Research Paper Overhydration Negatively Affects Quality Of .
Int. J. Med. Sci. 2016, Vol. 13IvyspringInternational Publisher686International Journal of Medical Sciences2016; 13(9): 686-695. doi: 10.7150/ijms.16372Research PaperOverhydration Negatively Affects Quality of Life inPeritoneal Dialysis Patients: Evidence from a ProspectiveObservational StudyHye Eun Yoon1, Young Joo Kwon2, Ho Cheol Song3, Jin Kuk Kim4, Young Rim Song5, Seok Joon Shin1,Hyung Wook Kim6, Chang Hwa Lee7, Tae Won Lee8, Young Ok Kim9, Byung Soo Kim10, Kyoung HyoubMoon11, Yoon Kyung Chang12, Seong Suk Kim13, Kitae Bang14, Jong Tae Cho15, Sung Ro Yun16, Ki RyangNa17, Yang Wook Kim18, Byoung Geun Han19, Jong Hoon Chung20, Kwang Young Lee21, Jong HyeokJeong22, Eun Ah Hwang23, Yong-Soo Kim24 , the Quality of Life of Dialysis Patients (QOLD) Study 19.20.21.22.23.24.Department of Internal Medicine, Incheon St. Mary’s Hospital, College of Medicine, The Catholic University of Korea;Department of Internal Medicine, Guro Hospital, Korea University;Department of Internal Medicine, Bucheon St. Mary’s Hospital, The Catholic University of Korea;Department of Internal Medicine, Soonchunhyang University Bucheon Hospital;Department of Internal Medicine, Hallym University Sacred Heart Hospital;Department of Internal Medicine, St. Vincent’s Hospital, The Catholic University of Korea;Department of Internal Medicine, Hanyang University Medical Center;Department of Internal Medicine, KyungHee University Medical Center;Department of Internal Medicine, Uijeongbu St. Mary’s Hospital, The Catholic University of Korea;Department of Internal Medicine, St. Paul’s Hospital, The Catholic University of Korea;Department of Internal Medicine, Veterans Health Service Medical Center;Department of Internal Medicine, Daejeon St. Mary’s Hospital, The Catholic University of Korea;Department of Internal Medicine, Daejeon Sun Hospital;Department of Internal Medicine, Eulji University Hospital;Department of Internal Medicine, Dankook University Hospital;Department of Internal Medicine, Konyang University Hospital;Department of Internal Medicine, Chungnam National University Hospital;Department of Internal Medicine, Inje University Haeundae Paik Hospital;Department of Internal Medicine, Yonsei University Wonju College of Medicine;Department of Internal Medicine, Chosun University Hospital;Department of Internal Medicine, Presbyterian Medical Center;Department of Internal Medicine, St. Carollo Hospital;Department of Internal Medicine, Keimyung University Dongsan Medical Center;Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea Corresponding author: Yong-Soo Kim, MD, PhD. Department of Internal medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, 222,Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea. Tel: 822-2258-6036 Fax: 822-599-3589 E-mail: kimcmc@catholic.ac.kr. Ivyspring International Publisher. Reproduction is permitted for personal, noncommercial use, provided that the article is in whole, unmodified, and properly cited. Seehttp://ivyspring.com/terms for terms and conditions.Received: 2016.06.03; Accepted: 2016.07.20; Published: 2016.08.11AbstractBackgound: This study evaluated whether the hydration status affected health-related quality oflife (HRQOL) during 12 months in peritoneal dialysis (PD) patients.Methods: The hydration status and the HRQOL were examined at baseline and after 12 monthsusing a bioimpedance spectroscopy and Kidney Disease Quality of Life-Short Form, respectively inPD patients. Four hundred eighty-one patients were included and divided according to the baselineoverhydration (OH) value; normohydration group (NH group, -2L OH 2L, n 266) andoverhydration group (OH group, OH 2L, n 215). Baseline HRQOL scores were comparedbetween the two groups. The subjects were re-stratified into quartiles according to the OHdifference (OH value at baseline – OH value at 12 months; -1, -1 – -0.1, -0.1 – 1, and 1L). Therelations of OH difference with HRQOL scores at 12 months and the association of OH differencewith the HRQOL score difference (HRQOL score at baseline – HRQOL score at 12 months)were assessed.Results: The OH group showed significantly lower baseline physical and mental health scores(PCS and MCS), and kidney disease component scores (KDCS) compared with the NH group (all,http://www.medsci.org
Int. J. Med. Sci. 2016, Vol. 13687P 0.01). At 12 months, the adjusted PCS, MCS, and KDCS significantly increased as the OHdifference quartiles increased (P 0.001, P 0.002, P 0.001, respectively). In multivariate analysis,the OH difference was independently associated with higher PCS (β 2.04, P .001), MCS(β 1.02, P 0.002), and KDCS (β 1.06, P 0.001) at 12 months. The OH difference wasindependently associated with the PCS difference (β -1.81, P 0.001), MCS difference (β -0.92,P 0.01), and KDCS difference (β -0.90, P 0.001).Conclusion: The hydration status was associated with HRQOL and increased hydration statusnegatively affected HRQOL after 12 months in PD patients.Key words: bioimpedance, fluid overload, overhydration, peritoneal dialysis, quality of life.IntroductionEuvolemia is a predictor of outcome inperitoneal dialysis (PD) patients [1, 2]. It is becausevolume overload is related with cardiac dysfunction[3, 4], arterial stiffness [5] and inflammation [6].Although achievement of euvolemia is crucial indialysis patients, assessment of volume status isrelatively crude in clinical practice. Bioimpedancespectroscopy (BIS) measures conductance andreactance at different frequencies by measuring theflow of electrical current through the body, andallows accurate measurement of fluid status [7].Different indices of hydration status are provided bythe BIS, including extracellular water (ECW),intracellular water (ICW), total body water (TBW),and overhydration (OH). The ECW/TBW is mostwidely accepted as a hydration index, however it canbe confounded by obesity [8], and it does not give thedegree of tissue hydration. By contrast, the OH dataprovides an estimate of hydration in liters allowingthe clinician to easily set a target weight for thepatient without calculating an index [1]. Recently itwas reported that the OH value was an independentpredictor of death in PD patients [1].Health-related quality of life (HRQOL) is apredictor of mortality in end-stage renal disease(ESRD) patients [9, 10]. Multiple factors are known toaffect HRQOL in ESRD patients, including underlyingdisease, nutrition, inflammation, adverse effects oftreatment modality, social support and rapport withcare providers [10-14]. Recent literature showed thatbody composition is associated with HRQOL inhemodialysis patients [15]. It was also reported thathydration status is related with HRQOL in elderlydialysis patients, which included a relatively smallnumber of patients [16]. However, whether thehydration status affects HRQOL has not beenevaluated in a large number of dialysis patients in aprospective manner.The Quality of Life of Dialysis (QOLD) studywas designed to analyze the change in HRQOL,depressive symptoms, and body composition ofdialysis patients in Korea. In this prospective,observational multi-center study, 708 PD patientswere recruited from 24 centers in Korea. In the currentanalyses, we analyzed 481 PD patients who wereeligible for both the hydration status and HRQOLdata at baseline and after 12 months to examine thehypothesis that hypervolemia is associated withworse HRQOL in PD patients.MethodsStudy populationWe studied PD patients who participated in theQOLD study. The QOLD study is a prospective,observational multi-center study to analyze thechange in HRQOL, depressive symptoms, and bodycomposition of dialysis patients in Korea. Inclusioncriteria were age 18 years and incident or prevalentdialysis patients. Exclusion criteria were those whohad psychiatric disease, current malignancy or livercirrhosis, who were bed-ridden, or who cannotundergo bioimpedance analysis because ofdefibrillators, artificial joints, pins or limbamputations. The study visits were conducted at eachcenter at baseline and 12 months by studycoordinators. At each visit (baseline and after 12months), HRQOL, depressive symptoms, and bodycomposition were assessed. Seven hundred eight PDpatients were recruited from 24 centers in Korea.In the current analyses, 481 PD patients, whowere eligible for both the hydration status andHRQOL data at baseline and after 12 months, wereincluded. As shown in Figure 1, 634 patients wereeligible for the baseline OH value. We used thebaseline OH value to classify the hydration status ofthe patients. The overhydration group (OH group)was defined according to a previous study whichshowed that 2.0 liters was a reasonable cutoff valuefor OH in PD patients (OH 2L) [17].Normohydration group (NH group) was defined aspatients with baseline OH value between 2L (-2L OH 2L). Six patients who were in anunderhydration status (OH -2L) were excluded fromthe current analysis as this study was to compare theOH group and NH group. Additionally, 111 patientshttp://www.medsci.org
Int. J. Med. Sci. 2016, Vol. 13who were lost for follow-up data, 33 patients whodied during the study period and 3 patients whoreceived renal transplantation were excluded. Among481 patients included in this study, 266 patients werein the NH group and 215 patients were in the OHgroup at baseline.The subjects were additionally stratified intoquartiles according to the change in the OH valueduring 12 months. The change in the OH value wasdefined as the OH difference, which is the differencebetween the baseline OH value and that at 12 months(OH difference OH value at baseline – OH value at12 months). The OH difference quartiles were;quartile 1 (OH difference -1L, n 120), quartile 2 (-1L OH difference -0.1L, n 120), quartile 3 (-0.1L OH difference 1L, n 121), and quartile 4 (OHdifference 1L, n 120).InstrumentsHRQOL was examined using the Korean versionof Kidney Disease Quality of Life-Short Form(KDQOL-SF) [18] at baseline and at 12 months. TheKDQOL-SF includes 36 items derived from a generic,validated instrument (SF-36) as well as 43 kidney688disease-targeted items and one overall health-ratingitem. This instrument has been validated in the ESRDpopulation [19]. The SF-36 domain includes subscalesof physical functioning, role-physical, bodily pain,general health, emotional well-being, ydisease-targeted items include subscales ofsymptom/problem list, effects of kidney disease,burden of kidney disease, work status, cognitivefunction, quality of social interaction, sexual function,sleep, social support, dialysis staff encouragement,and patient satisfaction to staff. Responses to theKDQOL-SF were used to determine the physicalhealth component scores (PCS), mental healthcomponent scores (MCS), and kidney diseasecomponent scores (KDCS). The change in eachcomponent score of KDQOL-SF was defined as theHRQOL score difference, which is the differencebetween the baseline score and score at 12 months(PCS difference PCS at baseline – PCS at 12 months;MCS difference MCS at baseline – MCS at 12months; KDCS difference KDCS at baseline – KDCSat 12 months).Figure 1. Patient population included in this study.http://www.medsci.org
Int. J. Med. Sci. 2016, Vol. 13Measurements of hydration status and bodycompositionThe hydration status and body compositionwere assessed at baseline and after 12 months. The BISdevice (Body Composition Monitor, FreseniusMedical Care, Germany) was used to measurebioimpedance at 50 frequencies between 5 and 1000kHz. The measurement was performed by placingelectrodes on one hand and one foot in the BIS deviceand entering current height and weight data into themachine. BIS measurements were performed with theperitoneal dialysate in situ, and were performed byone reference PD physician or nurse in each center.ECW, ICW, TBW, and OH were determined from themeasured impedance data. The OH/ECW wascalculated as the percentage of OH to ECW. The leantissue index (LTI) was calculated as the quotient oflean tissue mass/height2 (kg/m2). The adipose tissueindex (ATI) was calculated as the quotient of adiposetissue mass/height2 (kg/m2).Other variablesPatients’ comorbid status was quantified usingthe modified Charlson Comorbidity Index (CCI) [20].Blood pressure was recorded as the mean of twoconsecutive measurements with 5 minutes’ interval,using one single calibrated device in each center.Height and weight were measured using one singlecalibrated device in each center. Body mass index(BMI) was calculated as the quotient ofweight/height2 (kg/m2). Peritoneal membranecharacteristics were determined based on the resultsof the peritoneal equilibration test (PET) at the time ofbody composition measurements. Dialysis adequacy(total KT/Vurea per week), mean of renal urea andcreatinine clearance (renal CrCl), 24-h urine volume,ratio of dialysate to serum creatinine at 4-h PET (D/PCr), and laboratory values were collected. Dietaryprotein intake was estimated from the normalizedprotein equivalent of nitrogen appearance (nPNA)following the equation: PNA 15.1 0.1945 ureaappearance (mM/24 h) protein losses (g/24 h) [21].Statistical analysisContinuous data are expressed as the mean standard deviation (SD) or the median (range).Categorical variables are expressed as percentage oftotal. The normality of the distribution was assessedby the Shapiro-Wilk test. Differences between the NHgroup and the OH group were determined usingStudent’s t-test for variables with normal distributionor Wilcoxon rank-sum test for variables withnon-normal distribution. Categorical variables werecompared using a chi-square test or Fisher's exact test.Pearson’s correlation analysis was used to determine689the correlation between the OH difference and theHRQOL scores at 12 months. Analysis of covariancewas used to compare differences in the HRQOL scoresat 12 months between the OH difference quartiles.Linear regression test was used to determine theassociation of OH difference with the HRQOL scoresat 12 months and the HRQOL score difference.Multivariate models included the significantlyassociated parameters according to their weight onunivariate testing and clinically fundamentalparameters. A P value of 0.05 was considered toindicate a statistically significant difference andstatistical analysis was performed using SAS.Ethics statement and trial registrationAll participants gave written informed consent,and the study protocol was approved by thefollowing institutional review boards of the centersparticipated in the study: Korea University GuroHospital, Catholic University of Korea Bucheon St.Mary’s Hospital, Incheon St. Mary’s Hospital, St.Vincent’s Hospital, St. Paul’s Hospital, Uijeongbu St.Mary’s Hospital, Daejeon St. Mary’s Hospital andSeoul St. Mary’s Hospital, Soonchunhyang UniversityHospital, Hallym University Medical Center,Hanyang University Medical Center, KyungHeeUniversity Medical Center, Veterans Health ServiceMedical Center, Daejeon Sun Hospital, EuljiUniversity Hospital, Dankook University Hospital,Konyang University Hospital, Chungnam NationalUniversity Hospital, Inje University Haeundae PaikHospital, Wonju Severance Christian Hospital,Chosun University Hospital, Presbyterian MedicalCenter, St. Carollo Hospital, and KeimyungUniversity Dongsan Medical Center. The study wasconducted from August 2010 to May 2014.The study was registered at clinicaltrials.gov(NCT01668628), and was conducted in adherence tothe Declaration of Helsinki. The authors confirm thatall onging and related trials for this intervention havebeen registered. There was a delay in registering thisstudy because centers were additionally recruited toparticipate in this study.ResultsBaseline characteristicsTable 1 shows the baseline characteristics andlaboratory and bioimpedance measurements of thetotal patients and the comparison between the NHgroup and OH group. More male, diabetes, andcontinuous ambulatory PD patients were in the OHgroup than the NH group. The OH group showedhigher CCI, total drained dialysate volume, andsystolic blood pressure compared to the NH group.The OH group had higher D/P Cr and more patientshttp://www.medsci.org
Int. J. Med. Sci. 2016, Vol. 13690with high average or high membrane transportertypes than the NH group. The OH group consisted ofless patients using 1.5% glucose bags only and morepatients using 2.5% glucose bag at least once a day.The nPNA values were significantly lower in the OHgroup compared to the NH group.At baseline, the OH group showed lowerhaemoglobin and albumin levels than the NH group.As expected, the OH group showed higher TBW,ECW, ICW, OH, OH/ECW values than the NHgroup. The ATI was significantly lower in the OHgroup compared to the NH group, but there was nodifference in the LTI.Table 1. Baseline characteristics and laboratory and bioimpedance measurements.AgeMale (%)Dialysis vintage (mo)Diabetes (%)Cause of ESRD BMI (kg/m2)Systolic blood pressure (mmHg)Diastolic blood pressure (mmHg)Peritoneal dialysis modality (%)CAPDAPDD/P Cr at 4-h PETType of membrane transport (%)LowLow averageHigh averageHighTotal drained dialysate volume (mL/day)Dialysate usage (%)1.5% glucose bags only2.5% glucose bag at least once4.25% glucose bag at least onceIcodextrin bag usage24-h urine volume (mL/day)Renal CrCl (mL/min/1.73m2)Total KT/Vurea per weeknPNA (g/kg/day)Laboratory measurementsHaemoglobin (g/dL)Creatinine (mg/dL)Sodium (mEq/L)Potassium (mEq/L)Albumin (g/dL)Total cholesterol (g/dL)C-reactive protein (g/dL)Bioimpedance measurementsTBW (L)ECW (L)ICW (L)OH (L)OH/ECW (%)LTI (kg/m2)ATI (kg/m2)PTotal patients in thecurrent analysisn 48151.3 11.1256 (53.2)23.6 34.1208 (43.2)NH groupOH groupn 26650.9 11.6117 (44)25.1 34.775 (28.2)n 21551.8 10.4139 (64.7)21.6 33.3133 (61.9)198 (41.2)179 (37.2)52 (10.8)52 (10.8)2.6 1.024.2 3.5132.2 21.880.7 12.767 (25.2)124 (46.6)37 (13.9)38 (14.3)2.4 0.924.2 3.7128.8 19.179.7 12.5131 (60.9)55 (25.6)15 (7)14 (6.5)2.8 1.124.2 3.3136.4 24.281.9 12.9424 (88.1)57 (11.9)0.60 0.11222 (83.5)44 (16.5)0.59 0.12202 (94)13 (6.1)0.62 0.1182 (17.0)232 (48.2)148 (30.8)19 (4.0)8469.3 1328.059 (22.2)125 (47)72 (27.1)10 (3.8)8336.0 1370.423 (10.7)107 (49.8)76 (35.4)9 (4.2)8637.4 1255.60.01205 (42.6)253 (52.6)33 (6.9)18 (3.7)763.9 555.53.55 (0, 163.4)2.4 1.10.58 0.26126 (47.4)127 (47.7)15 (5.6)9 (3.4)741.3 540.63.6 (0, 163.4)2.5 1.10.6 0.379 (36.7)126 (58.6)18 (8.4)9 (4.2)793.6 574.83.4(0, 74.3)2.3 1.00.5 0.20.020.020.240.640.350.670.060.00310.7 1.49.6 3.7138.8 3.44.5 1.63.6 0.5176.3 42.60.2 (0, 61.2)10.8 1.39.8 3.7139 3.44.4 0.83.8 0.4179.6 42.00.2 (0, 61.2)10.5 1.49.4 3.7138.6 3.44.5 2.23.4 0.5172.1 43.00.2 (0, 18.8)0.0030.240.220.53 0.0010.060.0634.5 7.116.3 3.518.2 4.12.2 2.112.2 10.714.4 3.18.8 4.132.7 6.814.8 2.817.9 4.10.8 (-1.8, 2)4.5 6.214.3 3.19.4 4.336.7 6.818.2 3.218.5 43.5 (2.1, 9.6)21.7 6.914.4 3.18.1 3.7 0.001 0.0010.13 0.001 0.0010.86 0.0010.38 0.0010.27 0.001 0.001 0.0010.96 0.0010.05 0.0010.0050.007Values expressed with a plus/minus sign are the mean SD. Values expressed with a parentheses are the median (range).NH group, normohydration group; OH group, overhydration group; ESRD, end-stage renal disease; CCI, Charlson comorbidity index; BMI, body mass index; CAPD, continuousambulatory peritoneal dialysis; APD, automated peritoneal dialysis; D/P Cr at 4-h PET, the ratio of dialysate creatinine to plasma creatinine at 4-h peritoneal equilibration test; CrCl,creatinine clearance; nPNA, normalized protein equilvalent of nitrogen appearance; TBW, total body water; ECW, extracellular water; ICW, intracellular water; OH, overhydration;OH/ECW, the ratio of overhydration to extracellular water; LTI, lean tissue index; ATI, adipose tissue index.http://www.medsci.org
Int. J. Med. Sci. 2016, Vol. 13HRQOL scores at baselineEach component score of KDQOL-SF at baselinewas compared between the two groups. The averageof PCS, MCS, and KDCS at baseline were significantlylower in the OH group compared with the NH group(NH vs. OH; PCS, 55.5 16.2 vs. 51.5 16.5, P 0.008;MCS, 50.1 10.6 vs. 47.5 11.1, P 0.009; KDCS, 69.3 9.6 vs. 67.0 9.6, P 0.008; Fig 2).The subscales of the KDQOL-SF at baseline werecompared (Table 2). Among the SF-36 domains, theOH group showed significantly lower scores inphysical functioning, bodily pain, general health, andsocial function. Among the kidney disease-specificdomains, the OH group showed significantly lowerscores in effects of kidney disease, burden of kidneydisease, and cognitive function.691burden of kidney disease, cognitive function, sleep,social support and patient satisfaction afteradjustment for the baseline OH value.Table 2. Baseline HRQOL scores.Total patients (n NH group (n OH group (n 481)266) 215)SF-36 domainsPhysical functioning73.1 22.4Role-physical50 (0, 100)Bodily pain76.5 22.9General health39.9 21.7Emotional well-being 30.2 14.8Role-emotional74.5 24.5Social function69.6 25.0Vitality30.3 14.3Kidney disease-specific domainsSymptom problem list 79.2 15.6Effect of kidney75.6 16.2diseaseBurden of kidney36.4 25.3diseaseWork status47.9 25.3Cognitive function83.5 15.9Quality of social70.6 14.4interactionSexual function65.0 32.5Sleep69.3 15.5Social support65.9 23.6Dialysis staff100 (0, 100)encouragementPatient satisfaction66.7 17.1P75.3 21.550 (0, 100)79 20.542.8 21.129.7 13.875.7 22.572.1 24.530.2 14.270.4 23.250(0,100)73.5 25.336.4 22.130.9 1673 26.866.5 25.230.5 14.50.020.330.010.0010.390.250.010.7880.3 14.777.3 16.177.8 16.773.5 16.20.080.0138.7 25.933.5 24.20.0347.6 2585.5 14.671.0 15.248.4 25.881.1 17.170 13.30.730.0040.4568.0 32.470.3 15.666.7 22.3100 (0, 100)61.2 32.368 15.364.9 25.2100 (0, 100)0.130.100.410.8167.4 21.865.8 22.30.43Values expressed with a plus/minus sign are the mean SD. Values expressed with aparentheses are the median (range).NH group, normohydration group; OH group, overhydration group.Table 3. Correlations of the OH difference with the HRQOLscores at 12 months.Figure 2. The HRQOL scores at baseline according to the hydrationstatus. The average scores of PCS, MCS, and KDCS at baseline weresignificantly lower in the OH group compared with the NH group.Correlations between the OH difference andthe HRQOL scores at 12 monthsTable 3 shows the correlation coefficientsbetween the OH difference and subscales of theKDQOL-SF at 12 months. In unadjusted analysis, theOH difference showed positive correlations withscores of bodily pain and patient satisfaction. Afteradjustment for the baseline OH value, the OHdifference showed significant positive correlationswith scores of physical functioning, role-physical,bodily pain, general health, role-emotional, and socialfunction in the SF-36 domains. In the kidneydisease-specific domains, the OH difference showedsignificant positive correlations with scores ofsymptom problem list, effect of kidney disease,SF-36 domainsPhysical functioningRole-physicalBodily painGeneral healthEmotional well-beingRole-emotionalSocial functionVitalityKidney disease-specific domainsSymptom problem listEffect of kidney diseaseBurden of kidney diseaseWork statusCognitive functionQuality of social interaction0Sexual functionSleepSocial supportDialysis staff encouragementPatient satisfactionaAdjustedUnadjusted r PAdjusted 80.100.080.460.620.220.160.180.130.020.130.120.009 0.001 0.001 0090.500.01for the baseline OH value.http://www.medsci.org
Int. J. Med. Sci. 2016, Vol. 13Impact of the OH difference on the HRQOLscores at 12 monthsEach component score of KDQOL-SF at 12months was compared between the OH differencequartiles (Fig 3). As the OH difference quartileincreased, there was a significant trend toward anincrease in adjusted PCS, MCS, and KDCS at 12months after adjustments for age, sex, dialysisvintage, diabetes, haemoglobin, albumin, CCI, totalKT/Vurea per week, renal CrCl, nPNA, 24-h urinevolume, the baseline OH value, and each baselinecomponent score (PCS, P 0.001; MCS, P 0.002;KDCS, P 0.001).692To evaluate whether the change in hydrationstatus was associated with the HRQOL scores after 12months, linear regression analysis was performed(Table 4). After adjustments for age and sex (Model 1),the OH difference showed significant positiveassociations with PCS ( β 2.18, 95% confidenceinterval [CI] 1.27 – 3.09, P 0.001), MCS (β 1.06,95% CI 0.46 – 1.65, P 0.001), and KDCS (β 1.05,95% CI 0.54 – 1.56, P 0.001) at 12 months. Theseassociations remained robust after adjustments fordialysis vintage, diabetes, haemoglobin, albumin,CCI, total KT/Vurea per week, renal CrCl, nPNA,24-h urine volume and the baseline OH value (Model2; PCS, β 2.25, 95% CI 1.23 – 3.28, P 0.001; MCS, β 1.08, 95% CI 0.40 – 1.77, P 0.002; KDCS, β 1.29,95% CI 0.71 – 1.88, P 0.001). Moreover, theseassociations were significant after adjustments forbaseline PCS, MCS, and KDCS, respectively (Model 3;PCS, β 2.04, 95% CI 1.01 – 2.97, P 0.001; MCS, β 1.02, 95% CI 0.38 – 1.65, P 0.002; KDCS, β 1.06,95% CI 0.57 – 1.55, P 0.001).Table 4. Regression coefficients of the OH difference for theHRQOL scores at 12 months.PCS at 12 monthsModel 1Model 2Model 3MCS at 12 monthsModel 1Model 2Model 3KDCS at 12 monthsModel 1Model 2Model 3βa95% CIP2.182.252.041.27, 3.091.23, 3.281.01, 2.97 0.001 0.001 0.0011.061.081.020.46, 1.650.40, 1.770.38, 1.65 0.0010.0020.0021.051.291.060.54, 1.560.71, 1.880.57, 1.55 0.001 0.001 0.001aRegressioncoefficientModel 1: Adjusted for age and sex.Model 2: Adjusted for Model 1 plus dialysis vintage, diabetes, haemoglobin, albumin, CCI,total KT/Vurea per week, renal CrCl, nPNA, 24-h urine volume and the baseline OHvalue.Model 3: Adjusted for Model 2 plus baseline scores of PCS, MCS, and KDCS, respectively.Impact of the OH difference on the HRQOLscore differenceFigure 3. The Adjusted HRQOL scores at 12 months according tothe OH difference quartiles. As the OH difference quartile increased, therewas a significant trend toward an increase in scores of PCS (A), MCS (B), andKDCS (C) at 12 months. Adjustments were made for age, sex, dialysis vintage,diabetes, haemoglobin, albumin, CCI, total KT/Vurea, renal CrCl, nPNA, 24-hurine volume, the baseline OH value, and each component score at baseline(baseline PCS, MCS, and KDCS, respectively).To evaluate whether the change in hydrationstatus was associated with the change in HRQOLscores, linear regression analysis was performed(Table 5). After adjustments for age and sex (Model 1),the OH difference was significantly negativelyassociated with the PCS difference (β -1.64, 95% CI-2.47– -0.80, P 0.001), and the KDCS difference (β -0.48, 95% CI -0.95 – -0.01, P 0.04). These associationsremained robust after adjustments for dialysisvintage, diabetes, haemoglobin, albumin, CCI, totalhttp://www.medsci.org
Int. J. Med. Sci. 2016, Vol. 13693KT/Vurea per week, renal CrCl, nPNA, 24-h urinevolume and the baseline OH value (Model 2; PCSdifference, β -1.81, 95% CI -2.84 – -0.78, P 0.001;MCS difference, β -0.92, 95% CI -1.65 – -0.20, P 0.01; KDCS difference, β -0.90, 95% CI -1.44 – -0.36,P 0.001).Table 5. Regression coefficients of the OH difference for theHRQOL score difference.βa95% CIPCS difference (PCS at baseline - PCS at 12 months)Model 1-1.64-2.47, -0.80Model 2-1.81-2.84, -0.78MCS difference (MCS at baseline - MCS at 12 months)Model 1-0.59-1.19, 0.006Model 2-0.92-1.65, -0.20KDCS difference (KDCS at baseline - KDCS at 12 months)Model 1-0.48-0.95, -0.01Model 2-0.90-1.44, -0.36P 0.001 0.0010.0520.010.040.001aRegression coefficientModel 1: Adjusted for age and sex.Model 2: Adjusted for Model 1 plus dialysis vintage, diabetes, haemoglobin, albumin, CCI,total KT/Vurea per week, renal CrCl, nPNA, 24-h urine volume and the baseline OHvalue.DiscussionThe QOLD study is the first multi-center studyof change in HRQOL, depressive symptoms, andbody composition in PD patients. The results of thepresent study show that the baseline hydration statuswas associated with the baseline HRQOL scores andthat the change in hydration status was related withthe HRQOL scores after 12 months and the change inHRQOL scores in PD patients. The associations weresignificant after adjusting multiple factors includingnutrition, anemia, residual renal function, dialysisadequacy, as well as the baseline hydration status andbaseline HRQOL scores. These findings implicate thatinterventions to achieve euvolemia may potentiallyimprove the HRQOL in PD patients.HRQOL is a powerful predictor of mortality inESRD patients [9, 10]. Euvolemia is also a predictor ofmortality in PD patients [1, 2]. However, monitoringof HRQOL is not routinely done and accurateassessment of volume status is relatively crude inclinical practice. The novelty of this study is that wedemonstrated that the hydration status wasassociated with HRQOL, not only at baseline, but alsoafter 12 months. At baseline, the OH group showedbetter baseline PCS, MCS, and KDCS compared to theNH group. We speculate several reasons for thisassociation. First, the OH group was more anemicthan the NH group. A previous systematic reviewdemonstrated that hematocrit level showed aconsistent relationship with HRQOL in ESRD patients[22]. Second, the OH group was morehypoalbuminemic than the NH group. Nutritionalbiomarkers including albumin are well knownpr
Hye Eun Yoon1, Young Joo Kwon2, Ho Cheol Song3, Jin Kuk Kim4, Young Rim Song5, Seok Joon Shin1, Hyung Wook Kim 6 , Chang Hwa Lee 7 , Tae Won Lee 8 , Young Ok Kim 9 , Byung Soo Kim 10 , Kyoung Hyoub Moon 11 , Yoon Kyung Chang 12 , Seong Suk Kim 13 , Kitae Bang 14 , Jong Tae Cho 15 , Sung Ro Yun 16 , Ki Ryang
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