Weitering, Rick (2024) 1 Photoplethysmography as a new prognostic method for haemodynamic support therapy in sepsis patients at the Emergency Department. thesis, Medicine.
Full text available on request.Abstract
Rationale/background: Sepsis is a life-threatening condition caused by infection that results in high morbidity and mortality worldwide. Sepsis presents heterogeneously and patients may benefit from personalised treatment approaches, such as early initiation of vasopressor therapy. Identifying patient-specific factors that predict the need for vasopressor therapy is essential for improving patient outcomes. This study investigates whether photoplethysmography (PPG) data, which reflects haemodynamic status, can be predictive of need for vasopressor therapy in sepsis patients within the first 24 hours of Emergency Department (ED) admission. Methods: This is a secondary analysis of an observational study using data from the Acutelines data-biobank. Patients with suspected infection and haemodynamic instability were included. PPG features were pre-processed. Differences between outcome groups were analysed using Mann-Whitney U- and Pearson’s chi-squared test. Spearman correlation was used to test for correlation between PPG features and vital parameters. Logistic regression analysis was performed to evaluate the relationship between PPG features and vasopressor therapy, with Receiver Operating Characteristics (ROC)-curves generated for assessing predictive performance. Results: A total of 344 patients were included in this study, of whom 53 (15.4%) required vasopressor therapy. Systolic peak amplitude (SPA) and diastolic peak amplitude (DPA) differed between both outcome groups and were associated with vasopressor therapy. SPA demonstrated the strongest predictive value among the nine PPG features analysed, achieving moderate predictive accuracy (Area Under the Curve [AUC] 0.71). Conclusion: These findings highlight the potential of PPG data in personalising haemodynamic resuscitation strategies, thereby improving patient outcomes.
| Item Type: | Thesis (UNSPECIFIED) |
|---|---|
| Supervisor name: | Bouma, prof. dr. H.R. and Horst, drs. S. Ter PhD student |
| Faculty: | Medical Sciences |
| Date Deposited: | 10 Dec 2025 14:57 |
| Last Modified: | 10 Dec 2025 14:57 |
| URI: | https://umcg.studenttheses.ub.rug.nl/id/eprint/3869 |
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