UNIVERSITA’ DEGLI STUDI DI PISA
DIPARTIMENTO DI MEDICINA CLINICA & SPERIMENTALE
SCUOLA DI SPECIALIZZAZIONE IN NEFROLOGIA
Coordinatore: Prof. Carlo Donadio
TESI DI SPECIALIZZAZIONE
FLUID MANAGEMENT IN THE INTENSIVE CARE UNIT.
THE ROLE OF BIOELECTRICAL IMPEDANCE VECTOR ANALYSIS IN THE ASSESSMENT OF
HYDRATION STATUS AND TO EVALUATE THE IMPACT OF FLUID OVERLOAD ON THE
OUTCOME IN CRITICALLY ILL PATIENTS.
Relatore:
Chiar.mo Prof. CARLO DONADIO
Chiar.mo Prof. CLAUDIO RONCO
Specializzanda: Dott.ssa SARA SAMONI
1
CONTENTS
ABSTRACT ... 2
1. INTRODUCTION ... 4
i. RELATION BETWEEN HYDRATION STATUS AND OUTCOMES IN CRITICALLY ILL PATIENTS ... 4
ii. METHODS TO EVALUATE HYDRATION STATUS ... 6
iii. BIOELECTRICAL IMPEDANCE VECTORIAL ANALYSIS ... 8
2. AIM OF THE STUDY ... 10
3. MATERIALS AND METHODS ... 10
i. STUDY DESIGN ... 10
ii. PATIENTS SELECTION CRITERIA ... 10
iii. DATA COLLECTION ... 11
iv. HYDRATION STATUS MEASUREMENT METHOD ... 11
v. STATISTICAL ANALYSIS ... 14
4. RESULTS ... 16
i. DESCRIPTION OF STUDY POPULATION ... 16
ii. DESCRIPTION OF HYDRATION STATUS TREND IN ICU STAY ... 18
iii. OUTCOMES ... 24
iv. RELATION BETWEEN HYDRATION STATUS AND MEAN ARTERIAL PRESSURE (MAP) DURING OBSERVATION PERIOD ... 31
v. RELATION BETWEEN HYDRATION STATUS, MAP AND CVP DURING OBSERVATION PERIOD ... 34
5. DISCUSSION ... 38
6. CONCLUSIONS ... 41
REFERENCES ... 42
2
ABSTRACT
Background: Clinical trials have shown a positive correlation between fluid overload and adverse
outcomes in critically ill patients admitted to ICU. Nevertheless, there is not currently a single method that can provide an accurate and timely assessment of whole body hydration status. The aim of this study is to evaluate the role of BIVA in assessment of hydration status and to assess the impact of hyperhydration on outcomes in ICU patients.
Methods: This is a prospective, dual-center study in critically ill patients. Anthropometric, medical
history and laboratory data of each patient admitted in ICU with an expected length of stay of 72 hours or more were recorded. Assessments of body fluid status was performed using Bioelectric Impedance Vectorial Analysis (BIVA), using a single frequency analyzer, at the baseline and daily for a period of 72-120 hours. Patients were considered normohydrated if BIVA hydration level was 72.7%-74.3% of fat-free body mass, dehydrated and hyperhydrated if hydration level was respectively <72.7% and >74.3%. According to BIVA numerical scale, dehydration and hyperhydration was classified into mild, moderate and severe.
Results: Four-hundred and eighty three BIVA measurements were taken in 114 pts. Logistic regression
analysis found significant association between ICU mortality and maximum hydration level reached in observation period (MAX HYD), either in patients with or without AKI (OR 1.26; 95% CI 1.08-1.45; p=0.01). Cox model showed a significant association between long-term mortality and both MAX HYD (OR 1.14; 95% CI 1.02-1.27; p=0.01) and percentage of days in which patients was hyperhydrated (OR 12.82; 95% CI 1.03-158.92; p =0.04), either in patients with or without AKI.
Conclusions: Our study confirms and expands literature data of a correlation between ICU mortality and
long-term mortality with hyperhydration. Failing a method to assess whole body fluid status, we believe that the routinely use of BIVA beside to current clinical-structural methods may help physician to individuate patients’ ideal dry weight. However, RCTs that evaluate fluid administration and diuretic
3
therapy taking into account also hydration status are needed in order to assess the precise role of BIVA in goal-directed fluid management in ICU.
4
1. INTRODUCTION
i. RELATION BETWEEN HYDRATION STATUS AND OUTCOMES IN CRITICALLY ILL PATIENTS
Accurate fluid management in critically ill patients is one of the most challenging and important tasks both for intensivists and nephrologists. Despite progress in the delivery of intensive care, assessment of hydration status and subsequent treatments in critically ill patients remain a hard and complex topic which require in-depth knowledge of body fluid homeostasis. In patients undergoing an acute inflammatory insult, the presence of arterial vasodilation and transcapillary albumin leak related to proinflammatory cytokines and hormones leads to arterial underfilling, microcirculatory dysfunction and secondary interstitial edema with systemic hypoperfusion. In this phase, adequate intravenous fluid administration is required to prevent evolution to multiple organ dysfunction syndrome. Subsequently, compensatory neuroendocrine reflexes and potential renal dysfunction result in hydrosaline retention and fluid overload (1). While an early fluid repletion in critically ill patients is mandatory, authors have recently underlined the importance of a correct late fluid management (2). Indeed, several clinical trials have shown a positive correlation between fluid overload and adverse outcomes in critically ill patients admitted to Intensive Care Unit (ICU) (3-8).
In 2006, the ARDS network investigators demonstrated that a “liberal” strategy of fluid management, as compared with a “conservative” one, increases the duration of mechanical ventilation and ICU stay in patients with acute lung injury (ALI), without significant difference in 60-day mortality (3). These results are consistent with the pathophysiologic hypothesis that higher serum oncotic pressure and lower intravascular pressure in the conservative-strategy group limit the development of pulmonary edema. Otherwise they showed no significant difference between groups in non-pulmonary organ failure (3). These results from the randomized clinical trial (RCT) substantially confirm those from previous observational studies (9-11).
Among the 3147 patients enrolled in the SOAP study (4), 1120 developed acute renal failure (ARF) defined as a serum creatinine (sCr) greater than 3.5 mg/dL or a urine output less than 500 mL/day,
5
according to renal SOFA score. Mean fluid balance (MFB) was significantly more positive in patients with ARF than in patients without ARF (p<0.05). In ARF group mean fluid balance was more positive among non-survivors than among survivors (980 mL/day vs 150 mL/day, p<0.001) and it was considered an independent predictor of mortality (p<0.001) in patients with early-onset ARF (within 2 days of ICU admission). In addition, in oliguric patients and in patients treated with renal replacement therapy (RRT), mean fluid balance was significantly more positive than in non-oliguric (620 mL/day vs 270 mL/day, p<0.01) and non-RRT patients (600 mL/day vs 390 mL/day, p<0.01), respectively, with higher mortality rates (4). The PICARD study group (5) confirmed the association between fluid overload, defined as a percentage of fluid accumulation greater than 10% over baseline weight at hospital admission, and mortality in patients with acute kidney injury (AKI) with or without requirement of RRT (respectively p=0.01 and p=0.05 after adjustment for APACHE III score). In this study AKI was defined as an increase in sCr ≥0.5 mg/dL when baseline sCr was <1.5 mg/dL or an increase in sCr≥1 mg/dL when baseline sCr was ≥1.5 mg/dL and lower than 5 mg/dL. They also assessed the association between the duration of fluid overload after AKI diagnosis and mortality (p<0.0001) and showed that fluid overload is associated with suboptimal recovery from AKI (p=0.007), expanding on prior knowledge (5). The RENAL study, which randomized 1508 AKI patients on continuous renal replacement therapy (CRRT) to higher (effluent flow 40 mL/Kg/h) versus lower (25 mL/Kg/h) intensity therapy, showed that a negative mean daily fluid balance was associated with a close to 70% reduction in the odds ratio (OR) for death at 90 days. Positive mean fluid balance was also associated with decreased RRT-free days at day 90 after randomization (7).
A forward stepwise logistic regression multivariate analysis with the ICU outcome as the dependent factor in patients with sepsis enrolled in SOAP study found that both higher cumulative fluid balance within the first 72 hours of onset of sepsis and daily fluid balance was independently associated with a higher risk of death (respectively, OR 1.1 per liter increase; 95% CI 1.1-1.1; p<0.001 and OR 1.8 per liter increase; 95% CI 1.6-2; p<0.001) (6).
6
Fluid overload in patients with AKI is also associated with a reduced likelihood of recovery of renal function as suggested by the PICARD study (5) and a retrospective study by Heung M. et al. Among the 170 patients that started RRT, 61 (35.9%) reached renal recovery within 1 year. In the non-recovery group more patients had fluid overload ≥10% than in the recovery group (48.6% vs 31.2%, p = 0.027). Each rise in percent of fluid overload at dialysis initiation was a significant negative predictor of kidney recovery (hazard ratio for recovery 0.97; 95% CI 0.95-1.0; p = 0.024). Similar results were obtained for 1-year survival (OR 0.96; 95% CI 0.92- 0.99, p =0.01) (8).
ii. METHODS TO EVALUATE HYDRATION STATUS
In literature, there is no consensus about terms and definitions regarding hydration status. As we know from physiology, body fluids are distributed in three body spaces (intracellular, vascular and interstitial) to varying degrees. Despite normally these spaces are in balance each other’s, in some clinical conditions this equilibrium is broken. In ICU lots of clinical setting may generate different disorders in body fluid distribution balance (mechanical ventilation, malnourishment, sepsis, heart diseases etc…). In this contest, authors use indiscriminately terms as hyperhydration, fluid overload and positive fluid balance, giving different definitions to each of them.
Currently methods to evaluate hydration status consider intravascular or extravascular spaces. In clinical practice, physicians must be able to combine them in order to evaluate whole hydration status and prescribe adequate therapies. At present, most commonly used clinical tools for the assessment of hydration status in ICU can be divided in non-invasive: physical examination (peripheral edema, jugular venous distension, hepato-jugular reflux or poor skin turgor and capillary refill, hypotension, tachycardia etc…), registration of fluid intake and output, laboratory tests (brain natriuretic peptide (BNP), blood lactate, mixed venous oxygen saturation (SvO2)), bioimpedance, radiological (chest X-ray) and ultrasound techniques (echocardiography, inferior vena cava (IVC) diameter evaluation, lung comet tails); and invasive: filling pressures (central venous pressure (CVP) and pulmonary artery occlusion
7
pressure (PAOP)), continuous cardiac output (CO) monitoring system (thermodilution and non-thermodilution techniques). [Table 1.1]
Edema is not usually detected until the interstitial fluid volume has risen to about 30% above normal (4-5 Kg of body weight), while severe dehydration can develop before clinical signs (12). Low accuracy has been found between exact determination of body weight and registration of fluid balance in ICU (13). Lung comet-tail artifact originates from fluid-thickened interlobular septa and fanning out from the lung surface. Despite its promising use in the assessment of hydration status in maintenance hemodialysis patients (14), different causes of lung extravascular fluid increase (microcirculatory dysfunction, heart diseases) must be taken into consideration in critically ill patients in ICU. In a recent meta-analysis the pooled correlation coefficient between baseline CVP and change in stroke volume index (SVI)/cardiac index (CI) in response to volume expansion in ICU patients was 0.28 (95% CI 0.16-0.40) (15). Similarly no significant association has been found between PAOP and volume status in the vast majority of studies (16, 17). Taking into account pathophysiology of critically illness, frequently characterized by altered cardiac function and vascular compliance, a weak relationship between preload indices and intravascular volume is expected (18). Continuous CO monitoring systems areconsidered the gold standard in evaluation of intravascular volume. In a systematic review of 29 studies, the pooled correlation coefficients between baseline PPV/SVV and change in stroke/cardiac index were 0.78 and 0.72, respectively. Sensitivity, specificity, and diagnostic odds ratio were 0.89, 0.88 and 59.86 for PPV and 0.82, 0.86 and 27.34 for SVV, respectively (19). These techniques, however, are limited to patients who receive controlled ventilation.
A further potential approach to critically ill patients is provided by the so-called “echodynamics” which applies ultrasound to hemodynamic monitoring. It is a non-invasive and bedside method which requires skilled operators. This fascinating technique, combining pathophysiologic and ultrasonographic knowledge, needs further investigation to assess its role in monitoring of ICU patients (20).
8
Method Assess intravascular or
extravascular volume Limits
Physical examination Both - Delayed onset
BNP Intravascular volume - Low specificity: other conditions can affect BNP level
SvO2 Intravascular volume
- Low specificity: other conditions can affect SvO2 level
Blood lactate Intravascular volume - Low specificity: other conditions can affect blood lactate level
Bioimpedance Both together - Incapacity to assess compartmentalized edema
Chest X-ray Both
- Radiation exposure
- Necessity of standardized measures of vascular pedicle width and cardiothoracic ratio
Echocardiography Intravascular volume - Necessity of baseline data IVC diameter Intravascular volume - Body habitus dependence
- Limits in intra-abdominal hypertension
Lung comet tails Extravascular volume - Low specificity: other conditions can generate lung comet tails
CVP Intravascular volume - Low specificity: other conditions can affect CVP PAOP Intravascular volume - Low specificity: other conditions can affect PAOP SVV and/or PPV Intravascular volume - Necessity of sedated, mechanically ventilated
patient
Table 1.1 Summary of clinical tools to evaluate hydration status.
iii. BIOELECTRICAL IMPEDANCE VECTORIAL ANALYSIS
Bioelectrical Impedance Vector Analysis (BIVA) measures total body impedance which can be considered a combination of resistance R (the opposition to the flow of an alternating current through intra-and extracellular electrolyte solutions), and reactance Xc (the capacity produced by the interfaces of tissues and cell membranes). The two measurements, standardized for height (H), can be displayed graphically: this generates an output that simultaneously reflects changes in hydration and soft tissue mass [Figure 1.1].
This technique has been validated in depth in healthy individuals (21, 22) as well as in maintenance hemodialysis and peritoneal dialysis patients (23-26). Indeed, in Nephrology Units BIVA usually implements history and physical examination in assessment of patients’ ideal dry weight (23, 25).
9
Characteristics of critically ill individuals (decrease vascular peripheral resistance, transcapillary albumin leak, mechanical ventilation, malnourishment, etc…) have contributed to create a certain distrust toward the utilization of BIVA to determine patients’ hydration status in ICU. Moreover, previous studies reported controversial evidences about the effectiveness of bioimpedance in ICU patients (27,28). It cannot be excluded that controversial results and opinions depend on the confused terms used to define hydration status and to a misleading role attributed to BIVA in intravascular volume measurement. Indeed, BIVA does not assess intravascular volume and it cannot be used by itself neither to determine fluid responsiveness nor to prescribe fluid therapy in ICU. Otherwise the combined evaluation of peripheral tissue hydration with BIVA and intravascular volume with other techniques may provide a useful clinical evaluation tool in the planning of fluid therapy for ICU patients.
Figure 1.1. RXc graph. Resistance (R) and impedance (Xc) measurements, standardized for height (H), can be displayed
10
2. AIM OF THE STUDY
The aim of the study is to evaluate the role of BIVA in assessment of hydration status and to assess the impact of hyperhydration on outcomes in critically ill patients admitted to ICU. In particular, it wants to evaluate the following:
1. Patients hydration status at ICU admission and how it varies during the stay, following the local fluid management practices;
2. Relationship between hydration status and mortality.
3. MATHERIALS AND METHODS
i. STUDY DESIGN
The study is a prospective assessment of hydration status of adult patients admitted to general ICU at San Bortolo Hospital, Vicenza, and at Cisanello Hospital, Pisa. The observational period starts within 24 hours from the admission to ICU and lasts for a minimum of 72 hours to a maximum of 120 hours.
ii. PATIENTS SELECTION CRITERIA
The adult patients admitted to ICU within 24 hours with an expected length of stay of 72 hours or more, as judged by the practicing clinician, were considered for eligibility for the study.
Exclusion criteria: 1. Age < 18 years; 2. Pregnancy;
11
4. Limb amputations;
5. Multi-drug resistance infection.
iii. DATA COLLECTION
Anthropometric, demographic and anamnestic data of each enrolled patient were recorded using study specific case report form and database. Clinical data, including fluid balance and hydration status, according to BIVA measurement, was registered at the enrollment and each of the five days of observation.
iv. HYDRATION STATUS MEASUREMENT METHOD
The assessments of hydration status was performed using RenalEFG (Akern, Pontassieve, Florence, Italy) by different trained operators at baseline and for the following five days. Patient measurements were collected using BIVA bioelectrical parameters concerning R, Xc, and phase angle, as well as hydration percentage of fat-free body mass. The parameters were measured by an alternating electric flow of 300 microA and an operating frequency of 50 kHz.
BIVA analysis were performed with patient in supine position on hospital bed without touching metal objects. The angle between upper limbs and trunk and between the legs were 30 and 45 degrees, respectively, according to indications [Figure 3.1]. The surface of the skin where electrodes were applied was previously cleaned with alcohol (or saline or water, if allergic to alcohol). The electrodes were positioned on the right hand and on the foot corresponding as indicated in figure 3.2.
Patients’ hydration status is commonly classified into three main categories: normohydrated, dehydrated and hyperhydrated; the last two categories is further subdivided into mild, moderate or severe. According to numerical scale for BIVA, the normal level of hydration is set between 72.7% and 74.3% of fat-free body mass. Higher and lower values represent states of hyperhydration and dehydration respectively. Dehydration is classified into mild (71% to 72.7%), moderate (69% to 71%),
12
and severe (less than 69%). Similarly, over-hydration is classified into mild (74.3% to 81%), moderate (81% to 87%), and severe (more than 87%) (29) [Figure 3.3].
13
14
Figure 3.3. BIVA numeric scale.
v. STATISTICAL ANALYSIS
The sample of the study was analyzed using descriptive statistics of all available variables (sex, age, height, etc…): mean, median and quantiles of continuous variables and frequency tables of categorical variables. Trend of hydration status during observation period was described through box-plots of hydration percentage over time and descriptive statistics on how many patients get well and how many get worse over time in terms of hydration percentage. The relationship between maximum hydration level reached (MAX HYD) and both cumulative fluid balance (CFB) and mean daily fluid balance (MFB) in observation period was investigated with a logistic model.
The relationship between ICU mortality and hydration status was analyzed through a logistic linear model where the response variable was ICU mortality and the explanatory variables were MAX HYD and
15
all other variables available (sex, age, height, etc...). The correlation between hydration status and overall survival was investigated using Cox's regression model with the numbers of days lived by the patients as the dependent factor and the hydration status and all other characteristics available as explanatory variables. Overall survival was defined from date of ICU admission until death, censoring surviving patients at study end.
The relation between hydration status and mean arterial pressure (MAP) in each observation day was represented in quadrant graphs while level curves was used to show the correlation between hydration status, MAP and CVP during first 72 hours.
16
4. RESULTS
i. DESCRIPTION OF STUDY POPULATION
One hundred and fourteen patients were enrolled. Ninety-five were admitted to general ICU at San Bortolo Hospital, Vicenza, and 19 at Cisanello Hospital, Pisa. Demographic, anthropometric and anamnestic data, clinical and laboratory values of patients at admission are summarized in table 4.1. Taking into account both ICUs, the most frequent criteria for admission to the ICU were post-surgical follow up (34.2%), followed by trauma (28%) and sepsis (26.3%). AKI, defined on the basis of Acute Kidney Injury Network (AKIN) criteria (30), and septic shock, defined on the basis of Surviving Sepsis Campaign (SSC) criteria (31), occurred respectively in 28.9% and 15.8% of the patients. CRRT was performed in 14.9% of cases. Considering results from both ICUs, the overall survival was 68.4%. Twenty-two patients (19.3%) died during ICU stay, 10 patients (9.6%) died after ICU discharge during hospital stay and 3 patients (3.2%) died after hospital discharge. Two patients dropped out from the study after hospital discharge [Table 4.1; figure 4.1].
VARIABLES S. BORTOLO HOSPITAL CISANELLO HOSPITAL TOTAL
DEMOGRAPHIC, ANTHROPOMETRIC AND ANAMNESTIC DATA
NUMBER 95 19 114 MALE (%) 64/95 (67.3%) 11/19 (57.9%) 75/114 (65.8%) HISTORY OF CKD 1-4 (%) 9/95 (9.5%) 8/19 (42.1%) 17/114 (15%) HISTORY OF CKD 5 (%) 3/95 (3.1%) 0/19 (0%) 3/114 (2.6%) HISTORY OF DIALYSIS (%) 3/95 (3.1%) 0/19 (0%) 3/114 (2.6%) HISTORY OF DIABETES (%) 22/95 (23.1%) 1/19 (5.3%) 23/114 (20.2%) HISTORY OF ARTERIAL HYPERTENSION (%) 55/95 (57.9%) 9/19 (47.4%) 64/114 (56.1%) HISTORY OF CORONARY ARTERY DISEASE (%) 21/95 (22.1%) 1/19 (5.3%) 23/114 (20.2%) HISTORY OF COPD (%) 10/95 (10.5%) 1/19 (5.3%) 11/114 (9.6%) HISTORY OF CIRROSIS (%) 4/95 (4.2%) 0/19 (0%) 4/114 (3.5%) HISTORY OF CANCER (%) 13/95 (13.7%) 6/19 (31.6%) 19/114 (16.7%)
Min. 1st Qu. Median Mean 3rd Qu. Max. Min. 1st Qu. Median Mean 3rd Qu. Max. Min. 1st Qu. Median Mean 3rd Qu. Max. AGE (years) 28 57.5 68 65.9 77 92 29 41 71 62.3 76.5 93 28 56.2 68.5 65.3 77 93 HEIGHT (cm) 130 165 175 172 178 190 150 165 168 170 177 190 130 165 172 171 178 190
17
SEPSIS (%) 24/95 (25.2%) 6/19 (31.6%) 30/114 (26.3%) POST-SURGERY (%) 31/95 (32.6%) 8/19 (42.1%) 39/114 (34.2%) TRAUMA (%) 27/95 (28.4%) 5/19 (26.3%) 32/114 (28%) CARDIAC ARREST (%) 9/95 (9.5%) 0/19(0%) 9/114 (7.9%) HEART FAILURE (%) 24/95 (25.2%) 0/19(0%) 24/114 (21%) STROKE (%) 23/95 (24.2%) 8/19 (42.1%) 31/114 (27.2%)CLINICAL DATA AT ICU ADMISSION
MECHANICAL VENTILATION (%) 88/95 (92.6%) 14/19 (73.7%) 102/114 (89.5%) Min. 1st Qu. Median Mean 3rd Qu. Max. Min. 1st Qu. Median Mean 3rd Qu. Max. Min. 1st Qu. Median Mean 3rd Qu. Max. FiO2 0.21 0.4 0.4 0.466 0.5 1 0.21 0.4 0.45 0.448 0.5 0.8 0.21 0.4 0.4 0.463 0.5 1
pH 6.9 7.43 7.47 7.45 7.53 7.68 7.24 7.38 7.4 7.4 7.44 7.49 6.9 7.4 7.46 7.44 7.54 7.68 Potassium (mEq/L) 2.6 3.35 3.8 3.84 4.2 6.7 3.08 3.64 4 3.94 4.16 5.12 2.6 3.4 3.8 3.86 4.2 6.7 Serum bicarbonate (mmol/L) 4.3 23.2 25.7 25.5 28.2 47 20.2 22.6 25.3 25.4 26.7 34.3 4.3 23.1 25.6 25.4 28.2 47 Serum creatinine (mg/dL) 0.43 0.62 0.87 1.3 1.29 8.67 0.41 0.635 0.96 1.51 1.94 6.08 0.41 0.622 0.89 1.33 1.37 8.67 Urea (mg/dL) 10 32.5 43 57.7 64.5 372 15 28.5 42 63.3 77 230 10 31.2 43 58.6 67 372 Systolic BP (mmHg) 45 103 126 130 158 215 88 110 122 130 142 190 45 103 124 130 157 215 Diastolic BP (mmHg) 20 47 58 58.6 69 110 43 50.5 60 61.7 68.5 100 20 48 58 59.1 69 110 Mean Arterial Pressure (mmHg) 28.3 68.7 81.3 82.3 98 145 58 73.8 80 84.4 93.5 123 28.3 68.9 80.7 82.6 97.2 145
CVP (mmHg) 2 8 10 10.2 12.2 18 2 8 10 10.2 12.2 18
Heart rate 36 63 78 80.3 95 181 36 61.5 74 78.1 101 115 36 62.5 77.5 80. 95.8 181 Hemoglobin (g/dL) 5.4 9.7 11 11.1 12.4 15.4 7.4 8.5 9.1 9.52 10.1 13.5 5.4 9.2 10.7 10.8 12.3 15.4 White blood cells (103/mL) 0.8 8.35 10.7 11.2 13.4 31.4 5.46 8.48 10.9 14.1 15.5 49.0 0.8 8.32 10.9 11.7 13.6 49.0 Hydration status (%) 66.2 73.8 77.1 78.8 83.4 93.1 72.7 73.6 75.8 79.1 83.3 93.2 66.2 73.7 77 78.9 83.4 93.2
ICU SCORING SYSTEM
APACHE II SCORE 10 15 20 20.9 26.5 46 6 11.5 14 13.5 17 20 6 14.2 18 19.7 24.8 46 SAPS II SCORE 13 44 53 53.2 62 114 6 34 44 41.2 47 68 6 42 52 51.2 61 114 SOFA SCORE 2 6.5 9 9.53 12 23 4 7 8 8.42 9.5 15 2 7 8.5 9.34 12 23
CLINICAL DATA DURING ICU STAY
AKI 26/95 (27.4%) 7/19 (36.8%) 33/114 (28.9%)
CRRT 14/95 (14.7%) 3/19 (15.8%) 17/114 (14.9%)
SEPTIC SHOCK 15/95 (15.8%) 3/19 (15.8%) 18/114 (15.8%)
CENTRAL NERVOUS SYSTEM FAILURE 46/95 (48.4%) 6/19 (31.6%) 52/114 (45.6%) HEMATOLOGICAL FAILURE 3/95 (3.1%) 5/19 (26.3%) 8/114 (7%)
LIVER FAILURE 17/95 (17.9%) 6/19 (31.6%) 23/114 (20.2%)
OUTCOMES
SURVIVAL AT ICU DISCHARGE 74/95 (77.9%) 18/19 (94.7%) 92/114 (80.7%) SURVIVAL AT HOSPITAL DISCHARGE 65/95 (68.4%) 17/19 (89.5%) 82/114 (71.9%) SURVIVAL AT THE END OF THE STUDY 61/95 (64.2%) 17/19 (89.5%) 78/114 (68.4%) Table 4.1. Main characteristic of study population at admission and during stay in ICU. CKD, chronic kidney disease;
18
Figure 4.1. Overall survival for study population.
ii. DESCRIPTION OF HYDRATION STATUS TREND IN ICU STAY
Hydration status was assessed by means of BIVA in all patients from baseline to 72–120 hours after ICU admission. Four hundred and eighty three BIVA measurement were performed. Taking into account both hospitals, 71 patients were hyperhydrated, 41 patients were normohydrated and 2 patients were dehydrated at ICU admission, according to BIVA. Distribution of hydration status in classes is illustrated in Figure 4.2. Box-plot of hydration status at baseline showed the wide prevalence of hyperhydrated
19
patients in both ICUs (Figure 4.3). Median of hydration percentage was 77.1% and 75.8% respectively in S. Bortolo and Cisanello ICU (Table 4.1).
Median of hydration status remained above normal values for all period of observation, as illustrated in box-plot in figure 4.4, where red dashed lines set the normohydration limits. At last, studying how many patients get well and how many get worse over time in terms of hydration percentage, we found an improvement index of -0.128 (Table 4.2) which indicates a slight worsening.
Correlation coefficients between MAX HYD and both cumulative fluid balance (CFB) and mean daily fluid balance (MFB) in observation period was 0.2911 (p=0.001) and 0.2828 (p=0.002), respectively, showing low correspondence [figure 4.5, figure 4.6].
20
21
22
Figure 4.4. Box-plot of hydration status during observation period. The red dashed lines set the normohydration limits.
End of observation period
Non-normal hydration status
Normal hydration status
Sum
B
asel
in
e
Non-normal hydration status
56
17
73
Normal hydration status
22
19
41
Sum
78
36
114
Table 4.1. Number of patients that get well and get worse over time in terms of hydration percentage. Improvement
23
Figure 4.5. Relation between MAX HYD reached and CFB in observation period (Correlation coefficient 0.2911;
24
Figure 4.6. Relation between MAX HYD reached and MFB in observation period (Correlation coefficient 0.2828;
p=0.002).
iii. OUTCOMES
The primary outcome of the study was to evaluate the relationship between hydration status, measured by means of BIVA, and mortality. According to this aim, a multiple logistic regression analysis with ICU mortality as response variable and MAX HYD and all other characteristics available as explanatory variables was performed. The final analysis was modeled deleting variables retained nor statistically neither clinically significant, according to literature data. With the optimal threshold, equal
25
to 20% (i.e., classifying as dead those for whom, through the logistic model, we estimate a probability of death greater than or equal to 20%), the final logistic model correctly classifies 21 of the 22 deaths occurred in ICU (sensitivity=95.5%) and 74 of the 92 survivors at ICU discharge (specificity=80.4%) (Table 4.3). A significant association between ICU mortality and MAX HYD was found (OR 1.26; 95% CI 1.08-1.45; p=0.01). Each added percentage point of maximum hydration status was associated with a higher probability of death of 26%, either in patients with or without AKI.
By the analysis, factors significant associated with higher ICU mortality were: stroke as admission diagnosis (OR 20.03; 95% CI 2.74-146.30; p=0.003), high serum creatinine at ICU admission (OR 1.76 per each mg/dl increase; 95% CI 1.00-3.08; p=0.04), high admission APACHE II score (OR 1.27 per point increase; 95% CI 1.08-1.43; p=0.002) and occurrence of septic shock during ICU stay (OR 11.56; 95% CI 1.58-84.24; p=0.01). An added factor associated with a trend toward higher ICU mortality was history of arterial hypertension (p =0.08). Unexpectedly, an inversely correlation between ICU mortality and history of CKD was found. Otherwise the same analysis showed an increased death risk of 75% for each mg/dl of increase in baseline sCr. The lack of discrimination between different severity stages of CKD in this model may probably explain these controversial results and represent a bias.
In order to assess the relation between hydration status and mortality after ICU discharge, a multivariate survival analysis using Cox's regression model with numbers of days lived by the patients as dependent factor and hydration status and all other characteristics available as explanatory variables was performed. Similarly to the first model, the final multivariated analysis was modeled deleting variables retained nor statistically neither clinically significant, according to literature data (Table 4.4). A significant association between long-term mortality and MAX HYD was found (OR 1.14; 95% CI 1.02-1.27; p=0.01). Each added percentage point of maximum hydration status was associated with a higher probability of death of 14%. In addition the model showed also correlation between long-term mortality and percentage of days in which patients was hyperhydrated (OR 12.82; 95% CI 1.03-158.92; p =0.04), either in patients with or without AKI (Figure 4.7; figure 4.8).
26
Among the admission diagnosis taken into account, the analysis showed a strong association between mortality after ICU discharge and both cardiac arrest and acute cerebrovascular disease (OR 23.72; 95% CI 4.40-127.83; p<0.001 and OR 32.52; 95% CI 6.21-170.04; p<0.001). Further factors associated with higher mortality after ICU discharge were: high serum creatinine at ICU admission (OR 4.66 per each mg/dl increase; 95% CI 1.83-11.86; p<0.05), high admission SAPS II score (OR 1.07 per point increase; 95% CI 1.03-1.11; p<0.001) and occurrence of septic shock during ICU stay (OR 11.58; 95% CI 2.65-50.44; p=0.001). The occurrence of AKI during ICU stay was associated with a trend toward higher risk of death, but, by analysis, they were not significantly correlated (p=0.09) (figure 4.9).
Variables
coef
OR
95% CI
p value
Lower
upper
MAX HYD
0.231
1.260
1.089
1.457
0.002**
Age
-0.535
0.586
0.373
0.919
0.020*
Age^2
0.004
1.004
1.001
1.008
0.016*
S. Bortolo Hospital
0.085
1.089
0.045
26.265
0.958
Sex
-0.203
0.816
0.212
3.137
0.767
Stroke as ICU admission diagnosis
2.998
20.038
2.744
146.309
0.003**
History of hypertension
1.543
4.679
0.828
26.448
0.081
History of CKD
-3.421
0.033
0.002
0.478
0.012*
APACHE II
0.221
1.247
1.082
1.438
0.002**
sCr(mg/dL) at ICU admission
0.566
1.761
1.006
3.084
0.047*
Septic shock
2.448
11.567
1.588
84.246
0.016*
27
Variables
coef
OR
95% CI
p value
lower
upper
MAX HYD
0.133
1.142
1.023
1.276
0.018*
Duration of HH in observation period
2.551
12.822
1.034
158.926
0.047*
Age
-0.326
0.722
0.535
0.973
0.032*
Age^2
0.003
1.003
1.001
1.005
0.012*
S. Bortolo Hospital
1.539
4.659
0.445
48.745
0.199
Sex
-1.336
0.263
0.058
1.196
0.084
Cardiac arrest as ICU admission diagnosis
3.166
23.722
4.402
127.835
<0.001***
Stroke as ICU admission diagnosis
3.482
32.521
6.219
170.044
<0.001***
AKI
1.111
3.036
0.839
10.980
0.090
SAPS II
0.069
1.071
1.030
1.114
<0.001***
sCr(mg/dL) at ICU admission
1.539
4.662
1.831
11.869
0.001**
Septic shock
2.449
11.581
2.658
50.449
0.001**
Table 4.4. Multivariate survival analysis using Cox's regression model with numbers of days lived by the patients as
28
Figura 4.7. Kaplan-Meier survival curves showing relation between hydration status at ICU admission and mortality.
29
30
31
iv. RELATION BETWEEN HYDRATION STATUS AND MEAN ARTERIAL PRESSURE (MAP) DURING OBSERVATION PERIOD
Daily quadrant graphs were drawn to combine hydration percentage (HYD), as measure of extracellular volume, and mean arterial pressure (MAP), as index of peripheral perfusion pressure commonly used in ICU to prescribe fluid therapy. The relation between HYD and MAP in each observation day was represented in figure 4.10 and figure 4.11. The cut-off line for hydration status was set at 74.3%. Two different cut-off were considered for MAP: MAP below than 65 mmHg indicated shocked patients, according to SSC criteria guidelines (31), while MAP above than 105 mmHg indicated hypertensive patients, according to European Society of Hypertension/European Society of Cardiology (ESH/ESC) (32). Different quadrants represented different clinical settings: HH and low BP (LBP) patients, NH and LBP patients, HH and medium BP (MBP) patients, NH and MBP patients, HH and high BP (HBP) patients and NH and HBP patients. On the basis of starting quadrants, patients were identified with different symbols. This descriptive analysis showed a trend to normalization of BP during the first 72-96 hours, as response to therapy, without significant changes in hydration status, which remains above normal values. These results indicated low correlation between HYD and MAP. After 72 hours some patients enrolled were discharged from ICU. Graph of day 5 showed a clinical worsening of remaining patients, with widespread BP value. Septic (red symbols in figure 4.10) and CRRT patients (red symbols in figure 4.11) were more likely hypotensive and hyperhydrated during all observation period. Kaplan-Meier survival curves showed relation between CRRT during ICU stay and mortality (Figure 4.12).
32
Figure 4.10. Quadrant graphs showing the relation between HYD and MAP in the observation period. Red symbols
33
Figure 4.11. Quadrant graphs showing the relation between HYD and MAP in the observation period. Red symbols
34
Figure 4.12. Kaplan-Meier survival curves showing relation between CRRT during ICU stay and mortality.
v. RELATION BETWEEN HYDRATION STATUS, MAP AND CVP DURING OBSERVATION PERIOD
Taking into consideration CVP as surrogate index of cardiac preload, level curves were drawn to evaluate relation between HYD, MAP and CVP during the first 72 hours. CVP values were available only for S. Bortolo patients. Graph of day 2 showed HYD and CVP increase, according to early fluid repletion, while MAP trend is toward normal values, as response to therapy. Graph of day 3 illustrated a slightly CVP decrease, while HYD remained still high, probably as response to reduce fluid therapy and/or increase extravascular volume in critically ill patients in ICU.
35
Figure 4.13. Graph showing the relation between HYD, MAP and CVP (level curves) within first 24 hours from ICU
admission. Color scale varying from red toward yellow and white represents increasing CVP values. X represents septic patients.
36
Figure 4.12. Graph showing the relation between HYD, MAP and CVP (level curves) in day 2. Color scale varying from
37
Figure 3.15. Graph showing the relation between HYD, MAP and CVP (level curves) in day 3. Color scale varying from
38
6. DISCUSSION
The main findings from this study are the following: i) Most of patients admitted to ICU were hyperhydrated, according to BIVA measurement; ii) Hyperhydration persisted and got slightly worse during ICU stay; iii) Low correlation was found between hydration status evaluated by means of BIVA and fluid balance recorded in ICU; iv) Higher values of MAX HYD were associated with higher risk of ICU death, either in patients with or without AKI; v) Higher long-term risk of death was associated to both MAX HYD and duration of hyperhydration, either in patients with or without AKI. In addition, a descriptive analysis of patients’ clinical showed low correlation between HYD and MAP, suggesting a complementary role of HYD, MAP and CVP.
The principle of BIVA is the measurement of total body impedance as combination of resistance (R) and reactance (Xc), indexed to height (H). R/H and Xc/H are represented in a normogram: the shorter the resulting vector, the higher the content of body fluids. BIVA can assess intracellular and extracellular water with no discerning between extravascular and intravascular volume. An algorithm was developed to finally convert these parameters into a synthetic measure of fat-free body mass hydration percentage, which allows for a simpler interpretation. While BIVA has been validated in depth in healthy subjects (21, 22) and in patients suffering from kidney disease (23-26), there are a few articles about credibility of BIVA methods in patients with abnormal fluid balance treated in ICU.
The assessment of hydration status and the optimization of fluid management in critically ill patients admitted to ICU is one of the most challenge for intensive care physicians. Acute inflammatory insults, as described above, lead to fluid distribution balance disorders with interstitial edema and decreased effective volaemia. In this case, adequate intravenous fluid administration is required to guarantee an adequate peripheral perfusion. On the other hand, response to therapy, activation of physiological neuroendocrine reflexes and potential occurrence of renal dysfunction lead to hydrosaline retention and fluid overload with a different timing from one patient to another (1). High positive end-expiratory pressure (PEEP) mechanical ventilation leads to intra-abdominal hypertension, which
39
promotes venous and capillary pressure increase with further capillary leakage into extravascular tissues (33). Furthermore, malnourishment, which causes severe loss of body cellular mass with increase of extravascular fluid volume, potential associated heart depression, and other particular ICU settings may worsen fluid distribution balance. As results of these conditions, a variable but consistent amount of intravenous fluid administrated shifts from intravascular to interstitial space. This may explains trend toward increase hydration percentage in fat-free body mass during first days in ICU, as well as high prevalence of hyperhydration at baseline, reported in this study. Indeed, baseline BIVA was performed within 24 hours from ICU admission and was affected by fluid administration during first hours (from the first contact between patient and first aid unit or operating room staff). Kaplan-Meier survival curves showed relation between both hydration status at ICU admission and MAX HYD with mortality. Despite in our observational study hyperhydration may simply be a marker of poor health rather than a cause of mortality, these results are consistent with literature data (2) and suggest the crucial role of timing in fluid management of critically ill patients.
The relationship between positive fluid balance and adverse outcome in critically ill patients has already been described in several studies (3-8). As discussed above, literature data reported association between positive fluid balance and mortality in septic patients (6), in AKI patients (4, 5) and in patients on CRRT (7). In this study we reported significant correlation between MAX HYD and ICU mortality, either in patients with or without AKI. Moreover long-term mortality was significant associated to both MAX HYD and duration of hyperhydration, either in patients with or without AKI.
Given the aforementioned findings, the assessment of hydration status gains considerable importance. Otherwise there is not currently a single method that can provide an accurate and timely assessment of whole body hydration status. In clinical practice, indeed, physicians must combine results from different method to achieve an approximately ideal dry weight and prescribe adequate therapies. One of the most common methods used in ICU for a rapid evaluation of hydration status is fluid balance monitoring. A prospective observational study showed low accuracy between exact determination of body weight and registration of fluid balance in ICU (13). According to this article, in our study we found
40
low correlation between hydration status evaluated by means of BIVA and fluid balance recorded in ICU. Nevertheless these results may be also explained by the previous pathophysiological observations.
In order to explore whole patients’ hydration status, herein including intravascular and extravascular spaces, and how it varies in response to therapy, we combined graphically HYD, MAP and CVP measured in first 72-120 hours from ICU admission. MAP is an index of peripheral perfusion pressure and it is used in ICU to guide therapy and to evaluate responsiveness. According to the above pathophysiological observations, our descriptive analysis showed a trend to normalization of MAP during the first 72-96 hours at the cost of hyperhydration persistence. These observations are extremely true in septic patients and patients on CRRT, according to their fluid accumulation in interstitium, hemodynamic instability, and large amount of fluid commonly administrated. Otherwise, septic shock was associated with higher mortality both in logistic analysis and in Cox’s regression model and Kaplan-Meier curves indicated higher risk of death in patients on CRRT. Including in the analysis also CVP as surrogate index of cardiac preload, graph of day 2 showed, in contrast to MAP, a similar increasing trend for CVP and HYD. Otherwise graph of day 3 illustrated a slightly CVP decrease, while HYD remained still high, probably as response to reduce fluid therapy and/or increase extravascular volume in critically ill patients in ICU. According to literature data, hydration status seemed more correlated with CVP than with MAP (34).
41
6. CONCLUSION
Our study indicates that hyperhydration is a frequent condition in critically ill patients admitted to ICU and it tends to persist during ICU stay. Moreover, our findings confirm and expand literature data of a correlation between ICU mortality and long-term mortality with hyperhydration. Thus, hydration status should be carefully considered in clinical management of critically ill patients. Failing a method to assess whole body fluid status, we believe that the routinely use of BIVA beside to current clinical-structural methods may help physician to individuate patients’ ideal dry weight. Moreover, it may suggest pathophysiological considerations that can guide therapy and management of critically ill patients admitted to ICU.
However, RCTs that evaluate fluid administration and diuretic therapy taking into account also hydration status are needed in order to assess the precise role of BIVA in goal-directed fluid management in ICU.
42
REFERENCES
1. Cordemans C, De Laet I, Van Regenmortel N et al. Fluid management in critically ill patients: the role of extravascular lung water, abdominal hypertension, capillary leak, and fluid balance. Ann Intensive Care 2012; 2: S1;
2. Rivers E, Nguyen B, Havstad S et al. Early goal-directed therapy in the treatment of severe sepsis and septic shock. N Engl J Med 2001; 345 (19): 1368-77;
3. Wiedemann HP, Wheeler AP, Bernard GR et al. Comparison of two fluid-management strategies in acute lung injury. N Engl J Med 2006; 354 (24): 2564-75;
4. Payen D, de Pont AC, Sakr Y et al. A positive fluid balance is associated with a worse outcome in patients with acute renal failure. Crit Care 2008; 12 (3): R74;
5. Bouchard J, Soroko SB, Chertow GM et al. Fluid accumulation, survival and recovery of kidney function in critically ill patients with acute kidney injury. Kidney Int 2009; 76 (4): 422-7;
6. Vincent JL1, Sakr Y, Sprung CL et al. Sepsis in European intensive care units: results of the SOAP study. Crit Care Med 2006; 34 (2): 344-53;
7. Bellomo R, Cass A, Cole L et al. An observational study fluid balance and patient outcomes in the Randomized Evaluation of Normal vs. Augmented Level of Replacement Therapy trial. Crit Care Med 2012; 40 (6): 1753-60;
8. Heung M, Wolfgram DF, Kommareddi M, Hu Y, Song PX, Ojo AO. Fluid overload at initiation of renal replacement therapy is associated with lack of renal recovery in patients with acute kidney injury. Nephrol Dial Transplant 2012; 27 (3): 956-61;
9. Schuller D, Mitchell JP, Calandrino FS, Schuster DP. Fluid balance during pulmonary edema. Is fluid gain a marker or a cause of poor outcome? Chest 1991; 100 (4): 1068-75;
10. Upadya A, Tilluckdharry L, Muralidharan V, Amoateng-Adjepong Y, Manthous CA. Fluid balance and weaning outcomes. Intensive Care Med 2005; 31 (12): 1643-7;
43
11. Epstein CD, Peerless JR. Weaning readiness and fluid balance in older critically ill surgical patients. Am J Crit Care 2006; 15 (1): 54-64;
12. Guyton AC. Textbook of Medical Physiology, 8th ed. Philadelphia, Saunders, 1991; 274-329;
13. Perren A, Markmann M, Merlani G, Marone C, Merlani P. Fluid balance in critically ill patients. Should we really rely on it? Minerva Anestesiol 2011; 77 (8): 802-11;
14. Basso F, Milan Manani S, Cruz DN et al. Comparison and Reproducibility of Techniques for Fluid Status Assessment in Chronic Hemodialysis Patients. Cardiorenal Med 2013; 3 (2): 104-112;
15. Marik PE, Cavallazzi R. Does the central venous pressure predict fluid responsiveness? An updated meta-analysis and a plea for some common sense. Crit Care Med 2013; 41 (7): 1774-81;
16. Michard F, Teboul JL. Predicting fluid responsiveness in ICU patients: a critical analysis of the evidence. Chest 2002; 121 (6): 2000-8;
17. Osman D, Ridel C, Ray P et al. Cardiac filling pressures are not appropriate to predict hemodynamic response to volume challenge. Crit Care Med 2007; 35 (1): 64-8;
18. Kalantari K, Chang JN, Ronco C, Rosner MH. Assessment of intravascular volume status and volume responsiveness in critically ill patients. Kidney Int 2013; 83 (6): 1017-28;
19. Marik PE, Cavallazzi R, Vasu T, Hirani A. Dynamic changes in arterial waveform derived variables and fluid responsiveness in mechanically ventilated patients: a systematic review of the literature. Crit Care Med 2009; 37 (9): 2642-7;
20. Guarracino F. Il monitoraggio emodinamico in area critica. Elsevier, 2009; 223-263;
21. Piccoli A, Rossi B, Pillon L, Bucciante G. A new method for monitoring body fluid variation by bioimpedance analysis: the RXc graph. Kidney Int 1994; 46 (2): 534-9;
22. Piccoli A, Nigrelli S, Caberlotto A et al. Bivariate normal values of the bioelectrical impedance vector in adult and elderly populations. Am J Clin Nutr 1995; 61 (2): 269-70;
44
23. Piccoli A. Identification of operational clues to dry weight prescription in hemodialysis using bioimpedance vector analysis. The Italian Hemodialysis-Bioelectrical Impedance Analysis (HD-BIA) Study Group. Kidney Int 1998; 53 (4): 1036-43;
24. Pillon L, Piccoli A, Lowrie EG, Lazarus JM, Chertow GM. Vector length as a proxy for the adequacy of ultrafiltration in hemodialysis. Kidney Int 2004; 66 (3): 1266-71;
25. Piccoli A. Bioelectric impedance vector distribution in peritoneal dialysis patients with different hydration status. Kidney Int 2004; 65 (3): 1050-63;
26. Donadio C, Consani C, Ardini M et al. Estimate of body water compartments and of body composition in maintenance hemodialysis patients: comparison of single and multifrequency bioimpedance analysis. J Ren Nutr 2005; 15 (3): 332-44;
27. Roos AN, Westendorp RG, Brand R, Souverijn JH, Frölich M, Meinders AE. Predictive value of tetrapolar body impedance measurements for hydration status in critically ill patients. Intensive Care Med 1995; 21 (2): 125-31;
28. Foley K, Keegan M, Campbell I, Murby B, Hancox D, Pollard B. Use of single-frequency bioimpedance at 50 kHz to estimate total body water in patients with multiple organ failure and fluid overload. Crit Care Med 1999; 27 (8): 1472-7;
29. Valle R, Aspromonte N, Milani L et al. Optimizing fluid management in patients with acute decompensated heart failure (ADHF): the emerging role of combined measurement of body hydration status and brain natriuretic peptide (BNP) levels. Heart Fail Rev 2011; 16 (6): 519-29; 30. Kidney Disease: Improving Global Outcomes (KDIGO) Acute Kidney Injury Work Group. KDIGO
Clinical Practice Guideline for Acute Kidney Injury. Kidney Int Suppl. 2012; 2: 1-138;
31. Surviving Sepsis Campaign Guidelines Committee including the Pediatric Subgroup. Surviving sepsis campaign: international guidelines for management of severe sepsis and septic shock: 2012. Crit Care Med 2013; 41 (2): 580-637;
45
32. Mancia G et al. 2013 practice guidelines for the management of arterial hypertension of the European Society of Hypertension (ESH) and the European Society of Cardiology (ESC): ESH/EHC task force for the management of arterial hypertension. J Hypertens 2013; 31: 1281-357;
33. du Cheyron D. Lung injury and renal failure: from protective ventilation to renal protection. Crit Care Med 2005; 33 (6): 1460-1;
34. Piccoli A, Pittoni G, Facco E, Favaro E, Pillon L. Relationship between central venous pressure and bioimpedance vector analysis in critically ill patients. Crit Care Med 2000; 28 (1): 132-7.
46
RINGRAZIAMENTI
A tutte le persone che, lavorando a Cisanello, al San Bortolo o all’IRRIV, mi hanno accolto come in una famiglia, insegnandomi la professione di Nefrologo, ma ancor prima quella di Medico. A tutte le persone che hanno speso un minuto o cinque anni ad insegnarmi i particolari tecnici e quelli umani di questa professione. A tutte le persone che mi hanno insegnato l’importanza del lavoro di squadra e della multidisciplinarietà in corsia come nella ricerca scientifica. A tutte le persone che hanno fatto sì che questi cinque anni fossero a volte terribili e a volte fantastici come in una vera palestra di vita, preparandomi al futuro. Grazie.
ACKNOWLEDGEMENT
To all those who, working in Cisanello, in San Bortolo or in IRRIV, have welcomed me like in a family, teaching me to be a Nephrologist, but even before to be a Doctor. To all those who have spent one minute or five years to teach me technical details as well as human ones of this job. To all those who have showed me the importance of teamwork and multidisciplinary in ward as well as in research projects. To all those who have made these five years sometimes awful and sometimes wonderful as in a real training ground for life, preparing me to the future. Thank you.
