Construction and Verification of a Machine Learning-Based Early Warning Model for Unplanned ICU Admission among Elderly Hospitalized Patients

Status

Active, not recruiting

Phases

Early Phase 1

Study type

Observational

Source

ChiCTR

Registry ID

ChiCTR2600127711

Enrollment

Unknown

Registered

2026-07-06

Start date

2026-07-08

Completion date

Unknown

Last updated

2026-07-13

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

No specific diseases are involved

Interventions

Observation group of elderly hospitalized patients:None

Eligibility

Sex/Gender

All

Age

60 Years to No maximum

Inclusion criteria

Inclusion criteria: 1.Age >= 60 years old; 2.Inpatients.

Exclusion criteria

Exclusion criteria: 1. Elderly patients scheduled for ICU admission; 2. Hospital stay <= 3 days; 3. Patients with Alzheimer's disease; 4. Patients in terminal condition.

Design outcomes

Primary

Measure	Time frame
Predictive efficacy (AUC, sensitivity, specificity) of self-developed early warning scale;	—

Secondary

Measure	Time frame
Incidence of unplanned ICU admission in elderly inpatients;Types, degrees and incidence rates of adverse events;Non-specific symptom indicators;	—

Countries

China

Contacts

Public ContactWang Xing

Jiangsu Provincial Hospital of Chinese Medicine

wangxing1964@163.com+86 13 913 998 3636

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Jul 23, 2026