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Applying deep learning to predict the outcomes in renal dialysis patients with COVID-19 in the early stage

Applying deep learning to predict the outcomes in renal dialysis patients with COVID-19 in the early stage

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2200059778
Enrollment
Unknown
Registered
2022-05-11
Start date
2022-05-01
Completion date
Unknown
Last updated
2024-04-01

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

Conditions

COVID-19

Interventions

Gold Standard:Shanghai Expert Consensus on Comprehensive Treatment of COVID-19
Index test:Predictive models of disease outcome

Sponsors

Shanghai Jiao Tong University Affiliated Sixth People's Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 90 Years

Inclusion criteria

Inclusion criteria: 1. Renal dialysis patients diagnosed with COVID-19; 2. All patients with renal dialysis meet the diagnostic criteria of light, common and severe in novel coronavirus in the Expert Consensus of Comprehensive Treatment of Coronavirus in Shanghai in 2019; 3. At least 18 years old; 4. Voluntary participation in the clinical study.

Exclusion criteria

Exclusion criteria: 1. Combined with other serious underlying lung diseases (such as chronic obstructive pulmonary disease, lung tumors, tuberculosis, etc.); 2. Pregnant or lactating patients; 3. Critically ill patients whose survival period is less than 7 days or with insufficient follow-up data; 4. There are many artifacts in the inspection image quality, and the blood sample collection results are abnormal caused by human factors.

Design outcomes

Primary

MeasureTime frame
Diagnostic performance;Sensitivity;Specificity;

Countries

China

Contacts

Public ContactWu Chungen

Shanghai Jiao Tong University Affiliated Sixth People's Hospital

wucgsh@163.com+86 189301775 59

Outcome results

None listed

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