| Literature DB >> 28253839 |
Teerayuth Jiamjariyapon1, Atiporn Ingsathit2, Krit Pongpirul3,4, Kotcharat Vipattawat5, Suphattra Kanchanakorn5, Akhathai Saetie5, Duangjit Kanistanon6, Patimaporn Wongprompitak6, Vinai Leesmidt7, Watcharapong Watcharasaksilp7, Wei Wang8, Anil K Chandraker9, Kriang Tungsanga10.
Abstract
BACKGROUND: In developing countries, renal specialists are scarce and physician-to-patient contact time is limited. While conventional hospital-based, physician-oriented approach has been the main focus of chronic kidney disease (CKD) care, a comprehensive multidisciplinary health care program (Integrated CKD Care) has been introduced as an alternate intervention to delay CKD progression in a community population. The main objective is to assess effectiveness of Integrated CKD Care in delaying CKD progression.Entities:
Keywords: Chronic Kidney Disease; Integrated CKD care; Village health volunteers
Mesh:
Year: 2017 PMID: 28253839 PMCID: PMC5335731 DOI: 10.1186/s12882-016-0414-4
Source DB: PubMed Journal: BMC Nephrol ISSN: 1471-2369 Impact factor: 2.388
Fig. 1Flow chart of participants. Abbreviation: ESRD, End-stage renal disease
Baseline characteristics of participants
| Control ( | Intervention ( |
| |
|---|---|---|---|
| Age (years) | 62.4 ± 7.9 | 62.3 ± 6.4 | 0.89 |
| Female (%) | 152 (73.1%) | 170 (72.6%) | 0.92 |
| Educational status | |||
| Elementary school or lower (%) | 205 (98.6) | 217 (92.7) | 0.09 |
| BMI | 25.0 ± 5.5 | 25.7 ± 7.9 | 0.32 |
| Systolic BP (mmHg) | 123.8 ± 16.9 | 125.9 ± 15.6 | 0.19 |
| Diastolic BP (mmHg) | 75.6 ± 2.8 | 76.7 ± 2.9 | 0.22 |
| Smoking (%) | 7 (3.4) | 4 (1.7) | 0.23 |
| Co-morbidities | |||
| DM (%) | 108 (51.9) | 129 (55.1) | 0.50 |
| HT (%) | 192 (92.3) | 210 (89.7) | 0.35 |
| History of IHD | 11 (5.2) | 11 (4.7) | 0.44 |
| History of CVA | 2 (0.9) | 6 (2.5) | 0.07 |
| Initial laboratory parameter | |||
| Creatinine (mg/dl) | 1.53 ± 0.08 | 1.55 ± 0.07 | 0.21 |
| eGFR (CKD-EPI, ml/min/1.73 m2) | 41.8 ± 10.6 | 41.2 ± 10.3 | 0.32 |
| UPCR (mg/g) | 457.3 ± 700.3 | 442.4 ± 752.5 | 0.84 |
| Hemoglobin (g/dl) | 11.4 ± 2 | 11.6 ± 3.1 | 0.52 |
| HbA1C | 7.9 ± 2.4 | 7.3 ± 1.4 | 0.02 |
| LDL (mg/dl) | 113.9 ± 35.9 | 120.8 ± 38.5 | 0.06 |
| Potassium (mEq/L) | 4.6 ± 0.6 | 4.1 ± 0.6 | 0.04 |
| Bicarbonate (mEq/L) | 22.9 ± 3.7 | 25.4 ± 6.1 | 0.26 |
| 24-h u Na (mg/day) | 4,485 ± 80 | 3,241 ± 55 | 0.02 |
| 24-h nPNA (g/kg/day) | 1.08 ± 0.4 | 0.84 ± 0.2 | 0.01 |
| Treatment | |||
| No. of antihypertensive medications | 2.0 | 2.2 | 0.06 |
| ACEi/ARBs (%) | 190 (91.3) | 199 (85) | 0.05 |
| Statin use (%) | 156 (75.5) | 167 (71.4) | 0.33 |
| NSAID (%) | 32 (15.4) | 45 (19.2) | 0.08 |
| Aspirin (%) | 133 (63.9) | 85 (36.3) | 0.05 |
Data was shown as means (standard deviation) for continuous variables and percentages for categorical variables
Abbreviations: BMI Body Mass Index, BP Blood Pressure, DM Diabetes Mellitus, HT Hypertension, IHD Ischemic Heart Disease, CVA Cerebrovascular accident, eGFR estimated Glomerular Filtration Rate, CKD-EPI the Chronic Kidney Disease Epidemiology Collaboration equation, UPCR Urine Protein-Creatinine Ratio, HbA1C HemoglobinA1C, LDL Low-density Lipoprotein, nPNA normalized Protein Nitrogen Appearance, ACEi/ARBs Angiotensin Converting Enzyme inhibitors/Angiotensin Receptor Blockers, NSAIDs Non-steroidal Antiinflammatory Drugs
Fig. 2Changes in eGFR during the follow-up period (Primary outcome). GEE analyses were used to determine mean differences over time of estimated Glomerular Filtration Rate (eGFR) between intervention group and control group during the follow-up period
Mean levels of clinical outcomes, laboratory parameters, and medications between intervention group and control group
| Variables | Mean level during follow-up | Mean difference (coefficient) | 95% CI |
| |
|---|---|---|---|---|---|
| Control ( | Intervention ( | ||||
| BMI (kg/m2) | 24.8 ± 0.2 | 24.9 ± 0.2 | 0.49 | (−0.3)–1.2 | 0.22 |
| eGFR (CKD-EPI, ml/min/1.73 m2) | 39.9 ± 2.8 | 42.4 ± 1.5 | 2.74 | 0.7–4.8 | 0.009 |
| Serum Creatinine (mg/dl) | 1.6 ± 0.1 | 1.5 ± 0.1 | −0.10 | (−0.2)–(−0.02) | 0.02 |
| Systolic BP (mmHg) | 120 ± 2.3 | 125 ± 1.9 | 5.37 | 3.4–7.3 | 0.01 |
| Diastolic BP (mmHg) | 73 ± 1.3 | 74 ± 1.8 | 1.23 | 0.3–2.2 | 0.01 |
| Hemoglobin (g/dl) | 11.3 ± 0.2 | 11.2 ± 0.3 | 0.45 | 0.36 | 0.42 |
| Serum bicarbonate (mEq/L) | 21.5 ± 1.7 | 24.5 ± 1.1 | 2.84 | 2.4–3.3 | 0.001 |
| HbA1C in diabetics (%) a | 7.9 ± 0.4 | 7.3 ± 0.2 | −0.57 | (−0.9)–(−0.2) | 0.001 |
| LDL-C (mg/dL) | 108 ± 5 | 107 ± 16 | −1.09 | (−5.6)–3.4 | 0.63 |
| Triglyceride (mg/dL) | 209 ± 22 | 192 ± 15 | −18.15 | (−35.5)–(−0.8) | 0.04 |
| Urine protein-creatinine ratio (mg/g) | 260 ± 84 | 336 ± 55 | 11.42 | (−97)–119 | 0.84 |
| 24-h urine Na (mg/day) a | 3682 ± 635 | 2931 ± 309 | −739.0 | (−1136)–(−343) | 0.001 |
| 24-h urine nPNA (g/kg/day) | 0.91 ± 0.1 | 0.84 ± 0.02 | 0.10 | (−0.2)–(0.001) | 0.049 |
GEE analyses were used to determine mean differences over time of clinical outcomes and laboratory parameters between the two groups
Data was shown as means (standard deviation) for continuous variables
Abbreviations: GEE generalized estimating equation
aDiffrences already exist at baseline
Fig. 3Changes in clinical and laboratory parameters during the follow-up period. GEE analyses were used to determine mean differences over time of clinical outcomes and laboratory parameters between the two groups. Change in systolic BP (a), diastolic BP (b), hemoglobin A1C (c), serum bicarbonate (d), serum triglyceride (e), urine protein-creatinine ratio (f), 24-h urine normalized protein nitrogen appearance (g), 24-h urine sodium (h) between intervention group and control group during the follow-up period
Percentage of medication during the follow-up period
| Medications | At baseline |
| At the end of study |
| ||
|---|---|---|---|---|---|---|
| Control | Intervention | Control | Intervention | |||
| ( | ( | ( | ( | |||
| Mean of number of antihypertensive medications | 2.0 ± 0.5 | 2.2 ± 0.4 | 0.06 | 1.8 ± 0.4 | 2.7 ± 0.5 | 0.05 |
| Mean of number of glucose-lowering medications | 0.8 ± 0.2 | 1.1 ± 0.3 | 0.08 | 0.6 ± 0.1 | 1.7 ± 0.3 | 0.24 |
| Insulin (%) | 16.9 | 21.1 | 0.10 | 16.9 | 28.4 | 0.01 |
| ACEi/ARBs use (%) | 91.3 | 85 | 0.05 | 88.9 | 92.7 | 0.09 |
| Statins use (%) | 75.5 | 71.4 | 0.33 | 75 | 82.9 | 0.11 |
| Antiplatelets use (%) | 63.9 | 36.3 | 0.05 | 55.8 | 36.3 | 0.12 |
| NSAIDs (%) | 15.4 | 19.2 | 0.09 | 6.5 | 7.7 | 0.18 |
Data was shown as percent for categorical variables and compared using Chi-square test (of Fisher’s exact test)
Abbreviation: ACEi/ARBs Angiotensin Converting Enzyme inhibitors/Angiotensin Receptor Blockers, NSAIDs Non-steroidal Anti-inflammatory Drugs
Incidence of Clinical Endpoints (Cox regression analysis)a
| Clinical outcome | Control ( | Intervention ( |
| Hazard ratio | 95%CI | ||
|---|---|---|---|---|---|---|---|
| No. of events | Person-years | No. of events | Person-years | ||||
| All-cause mortality | 4 | 387.8 | 5 | 449.6 | 0.92 | 1.07 | 0.29–3.90 |
| CV eventsb | 4 | 384.0 | 2 | 448.6 | 0.33 | 0.43 | 0.08–2.34 |
| ESRDc | 14 | 370.5 | 8 | 439.6 | 0.11 | 0.49 | 0.21–1.16 |
| 50% increase in serum Cr from baseline | 31 | 359.5 | 23 | 426.8 | 0.10 | 0.64 | 0.37–1.09 |
| Composite clinical endpointsd | 41 | 344.3 | 29 | 417.6 | 0.03 | 0.59 | 0.37–0.96 |
Data was analyzed by using Cox proportional-hazard model based on intention to treat basis
Abbreviation: CV events cardiovascular events
aIn this analysis, data were censored at the date of death, the date of last visit of patients who loss to follow-up or withdrew from the study
bCV events in this analysis are consisted of acute myocardial infarction and stroke
cEnd-stage renal disease (ESRD) is defined as eGFR < 15 ml/min/1.73 m2
dComposite of clinical endpoints in this study is composed of CV events, ESRD, 50% increase in serum creatinine from baseline