter'da paylaşılan 12 derivasyonlu EKG görüntülerinden oluşturuldu. 08/01/2020 - 01/31/2021 tarihinde paylaşılan EKG görüntüleri manuel olarak taranmıştır.
Bulgular: Belirlenen tarihlerde kriterlere uyan toplam 286 tweet çalışmaya dahil edildi. Çoğunluğu (n = 231, %80,5) okuyucuya EKG'yi sordu. Tweetlerin ortalama etkileşim sayısı 70.42 ± 112.17 idi ve etkileşim ağırlıklı olarak "beğeni" (50.49 ± 80.64) şeklindeydi. EKG'lerin %83,5'inde ritim şeridi vardı. Toplam etkileşim sayıları ve diğer parametreler karşılaştırıldı. Küçük karelerin seçilebildiği EKG'ler daha fazla etkileşim topladı (p = 0.015). EKG'ler, vakayı açıklayan veya tanısı açıkça belirtilen daha fazla etkileşim topladı (p <0,001). Ayrıca ritim şeridi olmayan EKG'lerin daha fazla etkileşim içerdiği gözlendi (p<0,001).
Sonuç: Twitter'da paylaşılan 12 derivasyonlu EKG'lerin yüksek derecede değerlendirilebilir olduğu sonucuna vardık. Takipçi sayısı ile etkileşim sayısı arasında da orta düzeyde bir ilişki vardı. Bu nedenle takipçi sayısı yüksek, alanında uzman hesapların bilgi kirliliğini önlemesi önemlidir.

Keywords

Sosyal Medya, Twitter mesajlaşma, Elektrokardiyografi

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