Discussion 1: Traumatic Brain Injury-wk7-1

Journal of the Neurological Sciences 364 (2016) 12–18

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Journal of the Neurological Sciences

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Analysis of the association of fluid balance and short-term outcome in traumatic brain injury

Zilong Zhao a,b,c,1, Dong Wang a,b,c,1, Ying Jia a,b,c,1, Ye Tian a,b,c, Yi Wang a,b,c, Yingsheng Wei a,b,c, Jianning Zhang a,b,c,⁎, Rongcai Jiang a,b,c,⁎ a Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China b Key Laboratory of Injuries, Variations and Regeneration of Nervous System, Tianjin Neurological Institute, Tianjin, China c Key Laboratory of Post-trauma Neuro-repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin Municipal Government, Tianjin, China

⁎ Corresponding authors at: Tianjin Neurologica Neurosurgery, Tianjin Medical University General Hosp District, Tianjin 300052, China.

E-mail addresses: [email protected] (J. Zha (R. Jiang).

1 Collaborating first authors contributed equally to this

http://dx.doi.org/10.1016/j.jns.2016.03.007 0022-510X/© 2016 Published by Elsevier B.V.

a b s t r a c t

a r t i c l e i n f o

Article history: Received 9 August 2015 Received in revised form 18 February 2016 Accepted 2 March 2016 Available online 3 March 2016

Introduction: A balance of fluid intake and output (fluid balance) influences outcomes of critical illness, but the level of such influence remains poorly understood for traumatic brain injury (TBI) and was quantitatively exam- ined in this study. Methods: We conducted a retrospective cohort study of 351 moderate and severe TBI patients to associate the de- gree of fluid balance with clinical outcomes of TBI. Fluid balance and intracranial pressure (ICP) were continu- ously recorded for 7 days on patients admitted to neurocritical care unit (NCCU). The short-term outcome was dichotomized into improvement and deterioration groups based on changes in Glasgow Coma Scale (GCS) mea- sured between admission and 30 days after admission. Fluid balance was calculated as: Fluid intake (mL) - fluid outputs (mL)/day × 5 and used to group patients in tertiles to study its effect on TBI outcome. Results: Patients at the low (b637 mL) and upper (N3673 mL) tertiles of fluid balance were associated with poor outcomes. Those in the upper tertile also had a higher incidence of acute kidney injury (AKI) and refractory in- tracranial hypertension (RIH). There was a negative correlation between the cumulative fluid balance and the short-term outcome for patients in the low tertile and a positive correlation between the cumulative fluid bal- ance and the short-term outcome in the upper fluid balance group. Levels of fluid balance were also associated with serum creatinine (Cr, r = 0.451, P b 0.0001) and days in NCCU (r = 0.188, P = 0.001). More patients in the upper tertile had ICP higher than 20 mm Hg (P = 0.009). A fluid balance in the upper tertile is an independent predictor of poor 30-day clinical outcomes after the adjustment for confounding variables in a multivariable lo- gistic regression model. Conclusion: We found that fluid balance in low and upper tertiles were associated with poor short-term outcomes and ICP variations. Fluid balance in the upper tertile may be an independent predictor for poor 30-day outcome, primarily due to high AKI and RIH.

© 2016 Published by Elsevier B.V.

Keywords: Traumatic brain injury Fluid balance Intracranial pressure monitoring Acute kidney injury Refractory intracranial hypertension

1. Introduction

Traumatic brain injury (TBI) is a leading cause of death and disability in the US, accounting for 30.5% of all trauma death and reports approx- imately 2.4 million new cases in 2009 [1]. Following severe TBI, the blood–brain barrier is disrupted, predisposing a patient to the develop- ment of cerebral edema and increase in intracranial pressure (ICP) [2]. Sodium and fluid volume restriction are suggested by the Brain Trauma Foundation (BTF) guideline to prevent or relieve intracranial

l Institute; Department of ital, 154 Anshan Road, Heping

ng), [email protected]

work.

hypertension [3]. The avoidance of fluid overload and administration of diuretic agents and albumin to maintain a proper colloid osmotic pressure have been advocated by “Lund therapy” [2]. Fluid restriction is used by clinicians as an ICP-lowering strategy. However, guidance on the management of fluid balance for patients with TBI has not been well established.

As standard care for severe TBI, multimodal neurological monitoring such as ICP can influence clinicians' decision in controlling fluid intake and administering dehydration drugs [4]. A high ICP in early TBI is asso- ciated with high volumes of fluidic intakes [5–7]. However, the multi- center, randomized and controlled trial on ICP monitoring of patients with severe TBI indicates that ICP monitoring was not superior to repet- itive imaging and clinical examination in caring for severe TBI [4]. Be- cause ICP monitoring is widely used in the Neurocritical care unit (NCCU) in many countries including China to guide fluid managements of patients, we conducted a retrospective analysis of 351 moderate and

13Z. Zhao et al. / Journal of the Neurological Sciences 364 (2016) 12–18

severe TBI patients to evaluate the benefits of ICP-guided fluid manage- ments for the recovery of TBI patients.

2. Methods

2.1. Study design

We analyzed hospital records of 351 patients with moderate and se- vere TBI admitted to NCCU in Tianjin Medical University General Hospi- tal from Jan, 2011 to Dec, 2014 in a retrospective observational study design. Inclusion criteria were non-penetrating brain trauma of 14– 65 years old patients with a post resuscitation GCS of 3–12. A patient was excluded from the study if he or she was younger than 14 years old; died or withdrew from life-support within 24 h after admission; had incomplete clinical records; and had no head computed tomogra- phy (CT) scan within 12 h of initial presentation; had a recent history of infectious diseases, tumor, liver dysfunctions and renal insufficiency.

2.2. Data collection

Data were collected through reviewing medical charts, surgery re- ports, intensive care records and NCCU database by 3 independent re- viewers. Data collected and analyzed included patient demographics, GCS on admission, blood transfusion/fluid resuscitation, ICP, and medi- cal images.

The fluid intake and output were recorded every hour, including the oral fluid intake, intravenous fluid, the urine output, the amount of blood and cerebrospinal fluid loss.

2.3. Fluid balance

A cumulative fluid balance was calculated by subtracting daily fluid outputs (urine, blood and cerebrospinal fluid loss) from overall fluidic intakes (oral and IV fluid) for the first 5 hospital stays [8]. The fluid bal- ance was recorded at 7 a.m. each morning. Patients admitted after 7 p. m. had their first day fluid balance calculated between 24 and 36 h,

Table 1 Clinical characteristics and outcomes of TBI patients grouped in tertile.

Low tertile (n = 117)

Middle te (n = 117

Baseline characteristics Age 51.62 ± 19.75 47.47 ± 1 Male 95 (81.19%) 84 (71.79 GCS at admission 7.60 ± 3.48 8.85 ± 3. ISS 25.29 ± 10.17 22.97 ± 1 Hypertension 49 (41.88%) 51 (43.59 Bilateral unreactive pupils 30 (25.64%) 22 (18.80 Surgery 22 (18.80%) 37 (31.62

Marshall classificationa

I 3 (2.56%) 2 (1.71%) II 24 (20.51%) 28 (23.93 III 30 (25.64%) 38 (32.48 IV 29 (24.79%) 25 (21.37 V 27 (23.08%) 21 (17.95 VI 4 (3.42%) 3 (2.56%)

Outcomes Short-term improved 57 (48.71%) 87 (74.35 AKI 12 (10.25%) 13 (11.11 RIH 6 (26.1%) 9 (23.7%) Hospitalization (days) 35.862 ± 67.18 32.230 ± Mechanical ventilation (days) 1.842 ± 3.39 2.315 ± 4 NCCU stay (days) 10.284 ± 21.04 10.651 ± Mean ICP (mm Hg) 19.922 ± 13.40 18.475 ± Mannitol total usage (mg) 4678.82 ± 4869.33 6433.43 ± Time on mannitol (days) 4.482 ± 4.86 5.247 ± 3

Continuous variables are expressed as mean ± SD and compared with Student's unpaired t-tes test. P1: comparison between patients with low and moderate tertiles for fluid balance. P2: com Coma Scale, ISS: injury severity score, AKI: acute kidney injury, RIH: refractory intracranial hyp

a The Marshall classification is based on a review of computed tomography, with higher clas

and every 24 h thereafter. The enrolled patients were grouped into tertiles of low, moderate and upper fluid balance as previously reported [8,9].

2.4. Clinical assessment of neurological outcomes

A short-term outcome was evaluated based on changes in Glasgow Coma Scale (GCS) between the admission and 1 month follow up as pre- viously reported [10,11]. We defined improvement as GCS increased ≥1 point and deterioration as a GCS unchanged or decreased by N1 point, or death during the monitoring period.

2.5. Refractory intracranial hypertension (RIH) and acute kidney injury (AKI)

RIH was defined as: ICP N 25 mm Hg for at least 30 min in patients without craniectomy, or ICP N 15 mm Hg for at least 15 min in patients who underwent decompressive craniectomy following the surgical re- moval of a hematoma, regardless “first tier” therapies that include ven- tricular drainage, sedation, cerebral perfusion pressure optimization, osmotherapy, hypothermia (a target temperature ≦37 °C), and neuro- muscular blockade [9,12]. Second tier therapies were initiated once RIH was diagnosed. A secondary review of data was conducted to ex- clude extraneous ICP values due to agitation or external and irrelevant stimulations. AKI was defined as serum creatinine N26 μmol/L or serum creatinine N1.5 fold higher than the reference value, or a urine output of b0.5 mL/kg/h for more than 6 consecutive hours [13].

2.6. Statistical analysis

Shapiro-Wilk test was used to evaluate whether or not a set of data fits a normal distribution. The clinical information was presented as per- centage (%), means ± SD, or median (interquartile range [IQR]). Group comparisons were made using Pearson's χ2 test, Student's unpaired t- test or Mann–Whitney U test. A multiple logistic regression model was used to evaluate independent predictors for short-term outcomes

rtile )

Upper tertile (n = 117)

P1 P2

8.09 48.05 ± 17.97 0.109 0.813 %) 93 (79.48%) 0.090 0.170 67 8.64 ± 3.17 0.008 0.634 0.16 23.96 ± 8.95 0.082 0.433 %) 59 (50.43%) 0.792 0.295 %) 26 (22.22%) 0.208 0.517 %) 40 (34.18%) 0.024 0.676

4 (3.42%) %) 27 (23.08%) %) 25 (21.37%) %) 37 (31.62%) %) 18 (15.38%)

6 (5.13%)

%) 49 (41.88%) 0.000 0.000 %) 26 (22.22%) 0.832 0.023

21(52.5%) 0.833 0.009 38.44 49.660 ± 58.32 0.368 0.009 .29 4.195 ± 9.75 0.476 0.160 13.80 16.625 ± 16.48 0.880 0.004 15.29 22.11 ± 15.08 0.717 0.304 5678.14 8559.848 ± 7712.26 0.033 0.039

.99 5.414 ± 8.28 0.263 0.865

t. Categorical data are expressed as number (percentage) and compared with Pearson's χ2

parison between patients with upper and moderate tertiles in fluid balance. GCS: Glasgow ertension, NCCU: Neurocritical Care Units, ICP: intracranial pressure. s indicating greater injury severity.

Fig. 1. Relationship between fluid balance and short-term outcome: Correlations between fluid balance and 30 day outcome of patients in low (A) and upper (B) tertiles for fluid balance. (C) Dynamic changes in the low tertile for fluid balance of patients who had improved (solid line) and deteriorated (dot line) 30 day outcomes in the first 5 days of hospitalization. (D) Dynamic changes over times in 30 day outcomes of patients in the upper tertile for fluid balance in the first 5 days of hospitalization.

14 Z. Zhao et al. / Journal of the Neurological Sciences 364 (2016) 12–18

and reported as odds ratios (OR) and 95% confidence interval (CI). Uni- variate correlations were performed using Pearson correlation coeffi- cients. Receiver operating characteristic (ROC) curves and the areas under the curves (AUC) for fluid balance variability were analyzed and used to predict short-term outcome. All analyses were carried out using SPSS for Windows version 17.0 (SPSS Inc., Chicago, Ill), and a P value of b0.05 was considered statistically significant.

Fig. 2. Fluid balance ROC curve for prediction of short-term outcomes: ROC curves for patients in of 837.5 mL and 3725 mL, respectively, were determined to be the threshold end point to sens 95% confidence interval [CI] = 0.585–0.746 for the lower fluid balance group, P = 0.000 and 0 0.000).

3. Results

3.1. Patient baseline characteristics

Charts from 378 TBI patients were initially reviewed, but 27 patients were excluded for incomplete data (n = 11) and a hospitalization time of b24 h (n = 16). Patient baseline characteristics and outcomes of 351

the lower (A) and higher (B) fluid balance group; the successive variations of fluid balance itively and specifically predict short-term outcomes (area under the curve [AUC] = 0.665, .698, 95% confidence interval [CI] = 0.620–0.775 for the higher fluid balance group, P =

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patients included in the study are listed in Table 1. The 5 day cumulative fluid balance of all patients was divided into tertiles of low, moderate and high balances with the cumulative fluid balance of b637 mL (−389.683 ± 940.959 mL, n = 117), 637–3673 mL (2103.649 ± 814.662 mL, n = 117) and N3673 mL (6078.59 ± 2112.481 mL, n = 117), respectively. The baseline clinical characteristics and short-term outcomes of patients in each tertile are shown in Table 1.

Fig. 3. Correlation of fluid balance with other parameters: significant correlations of fluid balan hospital stay (E).

3.2. Cumulative fluid balance and short term outcomes

The 5 day cumulative fluid balance differed among the three groups of patients independent of ICP monitoring (data not shown). The rate of short-term outcome improvement was significantly higher for patients in the moderate tertile compared to those in the low and upper tertiles independent of ICP monitoring (P b 0.05, Table 1). In contrast, fluid

ce with mean Cr (A), and NCCU stay (B), but not with mean ICP (C), mannitol use (D), and

Fig. 4. Dynamic changes of ICP in three fluid balance groups: ICP changes over time for patients in three tertiles for fluid balance (*P b 0.05 for patients in the low tertile vs. those in the moderate tertile; #P b 0.05 for patients in the upper tertiles vs. those in the moderate tertile).

16 Z. Zhao et al. / Journal of the Neurological Sciences 364 (2016) 12–18

balance was bidirectionally correlated with the short-term outcome for patients in low tertile for fluid balance (Fig. 1A) and upper tertile for fluid balance (Fig. 1B). Dynamic changes in cumulative fluid balance of patients with improved and deteriorated outcomes in the first 5 days are shown in Fig. 1C and D, respectively.

3.3. Cumulative fluid balance is an independent predictor of short term outcomes

We also analyzed cumulative fluid balance by ROC curves and AUC in order to identify threshold that discriminates excessively positive and negative fluid intake from cumulative fluid balance. For the analy- sis, patients were divided into two groups based on the medium value of the cumulative fluid balance. We then tested the sensitivity and spec- ificity of the correlation between short-term outcome and fluid balance (Fig. 2A and B) and identified a fluid balance of 3.72 L as the cutoff point for a sensitive and specific short-term outcome prediction of patients in the higher fluid balance group (AUC = 0.698, 95% CI = 0.620–0.775, P = 0.000, Fig. 2B), and a fluid balance = 837.5 mL for patients in the lower fluid balance group (AUC = 0.665, 95% CI = 0.585–0.746, P = 0.000, Fig. 2A). An interesting finding is that when patients in the mod- erate tertile were further divided into low and high input/output for subgroups analysis, the length of NCCU stay was significantly shorter for patients with low output compared to those with high output (5.94 ± 6.58 vs. 15.35 ± 17.21 days, P b 0.05), who also had significantly large amount of mannitol infusion (2902.77 ± 2861.87 vs. 9385.22 ± 6345.69 mg, P b 0.001). Similarly, patients with low output had a shorter hospital stay (24.89 ± 37.99 days) than those with high output (39.61 ± 37.71 days, P b 0.05), even though the 30 day outcome showed no differences between the two groups of patients.

Using a multivariable logistic regression model, we determined that fluid balance in the upper tertile was independently associated with poor 30 day outcomes after adjustment for age, gender, admission GCS, surgery, length of hospitalization/NCCU stays and the time on me- chanical ventilation (Table 2). A multiple logistic regression also showed that fluid balance in upper tertile was not independently asso- ciated with the development of AKI after adjustment for confounding variables (Table 2).

3.4. Correlation of cumulative fluid balance with other parameters

The rate of RIH was significantly higher for patients in the upper tertile compared to those in the moderate tertile (P b 0.05). However, there was no significant difference between patients in the low and moderate tertiles. When data from all patients was pooled, fluid balance was associated with the serum Cr level (r = 0.451, P b 0.0001, Fig. 3A) and length of NCCU stay (r = 0.188, P = 0.001, Fig. 3B), but not with ICP values (r = 0.117, P = 0.225, Fig. 3C), mannitol usage (r = 0.031, P = 0.615, Fig. 3D) and the length of hospitalization (r = 0.021, P = 0.699, Fig. 3E). Patients in the low and upper tertile for fluid balance had higher ICP values than those in the moderate tertile (Fig. 4).

More patients in the moderate (76%) and low tertiles (61%) main- tained their ICP below 20 mm Hg than those in the upper tertile did (48%) (P = 0.009, Supplementary Fig. 1). Fig. 4 shows mean ICP being continually maintained under 20 mm Hg during 7 days of hospitaliza- tion for patients in the moderate tertile, suggesting that a moderate fluid balance could be helpful to maintain the ICP in a safe range.

4. Discussion

We conducted a retrospective analysis of 351 moderate and severe TBI patients to define the relationship between clinical outcomes and ICP-guided fluid managements. We found that 1) high and low fluid bal- ance were associated with poor short-term outcomes and unstable ICP in TBI patients; 2) a high fluid balance was associated with AKI and RIH after adjustment for confounding variables; 3) a high or low output

for patients with moderate fluid balance was associated with longer hospital/NCCU stays and diuretics usage, but did not appear to affect clinical outcomes. Together, these results suggest that fluid balance in low and upper tertiles was associated with poor short-term outcomes of TBI.

An insufficient fluid in the early stage of critical illness may lead to tissue hypoperfusion and ischemia [14], whereas excessive intravenous fluid contributes to the development of tissue edema [15]. An optimal volume of fluid at any given time maintains tissue viability [16]. Our data suggest the critical importance of maintaining an appropriate fluid balance for TBI patients as either high and low fluid balance could result in poor outcomes, specifically that a high fluid balance neg- atively impacts on TBI after variables known to affect TBI outcomes (gender, GCS score at admission, age, or surgical treatment) were ad- justed. Furthermore, the brain has a higher sensitivity to fluid overload due to disrupted cerebrovascular autoregulation after the initial injury. Excessive fluid balance may exacerbate secondary brain injures such as edema, intracranial hypertension and the disruption of the blood- brain barrier, leading to worse outcome. In this regard, fluid therapy, which is necessary for volume resuscitation and the prevention of sec- ondary brain injury paradoxically become a source of harm to aggravate the secondary brain injury when it was improperly used.

Consistent with our findings, a retrospective study of the National Acute Brain Injury Study of Hypothermia demonstrated that a fluid bal- ance lower than −594 mL during the first 96 h post-injury was inde- pendently associated with poor outcomes [8]. Our data further demonstrate that a high fluid balance may be more detrimental as it predisposes a patient to RIH and AKI. This observation supports early re- ports that a high fluid balance independently predicts mortality in pa- tients with acute kidney injury [17] and that a high cumulative fluid balance is strongly associated with the development of bilateral pulmo- nary infiltrates following TBI [9]. It has recently shown that a positive fluid balance during a period of vasospasm risk could lead to worse out- comes for patients with subarachnoid hemorrhage secondary to the rupture of cerebral aneurysms [18]. A high fluid balance sets a patient to a state of a full or extreme hydration. The over hydration may be nec- essary to maintain a proper plasma volume of the blood when capil- laries are leaky [19]. However, excessive fluid in the presence of leaky capillaries can also lead to brain edema and pulmonary edema after traumatic brain injury [9,20], more ICU complications and a higher mor- tality in patients who undergo surgery [21,22]. The ARDS Clinical Trails Network has indeed reported that patients with a conservative strategy demonstrated a significant improvement in lung function and fewer complications [19]. Furthermore, a fluid overload may also require di- uretics as we have shown in Table 1. Diuretics are reported to increase the risk of death or poor outcome in patients with acute renal failure [23] and diuretic use is an independent risk factor for AKI in patients

Table 2 Multivariable logistic regression for factors associated with poor short-term outcome and AKI in patients after TBI.

Variable Crude Adjusted

OR (95% CI) P value OR (95% CI) P value

Multivariable logistic regression for factors associated with poor short-term outcome

Fluid balance-Upper tertilea 1.404 (1.128–1.748) 0.002⁎ 1.373 (1.003–1.880) 0.047⁎

Age 0.978 (0.943–1.015) 0.248 Gender 1.524 (0.255–9.088) 0.643 GCS at admission 0.806 (0.647–1.003) 0.054 Surgical treatment 0.985 (0.271–3.578) 0.981 Length of hospitalization, days 1.003 (0.982–1.025) 0.736 Length of NCCU stay, days 1.002 (0.939–1.069) 0.942 Days of mechanical ventilation 1.015 (0.936–1.102) 0.705

Multivariable logistic regression for factors associated with AKI

Fluid balance-Upper tertilea 1.219 (1.002–1.484) 0.047⁎ 1.25 (0.949–1.659) 0.110 Age 0.987 (0.952–1.023) 0.488 Gender 1.457 (0.254–8.345) 0.671 GCS at admission 0.988 (0.791–1.235) 0.921 Surgical treatment 1.535 (0.384–6.137) 0.544 Length of hospitalization, days 0.980 (0.951–1.011) 0.220 Length of NCCU stay, days 1.003 (0.926–1.085) 0.937 Days of mechanical ventilation 1.016 (0.922–1.119) 0.744

TBI traumatic brain injury, OR odds ratio, CI confidence interval, GCS Glasgow Coma Scale, AKI acute kidney injury, NCCU neurocritical care units ⁎ P b 0.05 a Fluid balance at the end of first 5 days N3673.1808 mL.

17Z. Zhao et al. / Journal of the Neurological Sciences 364 (2016) 12–18

with brain trauma [24]. Here, we further demonstrated that the use of diuretics mannitol is associated with a high incidence of AKI in patients with TBI [17].

A low fluid balance always can also be resulted when a large amount of diuretics is applied to reduce TBI-induced cerebral edema [25]. The Lund protocol recommended that a balanced or moderately negative fluid balance, achieved by diuretic agents and albumin infusion would reduce mortality and improve outcome [2,26]. However, the euvolemia should not result in elevated ICP in patients with TBI [27], a notion that is consistent with our result that a moderate fluid balance maintained ICP in an acceptable range (b20 mm Hg). We were unable to detect sig- nificant difference in 30 day outcomes between patients on ICP moni- toring and those without. The finding begs for the question as whether ICP monitoring in severe TBI is beneficial. Consistent with our results, there are several reports to show that ICP is not associated with a better outcome in TBI patients when compared to those without ICP monitoring [28,29].

In summary, we have shown that high or low fluid balances corre- late with poor clinical outcomes of patients with TBI. The study is lim- ited in several aspects. First, the cohort is small and this is a single center study. Second, the retrospective design is limited because pa- tients were not enrolled and processed in a standardized protocol for a prospective study. These limitations can be addressed in a large mul- ticenter prospective study design.

Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.jns.2016.03.007.

Conflict of interest

There are no conflicts of interest for the authors.

Acknowledgements

This work was supported by grants from National Natural Science Foundation of China State Key Program Grant 81330029 (JNZ) and Na- tional Natural Science Foundation of China research Grants 81271361 (JNZ), 81271359 (RCJ), 81100920 (DW), and the Ontario-China Re- search and Innovation Fund (OCRIF, 2011DFG33430).

References

[1] Centers for Disease C, Prevention, CDC grand rounds: reducing severe traumatic brain injury in the United States, MMWR Morbidity and mortality weekly report 62 (2013) 549–552.

[2] P.O. Grande, The “Lund Concept” for the treatment of severe head trauma—physio- logical principles and clinical application, Intensive Care Med. 32 (2006) 1475–1484.

[3] F. Brain Trauma, American Association of Neurological S, Congress of Neurological S. Guidelines for the management of severe traumatic brain injury, Journal of neurotrauma 24 (Suppl. 1) (2007) S1–106.

[4] R.M. Chesnut, N. Temkin, N. Carney, S. Dikmen, C. Rondina, W. Videtta, et al., A trial of intracranial-pressure monitoring in traumatic brain injury, N. Engl. J. Med. 367 (2012) 2471–2481.

[5] J.A. Myburgh, D.J. Cooper, S.R. Finfer, B. Venkatesh, D. Jones, A. Higgins, et al., Epide- miology and 12-month outcomes from traumatic brain injury in Australia and New Zealand, J. Trauma 64 (2008) 854–862.

[6] R. Sahjpaul, M. Girotti, Intracranial pressure monitoring in severe traumatic brain in- jury—results of a Canadian survey, The Canadian journal of neurological sciences Le journal canadien des sciences neurologiques 27 (2000) 143–147.

[7] N. Stocchetti, K.I. Penny, M. Dearden, R. Braakman, F. Cohadon, F. Iannotti, et al., In- tensive care management of head-injured patients in Europe: a survey from the European brain injury consortium, Intensive Care Med. 27 (2001) 400–406.

[8] G.L. Clifton, E.R. Miller, S.C. Choi, H.S. Levin, Fluid thresholds and outcome from se- vere brain injury, Crit. Care Med. 30 (2002) 739–745.

[9] J.J. Fletcher, K. Bergman, P.A. Blostein, A.H. Kramer, Fluid balance, complications, and brain tissue oxygen tension monitoring following severe traumatic brain injury, Neurocrit. Care. 13 (2010) 47–56.

[10] L. Liu, H. Wei, F. Chen, J. Wang, J.F. Dong, J. Zhang, Endothelial progenitor cells correlate with clinical outcome of traumatic brain injury, Crit. Care Med. 39 (2011) 1760–1765.

[11] Y. Tian, Z. Wang, Y. Jia, S. Li, B. Wang, S. Wang, et al., Intracranial pressure variability predicts short-term outcome after intracerebral hemorrhage: a retrospective study, J. Neurol. Sci. 330 (2013) 38–44.

[12] Brain Trauma F, American Association of Neurological S, Congress of Neurological S, Joint Section on N, Critical Care AC, Bratton SL, et al., Guidelines for the management of severe traumatic brain injury. VI. Indications for intracranial pressure monitoring, J. Neurotrauma 24 (Suppl. 1) (2007) S37–S44.

[13] A. Lewington, S. Kanagasundaram, Renal Association clinical practice guidelines on acute kidney injury, Neph0072on Clin. Pract. 118 (Suppl. 1) (2011) c349–c390.

[14] R. Murugan, J.A. Kellum, Fluid balance and outcome in acute kidney injury: is fluid really the best medicine? Crit. Care Med. 40 (2012) 1970–1972.

[15] J.R. Prowle, J.E. Echeverri, E.V. Ligabo, C. Ronco, R. Bellomo, Fluid balance and acute kidney injury, Nat. Rev. Nephrol. 6 (2010) 107–115.

[16] D. Gantner, E.M. Moore, D.J. Cooper, Intravenous fluids in traumatic brain injury: what's the solution? Curr. Opin. Crit. Care 20 (2014) 385–389.

[17] C. Teixeira, F. Garzotto, P. Piccinni, N. Brienza, M. Iannuzzi, S. Gramaticopolo, et al., Fluid balance and urine volume are independent predictors of mortality in acute kidney injury, Crit. Care 17 (2013) R14.

[18] G.M. Ibrahim, R.L. Macdonald, The effects of fluid balance and colloid administration on outcomes in patients with aneurysmal subarachnoid hemorrhage: a propensity score-matched analysis, Neurocrit. Care. 19 (2013) 140–149.

[19] M.G. Davies, P.O. Hagen, Systemic inflammatory response syndrome, Br. J. Surg. 84 (1997) 920–935.

[20] Y.H. Lien, J.I. Shapiro, Hyponatremia: clinical diagnosis and management, Am. J. Med. 120 (2007) 653–658.

[21] J.M. Silva Jr., A.M. de Oliveira, F.A. Nogueira, P.M. Vianna, M.C. Pereira Filho, L.F. Dias, et al., The effect of excess fluid balance on the mortality rate of surgical patients: a multicenter prospective study, Crit. Care 17 (2013) R288.

[22] A. Stein, L.V. de Souza, C.R. Belettini, W.R. Menegazzo, J.R. Viegas, E.M. Costa Pereira, et al., Fluid overload and changes in serum creatinine after cardiac surgery: predic- tors of mortality and longer intensive care stay. A prospective cohort study, Crit. Care 16 (2012) R99.

18 Z. Zhao et al. / Journal of the Neurological Sciences 364 (2016) 12–18

[23] R.L. Mehta, M.T. Pascual, S. Soroko, G.M. Chertow, P.S. Group, Diuretics, mortality, and nonrecovery of renal function in acute renal failure, J. Am. Med. Assoc. 288 (2002) 2547–2553.

[24] L. Fang, H. You, B. Chen, Z. Xu, L. Gao, J. Liu, et al., Mannitol is an independent risk factor of acute kidney injury after cerebral trauma: a case–control study, Ren. Fail. 32 (2010) 673–679.

[25] K.T. Kahle, B.P. Walcott, J.M. Simard, Continuous Hyperosmolar Therapy for Trau- matic Brain Injury-associated Cerebral Edema: As Good as It Gets, or an Iatrogenic Secondary Insult? Journal of Clinical Neuroscience: Official journal of the Neurosur- gical Society of Australasia, 202013 30–31.

[26] C.H. Nordstrom, Physiological and biochemical principles underlying volume- targeted therapy—the “Lund Concept”, Neurocrit. Care. 2 (2005) 83–95.

[27] R.P. Dutton, M. McCunn, Traumatic brain injury, Curr. Opin. Crit. Care 9 (2003) 503–509.

[28] O.L. Cremer, G.W. van Dijk, E. van Wensen, G.J. Brekelmans, K.G. Moons, L.P. Leenen, et al., Effect of intracranial pressure monitoring and targeted intensive care on func- tional outcome after severe head injury, Crit. Care Med. 33 (2005) 2207–2213.

[29] S. Shafi, R. Diaz-Arrastia, C. Madden, L. Gentilello, Intracranial pressure monitoring in brain-injured patients is associated with worsening of survival, J. Trauma 64 (2008) 335–340.