Kidney Week

Abstract: TH-PO1089

Quality of Life of Patients with CKD: A Cross Sectional Analysis from the ICKD Cohort

Session Information

• CKD: Epidemiology, Risk Factors, Prevention - I
  October 25, 2018 | Location: Exhibit Hall, San Diego Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: CKD (Non-Dialysis)

• 1901 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention

Authors

• Yadav, Ashok Kumar, PGIMER, Chandigarh, India

Ashok Kumar Yadav,

• Kumar, Vivek, Postgraduate Institute of Medical Education and Research, Chandigarh, India

Vivek Kumar,

• Gang, Sishir D., Muljibhai Patel Urological Hospital, Nadiad, Gujarat, India

Sishir D. Gang,

• Parameswaran, Sreejith, JIPMER, Ponidcherry, India

Sreejith Parameswaran,

• Prasad, Narayan, SGPGIMS CAMPUS, Lucknow, India

Narayan Prasad,

• Varughese, Santosh, CMC , Vellore, India

Santosh Varughese,

• Gupta, Krishan Lal L., Postgraduate Institute of Medical Education & Research, Chandigarh, India

Krishan Lal L. Gupta,

• Jha, Vivekanand, George Institute for Global Health, New Delhi, India

Vivekanand Jha,

Group or Team Name

• ICKD study Investigators

Background

Improving symptoms and function in daily life are important patient centered outcomes in chronic diseases. Health-related quality of life (QOL) is an important key indicator of how a condition affects the patient’s life, and QOL has been expressed as the subjective assessment of the impact of disease and its treatment across the physical, psychological and social domains of functioning. We report QOL in patients with early stages of CKD who have been enrolled in the ICKD study.

Methods

All subjects, who had been enrolled in the on-going, multi-centric ICKD cohort study and had KDQOL-36^TM survey data recorded at baseline, were eligible for the present study. We assessed QoL by KDQOL-36^TM. Raw scores are converted to subscale scores using the Microsoft Excel tool (KDQOL-36^TM Scoring Program, v 2.0). These subscales are Mental Component Summary (MCS), Physical Component Summary (PCS), Symptoms, Effect and Burden. Each subscale category is scored between 0-100, with higher scores indicating better quality of life. demographic and socioeconomica as well as clinical parameter were studied for association with QOL. Low QOL was defined as subscale score that was 1 SD less than the mean for the respective subscale.

Results

The mean scores for KDQOL-36^TM subscales were 48.81±9.93, 44.17±9.49, 65.29±31.40, 81.31±24.70 and 86.68±21.43 for PCS, MCS, burden, effects and symptoms, respectively. Urban residence, non-vegetarian dietary pattern, education below high school, occupational exposure and lower income were associated with lower scores across all KDQOL-36 subscales (p<0.05). Professional workers had high score across all KDQOL-36 subscales compared to farmers, housewife and unemployed subjects (p<0.01). Increasing quartile of annual income ws associated with higher scores in all subscales (p<0.01). Urban residence, occupational exposure and housewife status were associated with low QOL across all KDQOL-36^TM subscales (p<0.05). Education below high school, lower eGFR, low annual income and BMI <18 kg/m² were associated with low QOL in all subscale scores (p<0.01) except in symptoms subscale.

Conclusion

We identified the association between a number of clinical and socio-economic variables related and one or more KDQOL-36^TM subscales.

Funding

• Government Support - Non-U.S.