Development of an ICU Physiological State Space Monitor Based on the ICCA Database: A Single-Center Retrospective Observational Study
Development of an ICU Physiological State Space Monitor Based on the ICCA Database: A Single-Center Retrospective Observational Study
Critically ill patients can deteriorate rapidly across multiple organ systems. Most intensive care unit (ICU) risk tools rely on measurements collected at a single time point and may not fully capture how physiology evolves or how quickly a patient recovers from disturbance. This single-center retrospective observational study will use routinely collected data from the ICCA reporting database at Zhongshan Hospital, Fudan University to develop and internally validate a research prototype called the ICU Physiological State Space Monitor. Adult ICU admissions will be represented as daily state vectors across 10 physiological domains. The study will characterize each patient's position and movement in a multidimensional state space, identify high-risk regions and possible critical transitions, and quantify physiological resilience using trajectory features such as variability, autocorrelation, curvature, recovery slope, and cross-domain coupling. The primary validation outcome is a composite clinical deterioration event within 72 hours after an eligible index patient-day. The monitor is an analytic and visualization framework for retrospective research and will not be deployed for real-time clinical decision-making in this study.
Inclusion Criteria:
Exclusion Criteria:
This is a single-center, retrospective, non-interventional methodological cohort study using routinely collected structured data from the ICCA reporting-layer database at Zhongshan Hospital, Fudan University. The source population comprises adult ICU patients admitted between September 2021 and May 31, 2026 who have an extractable and uniquely identifiable ICU encounter. No intervention will be assigned, no clinical decision will be altered, and no additional examination, treatment, follow-up visit, or biospecimen collection will be performed.
The unit of participant-level registration is the patient, while the principal analytic structure is the ICU encounter and the patient-day. ICU admission time will serve as the common temporal anchor. Monitoring, laboratory, fluid, medication, organ-support, diagnostic, and demographic data will be extracted from the ICCA reporting layer and aggregated primarily into consecutive 24-hour windows. Alternative 12-hour or shorter windows may be evaluated in sensitivity analyses.
Daily physiological state vectors will be constructed across 10 domains: oxygenation; ventilation and respiratory drive; hemodynamic perfusion; renal-fluid balance; hepatic-metabolic clearance; inflammation-immune activation; coagulation-blood integrity; brain-autonomic regulation; bioenergetic and acid-base status; and treatment-support burden. Prespecified data-governance rules will be used for variable-source mapping, unit harmonization, time alignment, limited carry-forward, missing-data handling, and physiological-range checks.
Principal component analysis will provide the primary low-dimensional state-space representation. UMAP may be used for supplementary visualization and local-structure exploration but will not be the sole primary analytical framework. Enhanced trajectory features will include state position, displacement, trajectory length, speed, acceleration, turning angle, curvature, local variability, lag-1 autocorrelation, recovery slope, and cross-domain coupling. These features will be used to characterize high-risk regions, possible basin crossings and critical transitions, and physiological resilience.
Eligible records will be divided chronologically into an earlier derivation cohort and a later temporal validation cohort, with an intended split of approximately 70% and 30%, respectively. The exact cutoff will be locked before analysis. The primary analysis will evaluate the association between state-space and trajectory features and a composite clinical deterioration outcome occurring within 72 hours after each eligible index patient-day. Multivariable logistic regression or discrete-time risk models will be used for the primary outcome. ICU and in-hospital mortality may be evaluated using Cox regression or competing-risk methods, and other outcomes will be analyzed with appropriate regression or time-to-event models. Internal validation will use the temporal validation cohort and bootstrap resampling to assess discrimination, calibration, and robustness.
The source data will remain in the hospital-controlled information environment. Investigators will use a deidentified research dataset without direct identifiers and without access to the reidentification key. Only aggregated results, model parameters, and approved figures will be released. The study seeks a waiver of written informed consent because it is retrospective, non-interventional, uses deidentified existing data, and does not affect participants' current or future care.