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Time series analysis and prediction of the number of patients transferred to the PACU during peak periods based on Python

Time series analysis and prediction of the number of patients transferred to the PACU during peak periods based on Python

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400091786
Enrollment
Unknown
Registered
2024-11-04
Start date
2024-10-16
Completion date
Unknown
Last updated
2024-11-11

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

Conditions

None

Interventions

Gold Standard:Compare the actual number of patients admitted to PACU from August 1, 2024, to August 30, 2024, with the numbers predicted by the ARIMA and LSTM models for the same period.
Index test:Mean Squared Error,Mean Absolute Error,Mean Absolute Percentage Error.

Sponsors

Shenshan Medical Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: Postoperative patients admitted to PACU

Exclusion criteria

Exclusion criteria: Patients with infectious diseases such as hepatitis C and syphilis who cannot be admitted to PACU for recovery; patients who are transferred directly to the ICU due to severe conditions

Design outcomes

Primary

MeasureTime frame
Mean Squared Error;Mean Absolute Error;Mean Absolute Percentage Error;—

Countries

China

Contacts

Public ContactLuo Jianwei

Sun Yat-sen Memorial Hospital, Sun Yat-sen University

363256833@qq.com+86 159 8918 5387

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026