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A model for predicting the outcome and risk of sequelae of COVID-19 based on complex causal networks

A model for predicting the outcome and risk of sequelae of COVID-19 based on complex causal networks

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2300077626
Enrollment
Unknown
Registered
2023-11-14
Start date
2023-11-15
Completion date
Unknown
Last updated
2023-11-21

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

Conditions

COVID-19

Interventions

Case series:none

Sponsors

Beijing Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 100 Years

Inclusion criteria

Inclusion criteria: (1) Age 18 or above, no restrictions on gender, ethnicity, occupation, etc.; (2) Have data on COVID-19 infection and recovery period; (3) Sign an informed consent form.

Exclusion criteria

Exclusion criteria: (1) In the acute phase of the disease, including acute heart failure, acute coronary syndrome, chronic obstructive pulmonary disease exacerbation, and acute pneumonia, etc.; (2) Have obvious data missing or errors, unable to perform effective causal network construction and prediction; (3) People who are unwilling to participate or cannot cooperate with the research data collection.

Design outcomes

Primary

MeasureTime frame
accuracy;F1 score;precision;recall;

Secondary

MeasureTime frame
model complexity;model stability;model interpretability;model scalability;

Countries

China

Contacts

Public ContactGang Song

Beijing Hospital

songgang4689@bjhmoh.cn+86 152 1090 7148

Outcome results

None listed

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