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NCT Number: NCT07773571

ICCA-Based ICU Physiological State Space Monitor

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.

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Key information

Conditions

Critical Illness Disease Attributes Pathologic Processes Pathological Conditions, Signs and Symptoms

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Zhongshan Hospital

Shanghai, Shanghai Municipality, 200032, China

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Age 18 years or older.
  • Admission to an ICU at Zhongshan Hospital, Fudan University between September 2021 and May 31, 2026, with a uniquely identifiable ICU encounter in the ICCA reporting-layer database.
  • ICU length of stay of at least 24 hours.
  • Availability of core variables from at least four physiological domains and at least one patient-day suitable for modeling.

Exclusion criteria

  • Duplicate import of the same ICU encounter that cannot be reliably deduplicated.
  • Severe missingness, inconsistency, or irreconcilable error in key identifiers, ICU admission/discharge times, or core timestamps.
  • Test data, demonstration data, or records determined through data governance to be non-genuine patient records.
  • Inability to lock the primary source mapping for key variables, or overall data quality insufficient to support construction of the physiological state vector.

Treatment and study plan

Multidimensional ICU Physiological State and Trajectory Features

Other

The exposure of interest is the participant's multidimensional physiological state and trajectory derived from routinely collected ICU monitoring, laboratory, fluid, medication, organ-support, diagnostic, and demographic data. Daily state vectors will cover 10 physiological domains. 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. The investigators will not assign any exposure, treatment, or clinical intervention.

Primary outcomes

  1. Composite Clinical Deterioration Within 72 Hours

    Time frame: Within 72 hours following each eligible index patient-day

    A binary composite outcome defined by the occurrence of at least one of the following events during the 72-hour window after an eligible index patient-day: ICU death; new initiation of invasive mechanical ventilation; new initiation of continuous renal replacement therapy (CRRT); new initiation of extracorporeal membrane oxygenation (ECMO); or a prespecified significant escalation in vasoactive medication support. A participant/index window meeting more than one component will be counted once for the composite outcome.

Secondary outcomes

  1. ICU mortality

    Time frame: From ICU admission through ICU discharge, an average of approximately 5 days

    Death from any cause before discharge from the ICU.

  2. In-Hospital Mortality

    Time frame: From hospital admission through hospital discharge, an average of approximately 30 days

    Death from any cause before discharge from the index hospitalization.

  3. Duration of Invasive Mechanical Ventilation

    Time frame: From ICU admission through ICU discharge, an average of approximately 5 days

    Total number of calendar days during which invasive mechanical ventilation is used during the ICU stay.

  4. Duration of Continuous Renal Replacement Therapy

    Time frame: From ICU admission through ICU discharge, an average of approximately 5 days

    Total number of calendar days during which CRRT is used during the ICU stay.

  5. Duration of Vasoactive Medication Exposure

    Time frame: From ICU admission through ICU discharge, an average of approximately 5 days

    Total number of calendar days with recorded vasoactive medication support during the ICU stay.

  6. ICU Length of Stay

    Time frame: From ICU admission through ICU discharge, an average of approximately 5 days

    Time from ICU admission to ICU discharge, reported in days.

  7. Hospital Length of Stay

    Time frame: From hospital admission through hospital discharge, an average of approximately 30 days

    Time from hospital admission to hospital discharge, reported in days.

Other outcomes

  1. Estimated 72-Hour Composite Deterioration Risk by Physiological State-Space Location

    Time frame: Within 72 hours following each eligible index patient-day

    Estimated probability of the 72-hour composite deterioration outcome associated with locations in the low-dimensional physiological state space derived from the prespecified state-space model. The estimated probability will be reported as a percentage ranging from 0% to 100%. High-risk bands, pockets, and local risk landscapes will be considered descriptive features of the estimated risk surface rather than separate outcome measures.

  2. State-Space Displacement Between Consecutive Patient-Days

    Time frame: Across consecutive eligible patient-days from ICU admission through ICU discharge, an average of approximately 5 days

    Magnitude of change in the participant's position in the PCA-derived low-dimensional physiological state space between two consecutive eligible patient-days, calculated using the prespecified trajectory algorithm and reported in standardized state-space units.

  3. Physiological State-Space Trajectory Length

    Time frame: From the first through the last eligible patient-day during the ICU stay, an average of approximately 5 days

    Cumulative path length of the participant's trajectory across consecutive positions in the PCA-derived physiological state space, calculated as the accumulated state-space displacement and reported in standardized state-space units.

  4. Physiological State-Space Trajectory Speed

    Time frame: Across consecutive eligible patient-days from ICU admission through ICU discharge, an average of approximately 5 days

    Rate of change in physiological state-space position between consecutive eligible patient-days, calculated from state-space displacement over elapsed time and reported in standardized state-space units per day.

  5. Physiological State-Space Trajectory Acceleration

    Time frame: Across consecutive eligible patient-days from ICU admission through ICU discharge, an average of approximately 5 days

    Change in physiological state-space trajectory speed between successive eligible patient-day intervals, calculated using the prespecified trajectory algorithm and reported in standardized state-space units per day squared.

  6. Physiological State-Space Turning Angle

    Time frame: Across consecutive eligible patient-days from ICU admission through ICU discharge, an average of approximately 5 days

    Angular change in trajectory direction between successive trajectory segments derived from consecutive physiological state-space positions, reported in degrees.

  7. Physiological State-Space Trajectory Curvature

    Time frame: Across consecutive eligible patient-days from ICU admission through ICU discharge, an average of approximately 5 days

    Curvature of the participant's physiological state-space trajectory derived from consecutive state-space positions using the prespecified trajectory algorithm. Higher values indicate greater local directional change in the trajectory.

  8. Local Physiological State-Space Variability

    Time frame: Across consecutive eligible patient-days from ICU admission through ICU discharge, an average of approximately 5 days

    Within-participant variability in physiological state-space position across consecutive eligible patient-days, calculated using the prespecified trajectory analysis and reported in standardized state-space units. Higher values indicate greater short-term physiological variability.

  9. Lag-1 Autocorrelation of Physiological State-Space Trajectory

    Time frame: Across consecutive eligible patient-days from ICU admission through ICU discharge, an average of approximately 5 days

    Lag-1 autocorrelation coefficient quantifying the correlation between consecutive physiological state-space observations within the participant's trajectory. The coefficient ranges from -1 to 1, with higher positive values indicating greater persistence of the preceding physiological state.

  10. Area Under the Receiver Operating Characteristic Curve for 72-Hour Composite Deterioration

    Time frame: Within 72 hours following each eligible index patient-day in the temporal validation cohort

    Discrimination of the prespecified state-space and trajectory prediction model in the temporal validation cohort, assessed using the area under the receiver operating characteristic curve (AUROC) for the 72-hour composite deterioration outcome. AUROC ranges from 0 to 1, with higher values indicating better discrimination.

  11. Calibration Slope for Predicted 72-Hour Composite Deterioration Risk

    Time frame: Within 72 hours following each eligible index patient-day in the temporal validation cohort

    Calibration of the prespecified state-space and trajectory prediction model in the temporal validation cohort, assessed using the calibration slope comparing predicted probabilities with observed 72-hour composite deterioration outcomes. A calibration slope of 1 indicates ideal calibration.

  12. Brier Score for Prediction of 72-Hour Composite Deterioration

    Time frame: Within 72 hours following each eligible index patient-day in the temporal validation cohort

    Overall prediction error of the prespecified state-space and trajectory prediction model in the temporal validation cohort, assessed using the Brier score, calculated as the mean squared difference between predicted probabilities and observed binary 72-hour composite deterioration outcomes. The Brier score ranges from 0 to 1, with lower values indicating better predictive accuracy.

Sponsors and collaborators

Lead sponsor

Shanghai Zhongshan Hospital

Other

Registry information

Official study title

Development of an ICU Physiological State Space Monitor Based on the ICCA Database: A Single-Center Retrospective Observational Study

Important dates

Study start
2026
Primary completion
2027
Study completion
2029
First posted
Aug 19, 2026
Registry last updated
Aug 19, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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