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China Collaborative Study on Epidemiology of Acute Kidney Injury

China Collaborative Study on Epidemiology of Acute Kidney Injury

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT03054142
Enrollment
1000000
Registered
2017-02-15
Start date
2017-01-31
Completion date
2027-12-31
Last updated
2022-12-13

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

Conditions

Acute Kidney Injury

Brief summary

Acute kidney injury (AKI) is a common clinical syndrome, especially patients in the hospital. AKI has become a huge medical burden in China. Little information is available about this disease burden in our country. The investigators aimed to evaluate the burden of AKI and to analyze the related risk factors.

Detailed description

The investigators launch a nationwide of all patients, who were admitted to hospital from 2011-2016. Patients were diagnosed on the basis of changes in serum creatinine by the laboratory information system. The investigators assessed rates of AKI according to the criteria of 2012 Kidney Disease Improving Global Outcomes (KDIGO).

Interventions

OTHERno intervention

Sponsors

XinLing Liang
Lead SponsorOTHER

Study design

Observational model
CASE_CONTROL
Time perspective
RETROSPECTIVE

Eligibility

Sex/Gender
ALL
Healthy volunteers
No

Inclusion criteria

* The patients diagnosed on the basis of changes in serum creatinine according to the criteria of 2012 Kidney Disease Improving Global Outcomes(KDIGO)

Exclusion criteria

* Serum creatinine record less than two times during hospitalization * Patients being diagnosed with End-stage kidney disease (chronic kidney disease stage 5) * Nephrectomy * Kidney transplantation * Peak serum creatinine of less than 53µ mol/L * Serum creatinine decrease after amputation

Design outcomes

Primary

MeasureTime frame
Incidence of AKIJan. 2011 to Oct. 2016

Secondary

MeasureTime frameDescription
Recognition rate of AKIJan. 2011 to Oct. 2016Using machine learning and deep learning methods to establish AKI prediction model and risk models
Proportion of nephrology referralJan. 2011 to Oct. 2016
In-hospital mortalityJan. 2011 to Oct. 2016
Longer ICU stayJan. 2011 to Oct. 2016
Higher medical costJan. 2011 to Oct. 2016

Countries

China

Contacts

Primary ContactLiang Xinling, M.D.,Ph.D
xinlingliang@139.com13808819770
Backup ContactLiang Xinling, M.D.,Ph.D
xinlingliang@139.com86-13808819770

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 24, 2026