Cluster trajectory of SOFA score in predicting mortality in sepsis

Objective: Sepsis is a life-threatening condition. Sequential Organ Failure Assessment (SOFA) score is commonly used to assess organ dysfunction and predict ICU mortality, but it is taken as a static measurement and fails to capture dynamic changes. This study aims to investigate the relationship between dynamic changes in SOFA scores over the first 72 hours of ICU admission and patient outcomes. Design, setting, and participants: 3,253 patients in the Medical Information Mart for Intensive Care IV database who met the sepsis-3 criteria and were admitted from the emergency department with at least 72 hours of ICU admission and full-active resuscitation status were analysed. Group-based trajectory modelling with dynamic time warping and k-means clustering identified distinct trajectory patterns in dynamic SOFA scores. They were subsequently compared using Python. Main outcome measures: Outcomes including hospital and ICU mortality, length of stay in hospital and ICU, and readmission during hospital stay, were collected. Discharge time from ICU to wards and cut-offs at 7-day and 14-day were taken. Results: Four clusters were identified: A (consistently low SOFA scores), B (rapid increase followed by a decline in SOFA scores), C (higher baseline scores with gradual improvement), and D (persistently elevated scores). Cluster D had the longest ICU and hospital stays, highest ICU and hospital mortality. Discharge rates from ICU were similar for Clusters A and B, while Cluster C had initially comparable rates but a slower transition to ward. Conclusion: Monitoring dynamic changes in SOFA score is valuable for assessing sepsis severity and treatment responsiveness.Comment: 26 pages, 4 figures, 2 table

MACHINE LEARNING IN THE PERIOPERATIVE SETTING: UNCOVERING THE VALUE OF DATA SCIENCE AND LARGE INSTITUTIONAL DATASETS AMONG PATIENTS UNDERGOING SURGERY

Ph.DDOCTOR OF PHILOSOPHY (DUKE

Data from: Development of the Combined Assessment of Risk Encountered in Surgery (CARES) surgical risk calculator for prediction of post-surgical mortality and need for intensive care unit admission risk ? a single-centre retrospective study

doi:10.5061/dryad.v14248

Prevalence of preoperative anemia, abnormal mean corpuscular volume and red cell distribution width among surgical patients in Singapore, and their influence on one year mortality

This is the patient database that was used to generate the results in our manuscript

Anaesthesia for the First Neurosurgery under Intraoperative High Field Magnetic Imaging Guidance in Singapore

In 2008, Singapore General Hospital installed an Intraoperative Magnetic Resonance Imaging system (IMRI) in its Major Operating Theatre. This article discusses the first ever case done in the IMRI suite, the challenges faced and identified, as well as their learning points and potential solutions

CARES risk model dataset

Retrospective cohort of 90785 patients who underwent surgery in Singapore General Hospital between 2012-201

Distribution of microcytosis, normocytosis, macrocytosis in anemic patients of various age and gender groups.

<p>Distribution of microcytosis, normocytosis, macrocytosis in anemic patients of various age and gender groups.</p

Graph showing the mean and 95% confidence intervals of red cell distribution width in various anemia / mean corpuscular volume (MCV) groups.

<p>Graph showing the mean and 95% confidence intervals of red cell distribution width in various anemia / mean corpuscular volume (MCV) groups.</p

Cox regression of one year mortality after surgery.

<p>Cox regression of one year mortality after surgery.</p

Results of multinomial analysis of odds of mild or moderate/severe anemia over no anemia.

<p>Results of multinomial analysis of odds of mild or moderate/severe anemia over no anemia.</p