NCT07803237

Brief Summary

This prospective observational cohort study aims to identify independent predictors of rapid chronic kidney disease (CKD) progression and determine its incidence among predialysis CKD patients. A total of 190 adult patients will be enrolled from the nephrology outpatient clinic and inpatient ward at Assiut University Hospitals and followed for 24 months. Rapid progression is defined as a sustained decline in eGFR \> 5 mL/min/1.73 m² per year according to KDIGO 2024 criteria. Clinical and laboratory parameters will be assessed at baseline and during follow-up to identify predictive factors

Trial Health

65
Monitor

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
190

participants targeted

Target at P50-P75 for all trials

Timeline
17mo left

Started Sep 2026

Status
not yet recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

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Study Timeline

Key milestones and dates

Study Progress6%
Sep 2026Mar 2028

First Submitted

Initial submission to the registry

August 31, 2026

Completed
1 day until next milestone

Study Start

First participant enrolled

September 1, 2026

Completed
2 days until next milestone

First Posted

Study publicly available on registry

September 3, 2026

Completed
12 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

September 1, 2027

Expected
6 months until next milestone

Study Completion

Last participant's last visit for all outcomes

March 1, 2028

Last Updated

September 3, 2026

Status Verified

August 1, 2026

Enrollment Period

1 year

First QC Date

August 31, 2026

Last Update Submit

August 31, 2026

Conditions

Keywords

Chronic Kidney DiseaseCKDPredictors; Predialysis; eGFR

Outcome Measures

Primary Outcomes (1)

  • Incidence of rapid CKD progression

    Proportion of participants who experience rapid CKD progression, defined as a sustained decline in eGFR greater than 5 mL/min/1.73 m² per year.

    24 months

Secondary Outcomes (3)

  • Independent predictors of rapid CKD progression

    24 months

  • Change in estimated glomerular filtration rate (eGFR)

    Baseline, 12 months, and 24 months

  • Change in albuminuria

    Baseline, 12 months, and 24 months

Study Arms (1)

Predialysis CKD Patients

Adult patients with chronic kidney disease not receiving maintenance dialysis, followed prospectively for 24 months to assess rapid disease progression. This is an observational study with no intervention.

Eligibility Criteria

Age18 Years+
Sexall
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

Adult patients with predialysis chronic kidney disease (CKD) attending the Nephrology outpatient clinic and inpatient ward at Assiut University Hospitals.

You may qualify if:

  • Age 18 years or older
  • Diagnosis of CKD according to KDIGO 2024 criteria
  • Predialysis status (not on maintenance dialysis)
  • Ability to provide written informed consent
  • Availability for 24-month follow-up

You may not qualify if:

  • Acute kidney injury
  • Current maintenance dialysis
  • Previous kidney transplantation
  • Active malignancy
  • Pregnancy

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Related Publications (3)

  • Ali I, Chinnadurai R, Ibrahim ST, Green D, Kalra PA. Predictive factors of rapid linear renal progression and mortality in patients with chronic kidney disease. BMC Nephrol. 2020 Aug 14;21(1):345. doi: 10.1186/s12882-020-01982-8.

    PMID: 32795261BACKGROUND
  • Lee FY, Islahudin F, Ali Nasiruddin AY, Abdul Gafor AH, Wong HS, Bavanandan S, Mohd Saffian S, Md Redzuan A, Mohd Tahir NA, Makmor-Bakry M. Effects of CYP3A5 Polymorphism on Rapid Progression of Chronic Kidney Disease: A Prospective, Multicentre Study. J Pers Med. 2021 Mar 30;11(4):252. doi: 10.3390/jpm11040252.

    PMID: 33808503BACKGROUND
  • Inaguma D, Hayashi H, Yanagiya R, Koseki A, Iwamori T, Kudo M, Fukuma S, Yuzawa Y. Development of a machine learning-based prediction model for extremely rapid decline in estimated glomerular filtration rate in patients with chronic kidney disease: a retrospective cohort study using a large data set from a hospital in Japan. BMJ Open. 2022 Jun 9;12(6):e058833. doi: 10.1136/bmjopen-2021-058833.

    PMID: 35680264BACKGROUND

MeSH Terms

Conditions

Renal Insufficiency, ChronicRenal InsufficiencyKidney Failure, Chronic

Condition Hierarchy (Ancestors)

Kidney DiseasesUrologic DiseasesFemale Urogenital DiseasesFemale Urogenital Diseases and Pregnancy ComplicationsUrogenital DiseasesMale Urogenital DiseasesChronic DiseaseDisease AttributesPathologic ProcessesPathological Conditions, Signs and Symptoms

Study Officials

  • Effat A tony, prof

    Internal Medicine Department, Assiut University Hospitals

    STUDY CHAIR

Central Study Contacts

Noura D Fahmi, Resident

CONTACT

Study Design

Study Type
observational
Observational Model
COHORT
Time Perspective
PROSPECTIVE
Target Duration
24 Months
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Resident Physician department of internal medicine

Study Record Dates

First Submitted

August 31, 2026

First Posted

September 3, 2026

Study Start

September 1, 2026

Primary Completion (Estimated)

September 1, 2027

Study Completion (Estimated)

March 1, 2028

Last Updated

September 3, 2026

Record last verified: 2026-08