Open access Jurnal
Global Longitudinal Strain and Global Circumferential Strain on Echo Heart Failure Score as 60-days Readmission Predictor in Congestive Heart Failure Patients with Left Ventricle Systolic Dysfunction in Makassar City
Nusantara Medical Science Journal · Vol. ume (2021) · pp. 18–32
- ISSN
- 2597-7288, 2460-9757
- Published
- 2021-10-21
- Publisher
- Faculty of Medicine, Hasanuddin University.
- Language
- en
Abstract
Introduction: The readmission rate due to heart failure increases every year in South Sulawesi. A Frequently used method for assessing readmission is an echocardiographic examination by measuring ejection fraction. However, recent studies show that the speckle tracking parameters are more sensitive to predict readmission of heart failure patients. In this study, we assess the role of Global Longitudinal Strain (GLS) and Global Circumferential Strain (GCS) parameters on the Echo Heart Failure Score (EHFS) as a 60-days readmission predictor in heart failure patients. Methods: We included 175 patients admitted through the inpatient installation of Integrated Heart Center Dr. Wahidin Sudirohusodo General Hospital. In addition, we reviewed up to 60 days after outpatient prospectively by collecting data through medical records. The correlation between echocardiographic parameters and readmissions was analyzed using the Spearman Rank Correlation. To determine each echocardiographic parameter's cut-off point, sensitivity, and specificity, we use Receiver Operating Characteristic (ROC) curve. Results:GLS and GCS are very sensitive and specific parameters in predicting 60-days readmission with an area under the curve (AUC) value > 0.7. This study shows that adding GLS and GCS parameters to the EHFS increases the predicted value (AUC 0.850 vs. 0.820) and sensitivity to 79%. Conclusion: GLS and GCS parameters additional on EHFS can help predict 60-days readmission of heart failure patients with sensitivity and specificity of 79% and 83%, respectively. The present study shows that with higher GLS and GCS scores on the EHFS, the risk of readmission in heart failure patients will increase.
Collaboration network of the authors
40 authors · 124 co-authorship links · showing the 40 most connected
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- Hasanuddin University
- Affiliation unknown
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Nurhaedar Jafar | Affiliation unknown | 5 |
| Citrakesumasari . | Affiliation unknown | 3 |
| Andi Alfian Zainuddin | Affiliation unknown | 3 |
| Veni Hadju | Affiliation unknown | 2 |
| Safrullah Amir | Affiliation unknown | 2 |
| Muhammad Niswar | Hasanuddin University | 1 |
| Muhammad Nur | Hasanuddin University | 1 |
| Sabrina Yasin | Affiliation unknown | 1 |
| Citra Kesumasari | Affiliation unknown | 1 |
| Anna Khuzaimah | Affiliation unknown | 1 |
| Harlinah Harlinah | Affiliation unknown | 1 |
| Ummu Kalsum | Affiliation unknown | 1 |
| Atjo Wahyu | Affiliation unknown | 1 |
| Veny Hadju | Affiliation unknown | 1 |
| Yulia Yusrini Djabir | Affiliation unknown | 1 |
| Mirnawati Salampe | Affiliation unknown | 1 |
| Nur Amaliah rahmadani | Affiliation unknown | 1 |
| Djunaedi M Dachlan | Affiliation unknown | 1 |
| ezha widnatusifah | Affiliation unknown | 1 |
| sabaria battung | Affiliation unknown | 1 |
| Marini Amalia | Affiliation unknown | 1 |
| Aminuddin Syam | Affiliation unknown | 1 |
| Devintha Virani | Affiliation unknown | 1 |
| DWI YUNIATY ISMAIL | Affiliation unknown | 1 |
| Hardianti . | Affiliation unknown | 1 |
| Marini Amalia Mansur | Affiliation unknown | 1 |
| Sabaria Manti | Affiliation unknown | 1 |
| Saifuddin Sirajuddin | Affiliation unknown | 1 |
| Hariani | Affiliation unknown | 1 |
| Marini Amaliah Mansur | Affiliation unknown | 1 |
| Risnah B | Affiliation unknown | 1 |
| Kurnia Rabbi | Affiliation unknown | 1 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.