Association between pain intensity, neck disability index, and working conditions among women employed in horticulture.

INTRODUCTION AND OBJECTIVE: One of the most frequent musculoskeletal disorders is neck pain (NP). NP can be associated with occupational activities and is more common among females than males. Horticulture is a branch of agriculture in which work is intensively manual, and characterized by repetitive tasks. The aim of the cross-sectional study was to analyze the association between pain intensity, neck disability index (NDI), and working conditions in terms of selected factors related to work in horticulture. MATERIAL AND METHODS: 44 women employed in horticulture met eligibility criteria (experienced necked pain). Five factors related to working conditions were investigated: work experience, upper extremity position, head position, prophylaxis, and stress frequency. NDI and visual analog scale (VAS) were used to investigate pain intensity and disability. RESULTS: It was found that the position of the upper limb at work and the frequency of stress were significantly associated with the VAS score (p=0.046 and p=0.02, respectively). With regard to NDI total score, a statistically significant association was found between work experience and stress frequency (p=0.02 and p=0.01, respectively). Analysis of the relationship between VAS and NDI total score showed a statistically significant weak positive correlation (R=0.39; p=0.01). CONCLUSIONS: NP and NDI are related to the activities that women working in horticulture have to perform. Stress seems to be an important factor in cervical problems among female workers leading to an increase in NP and disability.

Concentration of Apoptotic Factors in Bronchoalveolar Lavage Fluid, as Potential Brain-Lung Oxygen Relationship, Correspond to the Severity of Brain Injury.

BACKGROUND: The mechanism of acute brain injury initiates a cascade of consequences which can directly cause lung damage, and this can contribute to poor neurological outcomes. The aim of this study was to evaluate concentration of different apoptotic molecules in the bronchoalveolar lavage fluid (BALF) in patients after severe brain injury and to correlate them with selected clinical variables and mortality. METHODS: Patients with brain injury receiving BALF operation were included in the study. BALF samples were collected within the first 6-8 hours after traumatic brain injury (A) and at days 3 (B) and 7 (C) after admission to the intensive care unit (ICU). Changes in the BALF nuclear-encoded protein (Bax), apoptotic regulatory protein (Bcl-2), pro-apoptotic protein (p53) and its upregulated modulator (PUMA), apoptotic protease factor 1 (APAF-1), Bcl-2 associated agonist of cell death (BAD) and caspase-activated DNase (CAD) were analysed. These values were correlated with the selected oxygenation parameters, Rotterdam computed tomography (CT) score, the Glasgow Coma Score and 28-day mortality. RESULTS: We found a significant increase in the concentration of selected apoptotic factors at admission (A), at day 3 (B) and day 7 (C) after severe brain damage contrasted with baseline level A (p < 0.001, separately). That concentration of selected apoptotic factors was significantly correlated with the severity of the injury and mortality. CONCLUSIONS: Activation of different apoptotic pathways seems to be an important process occurring in the lungs of patients in the early phases after severe brain trauma. Levels of apoptotic factors in the BALF correlates with the severity of brain injury.

Synergistic Antifungal Interactions between Antibiotic Amphotericin B and Selected 1,3,4-thiadiazole Derivatives, Determined by Microbiological, Cytochemical, and Molecular Spectroscopic Studies.

In recent years, drug-resistant and multidrug-resistant fungal strains have been more frequently isolated in clinical practice. This phenomenon is responsible for difficulties in the treatment of infections. Therefore, the development of new antifungal drugs is an extremely important challenge. Combinations of selected 1,3,4-thiadiazole derivatives with amphotericin B showing strong synergic antifungal interactions are promising candidates for such formulas. In the study, microbiological, cytochemical, and molecular spectroscopy methods were used to investigate the antifungal synergy mechanisms associated with the aforementioned combinations. The present results indicate that two derivatives, i.e., C1 and NTBD, demonstrate strong synergistic interactions with AmB against some Candida species. The ATR-FTIR analysis showed that yeasts treated with the C1 + AmB and NTBD + AmB compositions, compared with those treated with single compounds, exhibited more pronounced abnormalities in the biomolecular content, suggesting that the main mechanism of the synergistic antifungal activity of the compounds is related to a disturbance in cell wall integrity. The analysis of the electron absorption and fluorescence spectra revealed that the biophysical mechanism underlying the observed synergy is associated with disaggregation of AmB molecules induced by the 1,3,4-thiadiazole derivatives. Such observations suggest the possibility of the successful application of thiadiazole derivatives combined with AmB in the therapy of fungal infections.

High Level of Irisin as a Marker of Malnutrition in Head and Neck Cancer Patients Subjected to Radiotherapy.

BACKGROUND Head and neck cancers (HNC) are the 7th most prevalent neoplasms in the world. In 50% of these patients, body weight loss and malnutrition are observed before the beginning of therapy. It is known that an important role in the pathomechanism of malnutrition and cachexia is played by the development of inflammation, degradation of muscle fibers, and browning of white adipose tissue (WAT). It was demonstrated that even a slight increase in irisin concentration leads to browning of WAT. MATERIAL AND METHODS The study group consisted of 50 patients with HNC. The nutritional status of the patients was assessed by the Nutritional Risk Score 2002 (NRS 2002) and Subjective Global Assessment (SGA) scales. Using bioelectrical impedance analysis (BIA), the parameters fat mass (FM) and fat-free mass (FFM) were obtained. RESULTS Higher irisin values (1.57 vs 1.18 [ng/ml], P=0.0004) were observed in patients with higher nutritional risk (≥3) evaluated according to the NRS scale. In patients assessed as B or C on the SGA scale, higher values of irisin concentration (1.38 vs 1.07 [ng/ml], P=0.0139) were noted. It was also observed that the level of irisin before treatment was negatively correlated (rho=-0.30, p=0.0350) with FM% and was positively correlated (rho=0.30, p=0.0340) with FFM% in BIA measurements performed after the 7th cycle of RTH. CONCLUSIONS Based on these results, we conclude that patients with malnutrition tend to have higher irisin values compared to normally nourished patients. A high level of irisin may be a useful marker of malnutrition in patients with HNC.

Impact of depressive disorders on clinical outcomes in patients with chronic heart failure.

Introduction: To date, there are no literature reports of research investigating the relationship between depression and chronic heart failure (CHF) in relation to selected nutritional, cardiac and laboratory parameters. Aim: To compare CHF parameters in relation to nutritional and laboratory parameters between depressed and non-depressed patients. Material and methods: We enrolled 94 CHF individuals from Lubelskie Voivodeship to assess depression prevalence and to compare values of cardiac, laboratory and nutritional parameters between depressed and non-depressed patients. Results: Depression was diagnosed in 66 (70.2%) individuals. We noted significantly lower ejection fraction (EF) (EF%) in the group of depressive patients compared to disease-free individuals (mean EF%: 42 ±12 and 49 ±9; p = 0.030) and worse outcomes in NYHA examination (p < 0.001). Depressed patients had lower body weight (p = 0.023), body mass index (BMI) (p = 0.044), serum albumin concentration (p = 0.015), and hemoglobin concentration (p = 0.042) and an elevated level of C-reactive protein (CRP) (p = 0.025) in comparison to the non-depressed group. The moderate or severely depressed group had a lower level of EF% (p = 0.019) and higher left anterior descending artery (LAD) (p = 0.040) compared with the group suffering from mild depression. We observed greater susceptibility to develop cachexia in patients diagnosed as moderately or severely depressed (p = 0.030). Moreover, in the mentioned group of patients, lower values of body weight (p = 0.037), fat-free mass (FFM) (p = 0.022) and hemoglobin concentration (p = 0.007) were found. Moreover, an inverse correlation between Beck Depression Inventory (BDI) score and EF% (r = -0.371; p = 0.017) was recorded. Conclusions: Depression in CHF patients is associated with worse cardiac, laboratory and nutritional outcomes. Unfavorable clinical characteristics of CHF patients are related to depression severity.

Association between Biomarkers of Mineral and Bone Metabolism and Removal of Calcium and Phosphate in Hemodialysis.

BACKGROUND: A significant drop of serum phosphate and calcium removal or loading during hemodialysis induce reactions in mineral and bone remodeling that may inversely affect phosphate and calcium removal during dialysis. OBJECTIVES: We aimed to analyze the interdependencies between biomarkers of mineral and bone metabolism and removal of phosphate and calcium during hemodialysis, as this complex relationship is not fully understood. METHODS: Three subsequent hemodialysis sessions during a 1-week treatment cycle with interdialytic periods of 2-2-3 days were monitored in 25 anuric patients. Calcium and phosphate concentrations were measured in serum before, at 1, 2, and 3 h, at the end, and 45 min after each session and in the outlet dialysate every 30 min. Biomarkers associated with mineral and bone metabolism: parathyroid hormone (PTH 1-34 and PTH 1-84), calcitonin, 25(OH)-vitamin D, fetuin-A, osteopontin, osteocalcin 1-43/49, and intact osteocalcin were assayed once in each patient before the midweek hemodialysis session. RESULTS: Post-dialytic and intra-dialytic serum phosphate of midweek hemodialysis session and phosphate mass removed within 1 week correlated positively with serum PTH (0.40 < rho <0.46, p value <0.05). Higher concentration of serum PTH was associated with an increased level of osteocalcin. Pre-dialytic, post-dialytic, average for treatment time and average weekly concentrations of ionized calcium in serum correlated positively with serum osteocalcin. Serum osteocalcin and osteopontin levels were associated with the masses of total and ionized calcium, respectively, removed during 3 hemodialysis sessions. CONCLUSIONS: During hemodialysis, phosphate removal was associated with serum PTH, whereas calcium kinetics was influenced by serum osteocalcin and osteopontin. These results demonstrate that active processes involving biomarkers of mineral and bone metabolism are affected by the phosphate and calcium kinetics already within 4 h hemodialysis sessions.

Hemodialysis-induced changes in hematocrit, hemoglobin and total protein: Implications for relative blood volume monitoring.

BACKGROUND: Relative blood volume (RBV) changes during hemodialysis (HD) are typically estimated based on online measurements of hematocrit, hemoglobin or total blood protein. The aim of this study was to assess changes in the above parameters during HD in order to compare the potential differences in the RBV changes estimated by individual methods. METHODS: 25 anuric maintenance HD patients were monitored during a 1-week conventional HD treatment. Blood samples were collected from the arterial dialysis blood line at the beginning and at the end of each HD session. The analysis of blood samples was performed using the hematology analyzer Advia 2120 and clinical chemistry analyzer Advia 1800 (Siemens Healthcare). RESULTS: During the analyzed 30 HD sessions with ultrafiltration in the range 0.7-4.0 L (2.5 ± 0.8 L) hematocrit (HCT) increased by 9.1 ± 7.0% (mean ± SD), hemoglobin (HGB) increased by 10.6 ± 6.3%, total plasma protein (TPP) increased by 15.6 ± 9.5%, total blood protein (TBP) increased by 10.4 ± 5.8%, red blood cell count (RBC) increased by 10.8 ± 7.1%, while mean corpuscular red cell volume (MCV) decreased by 1.5 ± 1.1% (all changes statistically significant, p < 0.001). HGB increased on average by 1.5% more than HCT (p < 0.001). The difference between HGB and TBP increase was insignificant (p = 0.16). CONCLUSIONS: Tracking HGB or TBP can be treated as equivalent for the purpose of estimating RBV changes during HD. Due to the reduction of MCV, the HCT-based estimate of RBV changes may underestimate the actual blood volume changes.

Model of fluid and solute shifts during hemodialysis with active transport of sodium and potassium.

BACKGROUND: Mathematical models are useful tools to predict fluid shifts between body compartments in patients undergoing hemodialysis (HD). The ability of a model to accurately describe the transport of water between cells and interstitium (Jv,ISIC), and the consequent changes in intracellular volume (ICV), is important for a complete assessment of fluid distribution and plasma refilling. In this study, we propose a model describing transport of fluid in the three main body compartments (intracellular, interstitial and vascular), complemented by transport mechanisms for proteins and small solutes. METHODS: The model was applied to data from 23 patients who underwent standard HD. The substances described in the baseline model were: water, proteins, Na, K, and urea. Small solutes were described with two-compartment kinetics between intracellular and extracellular compartments. Solute transport across the cell membrane took place via passive diffusion and, for Na and K, through the ATPase pump, characterized by the maximum transport rate, JpMAX. From the data we estimated JpMAX and two other parameters linked to transcapillary transport of fluid and protein: the capillary filtration coefficient Lp and its large pores fraction αLP. In an Expanded model one more generic solute was included to evaluate the impact of the number of substances appearing in the equation describing Jv,ISIC. RESULTS: In the baseline model, median values (interquartile range) of estimated parameters were: Lp: 11.63 (7.9, 14.2) mL/min/mmHg, αLP: 0.056 (0.050, 0.058), and JpMAX: 5.52 (3.75, 7.54) mmol/min. These values were significantly different from those obtained by the Expanded model: Lp: 8.14 (6.29, 10.01) mL/min/mmHg, αLP: 0.046 (0.038, 0.052), and JpMAX: 16.7 (11.9, 25.2) mmol/min. The relative RMSE (root mean squared error)averaged between all simulated quantities compared to data was 3.9 (3.1, 5.6) %. CONCLUSIONS: The model was able to accurately reproduce most of the changes observed in HD by tuning only three parameters. While the drop in ICV was overestimated by the model, the difference between simulations and data was less than the measurement error. The biggest change in the estimated parameters in the Expanded model was a marked increase of JpMAX indicating that this parameter is highly sensitive to the number of species modeled, and that the value of JpMAX should be interpreted only in relation to this factor.

Impact of hemodialysis on cardiovascular system assessed by pulse wave analysis.

Valuable information about cardiovascular system can be derived from the shape of aortic pulse wave being the result of reciprocal interaction between heart and vasculature. Pressure profiles in ascending aorta were obtained from peripheral waveforms recorded non-invasively (SphygmoCor, AtCor Medical, Australia) before, during and after hemodialysis sessions performed after 3-day and 2-day interdialytic intervals in 35 anuric, prevalent hemodialysis patients. Fluid status was assessed by Body Composition Monitor (Fresenius Medical Care, Bad Homburg, Germany) and online hematocrit monitoring device (CritLine, HemaMetrics, Utah). Systolic pressure and ejection duration decreased during dialysis. Augmentation index remained stable at 30 ± 13% throughout hemodialysis session despite the decrease of augmented pressure and pulse height. Subendocardial viability ratio (SEVR) determined after 3-day and 2-day interdialytic intervals increased during the sessions by 43.8 ± 26.6% and 26.1 ± 25.4%, respectively. Hemodialysis performed after 3-day and 2-day interdialytic periods reduced significantly overhydration by 2.4 ± 1.0 L and 1.8 ± 1.2 L and blood volume by 16.3 ± 9.7% and 13.7 ± 8.9%, respectively. Intradialytic increase of SEVR correlated with ultrafiltration rate (R = 0.39, p-value < 0.01), reduction in overhydration (R = -0.57, p-value < 0.001) and blood volume drop (R = -0.38, p-value < 0.01). The strong correlation between the decrease of overhydration during hemodialysis and increase in SEVR confirmed that careful fluid management is crucial for proper cardiac function. Hemodialysis affected cardiovascular system with the parameters derived from pulse-wave-analysis (systolic and augmented pressures, pulse height, ejection duration, SEVR) being significantly different at the end of dialysis from those before the session. Combination of pulse-wave-analysis with the monitoring of overhydration provides a new insight into the impact of hemodialysis on cardiovascular system.

Does the plasma refilling coefficient change during hemodialysis sessions?

The filtration coefficient in the Starling equation is an important determinant of plasma refilling during hemodialysis. A method for calculating from clinical data an estimate of the filtration coefficient, called the refilling coefficient, was proposed in the past. The assumption behind this method was that the only drive for refilling is the increase in plasma oncotic pressure, and the remaining Starling forces have negligible effect. The refilling coefficient was observed to decrease during hemodialysis, and this was interpreted as a change in the filtration coefficient. The purpose of our study was providing an alternative explanation for the behavior of the refilling coefficient and, using clinical data and mathematical modeling, to predict the values of the immeasurable Starling forces and provide the theoretical basis for the interpretation of the refilling coefficient as the filtration coefficient. Blood volume and bioimpedance data from 23 patients undergoing hemodialysis were used to calculate the refilling coefficient according to the original formulation and to fit a two-compartment model of protein and fluid transport. The changes in the other Starling forces were non-negligible, ranging from 19% to 60% of plasma oncotic pressure. The results showed that the decrease observed in the refilling coefficient is likely caused by neglecting important changes in the Starling forces while deriving the equation for the refilling coefficient. When these Starling forces were taken into account, constant filtration coefficient and dynamic refilling coefficient provided an equivalent description of the data in most cases. However, this was not true for a subgroup of sessions, which suggests that additional factors may also be responsible for the observed decrease in the refilling coefficient.

Patient-specific pulse wave propagation model identifies cardiovascular risk characteristics in hemodialysis patients.

Risk of cardiovascular associated death in dialysis patients is the highest among all other co-morbidities. Improving the identification of patients with the highest cardiovascular risk to design an adequate treatment is, therefore, of utmost importance. There are several non-invasive cardiovascular state biomarkers based on the pulse (pressure) wave propagation properties, but their major determinants are not fully understood. In the current study we aimed to provide a framework to precisely dissect the information available in non-invasively recorded pulse wave in hemodialysis patients. Radial pressure wave profiles were recorded before, during and after two independent hemodialysis sessions in 35 anuric prevalent hemodialysis patients and once in a group of 32 healthy volunteers. Each recording was used to estimate six subject-specific parameters of pulse wave propagation model. Pressure profiles were also analyzed using SphygmoCor software (AtCor Medical, Australia) to derive values of already established biomarkers, i.e. augmentation index and sub-endocardial viability ratio (SEVR). Data preprocessing using propensity score matching allowed to compare hemodialysis and healthy groups. Augmentation index remained on average stable at 142 ± 28% during dialysis and had similar values in both considered groups. SEVR, whose pre-dialytic value was on average lower by 12% compared to healthy participants, was improved by hemodialysis, with post-dialytic values indistinguishable from those in healthy population (p-value > 0.2). The model, however, identified that the patients on hemodialysis had significantly increased stiffness of both large and small arteries compared to healthy counterparts (> 60% before dialysis with p-value < 0.05 or borderline) and that it was only transiently decreased during hemodialysis session. Additionally, correlation-based clustering revealed that augmentation index reflects the shape of heart ejection profile and SEVR is associated with stiffness of larger arteries. Patient-specific pulse wave propagation modeling coupled with radial pressure profile recording correctly identified increased arterial stiffness in hemodialysis patients, while regular pulse wave analysis based biomarkers failed to show significant differences. Further model testing in larger populations and investigating other biomarkers are needed to confirm these findings.

Correction: Quantification of Dialytic Removal and Extracellular Calcium Mass Balance during a Weekly Cycle of Hemodialysis.

[This corrects the article DOI: 10.1371/journal.pone.0153285.].

Subject-specific pulse wave propagation modeling: Towards enhancement of cardiovascular assessment methods.

Cardiovascular diseases are the leading cause of death worldwide. Pulse wave analysis (PWA) technique, which reconstructs and analyses aortic pressure waveform based on non-invasive peripheral pressure recording, became an important bioassay for cardiovascular assessment in a general population. The aim of our study was to establish a pulse wave propagation modeling framework capable of matching clinical PWA data from healthy individuals on a per-subject basis. Radial pressure profiles from 20 healthy individuals (10 males, 10 females), with mean age of 42 ± 10 years, were recorded using applanation tonometry (SphygmoCor, AtCor Medical, Australia) and used to estimate subject-specific parameters of mathematical model of blood flow in the system of fifty-five arteries. The model was able to describe recorded pressure profiles with high accuracy (mean absolute percentage error of 1.87 ± 0.75%) when estimating only 6 parameters for each subject. Cardiac output (CO) and stroke volume (SV) have been correctly identified by the model as lower in females than males (CO of 3.57 ± 0.54 vs. 4.18 ± 0.72 L/min with p-value < 0.05; SV of 49.5 ± 10.1 vs. 64.2 ± 16.8 ml with p-value = 0.076). Moreover, the model identified age related changes in the heart function, i.e. that the cardiac output at rest is maintained with age (r = 0.23; p-value = 0.32) despite the decreasing heart rate (r = -0.49; p-value < 0.05), because of the increase in stroke volume (r = 0.46; p-value < 0.05). Central PWA indices derived from recorded waveforms strongly correlated with those obtained using corresponding model-predicted radial waves (r > 0.99 and r > 0.97 for systolic (SP) and diastolic (DP) pressures, respectively; r > 0.77 for augmentation index (AI); all p-values < 0.01). Model-predicted central waveforms, however, had higher SP than those reconstructed by PWA using recorded radial waves (5.6 ± 3.3 mmHg on average). From all estimated subject-specific parameters only the time to the peak of heart ejection profile correlated with clinically measured AI. Our study suggests that the proposed model may serve as a tool to computationally investigate virtual patient scenarios mimicking different cardiovascular abnormalities. Such a framework can augment our understanding and help with the interpretation of PWA results.

Phosphate Kinetics in Hemodialysis: Application of Delayed Pseudo One-Compartment Model.

BACKGROUND/AIMS: Various body-regulating mechanisms try to counteract rapid changes in serum phosphate levels during hemodialysis (HD). Neither recently proposed nor other existing standard compartment models are able to capture clinically observed intradialytic serum phosphate rebound. METHODS: Phosphate serum concentration was frequently measured during 75 HD sessions in 25 patients. Time delay was introduced into the standard pseudo one-compartment model in order to reflect the time needed for the body-regulating mechanism to affect serum phosphate level. RESULTS: Measured serum phosphate concentration at the end of 4 h dialysis session was on average larger than 1 h earlier (p value = 0.015). The model with time delay reproduced successfully 19 out of 21 and 9 out of 10 sessions with and without recorded intradialytic rebound, respectively. CONCLUSION: The intradialytic serum phosphate rebound is associated with the time delay reflecting efficacy of body-regulating mechanisms, that is, the larger the delay the larger is the intradialytic rebound.

Quantification of Dialytic Removal and Extracellular Calcium Mass Balance during a Weekly Cycle of Hemodialysis.

OBJECTIVES: The removal of calcium during hemodialysis with low calcium concentration in dialysis fluid is generally slow, and the net absorption of calcium from dialysis fluid is often reported. The details of the calcium transport process during dialysis and calcium mass balance in the extracellular fluid, however, have not been fully studied. METHODS: Weekly cycle of three dialysis sessions with interdialytic breaks of 2-2-3 days was monitored in 25 stable patients on maintenance hemodialysis with calcium concentration in dialysis fluid of 1.35 mmol/L. Total and ionic calcium were frequently measured in blood and dialysate. The volume of fluid compartments was measured by bioimpedance. RESULTS: Weekly dialytic removal of 12.79 ± 8.71 mmol calcium was found in 17 patients, whereas 9.48 ± 8.07 mmol calcium was absorbed per week from dialysis fluid in 8 patients. Ionic calcium was generally absorbed from dialysis fluid, whereas complexed calcium (the difference of total and ionic calcium in dialysis fluid) was removed from the body. The concentration of total calcium in plasma increased slightly during dialysis. The mass of total and ionic calcium in extracellular fluid decreased during dialysis in patients with the dialytic removal of calcium from the body and did not change in patients with the absorption of calcium from dialysis fluid. CONCLUSIONS: We conclude that about one third of patients on dialysis with calcium 1.35 mmol/L in dialysis fluid may absorb calcium from dialysis fluid and therefore individual prescriptions of calcium concentration in dialysis fluid should be considered for such patients.

Phosphate Kinetics During Weekly Cycle of Hemodialysis Sessions: Application of Mathematical Modeling.

Both hyperphosphatemia and hypophosphatemia are associated with increased morbidity and mortality among patients on dialysis. The control of serum phosphate concentration is a considerable clinical problem. Our study aimed to improve understanding of phosphate kinetics in patients on dialysis using mathematical modeling. Three consecutive hemodialysis sessions with breaks of 2-2-3 days were monitored in 25 patients. Phosphate concentration was measured every hour and 45 min after the end of dialysis in blood serum and every 30 min in dialysate during each session. Volume of fluid compartments and body composition were assessed by bioimpedance. The pseudo one-compartment model was applied to describe the profile of phosphate in blood serum during intra- and interdialytic periods of 1-week cycle of three hemodialysis sessions. Model parameters, such as phosphate internal clearance (KM ) and the rate of phosphate mobilization (RM ), were correlated with the reduction of serum phosphate concentration during dialysis (Cpost /Cpre ) and with equivalent continuous clearance (ECC) for phosphate. KM correlated negatively with predialysis serum phosphate concentration. There was significant positive correlation between RM and age. Postdialysis volume of phosphate central compartment was lower than, but correlated to, extracellular water volume. Parameters of the pseudo one-compartment model, phosphate internal clearance, and the rate of phosphate inflow to the central compartment (the one accessible for dialysis) from other phosphate body reservoirs correlated with the indices of dialysis adequacy, such as reduction of serum phosphate and ECC. The pseudo one-compartment model can be successfully extended from a single hemodialysis to the standard weekly cycle of sessions and the model parameters strongly correlate with the adequacy parameters of dialytic removal of phosphate.

Phosphate, urea and creatinine clearances: haemodialysis adequacy assessed by weekly monitoring.

BACKGROUND: The specific distribution of phosphate and the control mechanisms for its plasma level makes phosphate kinetics during haemodialysis (HD) considerably different from those of urea and creatinine and makes the quantitative evaluation of adequacy of phosphate removal difficult. We propose the application of equivalent continuous clearance (ECC) as a phosphate adequacy parameter and compare it with ECC for creatinine and urea. METHODS: Three consecutive dialysis sessions were evaluated for 25 patients on maintenance HD. Concentrations of phosphate, urea and creatinine in plasma were measured every 1h during the treatment and 45 min after, and every 30 min in dialysate. ECC was calculated using the removed solute mass assessed in dialysate and weekly solute profile in plasma. Similar calculations were performed also for the midweek dialysis session only. Different versions of the reference concentration for ECC were applied. RESULTS: ECC with peak average reference concentration was 5.4 ± 1.0 for phosphate, 7.0 ± 1.0 for urea and 4.7 ± 1.0 mL/min for creatinine. ECC for urea and creatinine were well correlated in contrast to the correlations of ECC for phosphate versus urea and creatinine. Midweek ECC were higher than weekly ECC, but they were well correlated for urea and creatinine, but only weakly for phosphate. CONCLUSIONS: HD adequacy monitoring for phosphate may be performed using ECC, but it is less predictable than similar indices for urea and creatinine. The values of ECC for phosphate are within the range expected for its molecular size compared with those for urea and creatinine.