A fixed protocol for outpatient clinic routines in the care of patients with severe renal failure

Abstract

Background: The primary aim of this study was to assess whether a fixed protocol, using a specially trained team, for intermediate follow-up to fulfillment of guideline targets is non-inferior to conventional follow-up in the care of uraemic patients. A secondary aim was to investigate possible impact on patient outcome. Methods: The cohort comprised 424 patients from seven centers. Inclusion criteria were either serum creatinine exceeding 200 µmol/l or calculated clearance below 30 ml/min, representing CKD 4 or 5a. Six centers followed a standardized protocol (group 1). One center provided controls (group 2). The study design was prospective and interventional. The variables measured were blood hemoglobin, bicarbonate, calcium, phosphate, intact parathyroid hormone, albumin, renal function variables, blood pressure and RAAS blockade. The number of patients achieving the set goals was analyzed as a time trend to determine if the intervention resulted in an improvement. Results: At baseline, group 1 had significantly lower GFR and higher serum creatinine, calcium, phosphate, calcium × phosphate product and bicarbonate, lower mean arterial pressure (MAP), systolic blood pressures and less use of RAAS. During the intervention, group 1 improved in the direction of guidelines for blood hemoglobin, albumin, bicarbonate and MAP. Outcome of secondary endpoints gave a risk of death of 30% in both groups, while the risk of renal replacement therapy was higher in group 1. Conclusions: However, the time to renal replacement therapy was significantly shorter in the intervention group, indicating that other variables than guideline achievements are important for the patient.

• Guideline targets
• risk factors
• progression
• protocol
• renal replacement therapy
• survival
• uraemia

Introduction

Uraemia is a condition of impaired health in which various irregularities need to be managed simultaneously during follow-up in the outpatient clinic. Positive effects of timely referral to a nephrologist for the care of the patient include delayed progression of renal failure and adequate preparation before entering RRT.1 Referring the patient to a nephrologist increases the possibility for initiation of optimal treatment.2–12

However, in relation to anemia, acidosis, hyperlipidemia, hyperphosphatemia, hyperparathyroidism, use of angiotensin renal blockers (ARB) and hypertension, the management of the patient is often suboptimal.2,4,5,13,14 The implementation of new strategies in daily care may also be impeded by the difference in treatment goals.15–20

Primary aim of this study was to assess whether a fixed protocol, using specially trained renal co-ordinators for intermediate control of data and appointments, is non-inferior in terms of fulfilling guideline targets. The secondary aim was to investigate the impact on patient outcome.

Material and methods

The investigation was performed as a prospective, interventional study. The patient cohort comprised 424 consecutively included subjects from seven centers. Inclusion criteria were either serum creatinine exceeding 200 µmol/l or calculated clearance below 30 ml/min. This corresponds to CKD stages 4 and 5a.21,22 The various diagnoses are presented in Table 1.

Table 1. Demographic data, patients in group 1 and group 2.

Diagnoses	Group 1 N (%)	Group 2 N (%)
Not clarified	60 (20)	27 (21)
Alport syndrome	3 (1)	6 (5)
Renal carcinoma	0	1 (1)
APKD	21 (7)	4 (3)
Diabetic nephropathy	47 (16)	13 (10)
Focal segmental glomerulosclerosis	5 (2)	3 (2)
Glomerulonephritis UNS	4 (1)	2 (1)
IgA nephritis	10 (4)	6 (5)
Glomerulonephritis chronic	38 (13)	2 (1)
Glomerulonephritis membranous	4 (1)	2 (1)
Henoch Schönlein purpura/vasculitis	16 (6)	1 (1)
Hydronephrosis	18 (6)	1 (1)
Hypoplastic kidneys	0	1 (1)
Interstitial nephritis	38 (13)	9 (7)
Renal failure, chronic UNS	10 (4)	27 (21)
Myeloma kidney	4 (1)	2 (1)
Nephrosclerosis	7 (2)	14 (11)
Renal artery stenosis	0	1 (1)
Rapidly progressive glomerulonephritis	2 (1)	3 (2)
Transplant rejection	7 (2)	5 (4)

Six centers followed a standardized program (group 1). Five of the centers were county hospitals and one was a university clinic. Another center at a second university clinic, provided controls, where clinicians and staff were blinded to the aim of the study. The inclusion period ranged from January 2002 to December 2005. The patients were followed until uptake into RRT or death.

A uniform protocol was designed (group 1, Table 2, Figure 1). Intermediate outpatient clinical appointments were performed by specially trained renal nurses (renal co-ordinators) for intermediate control of data and extra appointments performed in collaboration with local physicians. Variables considered mandatory in the treatment of CKD were identified: hemoglobin, blood pressure (mean), acid–base balance, phosphate, intact parathyroid hormone, albumin, renal function variables and the use of renin--angiotensin--aldosterone-system (RAAS) blockade (Table 2).

Figure 1. Schedule for registration of guideline variables.

Table 2. Targets set for patients treated in group 1.

Variable	Aim-level (Group 1)	Aim-level (Group 2)
B-Haemoglobin (g/l)	≥120	≥110
Standard bicarbonate (mmol/l)	≥22	≥20
PTH (µmol/l)	≤130	≤300
Calcium × phosphate	≤4.5	–
s-Albumin (g/l)	≥30	–
ACEinh/ARB	Yes	–
MAP (mmHg)	115	–

Note: MAP = mean arterial pressure.

Follow-up appointments were scheduled quarterly in group 1. Patients expected to have less than three months to RRT were excluded. Secondary endpoint was defined as time to start of dialysis or death before start of dialysis.

The Ethics Committee of the University of Linköping approved the study.

Demographic data and measurement of glomerular filtration rate (GFR)

Baseline data for patients are presented in Table 3. Since the patients were selected based either on a serum creatinine level exceeding 200 µmol/l at entry or a glomerular filtration rate below 30 ml/min, measured on a sample or estimated by calculation according to the Cockroft–Gault formula (using an estimated height for men of 175 cm and women of 162 cm).

Blood pressure

Mean arterial pressure (MAP) was calculated according to the formula: ((diastolic blood pressure) + (1/3 × (systolic blood pressure – diastolic blood pressure))).

Edmonton system assessment scale (ESAS)

At the scheduled appointments (group 1 only) a self-report form was used and ESAS23 scores were calculated on 570 occasions in 92 patients. The score evaluates the well-being of the patient.

Statistical analyses

Group differences in time to event were analyzed using the Cox proportional hazard regression. It was evaluated graphically by examining the Kaplan–Meier survival curves. Time to event was defined as months from study inclusion to time of death or RRT. Patients who had not experienced an event at the end of the study were censored. The regression included the following independent factors: group, gender and age. To analyze whether possible differences varied with age or gender, the 2-way interactions group * age and group * gender were included in the initial model and removed if non-significant. Further analyses were adjusted for group differences at baseline by also including creatinine, glomerular filtration rate (GFR), blood hemoglobin, calcium × phosphate product, albumin, bicarbonate, mean arterial pressure (MAP) and use of ACE-inhibitors/ARB. Parathyroid hormone data (PTH) were excluded from that calculation due to insufficient number of measurements.

Analyses were performed for trends in risk factors such as mean arterial blood pressure, systolic and diastolic blood pressure, serum bicarbonate, phosphate, calcium, PTH, albumin, calcium × phosphate product, creatinine and glomerular filtration rate (GFR) using generalized estimation equations (GEE, Table 4) assuming different correlation structures between repeated samples depending on what outcome-variable was measured (Table 4A). Analyses included data up to 2 years of follow-up. Survival analysis was followed up for a prolonged period of time.

Chi-square analyses were calculated. The level of significance was set at less than 0.05.

Results

Baseline data

At entry into the study (baseline) GFR was significantly lower in group 1 (19 ± 8 vs. 22 ± 7 ml/min, p < 0.001, Figure 2A, Table 4A, B), corresponding to a higher serum creatinine in group 1 (299 µmol/l ± 95 vs. 273 ± 92, p = 0.009, Figure 2B). Uptake into dialysis occurred at GFR level 6–10 at all centers. Women had lower values than men; this is congruent with inclusion based on serum creatinine below 200 µmol/l women will have lower GFR.

Figure 2. Change of mean value of various variables at visit 1 (start), and then every three months until visit 9 (24 months). Group 1 filled circles and filled line versus Group 2 (controls) with open squares and hatched line. (A) Estimated GFR; (B) serum creatinine; (C) blood haemoglobin; (D) serum albumin; (E) Ca × phosphate product; (F) serum total calcium; (G) serum bicarbonate; (H) mean arterial pressure (MAP).

There was no significant difference between the groups at baseline with regard to gender, age, albumin, PTH and diastolic blood pressure. Group 1 had higher serum calcium, phosphate and calcium × phosphate product, while group 2 had higher bicarbonate levels, systolic blood pressure, mean arterial pressure and more extensive use of ACE inhibitors/ARB.

Achievement of treatment goals toward guidelines

The use of a protocol resulted in a significant improvement of several of the variables over time.

Blood hemoglobin

The mean blood hemoglobin differed between genders but was similar at start. It increased over time in group 1 in contrast to group 2 (p = 0.00, Table 4A, B; Figure 2C). The trend differed between the groups. More patients were below guideline level 110 g/l in group 1 at start (16.5% vs. 7.5, p = 0.018) but this did not differ at 12 and 24 months (Figure 3A, B).

Figure 3. Percentage of patients that are outside of guideline values in Group 1 (hatched bars) and Group 2 (open bars). (A) Blood haemoglobin less than 110 g/L; (B) blood haemoglobin less than 120 g/L; (C) serum albumin less than 30 g/L; (D) serum calcium × phosphate product above 4.5; (E) standard bicarbonate (SBC) less than 20 mmol/L; (F) standard bicarbonate (SBC) less than 22 mmol/L; (G) parathyroid hormone (PTH) above 300 pmol/L; (H) percentage of patients prescribed ACE-inhibitors/ARB.

Calcium × phosphate product

There was a significantly higher calcium × phosphate product in group 1 at start. This difference was maintained while a similar increase was noted in both groups (p = 0.001, Table 3, Figure 2C).

Table 3. Baseline data for patients in groups 1 and 2 (controls).

	Group 1 or 2	N	Mean	Std. dev.	Sig. (2-tailed)
Age (years)	Group 1	294	66	14	ns.
	Group 2 Ctrl	130	66	16
Men (%)	Group 1	202	69		ns.
	Group 2 Ctrl	93	72
Estimated GFR  (ml/min)	Group 1	291	19	8	<0.001
	Group 2 Ctrl	130	22	7
Creatinine (µmol/l)	Group 1	291	299	95	0.009
	Group 2 Ctrl	125	273	92
Haemoglobin (g/l)	Group 1	289	124	15	ns.
	Group 2 Ctrl	117	127	13
PTH (ng/l)	Group 1	250	199	175	ns.
	Group 2 Ctrl	59	252	304
Calcium (mmol/l)	Group 1	265	2.39	0.17	<0.001
	Group 2 Ctrl	123	2.31	0.11
Phosphate (mmol/l)	Group 1	281	1.39	0.33	0.011
	Group 2 Ctrl	121	1.31	0.30
Calcium × Phosphate  product	Group 1	262	3.36	0.82	<0.001
	Group 2 Ctrl	118	3.02	0.71
Bicarbonate (mmol/l)	Group 1	279	23	3.0	<0.001
	Group 2 Ctrl	125	24	2.8
Albumin (g/l)	Group 1	288	38	4.8	ns.
	Group 2 Ctrl	123	39	4.7
BP systolic (mmHg)	Group 1	284	146	23.1	0.013
	Group 2 Ctrl	114	152	23.0
BP diastolic (mmHg)	Group 1	281	80	12.2	ns.
	Group 2 Ctrl	114	82	11.9
MAP (mmHg)	Group 1	281	102	13.7	0.016
	Group 2 Ctrl	111	106	13.5
ACE inhibitors (%)	Group 1	294	49		<0.001
	Group 2 Ctrl	127	78

Note: ns. = not significant.

More patients were above the guideline product of 4.5 in group 1 at start (8% vs. 2, p = 0.011). This did not differ between the groups at 12 and 24 months (Figure 3D). There were differences between the groups and genders. There was a significant change over time (p = 0.001, Table 4B) while this trend did not differ between the groups (Table 4A, B).

Table 4. (A) Overview of the correlation structure used (Corr. Structure: I = Independent, A = Autoregressive), U = unstructured), distribution (N = Normal, G = Gamma) and Link function (I = Identity, L = Log) for the various variables analyzed. (B) Risk factor trend analysis using GEE models, separate model for each factor. p Values are given in the table.^a

	MAP	SBP	Hb	Ca × PO4	PO4	Albumin	Ca	Creat.	GFR	Bicarb	DBP
A
Corr. Structure	I	I	I	U	A	I	I	I	U	I	I
Distribution	N	N	N	G	G	N	N	G	N	N	N
Link function	I	I	I	L	L	I	I	L	I	I	I
B
Group	0.999	0.127	0.051	0.000	0.000	0.226	0.000	0.000	0.000	0.000	0.333
Age	0.510	0.063	0.332	0.685	0.449	0.211	0.995	0.633	0.165	0.982	0.173
Gender	0.095	0.182	0.000	0.004	0.019	0.068	0.095	0.011	0.000	0.220	0.102
Sample time	0.018	0.029	0.439	0.001	0.010	0.289	0.000	0.000	0.022	0.000	0.033
Group * time	0.007	0.015	0.000	0.639	0.545	0.005	0.094	0.000	0.108	0.613	0.029

Notes: ^aInterpretation can be made by Group * time. Significant means that there are different trends between the groups (i.e., one is increasing and the other declining) such as for MAP, SBP, DBP, haemoglobin (Hb), albumin and creatinine. Age and gender indicate that these factors interfere with outcome of variables if they are significant. Interpretation of the factor “sample time” shows whether there was a change/trend (increase or decline) over time (mean for both groups). The term “group” indicates whether the mean values over time differs between groups 1 and 2.

Serum albumin

Serum albumin was similar between the groups at start (Table 3). There was a significant trend of improvement in group 1, while a reduction was seen in group 2 (Figure 2D). The proportion of patients who had a serum albumin of less than 30 g/l at start of study were 6% in both groups and at 24 months, 0 versus 1.7% (Figure 3C). The trend for serum albumin changed differently between the groups (p = 0.005, Table 4A, B) over time.

Serum bicarbonate

There was higher serum bicarbonate at start in group 2 than group 1 (Table 3). There was an increase in mean standard bicarbonate over time in both groups (Figure 2G).

At start, 43% of patients in group 1 were below the guideline level versus 12.5% in group 2 (p = 0.001). At 24 months, the difference was not present and 9.5 versus 6.6% of patients were below guideline levels (Figure 3E, F).

There was a significant trend toward fewer patients with pathologically lowered concentrations in group 1 (R = −0.95, p < 0.001) and group 2 (R = −0.69, p = 0.038) (Figure 3E, F). There was a difference between the groups and a trend of change over time that was similar for the groups (p < 0.001, Table 4A, B).

Parathyroid hormone

The proportion of patients with serum PTH exceeding 300 µmol/l did not differ between the groups during the observation period (18 vs. 17% at start, Figure 3G).

Blood pressure

The MAP was higher at start in group 2 (Table 3). There was a significant trend over time (p = 0.018, Table 4B). In addition, there was a reduction in group 1 and in contrast an increase in group 2 (p = 0.007, Table 4B, Figure 2H). At the first appointment MAP was above the guidelines in 13% in the group 1 versus 24% in the group 2 (p = 0.015). At the one-year appointment 10 versus 15% were above the guidelines (not significant, ns.) and at the 2-year appointment 24 versus 8.5% (ns.) were above guidelines.

ACE inhibitors/ARB

A larger proportion of patients in group 2 were treated with either ACE-inhibition/ARB at start (78% vs. 48, p = 0.001, Table 3) and at 3, 12, 15, 18 and 24 months than in group 1 (p < 0.05).

Over the observation period there was a significant trend of an increased prescription of ACE-inhibitors or ARB in group 2 (p = 0.001). Such trend could not be detected in group 1 (Figure 3H).

There was no difference in blood pressure when comparing data of those measures when the patients were prescribed ACE-inhibition/ARB or not (systolic blood pressure 145 ± 22 vs. 146.8 ± 24; diastolic 80 ± 11 vs. 80 ± 12). Neither was there a difference in blood hemoglobin at these occasions (127 ± 14, n = 1012 vs. 126 ± 15 g/l).

There was no difference in risk for death if the patients were on ACE/ARB-medication or not at baseline (67 of 242 vs. 63 of 178).

ESAS

ESAS was determined only in group 1. There was a significant correlation between the ESAS score and PTH (R = 0.12, n = 540, p = 0.005). ESAS correlated inversely to iohexol clearance values (R = −0.10, n = 493, p = 0.025), hemoglobin (R = −0.12, n = 493, p = 0.006), and albumin (R = −0.11, n = 572, p = 0.011). The mean ESAS score was 2.7 (±2.0, n = 252) for patients not on ACEinh, and 2.2 (±2.4, n = 320, p = 0.010) for patients on ACEinh treatment.

Gender comparison

Women had, compared to men, at baseline a significantly lower estimated creatinine clearance, (14 ± 6 ml/min vs. 23 ± 7, p = 0.000), serum creatinine (270 ± 83 vs. 301 ± 99, p = 0.001) and hemoglobin, while higher levels were present for PTH, phosphate and the calcium × phosphate product. Except for estimated GFR and serum creatinine these differences were not present at 24-month follow-up.

Secondary endpoints

During the follow-up period, 29% died in group 1 and 34% in group 2 (not significant).

The mean number of months used in the Kaplan–Meier estimation for time to death of patients was 59.7 (CI 55.3–64.1) versus 68.3 (CI 62.2–74.3). The survival distribution did not differ between the groups (Tables 5 and 6, Figure 4).

Figure 4. Kaplan--Meier curve of survival over observation time in month in Group 1 (lower line) or Group 2 (upper line).

Table 5. Cox regression forward conditional with analysis using “death” as endpoint and variables at first appointment.

							95.0% CI for Exp(B)
	B	SE	Wald	df	Sig.	Exp(B)	Lower	Upper
Variables in the Equation
Step 4
Age	0.082	0.011	59.207	1	0.000	1.086	1.063	1.109
MAP	−0.022	0.008	8.353	1	0.004	0.978	0.964	0.993
Creatinine	0.002	0.001	4.539	1	0.033	1.002	1.000	1.005
Calcium × phosphate	0.266	0.110	5.862	1	0.015	1.305	1.052	1.618
	Score	df	Sig.
Variables not in the Equation^a
Step 4
Gender	0.715	1	0.398
Albumin	2.204	1	0.138
ACE/ARB	0.553	1	0.457
Est. GFR	0.000	1	0.995
Bicarbonate	0.051	1	0.822
Groups	0.490	1	0.484

Note: ^aResidual Chi Square = 5.414 with 6 df; Sig. = 0.492.

Table 6. Means and median months for survival time in the Kaplan–Meier equation.

Means and medians for survival time
	Mean^a				Median
			95% Confidence Interval				95% Confidence Interval
Group 1 or 2	Esti-mate	Std. Error	Lower Bound	Upper Bound	Esti-mate	Std. Error	Lower Bound	Upper Bound
Group 1	59.7	2.26	55.3	64.1	78	8.17	62.0	94.0
Group 2	68.3	3.08	62.2	74.3	92	.	.	.
Overall	65.5	1.95	61.6	69.3	92	.	.	.

Note: ^aEstimation is limited to the largest survival time if it is censored.

The mean number of months used in the Kaplan–Meier estimation for time to Renal Replacement Therapy was 49 months for group 1 (CI 45–53) and 66 months for group 2 (CI 60–72). The extent of patient who entered the dialysis program was higher in group 1 than group 2 (50%, n = 146 vs. 38%, n = 50, p = 0.044). The hazard ratio, adjusted for age and gender, was 1.77 (95% CI: 1.38–2.26) for group 1 compared to group 2 (Tables 7 and 8). The difference was still significant after adjustments for baseline factors (Figure 5). The patients who entered into RRT (n = 146 group 1 and 50 in group 2) started hemodialysis (44% in group 1 vs. 23% in group 2), peritoneal dialysis (3% vs. 16%) and transplantation directly, respectively (3% vs. 1%).

Figure 5. Kaplan--Meier curve of retention free of renal replacement therapy over observation time in month in Group 1 (lower line) or Group 2 (upper line).

Table 7. Cox regression analysis using “renal replacement therapy” as endpoint and variables at baseline (first appointment). Forward conditional analyses.

Variables in the equation
							95.0% CI for Exp(B)
	B	SE	Wald	df	Sig.	Exp(B)	Lower	Upper
Step 3
Creatinine	0.004	0.001	17.454	1	0.000	1.004	1.002	1.005
Ca × phosphate	0.309	0.111	7.817	1	0.005	1.362	1.097	1.692
Groups	-0.624	0.197	10.000	1	0.002	0.536	0.364	0.789
Variables not in the Equation^a
	Score	df	Sig.
Step 3
Age	0.937	1	0.333
Gender	1.638	1	0.201
MAP	0.361	1	0.548
Albumin	1.598	1	0.206
ACE/ARB	2.010	1	0.156
eGFR	0.376	1	0.540
Bicarbonate	3.786	1	0.052

Note: ^aResidual Chi Square = 10.461 with 7 df; Sig. = 0.164.

Table 8. Means and medians for survival time. Kaplan–Meier estimation for time to renal replacement therapy.

Means and medians months until RRT
	Mean^a				Median
			95% Confidence Interval				95% Confidence Interval
Group 1 or 2	Estimate	Std. Error	Lower Bound	Upper Bound	Estimate	Std. Error	Lower Bound	Upper Bound
Group 1	49.2	1.91	45.5	53.0	56	3.3	49.5	62.5
Group 2	65.9	3.13	59.8	72.0	81	9.5	62.4	99.6
Overall	56.0	1.80	52.5	59.6	60	2.7	54.6	65.4

Note: ^aEstimation is limited to the longest time staying without RRT if it is censored.

Cox regression analyses were performed with death or start of renal replacement therapy by any reason as endpoint and including the variables age, gender, study groups, estimated GFR, serum creatinine, calcium × phosphate product, serum bicarbonate level, serum albumin, mean arterial pressure (MAP) and use of ACE inhibitors or ARB in the models. In a forward conditional analysis for the end point, death significant variables were age, serum creatinine, calcium × phosphate product and mean arterial pressure (MAP, Table 5). The Cox regression analysis with renal replacement therapy as endpoint revealed as significant base line variables the group effect, serum creatinine and the calcium × phosphate product (Table 7).

Discussion

This study investigated if there would be a change in outcome using the addition of intermediate outpatient visits with the help of renal co-ordinators for group 1 patients. Such intervention resulted in improvements in patients’ adherence to guidelines with regard to the levels of hemoglobin, the calcium × phosphate product, albumin and bicarbonate, while there was no increase in prescription of ACE inhibitors among care providers. This indicates that the support of the renal co-ordinator and dietician guided by local physicians in this regard was not inferior and even to some extent improved outcome as a resource to achieve adherence to guidelines of these patients.

Approximately 30% of patients in both groups died during the study period. Although the time from study start to death was longer in the non-intervention group, the survival distribution did not differ.

A larger proportion of patients in group 1 entered RRT. One explanation may be the lower GFR and higher serum creatinine levels at baseline in that group. Another could be that although patients in group 1 had improved variables in relation to guideline levels, a number of significant baseline variables were worse than in group 2, although not blood pressure. However, there was no evident improvement in group 1 toward the mean over time in the Kaplan–Meier curve. The Cox analysis confirmed that higher serum creatinine but not lower GFR was of worse prognosis. This may indicate that patients with small muscle mass receive dialysis later.24 Worse prognosis for patients with a higher calcium × phosphate product is consistent with faster deterioration of renal function, but may also indicate poor adherence to dietary recommendations, phosphate binder intake and other medication. Another reason for group 2 having a more favorable outcome may be that a lack of renal co-ordinators will not result in a replacement of a planned outpatient clinic visits to an experienced physician. In such visits the physician also will consider other clinical disturbances and risk factors besides guideline criteria, such as cardiac function, fluid state, metabolic and lipid control and physical activity recommendations. However, according to others when the option is to use multiple nephrology trainees rotating through a nephrology clinic, the time to RRT does not differ although the support of single experienced renal nurse practitioner working to a protocol, are more likely to adhere to guidelines.25,26 Notable is that longer duration of regular nephrological care in the predialysis period, at least for several years prior to the start of dialysis, is associated with a better long-term survival on dialysis. Such data strongly support the argument for early referral and regular nephrological care of chronic renal failure patients.3

In the Cox regression analysis, it was noteworthy that lower MAP indicated worse outcome. Another reason for the adverse effect of low MAP may be that the guidelines support too low blood pressure for the individual patient, especially patients who are older and/or suffer from arteriosclerosis resulting in ischaemic lesions. Inappropriate use of RAAS inhibitors may also accelerate the decline of renal function in vulnerable patients.27,28 The higher extent and possibly earlier prescription of ACE-inhibitors or ARB to group 2 may be another reason for prolonged renal survival of those patients. However, the beneficial effect of ACE inhibitors or ARB was not verified in the Cox model.

A systemic approach in the care of patients with renal insufficiency has been described as beneficial to outcome in studies where patients with diabetic nephropathy and anemia were treated according to a structured protocol, with positive effects achieved in terms of the rate of renal decline and anemia correction.29,30 All variables included in the protocol were considered risk factors for shortening of renal and patient survival, such as elevated blood pressure,7,19 anemia,8 hyperparathyroidism,9 metabolic acidosis31 and hypoalbuminemia.10

ESAS score did not deteriorate over the time, suggesting that the interventions did not affect the subjective wellbeing. Adjustment of quality of life expectations during the course of renal disease may also take place.32

This study confirms that a structured protocol used by a specially trained multidisciplinary team in daily patient care at centers with limited resources facilitates to achievement of guideline targets. However, secondary end-point data indicate that more intense follow-up and possibly even earlier interventions performed by the physicians, i.e. “doctor’s time,” are important.

Declaration of interest

The authors report no conflicts of interest. We also thank Amgen, Genzyme, Astra Zeneca and the Jönköping County Council for financial support.

Acknowledgements

We would like to thank the nurses for patient coordination and data retrieval: Annika Johansson, Annika Svensson, Catarina Löwhagen, Maria Grubbström, Susanne Sparr, Solveig Lund, Lena Ringstad, Anna Hallberg-Karlsson, Ingrid Göransson, Annika Eriksson, Helene Arbman and others.