Saudi Cultural Missions Theses & Dissertations
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Item Restricted Enhancing prehospital triage for patients with suspected cardiac chest pain using prediction models(University of Manchester, 2024-05-14) Alotaibi, Ahmed; Body, Richard; Brown, Benjamin; Martin, GlenBackground: Chest pain, a primary symptom of acute coronary syndromes (ACS), frequently prompts ambulance calls and emergency department (ED) visits. Despite this, a significant number of patients transported for chest pain ultimately receive diagnoses of self-limiting, non-cardiac conditions. This leads to systematic over-triage, elevating ambulance resource utilization and contributing to crowding in EDs. Aim: To understand and improve the accuracy of current processes for telephone triage and prehospital assessment of patients with acute chest pain. For telephone triage, specific objectives included to systematically review the literature; gain consensus on the life-threatening conditions (LTCs) that should be identified by call handlers; and to derive and validate a prediction model. I also aimed to refine and validate prediction models to enhance prehospital risk stratification by paramedics. Methods: I completed (a) a systematic review searching three databases with narrative synthesis; (b) a Delphi study to define the LTCs that should guide future telephone triage; and (c) a retrospective cohort study using North West Ambulance Services (NWAS) data linked with Manchester University NHS Foundation Trust (MFT) to derive and validate a prediction model. Further, I completed secondary analyses of a multi-centre prospective diagnostic test accuracy study to create meta-models of established decision aids using stacked regression, and I validated the Manchester only Acute Coronary Syndrome ECG (MACS-ECG) prediction model in prehospital setting. Result: The systematic review identified three relevant papers supporting the feasibility of using prediction models to reduce over-triage by telephone but highlighting a paucity of data. The Delphi study identified 26 LTCs that should receive a priority 1 or 2 ambulance response. Due to a cyber-attack, results of the derivation and validation of a new prediction model for telephone triage cannot be presented. The existing MACS-ECG risk model achieved a sensitivity of 2.3% (95% CI 0.3-8.1%) and specificity of 99.5% (95% CI 98.6-99.9%) for myocardial infarction with poor calibration (gradient 0.0628, intercept 0.0852). Meta-modelling did not enhance the accuracy of established prediction models. The paramedic ECG interpretation showed a 30.8% (95% CI: 22.1-40.6%) sensitivity and 89.7% (95% CI: 87.2-91.9) specificity. Conclusions: This work has (a) identified an important evidence gap to guide telephone triage for chest pain, (b) defined outcome measures for such future research, and (c) identified that currently available prediction models do not have any advantage over human interpretation of an ECG by a paramedic. Future research should focus on completing the work to develop a new prediction model a telephone triage and supporting training paramedics for ECG interpretation.20 0Item Restricted Intraoperative blood pressure management and postoperative acute kidney injury: Systematic review(Saudi Digital Library, 2023-09-21) Alotaibi, Ahmed; Prowle, JohnBACKGROUND: Postoperative acute kidney injury (PO-AKI) represents a significant and potentially severe complication following surgery. This systematic review aims to examine the impact of goal-directed therapy (GDT) on the incidence of PO-AKI in adult patients who underwent major noncardiac surgery. METHOD: We adhered to the PRISMA guidelines to evaluate GDT versus conventional therapies in adult surgical patients. MEDLINE (via PubMed) was scoured from 2018 to May 2023 for relevant RCTs. Participants included adults undergoing major abdominal surgeries, with exclusions. Primary outcomes focused on post-operative acute kidney injury, with secondary outcomes assessing hospital stay length and 30-day mortality. RESULT: Of 27,243 initial citations, 6 single-centre RCTs were included, encompassing 652 patients and classified into Blood Flow Optimization (BFO) and Perfusion Pressure Optimization (PPO). The primary outcome was reported in all. Various AKI definitions were used, including KDIGO, RIFLE, and AKIN. BFO trials explored blood flow strategies impacting PO-AKI incidence, with mixed results. PPO studies assessed perfusion pressure's role in PO-AKI, one showing significantly reduced AKI incidence. Secondary outcomes were the hospital stay length and 30-day mortality, with no consistent trend across studies. The risk of bias assessment highlighted challenges in blinding and statistical planning, with two trials deemed low risk. CONCLUSION: The body of evidence gathered from these studies, including the OPTIMISE trial, suggests that while GDT strategies do not consistently reduce the incidence of PO-AKI, they may still influence other postoperative outcomes. Given the significant morbidity and mortality associated with PO-AKI, further research in this area is warranted to optimize perioperative care strategies. Future research should include multi-centre RCTs with larger sample sizes, consider the definition of AKI, and account for the protocol being implemented.16 0