Plant-based low-protein diet for preventing malnutrition‒inflammation complex syndrome in adults with CKD: a single-centre preliminary experience

Abstract

Background

Chronic kidney disease (CKD) is a rising public health concern. Low protein intake reduces uremic toxin generation and improves the hemodynamic profile of the kidneys, postponing the need for eventual dialysis. Vegetarian diets have been shown to positively influence cardiovascular health and reduce uremic toxin levels and inflammation in CKD patients. The so-called “Malnutrition-Inflammation Complex Syndrome” (MICS) is a nontraditional cardiovascular risk factor that is associated with poor overall outcomes in CKD patients. The type of protein, not only the amount, may be relevant in the prevention of MICS, but at present no studies are published in the literature addressing this topic. The aim of our study was to evaluate the feasibility and efficacy of a plant-based diet in reducing CKD-related complications and preventing MICS.

Methods

Adult subjects with CKD (3–5 stages) were retrospectively recruited. Each patient was evaluated for biochemical parameters, anthropometric measurements, body composition, and pharmacological treatments at baseline and after 6 months of dietary intervention.

Results

After six months of treatment, significant improvements (p < 0.05) were observed in indices of kidney function, lipid and glycemic profiles, vitamin D levels, plasma fibrinogen, anthropometric and body composition parameters, as well as muscle strength, whereas no significant changes were detected in plasma albumin levels or in the other parameters assessed. As observed in recent literature, the risk of hyperkalaemia associated with plant-based regimens in CKD patients has been set aside.

Conclusions

Our preliminary study confirms the feasibility and efficacy of a plant-based diet in reducing CKD-related complications and preventing MICS.

Introduction

Chronic kidney disease (CKD) is a rising public health concern. According to the World Health Organization (WHO) regions, kidney disease is a part of noncommunicable diseases (NCDs) with the greatest increase in incidence in recent years. Type II diabetes mellitus (DM) and obesity are the leading causes of end-stage renal disease worldwide, together with sedentary lifestyles, unhealthy eating habits, increase in the average age of the general population and smoking, contributing to a significant increase in cardiovascular burden in almost all countries [1]. Currently, CKD is defined as an abnormality of kidney structure or function present for a minimum of 3 months, as evaluated by the estimated glomerular filtration rate (eGFR), the urine albumin-to-creatinine ratio (UACR), and other different markers of kidney damage (hematuria, structural abnormalities of kidneys and urinary tract, electrolyte abnormalities, genetic factors) [2–4]. In addition to the available pharmacological strategies targeting etiological factors, nutritional therapy has a fundamental role in preventing CKD progression [5, 6]. Although the specific recommendations can change greatly in based on the severity of worsening renal function and the presence of comorbidities, low-protein diets (LPDs) are universally recognized as a cornerstone of conservative therapy in CKD [7]. According to the latest Kidney Disease Outcomes Quality Initiative (KDOQI) guidelines [8], a protein intake of 0.55–0.60 g/kg of ideal body weight (IBW)/day is recommended in patients without DM and an intake of 0.6–0.8 g/IBW/day is recommended in patients with type II DM along with other recommendations such as energy intake of 25–35 kcal/IBW/day, depending on age, sex, physical activity level, body composition, weight status goals, stage of CKD, concomitant diseases or presence of inflammation to ensure a stable nutritional status and optimize glycemic control. Low protein intake reduces uremia and uremic toxin generation and improves the hemodynamic function of kidneys, postponing the need to start dialysis [9]. However, a possible risk related to protein intake restriction is a reduction in energy intake, which could promote the development of malnutrition and protein-energy wasting (PEW) [10]. Protein–energy wasting (PEW) is associated with poor prognosis in patients with chronic kidney disease (CKD) and represents a serious complication; therefore, identifying patients with early alterations in nutritional status, muscle mass, or muscle strength—and, more importantly, preventing its development—may have clinically relevant implications [11].

Malnutrition in CKD involves an interplay between several factors such as inflammation, increased catabolism, metabolic and hormonal imbalances [12], resulting in a negative impact on clinical, functional, and body composition outcomes.

The so-called “malnutrition inflammatory complex syndrome” (MICS) is a non-traditional cardiovascular risk factor that is associated with an overall poor outcome in CKD patients. It was first and most widely described in patients with end-stage renal disease (ESRD) undergoing dialysis treatment [13], but further investigations should also be conducted in patients with CKD receiving conservative therapy, as there is now evidence that the increased morbidity and mortality associated with CKD correlates with malnutrition and chronic inflammation in addition to traditional risk factors, such as increased blood pressure, serum LDL cholesterol, body mass index, and the presence of cardiovascular disease [14]. Several scoring systems are useful for preventing and monitoring MICS, such as the subjective global assessment (SGA), the dialysis malnutrition score (DMS) and the malnutrition-inflammation score (MIS), which are also recommended in clinical settings [15]. In the malnutrition-inflammation score, a cut-off of 5 is needed to diagnose MICS, indicating an 88% risk of malnutrition [16]. Hence, appropriate nutritional management is important for preventing disease progression and ensuring proper metabolic status and overall health in CKD patients.

Vegetarian diets have been shown to positively impact cardiovascular health and reduce uremic toxin levels and inflammation through the consumption of large amounts of dietary fibres, n-3 fatty acids, vitamins and minerals [17]. Therefore, the type of protein, not only the amount, may be relevant in the prevention of MICS, but no studies are currently published in the literature regarding this aspect.

The aim of our study was to evaluate the feasibility and efficacy of a plant-based diet in reducing CKD-related complications and preventing MICS, assessing metabolic, mineral-bone, inflammatory and nutritional complications.

Materials and methods

Study design

The present investigation was a single-centre retrospective study based on forty-four patients aged ≤ 64 years old with CKD (between stage 3–5) in follow up at our ambulatory clinic. This study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki, and it was approved by the Institutional Ethical Committee of the University of Federico II Medical School, Naples as part of a previous data-banking project (Project identification code 181/18, approval date 18 July 2018). Between March 2023 and January 2024, the patients were followed in an outpatient dietetics clinic and received counselling from a doctor specializing in clinical nutrition and a dietician in our department. All subjects gave written informed consent and were recruited according to the following inclusion criteria: age ≤ 64, CKD (stage 3–5) in conservative therapy. Individuals with BMI ≤ 18 (kg/m²), eating disorders (bulimia, anorexia), impactful changes in drug therapy, food allergies or intolerances, on warfarin therapy, bedridden or with other possible causes of malnutrition (such as gastrointestinal malabsorption syndrome, cancer, dementia, depression, neurological disorders, and infections) were excluded from the study population.

A preliminary nutritional assessment (V-1) was carried out and each patient was asked to compile a food diary and starting from the following visit (V0), patients were assigned to either a low-protein vegetarian diet (LPVD) or a conventional low-protein animal diet (CLPAD) according to their habitual dietary patterns, food preferences, and clinical indications assessed during the baseline nutritional evaluation. After six months (V6), each patient underwent an evaluation involving biochemical parameters, anthropometric measurements, body composition, and pharmacological treatments.

Both dietary plans had identical protein intakes of 0.6–0.8 g/IBW/day and energy intake of 25–35 kcal/IBW/day, according to the latest KDOQI guidelines. Those who were prescribed a conventional low-protein diet needed to use protein-free products made up of carbohydrates, with almost no protein, phosphorus, sodium, or potassium [9]. They are used to ensure adequate calorie intake, leaving more room for foods rich in high biological value proteins, which guarantee the intake of essential amino acids.

All the clinically relevant parameters were recorded in a database during the follow up period of 6 months.

Biochemical parameters

Fasting venous blood samples were collected from patients, and the levels of serum albumin, serum electrolytes (calcium, phosphorus, potassium, and sodium), total cholesterol (TC), LDL cholesterol (LDL-C), HDL cholesterol (HDL-C), triglycerides (TG), blood glucose, glycated hemoglobin (HbA1c), 25(OH)D, vitamin B12, vitamin B9, uric acid, blood urea, creatinine, serum hemoglobin, and parathyroid hormone (PTH), fibrinogen, ferritin, iron, and cholinesterase (AChE) were evaluated via standard analytic laboratory methods. The eGFR was evaluated via the CKD-EPI formula [18].

Anthropometric measurements

The subjects had to be barefoot and in light clothes. Body weight and height were determined via a calibrated balance beam scale and a stadiometer (Seca 711; Seca Hamburg, Germany), after which body mass index [BMI (kg)/(m²)] was calculated. Waist circumference (WC) was assessed, according to National Institutes of Health (NIH) protocols, with a no-stretch tape measure, halfway between the lower edge of the rib cage and the iliac crest.

Blood pressure was measured via an aneroid sphygmomanometer.

Body composition analysis

Body composition was assessed via bioelectrical impedance analysis (BIA) with an 800 µ current at a single frequency of 50 kHz (BIA 101 RJL, Akern Bioresearch, from Florence, Italy) [19]. The exam was performed according to ESPEN guidelines: the electrodes were placed on the hand and the foot, according to Kushner, while patients lay supine with limbs slightly apart from their body after an overnight fast [20, 21]. The BIA parameters used to assess body composition were fat-free mass (FFM), fat mass (FM) (expressed in %), and phase angle (PA). Skeletal muscle mass (SM) was calculated via the following BIA equation from Janssen et al. 2000 ²⁰: SM (kg)=[(h2/BIA resistance × 0.401) + (gender × 3.825) + (age × 0.071)] + 5.102, where height (h) is expressed in cm, gender = 1 in men and 0 in women [22]. This value can be converted into the skeletal muscle mass index (SMI) by dividing the limb skeletal muscle mass (kg) by the square of the height (m²). Appendicular skeletal muscle mass (ASM) was extrapolated by BIA-measured resistance and reactance via the Kyle prediction equation ²¹: ASM (kg) = (-4.211 + (0.267*h²/BIA resistance) + (0.095*weight) + (1.909*gender)) + (-0.012*age) + (0.058*BIA reactance), where height (h) is expressed in cm and gender = 1 in men and 0 in women. ASM was normalized to height and expressed as appendicular muscle/height² (ASM/h²) [23].

Malnutrition inflammation score (MIS)

A modified version of the Malnutrition–Inflammation Score (MIS) was applied, excluding the dialysis-vintage item (not applicable to non-dialysis CKD patients) [24, 25]. Thus, nine of the ten standard items were evaluated: dietary intake, gastrointestinal symptoms, functional capacity, comorbidities, subcutaneous fat, signs of muscle wasting, BMI, serum albumin, and total iron-binding capacity (TIBC) (Table 1). The standard item assessing weight loss in dialysis patients was not included because intentional weight reduction in overweight/obese CKD subjects would not necessarily indicate malnutrition.

Table 1.

Components of the modified “Malnutrition-Inflammation Score” (MIS)

MIS Components	Score
	0	1	2	3
Medical History
Dietary intake	Good appetite, no deterioration of dietary intake	Sub-optimal solid dietary intake	Moderate overall decrease to full liquid diet	Hypo-caloric liquid to starvation
Gastrointestinal symptoms	No symptoms with good appetite	Mild symptoms, poor appetite or nauseated occasionally	Occasional vomiting or moderate GI symptoms	Frequent diarrhea or vomiting or sever anorexia
Functional capacity (nutritionally related functional impairment)	Normal to improved functional capacity, feeling fine	Occasional difficulty with baseline ambulation, or feeling tired frequently	Difficulty with otherwise independent activities (e.g. going bathroom)	Bed/chair ridden, or little to no physical activity
Comorbidity *	No comorbidity	Mild comorbidity (excluding MCC**)	Moderate comorbidity (including one MCC*)	Any severe multiple comorbidity (≥ 2 MCC*)
Physical exam
Decreased fat stores or loss of subcutaneous fat (below eyes, triceps, biceps, chest)	No change	Mild	Moderate	Severe
Signs of muscle wasting (temple, clavicle, scapula, ribs, quadriceps, knee, interosseous)	No change	Mild	Moderate	Severe
Body size
Body mass index (kg/m2)	≥ 20	18–19.9	16–17.99	< 16
Laboratory parameters
Serum albumin (g/L)	≥ 4	3.5–3.9	3.0–3.4	< 3.0
Serum total iron binding capacity (mg/d	≥ 250	200–249	150–199	< 150

**Major comorbid conditions (MCC) include CHF class III or IV, full blown AIDS, severe coronary artery disease, moderate to severe chronic obstructive pulmonary disease, major neurological sequelae, metastatic malignancy or recent chemotherapy

Each of the above parameters was scored into four levels of severity, from 0 (normal) to 3 (severely abnormal) [26]. A total score of 6–10 indicates mild malnutrition, whereas a score > 11 indicates severe malnutrition, which is predictive of an unfavourable prognosis [27, 28].

Hand grip strength measurement

Hand Grip Strength was measured to the nearest kilogram via a dynamometer on both hands (78010; Lafayette Instrument Company, Lafayette, IN, USA). The measurement was performed by having the patient stand upright with the arms lying not supported and parallel to the body. An average of three consecutive measurements were obtained with 30 s of rest between the measurements. According to the most recent consensus by EWGSOP2 the cut-off values for normal HGS were set to ≥ 27 kg for men and ≥ 18 kg for women [29].

Dietary assessment

Both LPVD and CLPAD were prescribed following the macronutrient and micronutrient distribution recommended by the Kidney Disease Outcomes Quality Initiative (KDOQI) guidelines [8]. The LPVD consisted of a lacto-ovo-vegetarian regimen providing 0.6–0.8 g protein/kg IBW/day, mainly from plant sources (legumes, cereals, vegetables, fruits), with inclusion of dairy products and eggs. Complementary combinations of cereals and legumes ensured adequate intake of essential amino acids. Whole-grain products were recommended whenever tolerated to increase fiber and micronutrient supply. The CLPAD provided the same protein target (0.6–0.8 g /kg IBW/day) with mixed animal and plant sources. Adherence to the diet was assessed monthly in all patients via the Food Frequency Questionnaire (FFQ) BLOCK questionnaire conducted by dietitians, which included 100 questions that are specifically tailored to the population with CKD [30]. More specifically, in this questionnaire, patients were asked how many servings (as defined in the questionnaire) of each considered food they consumed during the period of interest. From the data obtained by this questionnaire and by comparing them with specific tables showing the nutrient composition of each food, the nutrient and energy intake was calculated via the “Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria” (CREA) food composition Table [31]. At the same time, monthly dietary counselling was offered to all enrolled subjects with the aim of improving adherence to the prescribed diet.

Statistical analyses

For categorical variables, absolute numbers and frequencies (%) are shown. The Kolmogorov‒Smirnoff test was used to check normality. Normally distributed variables are presented as the means ± standard deviations (SDs). Abnormally distributed variables are expressed as the median and interquartile range. For comparisons between baseline data and follow-up data, normally distributed data were analysed via paired t tests, and abnormally distributed data were analysed via the nonparametric Wilcoxon test. For comparison between independent groups, Student’s t test or nonparametric Mann‒Whitney and chi-square tests were used. McNemar’s test and Pearson’s chi-squared test were performed to assess differences in paired and independent categorical variables, respectively. Linear regression analysis was performed to verify that independent variables (diabetes, drug therapy, BMI, WC and eGFR) associated with changes in serum urea, uric acid, cholinesterase serum creatinine, TC, LDL-C, fibrinogen, vitamin D, serum potassium, blood glucose and HbA1c levels after six months of treatment. All the statistical analyses were performed via SPSS 29.0 (SPSS Inc., Chicago, IL, USA). The statistical significance was set at p < 0.05.

Results

Baseline characteristics

A total of 44 patients were included in the analysis. At V0, patients were allocated to two groups according to habitual dietary patterns, food preferences, and clinical indications: the first group (n = 20; 45.5%) followed a LPVD and the second group (n = 24; 54.5%) followed a CLPAD. The baseline demographic characteristics, anthropometric measures, body composition, metabolic parameters and main comorbidities of the study population (n = 44, 65,9% males; mean age of 54,7 ± 9,4 years; mean BMI of 28,3 ± 5,3 kg/m²) are detailed in Table 2. No differences in baseline demographic characteristics, anthropometric measurements, body composition, metabolic parameters or major comorbidities between the two groups were reported. On the other hand, a significant difference in the Protein Intake was observed between two groups (p = 0.02). None of the enrolled subjects practiced structured physical activity.

Table 2.

Baseline anthropometric and dietary features, body composition characteristics, metabolic parameters and main comorbidities of the study population, assigned to the LPVD or CLPAD group

	LPVD (n.20)	CLPD (n.24)
Male sex, n (%)	15 (75.0%)	14 (58.3%)
Age, years	53.4 ± 9.5	55.7 ± 9.3
BMI, Kg/m2	29.1 ± 5.7	27.7 ± 5.2
Weight, Kg	85.1 ± 21.3	74.8 ± 12.5
WC, cm	99.4 ± 16.2	93.4 ± 13.7
MIS	1.6 ± 0.6	1.5 ± 0.6
CKD stage	Stage 3: 0.9 (45.0%) Stage 4: 11 (55.0%) Stage 5: 0 (0%)	Stage 3: 9 (37.5%) Stage 4: 12 (50.0%) Stage 5: 3 (12.5%)
Diabetes (n, %)	5 (25.0%)	1 (4.4%)
Dyslipidemia (n,%)	14 (70.0%)	17 (70.8%)
Hypertension (n,%)	20 (100%)	22 (91.7%)
Smoking (n,%)	5 (25.0%)	3 (12.5)
Causes of CKD	Diabetes: 1 (5.0%) ADPKD: 5 (25.0%) GN: 2 (10.0%) IA: 4 (20.0%) FSGS: 1 (5.0%) N.D.D : 5 (25.0%) OTHERS : 2 (10.0%)	Diabetes: 1 (4.2%) ADPKD: 5 (20.8%) GN: 4 (16.7%) IA: 4 (16.7%) RCC: 3 (12.2%) N.D.D : 4 (16.7%) OTHERS : 3 (12.7%)

Continuous variables are expressed as the *mean ± SD or **median and interquartile range (IQR). Categorical variables are expressed as numbers and percentages, and were compared using the chi-squared test. *P < 0.05 or **p < 0.001 vs. LPVD.Abbreviations: MIS, malnutrition inflammation score; BMI, body mass index; WC, waist circumference; CKD, chronic kidney disease; ADPKD, Autosomal Dominant Polycystic Kidney Disease; GN, Glomerulonephritis; AH, Arterial Hypertension; FSGS, Focal Segmental Glomerulosclerosis; N.D.D, Non Diagnosticable Disease

Continuous variables are expressed as the *mean ± SD or **median and interquartile range (IQR). Categorical variables are expressed as numbers and percentages, and were compared using the chi-squared test. *P < 0.05 or **p < 0.001 vs. LPVD.Abbreviations: MIS, malnutrition inflammation score; BMI, body mass index; WC, waist circumference; CKD, chronic kidney disease; ADPKD, Autosomal Dominant Polycystic Kidney Disease; GN, Glomerulonephritis; AH, Arterial Hypertension; FSGS, Focal Segmental Glomerulosclerosis; N.D.D, Non Diagnosticable Disease.

Nutritional and inflammatory status (MIS and related variables)

At baseline, the mean MIS score was comparable between groups (p < 0.001, LPVD; (p < 0.001, CLPAD) (Table 4). After six months, MIS remained stable in both groups, with a slight, non-significant reduction in LPVD patients (Δ = − 0.5 ± 0.8, p = 0.12). No participants developed malnutrition-inflammation complex syndrome (MICS) during follow-up.

Table 4.

Dietary features of LPVD e CLPAD group at baseline and after 6 months of treatment

	LPVD (n. 20)			CLPAD (n. 24)
	V0	V6	P value	V0	V6	P value
WC, cm	99.4 ± 16.2	96.5 ± 15.8	0.031	92.7 ± 13.7	91.3 ± 11.6	0.129
Weight, kg	85.1 ± 21.3	81.2 ± 20.5	0.012	74.8 ± 12.5	72.1 ± 10.8	0.023
BMI, kg/m2	29.1 ± 5.7	27.9 ± 5.5	0.016	27.7 ± 5.2	26.7 ± 4.7	0.022
FM, %	25.6 ± 9.6	23.6 ± 7.5	0.159	25.9 ± 12.1	24.8 ± 10.8	0.354
FM, kg	22.9 ± 11.5	20.0 ± 9.7	0.028	20.7 ± 12.5	18.5 ± 10.2	0.101
FFM, %	74.8 ± 9.7	76.8 ± 7.4	0.166	74.0 ± 12.1	75.3 ± 11.1	0.307
FFM, kg	62.2 ± 12.7	62.0 ± 13.7	0.593	54.0 ± 7.0	54.0 ± 7.0°	0.912
TBW, %	55.7 ± 8.1	56.7 ± 5.6	0.416	54.6 ± 8.9	55.6 ± 8.4	0.324
Phase Angle, Φ	6.1 ± 1.2	5.9 ± 0.9	0.322	6.2 ± 0.9	6.3 ± 1.2	0.731
SM, kg	34.3 ± 5.8	35.3 ± 6.7	0.092	31.8 ± 3.7	32.5 ± 5.0	0.208
SMI, kg\m²	11.8 ± 1.3	12.1 ± 1.6	0.099	11.7 ± 0.9	11.8 ± 0.9	0.267
ASM, kg	24.4 ± 6.3	24.4 ± 6.4	0.947	21.4 ± 3.0	21.6 ± 3.7	0.560
ASMI, kg\m²	8.3 ± 01.6	8.3 ± 1.6	0.980	7.8 ± 0.7	7.9 ± 0,8	0.608
HGSr, kg	37.1 ± 13.1	38.6 ± 11.4	0.394	29.1 ± 7.9	30.9 ± 11,2	0.402
HGSl, kg	35.0 ± 13.1	37.3 ± 10.6	0.146	27.8 ± 8.1	30.2 ± 9.5	0.118
MIS	1.6 ± 0.6	1.7 ± 0.9	< 0.001	1.5 ± 0.6	2.7 ± 0.8	< 0.001

Continuous variables are expressed as the mean ± SD or median and interquartile range (IQR). p values are for paired t test for each group ( V6 vs. V0). *P < 0.05 or **p < 0.001 vs. LPVD are for t tests of comparisons of between-group at baseline. °P < 0.05 or °°p < 0.001 vs. LPVD are for t tests of comparisons of between-group after six months

The effects of the two different dietary patterns on the prespecified parameters were evaluated after six months of treatment, with the following results: MIS malnutrition inflammation score; BMI, body mass index; WC, waist circumference; FM, fat mass; FFM, fat-free mass; SM, skeletal muscle mass; SMI, Skeletal Muscle Index; ASM, Appendicular Skeletal Muscle Mass; ASMI, Appendicular skeletal muscle index; HGSr, Right Handgrip Strength; HGSl,, Left Handgrip Strength

Serum albumin and total protein levels were maintained, while fibrinogen levels significantly decreased in the LPVD group compared with CLPAD (p < 0.05). Hand-grip strength (HGS) and body-composition parameters (fat-free mass, muscle mass index) remained stable.

These findings indicate that the plant-based low-protein diet was nutritionally safe and did not increase the risk of malnutrition or inflammation, as detailed in Tables 3 and 4.

Table 3.

Metabolic and dietary features of LPVD e CLPAD group at baseline and after 6 months of treatment

	LPVD (n.20)			CLPAD (n.24)
	V0	V6	P values	V0	V6	P values
Creatinine, mg/dL	2.5 ± 0.7	2.3 ± 0.7	0.004	2.9 ± 1.1	2.9 ± 1.2	0.441
Urea, mg/dL	95.2 ± 37.9	81.5 ± 29.5	0.016	101.8 ± 41.5	85.8 ± 35.8	0.045
eGFR (CKD-EPI)	29.3 ± 10.0	32.5 ± 10.4	0.003	26.9 ± 12.4	27.9 ± 14.6	0.416
Uric Acid, mg/dL	6.4 ± 1.4	5.4 ± 1.2	0.008	7.2 ± 1.7	6.4 ± 1.7°	0.015
TC, mg/dL	164.0 ± 35.4	155.2 ± 34.7	0.039	184.2 ± 41.8	177.7 ± 51.3	0.558
HDL-C, mg/dL	47.0 ± 14.8	46.9 ± 14.8	0.929	48.7 ± 13.4	51.3 ± 14.7	0.055
LDL-C, mg/dL	91.6 ± 30.9	82.9 ± 28.4	0.011	105.9 ± 35.8	100.4 ± 45.0	0.563
TG, mg/dL	127.3 ± 65.3	130.3 ± 53.2	0.786	148.3 ± 87.7	130.2 ± 44.6	0.221
AChE, U/L	8788.7 ± 2132.2	7702.2 ± 1742.2	< 0.001	9512.9 ± 2808.1	8367.1 ± 2014.2	0.005
25(OH)D, ng/mL	23.6 ± 9.6	27.3 ± 9.5	0.011	28.7 ± 15.1	28.7 ± 12.4	0.994
Fibrinogen, mg/dL	343.8 ± 65.4	319.7 ± 64.2	0.041	372.9 ± 85.3	363.8 ± 79.9	0.245
HbA1c, %	5.7 ± 0.8	5.6 ± 0.8	0.025	5.9 ± 0.9	5.8 ± 0.9	0.032
Glucose, mg/dL	96.3 ± 28.4	91.7 ± 23.7	0.048	88.8 ± 14.0	89.9 ± 16.0	0.730
Potassium, mmol/L	5.1 ± 0.7	4.8 ± 0.6	0.015	5.1 ± 0.5	4.9 ± 0.5	0.292
Phosphorus, mg/dL	3.7 ± 0.5	3.8 ± 0.7	0.684	3.9 ± 1.1	3.8 ± 0.8	0.678
Calcium, mg/dL	9.5 ± 0.4	9.5 ± 0.3	0.784	9.6 ± 0.6	9.5 ± 0.5	0.850
Sodium, mmol/L	140.9 ± 3.3	141.4 ± 3.5	0.131	141.2 ± 2.4	141.4 ± 1.6	0.584
PTH, pg/mL	170.0 ± 93.1	150.9 ± 82.6	0.297	216.1 ± 174.8	188.9 ± 191.9	0.190
Hemoglobin, g/dL	14.0 ± 1.4	13.8 ± 1.6	0.369	12.9 ± 1.7	13.2 ± 1.6	0.315
Albumin, g/dL	4.5 ± 0.3	4,4 ± 0.3	0.073	4.3 ± 0.4	4.4 ± 0.4	0.354
B12, pg/ml	333.6 ± 108.9	336.0 ± 93.9	0.769	398.9 ± 194.3	420.1 ± 144.6	0.530
B9, ng/mL	12.6 ± 12.1	10.2 ± 10.4	0.278	9.7 ± 12.6	14.4 ± 16.6	0.304
Iron, µg/dL	75.3 ± 22.9	79.5 ± 26.2	0.515	66.4 ± 19.9	80.9 ± 33.8	0.053
Ferritin, ng/mL	146.9 ± 130.9	170.0 ± 166.2	0.194	160.4 ± 121.7	141.3 ± 100.3	0.125
TIBC, µg/dL	311.5 ± 53.1	380.7 ± 149.9	0.097	292.7 ± 66.7	337.0 ± 81.8	0.120
SBAP, mmHg	133.7 ± 22.9	128.6 ± 23.3	0.192	129.9 ± 21.3	128.1 ± 19.5	0.567
DSAP, mmHg	82.0 ± 10.0	81.6 ± 9.3	0.868	79.8 ± 8.6	81.2 ± 12.3	0.410

Continuous variables are expressed as the mean ± SD or median and interquartile range (IQR). p values are for paired t test for each group ( V6 vs. V0). *P < 0.05 or **p < 0.001 vs. LPVD are for t tests of comparisons of between-group at baseline. °P < 0.05 or °°p < 0.001 vs. LPVD are for t tests of comparisons of between-group after six months. The effects of the two different dietary patterns on the prespecified parameters were evaluated after six months of treatment, with the following results

HDL, high-density lipoprotein; LDL-C, low-density lipoprotein; TC, total cholesterol; TG, triglyceride/HDL ratio, triglyceride/high-density lipoprotein ratio; PTH, parathyroid hormone; HbA1c, glycated hemoglobin; AChE, cholinesterase; 25(OH)D, 25-hydroxy-vitamin D; B12, B12 Vitamin; TIBC, total iron-binding capacity; SBAP, systolic blood arterial pressure; DBAP, diastolic blood arterial pressure

Dietary patterns and biochemical outcomes

Table 3 shows the results after 6 months of treatment, compared with baseline, for both groups. Six months after baseline, both groups were adherent to the prescribed protein intake but not to the prescribed energy intake (kcal/IBW/day) (p = 0.003, LPVD; p < 0,001, CLPAD). Significant improvements in serum urea (p = 0.016, LPVD; p = 0.045, CLPAD), uric acid (p = 0.008, LPVD; p = 0.015, CLPAD; p < 0.05), glycated hemoglobin (p = 0.025, LPVD; p = 0.022, CLPAD) levels were observed in both groups. Compared with the CLPAD group, the LPVD group presented a reduction in the serum creatinine level (p = 0.004) and a significant improvement in the eGFR (p = 0.003), vitamin D (p = 0.011) compared to the CLPAD group; a significant improvement in total cholesterol (p = 0.039), LDL cholesterol (p = 0.011), serum potassium level (p = 0.015) was observed in the LPVD group but not in the CLPAD group. Furthermore, a significant improvement in cholinesterase was observed in both groups (p < 0.001, LPVD; p = 0.005, CLPAD) and a significant decrease in blood glucose (p = 0.048) was observed in the LPVD group only. Furthermore, a significant difference was observed in the uric acid level between two groups at V6 (p = 0.034). Changes in fibrinogen and albumin are discussed in relation to the MIS results in Sect. 3.2.

Anthropometric and body composition

A significant decrease in body weight (p = 0.012, LPVD; p = 0.023, CLPAD) and Body Mass Index (p = 0.016, LPVD; p = 0.022, CLPAD) was observed in both groups, but a significant decrease in Fat Mass, Kg (p = 0.028) and waist circumference (p = 0.031) was observed in the group with LPVD only. No significant differences in Skeletal Muscle Mass, Skeletal Muscle Index, Appendicular Skeletal Muscle Mass or Appendicular skeletal muscle index were observed among the groups. On the other hand, a significant difference was observed in the Fat Free Mass (Kg) between two groups at V6 (p = 0.023).

Drug therapy and linear regression

At baseline, a significant difference was observed in the sodium bicarbonate therapy between two groups (p = 0.015). Significant modifications in the patients’ pharmacological therapy were observed during the period of dietary intervention in the group with CLPAD, particularly for vitamin D (p = 0.016) and urate-lowering therapy (p = 0.002) (Table 5). On the other hand, no significant associations were detected (Table 6) between independent variables (diabetes, drug therapy, Body Mass Index, Waist Circumference and eGFR) and serum urea, uric acid, cholinesterase serum creatinine, total cholesterol, LDL Cholesterol, fibrinogen, vitamin D, serum potassium, blood glucose or glycated hemoglobin levels.

Table 5.

Drug therapy in the LPVD group and CLPAD group at baseline and after 6 months

	LPVD (n. 20)			CLPAD (n. 24)
	V0	V6	P value	V0	V6	P value
Sodium bicarbonate	14 (70.0%)	14 (70.0%)	1.0	8 (33,3%)*	13 (54.2%)	0.063
Potassium therapy	1 (5.0%)	1 (5.0%)	1.0	2 (8,3%)	2 (8.3%)	1.0
Erythropoiesis-stimulating therapy	0 (0%)	1 (5.0%)	1.0	2 (8,3%)	4 (16.7%)	0.5
iron therapy	2 (10.0%)	2 (10.0%)	1.0	5 (28,8%)	8 (33.3%)	0.25
Folate Therapy	6 (30.0%)	11 (55.0%)	0.063	3 (12,5%)	7 (29.2%)	0.072
Urate-lowering therapy	12 (60.0%)	16 (80.0%)	0.125	8 (33,3%)	18 (75.0%)	0.002
Antihypertensive therapy	16 (80.0%)	20 (100%)	1.0	18 (75,0%)	23 (95.8%)	0.063
Statin therapy	10 (50.0%)	n.15 (75.0%)	0.063	14 (58,3%)	19 (79.2%)	0.063
Activated forms Vitamin D	8 (40.0%)	n.13 (54.2%)	0.063	6 (25,0%)	13 (54.2%)	0.016
Insulin therapy	1 (5.0%)	1 (5.0%)	1.0	1 (4.2%)	1 (4.2%)	1.0
oral hypoglycemics	2 (10.0%)	3 (15.0%)	1.0	1 (4.2%)	1 (4.2%)	1.0
GLP-1 analogues	1 (5.0%)	1 (5.0%)	1.0	1 (4.2%)	1 (4.2%)	1.0

p values are for McNemar test for each group ( V6 vs. V0). *P < 0.05 or **p < 0.001 vs. LPVD are for chi-squared test of between-group at baseline. °P < 0.05 or °°p < 0.001 vs. LPVD are for t tests of comparisons of between-group after six months

Table 6.

Regression analysis for the independent determinants of changes in fibrinogen, 25(OH)D, Che, LDL-C, HbA1c, potassium and uric acid

	Dependent Variables
Independent Variables	Fibrinogen	25(OH)D	AChE	LDL-C	HbA1c	Potassium	Uric Acid
eGFRβ pvalue	-0.2 0.2	0.01 0.7	-0.3 0.1	0.2 0.3	0.1 0.8	0.03 0.8	-0.2 0.3
WCβ pvalue	0.7 0.1	0.4 0.2	-0.03 0.9	0.4 0.1	0.04 0.9	0.2 0.5	-0.1 0.7
BMIβ pvalue	-0.2 0.3	-0.4 0.1	0.2 0.4	-0.3 0.2	-0.01 0.9	0.2 0.5	0.3 0.3
Drug Therapyβ pvalue	- -	0.2 0.5	- -	-0.04 0.8	0.3 0.2	0.2 0.3	-0.1 0.3
Diabetesβ pvalue	-0.01 0.9	0.4 0.1	0.3 0.1	-0.2 0.2	0.1 0.6	-0.2 0.2	-0.01 0.9

Discussion

Our retrospective study, which was conducted in a population of adult subjects with stage 3–5 CKD undergoing conservative therapy, evaluated the effects of a plant-based low-protein diet compared with a conventional low-protein diet supplemented with protein-free products in reducing complications secondary to CKD and preventing MICS.

Beneficial effects have been shown on indices of kidney function, lipid profile, glycemic profile, vitamin D levels, plasma fibrinogen, and anthropometric and body composition parameters as well as muscle strength, with no significant changes in the plasma Albumin level or other explored parameters after six months of treatment.

In general, the positive results attributed to LPDs in CKD patients are likely due to complex metabolic benefits rather than the simple reduction in nephron hyper filtration. In fact, the use of LPDs results in lower blood levels of uremic toxins and fixed acids but also potentially in better control of dyslipidemia and inflammation.

The progression of chronic kidney disease leads to impaired lipid metabolism. Several studies have shown that patients with CKD have elevated levels of TC, reduced concentrations and function of HDL-C and high levels of LDL-C, increasing the risk of cardiovascular disease (CVD) [32]. As expected, LPVD improved the serum urea and uric acid levels in the study group, but it also reduced the total serum cholesterol and LDL-C levels. Compared with CLPAD, the significant improvement of lipid metabolism depends on the different qualities of the protein source: animal-derived foods are rich in saturated fatty acids, in contrast with plant-based foods, which contain a higher percentage of polyunsaturated fatty acids [33].

The HDL-C levels did not differ between the groups during the study period. This may be because HDL-C levels are influenced by many factors, such as diabetes, smoking, alcohol consumption, and physical activity levels, as shown in several studies [34–37].

In addition to traditional risk factors, persistent inflammation and malnutrition seem to play major contributing roles in cardiovascular morbidity and mortality [38]. Chronic low-grade inflammation is very common in CKD patients and is associated with the progression of kidney dysfunction [39]. In fact, the progressive loss of renal function during CKD has been shown to be inversely correlated with increased levels of markers associated with inflammation, particularly C-reactive protein (CRP) and fibrinogen, as well as increased levels of proinflammatory mediators [40]. According to the literature, diets rich in plant-based foods are associated with lower levels of inflammatory markers [41, 42]. In the present study, the LPVD group presented a significant reduction in serum fibrinogen and AChE; the latter has been proposed as a possible marker of low-grade systemic inflammation in a few older studies [43]. However, given the retrospective nature of the study, we did not collect data related to CRP or other direct proinflammatory biomarkers that we do not use in our clinical practice. Furthermore, an increase in vitamin 25(OH)D (VitD) from baseline to follow-up was observed in the LPVD group compared with the CLPAD group. VitD, a fat-soluble steroid hormone, plays an essential role in maintaining bone health and is recognized for its antibacterial, antiproliferative and anti-inflammatory actions [44, 45]. It is commonly believed that the lower levels detected in individuals with excess adiposity may also be due to absorption by adipose tissue (AT) and its clearance from plasma [46]. According to the literature, the significant reduction in FM and WC in the LPVD group compared with those in the CLPAD group could explain the increase in plasma vitamin D levels in the first group, considering the absence of a change in drug therapy. Furthermore, no significant changes in angular phase or muscle mass indices, as assessed by BIA, were observed. Moreover, although there was no significant change, we reported an improvement in the HSG values, bilaterally, in both the LPVD and CLPAD groups. As shown by Cacciapuoti et al. [47], a low-protein diet is not associated with an increased risk of malnutrition or with worsening skeletal muscle mass as long as the prescribed energy intake is met.

In this regard, we should specify that in our study, real caloric intake was lower than prescribed in both groups. However, the significant loss of body weight and reduction in WC were still not accompanied by a loss of muscle mass in either group studied, probably because the mean energy intake remained within the recommended range according to the KDOQI guidelines [9].

In contrast with the recent literature [25], it is clear that the MIS is not always applicable for the nondialysis CKD population. All parameters of the MIS did not significantly vary in either group from baseline to follow-up, except for BMI; the latter significantly influences the MIS result, because a reduction in BMI corresponds to an increase in the MIS. This finding is not clinically unfavourable in our study population, as these are overweight subjects, in whom weight loss is not accompanied by a worsening of muscle mass or loss of strength but rather by FM and WC. In the case of an intentionally very low-protein diet, ketoanalogues should be added to the dietary plan to avoid increasing the risk of malnutrition [48].

Another interesting result is related to the improvement in glucose levels in the LPVD group compared with those in the CLPAD group, even if an improvement in the serum glycated haemoglobin (HbA1c) level was observed in both groups. As suggested in the literature [49], our evidence confirmed that adherence to a plant-based regimen rich in fibre benefits glycemic control [50], with a greater possibility of safety and feasibility in diabetic patients with CKD than in those with CLPAD.

In the LPVD group, the use of plant-based foods promoted an improvement in the eGFR and creatinine, which again did not depend on a reduction in muscle mass; however, compared with the conventional diet, the use of plant-based foods appeared to have an obvious beneficial effect on the eGFR and creatinine. Several studies in the literature have shown that animal-based proteins are detrimental to kidney health, whereas a plant-dominated diet can slow the progression of CKD [51] and have beneficial effects on overall renal health.

These include a reduction in nitrogen compounds and consequently lower production of ammonia and uremic toxins, a reduction in the formation of metabolites derived from animal proteins by intestinal bacteria that are linked to renal fibrosis and CV diseases and anti-inflammatory and antioxidant effects since a vegetarian diet is associated with a greater intake of natural anti-inflammatory and antioxidant ingredients, including carotenoids, tocopherols and ascorbic acid, which reduce the progression of CKD and CV risk [51].

A legitimate concern is the possible negative effect of the vegetarian diet on potassium levels. Recent studies have shown that dietary potassium intake has little influence on serum potassium levels and is not correlated with hyperkalaemia [52–54]. Therefore, concerns about increased intake of potassium from the diet and the risk of hyperpotassemia associated with plant-based regimens in CKD patients have been set aside. In fact, the results of our study revealed that the serum potassium levels in the subjects who underwent LPVD were significantly lower than those in the controls, confirming the above findings. Furthermore, it should be considered that the alkaline load due to the increased intake of fruits and vegetables favours the shift of potassium from the extracellular to the intracellular compartment. In contrast, the presence of a constipated bowel remains an important risk factor for hyperkalaemia [53]. Constipation was not systematically collected in our groups but we can deduce that the increased fibre intake of the plant-based diet corrects the constipation often observed in these patients by causing shorter intestinal transit and reduced potassium absorption. In addition, a plant-based diet may reduce gut-derived uremic toxins by increasing fibre intake and modulating the intestinal microbiota [55]. Given the small sample size, our preliminary data should be interpreted with caution.

Conclusions

In summary, a lacto-ovo-vegetarian low-protein diet was feasible and safe in non-dialysis CKD adults. After six months, LPVD improved renal and metabolic parameters and reduced inflammation markers without worsening nutritional status. Although the small number of patients recruited, these preliminary results support the potential benefits of plant-dominant protein restriction and warrant confirmation in larger, prospective trials.

Abbreviations

ADPKD

Autosomal Dominant Polycystic Kidney Disease

ASM

Appendicular Skeletal Muscle Mass

BIA

Bioelectrical Impedance Analysis

BMI

Body Mass Index

AChE

Cholinesterase

CKD

Chronic Kidney Disease

CLPAD

Low-Protein Animal-Based Diet

CREA

“Consiglio Per La Ricerca In Agricoltura E l’Analisi Dell’economia Agraria”

DBAP

Diastolic Blood Arterial Pressure

DM

Diabetes Mellitus

DMS

Dialysis Malnutrition Score

eGFR

estimated Glomerular Filtration Rate

ESRD

End Stage Renal Disease

FFM

Fat-Free Mass

FFQ

Food Frequency Questionnaire

FM

Fat Mass

FSGS

Focal Segmental Glomerulosclerosis

GLP-1

Glucagon-Like Peptide 1

GN

Glomerulonephritis

Hba1c

Glycated Hemoglobin

HDL-C

HDL-Cholesterol

HGS

Hand Grip Strength

IBW

Ideal Body Weight

KDOQI

Kidney Disease Outcomes Quality Initiative

LDL-C

LDL-Cholesterol

LPDs

Low-Protein Diets

LPVD

Low-Protein Vegetarian Diet

MICS

Malnutrition-Inflammation Complex Syndrome”

MIS

Malnutrition-Inflammation Score

NCDs

Non-Communicable Diseases

NIH

National Institutes Of Health

PA

Phase Angle

PEW

Protein-Energy Wasting

PTH

Parathyroid Hormone

SBAP

Systolic Blood Arterial Pressure

SD

Standard Deviation

SGA

Subjective Global Assessment

SM

Skeletal Muscle Mass

SMI

Skeletal Muscle Mass Index

TBW

Total Body Water

TC

Total Cholesterol

TG

Triglycerides

TIBC

Total Iron-Binding Capacity

UACR

Urine Albumin-To-Creatinine Ratio

WC

Waist Circumference

WHO

World Health Organization

Author contributions

Conceptualization, M.A. and M.R.; methodology, M.D.L. and M.A.; formal analysis, B.G. and M.D.L.; data curation, M.A. and M.D.L.; writing—original draft preparation, M.A. and M.D.L.; writing—review and editing, M.S.L., T.D.L., N.C.; visualization, I.C and G.G.; supervision, A.P. and B.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

This study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki, and it was approved by approved by the Institutional Ethical Committee of the Federico II University Medical School of Naples as part of a previous data-banking project (Project identification code 181/18, approval date 18 July 2018). All patients provided written inform consent for the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.