Intraoperative ventilator settings and their association with postoperative pulmonary complications in neurosurgical patients: post-hoc analysis of LAS VEGAS study
verfasst von:
Chiara Robba, Sabrine N. T. Hemmes, Ary Serpa Neto, Thomas Bluth, Jaume Canet, Michael Hiesmayr, M. Wiersma Hollmann, Gary H. Mills, Marcos F. Vidal Melo, Christian Putensen, Samir Jaber, Werner Schmid, Paolo Severgnini, Hermann Wrigge, Denise Battaglini, Lorenzo Ball, Marcelo Gama de Abreu, Marcus J. Schultz, Paolo Pelosi, FERS for the LAS VEGAS investigators, the PROtective VEntilation Network and the Clinical Trial Network of the European Society of Anaesthesiology
Limited information is available regarding intraoperative ventilator settings and the incidence of postoperative pulmonary complications (PPCs) in patients undergoing neurosurgical procedures. The aim of this post-hoc analysis of the ‘Multicentre Local ASsessment of VEntilatory management during General Anaesthesia for Surgery’ (LAS VEGAS) study was to examine the ventilator settings of patients undergoing neurosurgical procedures, and to explore the association between perioperative variables and the development of PPCs in neurosurgical patients.
Methods
Post-hoc analysis of LAS VEGAS study, restricted to patients undergoing neurosurgery. Patients were stratified into groups based on the type of surgery (brain and spine), the occurrence of PPCs and the assess respiratory risk in surgical patients in Catalonia (ARISCAT) score risk for PPCs.
Results
Seven hundred eighty-four patients were included in the analysis; 408 patients (52%) underwent spine surgery and 376 patients (48%) brain surgery. Median tidal volume (VT) was 8 ml [Interquartile Range, IQR = 7.3–9] per predicted body weight; median positive end–expiratory pressure (PEEP) was 5 [3 to 5] cmH20. Planned recruitment manoeuvres were used in the 6.9% of patients. No differences in ventilator settings were found among the sub-groups. PPCs occurred in 81 patients (10.3%). Duration of anaesthesia (odds ratio, 1.295 [95% confidence interval 1.067 to 1.572]; p = 0.009) and higher age for the brain group (odds ratio, 0.000 [0.000 to 0.189]; p = 0.031), but not intraoperative ventilator settings were independently associated with development of PPCs.
Conclusions
Neurosurgical patients are ventilated with low VT and low PEEP, while recruitment manoeuvres are seldom applied. Intraoperative ventilator settings are not associated with PPCs.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Abkürzungen
VT
Tidal volume
Pplat
Plateau pressure
PEEP
Positive end-expiratory pressure
RM
Recruitment manoeuvres
PBW
Predicted body weight
PPCs
Post-operative pulmonary complications
ESM
Electronic supplemental material
Ppeak
Peak pressure
RR
Respiratory rate
FiO2
Fraction of inspired oxygen
ETCO2
End-tidal carbon dioxide
SpO2
Peripheral saturation of oxygen
MP
Mechanical power
ASA
American Society of Anaesthesiologists
ARISCAT
Assess Respiratory Risk in Surgical Patients in Catalonia
VCV
Volume-controlled ventilation
IQR
Interquartile range
SD
Standard deviation
PCV
Pressure-controlled ventilation
LOS
Length of stay
CPP
Cerebral perfusion pressure
ICP
Intracranial pressure
Background
Lung–protective ventilation strategies are increasingly used in surgical patients [1, 2]. Typical lung–protective strategies include the use of a low tidal volume (VT) and a low plateau pressure (Pplat), with moderate positive end–expiratory pressure (PEEP) and use of recruitment manoeuvres (RM) if needed [1, 2]. Among these settings, a low VT seems to have the most protective effects compared with moderate or high PEEP [3, 4].
However, lung–protective ventilation is rarely used in brain injured patients, in whom median VT is generally 9 ml/kg of predicted body weight (PBW) [5]. The role of intraoperative ventilator settings and their potential impacts on the development of postoperative complications (PPCs) has been scarcely evaluated in neurological patients [6]. Typically, patients with neurosurgical pathologies have been excluded from most trials on protective intraoperative ventilation. This may be because lung–protective strategies could have detrimental effects on cerebrovascular physiology, and thus might be potentially contraindicated in acute neurosurgical patients [7]. Moreover, just few and inconclusive data exist regarding the ventilator settings applied in patients undergoing spinal surgery and the incidence of PPCs in this population [8, 9].
Anzeige
We therefore conducted a post-hoc analysis of the ‘Local ASsessment ofVEntilatory management during General Anaesthesia for Surgery–study’ (LAS VEGAS), a conveniently sized international observational study in the operating rooms of patients receiving mechanical ventilation [10]. We focused on neurosurgical patients, including patients undergoing brain or spine surgery. The aims of this analysis were to assess which ventilator strategies were used in neurosurgical patients during general anaesthesia, and to assess the incidence of PPCs and risk factors (including type of surgery, ventilator settings, risk for PPCs) associated with the development of PPCs. The main hypothesis tested was that neurosurgical patients are ventilated with high tidal volume and low positive end expiratory pressure, and that intraoperative ventilator settings can have an effect on PPCs development.
Methods
LAS VEGAS study
This article is reported as per Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines (www.strobe-statemenent.org) (Electronic supplementary material ESM Table S1).
LAS VEGAS [8] was an international multicentre observational prospective study (registered at www. clinicaltrials.gov (study identifier NCT01601223)), endorsed and supported by the European Society of Anaesthesiology and the Amsterdam University Medical Centres, location AMC, Amsterdam, The Netherlands. Details about the LAS VEGAS study collaborators, participating centres and hospital characteristics of participating centres are reported in ESM Tables S2a, b and S3.
All adult patients requiring invasive ventilation for surgical procedures in a time window of 7 days were included. Exclusion criteria were: age under 18 years, obstetric procedures, recent ventilation before surgery (< 28 days), surgical procedures not performed in the operating room, and interventions requiring cardiopulmonary bypass.
Anzeige
For this study, we restricted the analysis to patients receiving intraoperative ventilation for neurosurgical procedures (brain or spine surgery) (ESM Flow Chart).
Data collection
After inclusion, the following data were collected: patients’ baseline and demographic characteristics; the assess respiratory risk in surgical patients in Catalonia (ARISCAT) score [11]; American Society of Anaesthesiologists (ASA) scale; details on the surgical procedure including intraoperative hourly vital parameters and ventilation data (mode of ventilation, fraction of inspired oxygen (FiO2), VT, PEEP, peak pressure (Ppeak), respiratory rate (RR)), end-tidal CO2 (ETCO2), oxygen saturation (SpO2), number and type of recruitment manoeuvres, and intraoperative complications.
Recruitment manoeuvres were defined as ‘rescue’ when the recruitment manoeuvre was not part of the planned ventilation strategy and defined as ‘planned’ if it was part of routine ventilation practice (ESM Table S4). Mechanical power (MP) was calculated according to the following formula [12]: 0.098 x VT x RR x [Ppeak x (Pplat - PEEP)/2]. Hourly data were collected starting at the induction of anaesthesia (T1/40) and then hourly until the end of anaesthesia, up to the 7th hour of surgery (T1/47).
Endpoints
The primary endpoint was to describe the current practice and ventilator strategies in patients undergoing neurosurgical interventions, in particular ventilator mode, VT, PEEP, driving pressure, Ppeak and Pplat and RR, as well as mechanical power.
The secondary outcome was to assess the prevalence of PPCs and the association with preoperative and intraoperative variables including mechanical ventilator settings, type of surgery, ARISCAT score. Detailed definitions of the composites of PPCs and severe PPCs are provided in ESM Table S5. Intraoperative complications included desaturation, rescue recruitment manoeuvres, need for airway pressure reduction, expiratory flow limitation, hypotension and use of vasoactive drugs, onset of a new cardiac arrhythmia (ESM Table S6). The occurrence of each type of PPC was monitored until hospital discharge, but maximum up to postoperative day 5.
Other secondary endpoints included the occurrence of severe PPCs, intraoperative complications, in-hospital mortality and length of hospital stay.
Statistical analysis
Patients were stratified into groups based on type of surgery (brain and spine), the occurrence of PPCs and risk for PPC according to ARISCAT (low risk [ARISCAT < 26] vs. moderate-to-high risk [ARISCAT ≥26]. Continuous variables are expressed as mean ± standard deviation (SD) or median (interquartile range [IQR]) per variable distribution. Discrete variables are presented as percentages. Baseline characteristics among type of neurosurgery were compared by either t-test, Wilcoxon rank-sum test, or chi-squared tests, as appropriate. The effect of type of neurosurgery on the incidence (per 10 P-days) of in-hospital PPC, severe PPC, and discharged alive was evaluated using log-rank test (stratified by centre); differences in survival probabilities and hospital discharge were depicted with an outcome-specific Kaplan-Meier plot.
A multivariable regression model was built, with PPC as dependent variables. Because this outcome is binary (0/1), a logistic regression analysis was applied. Candidate covariates were chosen based on previous medical knowledge, independent of their p-value. From this preliminary selection, those variables with P < 0.20 in the univariate analysis were preferentially chosen for the stepwise procedure. Then, a reduced and parsimonious model was derived using backward stepwise selection. During this selection process, the linearity assumption for continuous variables was tested and transformed, if appropriate, with fractional polynomials (14). In all regression models, the Huber/White/sandwich estimator of variance correction was applied to account for any clustering effect due to centre sampling.
We set a two-sided p value of < 0.05 as the threshold for statistical significance. Stata 15.1 (Stata Statistical Software, release 15 [2017] (Stata Corp LP, College Station, TX, USA), and R (Version 3.5.3; R Foundation for Statistical Computing, Vienna, Austria) were used.
Results
A total of 784 patients were included in the analysis. Of these, 408 (52%) underwent spine surgery and 376(48%) brain surgery. The characteristics of the patients according to subgroups are described in Table 1. Patients with moderate-to-high risk for PPCs- compared to those at low risk were older, with a higher incidence of co-morbidities (in particular chronic kidney failure), worse ASA physical status, and worse pre-hospital functional status and preoperative conditions (as for laboratory tests and vital signs) (Table 1). Patients who developed PPCs were older, with more frequent co-morbidities (in particular respiratory and cardiological), worse ASA and preoperative functional status (Table 1).
Table 1
Pre-Operative Characteristics of the Patients According to Subgroups
All Patients
Brain
Spine
p value
All patients
PPC
No PPC
p value
All patients
ARISCAT < 26
ARISCAT ≥ 26
p value
n (%)
784 (100)
376 (48)
408 (52)
777 (100.0)
81 (10.4)
696 (89.6)
548 (73.3)
200 (26.7)
748 (100.0)
Demographics
Age, years, mean (SD)
53 (16)
52 (16)
54 (15)
0.104
53 (16)
59 (15)
52 (16)
0.000
50 (15)
51 (15)
63 (16)
0.000
Gender, n (%)
Male
392 (50)
183 (48.7)
209 (51.2)
0.060
392 (50.5)
37 (45.7)
355 (51.0)
0.072
285 (52.0)
97 (48.5)
382 (51.1)
0.065
Ethnicity, n (%)
Black
2 (0.3)
0 (0.0)
2 (0.5)
2 (0.3)
2 (2.5)
0 (0.0)
1 (0.2)
1 (0.5)
2 (0.3)
0.663
Caucasian
709 (90.4)
340 (90.4)
369 (90.4)
704 (90.6)
71 (87.7)
633 (90.9)
493 (90.0)
183 (91.5)
676 (90.4)
Asian
4 (0.5)
1 (0.3)
3 (0.7)
4 (0.5)
1 (1.2)
3 (0.4)
4 (0.7)
0 (0.0)
4 (0.5)
Other
33 (4.2)
13 (3.5)
20 (4.9)
33 (4.2)
2 (2.5)
31 (4.5)
26 (4.7)
6 (3.0)
32 (4.3)
Anthropometry
Height, cm, mean (SD)
170 (10)
170 (10)
170 (9)
0.416
170 (10)
169 (10)
170 (10)
0.421
170 (10)
169 (10)
170 (10)
0.243
Weight, kg, mean (SD)
79 (17)
80 (18)
78 (16)
0.309
79 (17)
80 (18)
79 (17)
0.597
79 (17)
79 (17)
79 (17)
0.677
BMI, kg/m2, mean (SD)
27.3 (5.8)
27.7 (6.6)
27.0 (4.9)
0.148
27.3 (5.8)
28.3 (6.5)
27.2 (5.7)
0.141
27.3 (6.0)
27.4 (5.0)
27.3 (5.8)
0.874
Co-morbidities, n (%)
Co-morbidities
161 (20.5)
84 (22.3)
77 (18.9)
0.230
160 (20.6)
30 (37.0)
130 (18.7)
0.000
98 (17.9)
59 (29.5)
157 (21.0)
0.001
COPD
47 (6.0)
21 (5.6)
26 (6.4)
0.643
47 (6.0)
8 (9.9)
39 (5.6)
0.127
32 (5.8)
15 (7.5)
47 (6.3)
0.407
Respiratory
19 (2.4)
8 (2.1)
11 (2.7)
0.605
19 (2.4)
5 (6.2)
14 (2.0)
0.022
12 (2.2)
7 (3.5)
19 (2.5)
0.313
Liver cirrhosis
4 (0.5)
2 (0.5)
2 (0.5)
0.935
4 (0.5)
0 (0.0)
4 (0.6)
0.494
3 (0.5)
1 (0.5)
4 (0.5)
0.937
Chronic kidney failure
16 (2.0)
4 (1.1)
12 (2.9)
0.063
16 (2.1)
4 (4.9)
12 (1.7)
0.054
6 (1.1)
9 (4.5)
15 (2.0)
0.003
Heart failure
45 (5.7)
27 (7.2)
18 (4.4)
0.096
45 (5.8)
10 (12.3)
35 (5.0)
0.008
29 (5.3)
14 (7.0)
43 (5.7)
0.374
Neuro disease
12 (1.5)
8 (2.1)
4 (1.0)
0.191
12 (1.5)
2 (2.5)
10 (1.4)
0.476
11 (2.0)
1 (0.5)
12 (1.6)
0.146
Pre-operative medical history
ASA physical status, n (%)
214 (27.4)
96 (25.5)
118 (29.1)
0.007
208 (26.8)
14 (17.5)
194 (27.9)
0.000
165 (30.1)
29 (14.6)
194 (26.0)
0.000
ASA I
395 (50.5)
178 (47.3)
217 (53.4)
395 (51.0)
33 (41.3)
362 (52.1)
292 (53.3)
90 (45.2)
382 (51.1)
ASA II
395 (50.5)
178 (47.3)
217 (53.4)
153 (19.7)
28 (35.0)
125 (18.0)
85 (15.5)
68 (34.2)
153 (20.5)
ASA III
154 (19.7)
87 (23.1)
67 (16.5)
18 (2.3)
5 (6.3)
13 (1.9)
6 (1.1)
11 (5.5)
17 (2.3)
ASA IV
18 (2.3)
14 (3.7)
4 (1.0)
1 (0.1)
0 (0.0)
1 (0.1)
0 (0.0)
1 (0.5)
1 (0.1)
ASA V
1 (0.1)
1 (0.3)
0 (0.0)
208 (26.8)
14 (17.5)
194 (27.9)
165 (30.1)
29 (14.6)
194 (26.0)
Functional status, n (%)
0.004
0.000
0.006
Independent
708 (90.3)
327 (87.0)
381 (93.4)
702 (90.3)
67 (82.7)
635 (91.2)
506 (92.3)
168 (84.0)
674 (90.1)
Partially dependent
62 (7.9)
38 (10.1)
24 (5.9)
62 (8.0)
12 (14.8)
50 (7.2)
33 (6.0)
27 (13.5)
60 (8.0)
Totally dependent
13 (1.7)
11 (2.9)
2 (0.5)
12 (1.5)
2 (2.5)
10 (1.4)
8 (1.5)
5 (2.5)
13 (1.7)
ARISCAT score, median (IQR)
215 (27.4)
102 (27.1)
113 (27.7)
0.000
16 (3; 26)
23 (11; 32)
16 (3; 24)
0.002
8 (3; 18)
31 (26; 37)
16 (3; 26)
0.000
Smoking, n (%)
40 (5.1)
23 (6.1)
17 (4.2)
0.859
214 (27.5)
22 (27.2)
192 (27.6)
0.442
165 (30.1)
44 (22.0)
209 (27.9)
0.029
Transfusion (< 24 h), n (%)
5 (0.6)
3 (0.8)
2 (0.5)
0.215
39 (5.0)
6 (7.4)
33 (4.7)
0.000
16 (2.9)
22 (11.0)
38 (5.1)
0.000
RBC transfusion (< 24 h)
28 (3.6)
16 (4.3)
12 (2.9)
0.589
5 (0.6)
1 (1.2)
4 (0.6)
0.722
1 (0.2)
4 (2.0)
5 (0.7)
0.007
Respiratory infection (<30d), n (%)
1 (0.1)
0 (0.0)
1 (0.2)
0.322
28 (3.6)
3 (3.7)
25 (3.6)
0.002
7 (1.3)
19 (9.5)
26 (3.5)
0.000
Laboratory tests and vital signs
Pre-operative values
SpO2, %, median (IQR)
97 (96; 99)
97 (96; 98)
97 (96; 99)
0.230
97 (96; 99)
97 (95; 98)
98 (96; 99)
0.002
98 (96; 99)
96 (94; 98)
97 (96; 99)
0.000
Hb, (g/dL), mean (SD)
13.8 (1.8)
13.8 (1.8)
13.9 (1.8)
0.540
13.8 (1.8)
13.7 (2.0)
13.8 (1.8)
0.442
14.0 (1.6)
13.3 (2.1)
13.8 (1.8)
0.000
WBC, (cell/mm3), mean (SD)
7879 (3497)
8199 (3097)
7568 (3825)
0.019
7891 (3503)
9261 (6168)
7721 (2978)
0.000
7696 (3362)
8438 (3845)
7905 (3518)
0.015
Creatinine, (mg/dL), mean (SD)
0.89 (0.69)
0.90 (0.86)
0.88 (0.49)
0.758
0.89 (0.69)
0.87 (0.28)
0.90 (0.73)
0.722
0.87 (0.59)
0.95 (0.91)
0.89 (0.70)
0.192
Surgical characteristics
Condition, n (%)
0.318
0.140
0.000
Elective
717 (91.5)
338 (89.9)
379 (92.9)
712 (91.6)
73 (90.1)
639 (91.8)
513 (93.6)
172 (86.0)
685 (91.6)
Urgency
50 (6.4)
28 (7.4)
22 (5.4)
49 (6.3)
4 (4.9)
45 (6.5)
31 (5.7)
16 (8.0)
47 (6.3)
Emergency
17 (2.2)
10 (2.7)
7 (1.7)
16 (2.1)
4 (4.9)
12 (1.7)
4 (0.7)
12 (6.0)
16 (2.1)
Planned duration, hours, n (%)
0.000
0.000
0.000
0
1 (0.1)
1 (0.3)
0 (0.0)
1 (0.1)
0 (0.0)
1 (0.1)
≤ 2
432 (55.1)
186 (49.5)
246 (60.3)
426 (54.8)
36 (44.4)
390 (56.0)
378 (69.0)
25 (12.5)
403 (53.9)
2–3
201 (25.6)
90 (23.9)
111 (27.2)
201 (25.9)
15 (18.5)
186 (26.7)
124 (22.6)
73 (36.5)
197 (26.3)
> 3
150 (19.1)
99 (26.3)
51 (12.5)
149 (19.2)
30 (37.0)
119 (17.1)
46 (8.4)
102 (51.0)
148 (19.8)
Antibiotic prophylaxis, n (%)
711 (90.9)
338 (90.1)
373 (91.6)
0.462
705 (91.0)
74 (91.4)
631 (90.9)
0.897
500 (91.4)
184 (92.0)
684 (91.6)
0.796
P value refers to the between-groups with Fisher-Freeman-Halton Exact test, Mann Whitney u-test, or Kruskal Wallis test, as appropriate. N Number, IQR Interquartile range, SD Standard deviation, h Hours, d Days, PPC Postoperative pulmonary complications, COPD Chronic obstructive pulmonary disease, ASA American society of anesthesiologists, RBC Blood red cells, SpO2 Blood oxygen saturation, Hb Hemoglobin, WBC White blood cells
Ventilation variables and intraoperative characteristics
Most of the patients underwent elective surgical procedure (72%), with a median surgical duration of 95 min (1st-3rd interquartile range IQR = 60–160) and median anaesthetic time of 126 min (IQR = 90–192.8 min). The most common ventilation mode was volume-controlled ventilation (VCV) (Table 2). VCV was more commonly used in patients undergoing brain surgery. Median VT was 510 ml (Interquartile range, IQR 475–575), thus resulting in 8 ml/kg predicted body weight (IQR = 7.3–9). Median PEEP level was 5 cmH2O (IQR 3–5), Ppeak was 18 cmH2O (IQR = 15–21) and driving pressure was 12 (IQR = 11–15) cmH2O (Table 2).
Table 2
Intra-Operative Characteristics of the Patients According to Subgroups
All Patients
Brain
Spine
p value
All patients
PPC
No PPC
p value
All patients
ARISCAT
< 26
ARISCAT
≥ 26
p value
n (%)
784 (100.0)
376 (48.0)
408 (52.0)
777 (100.0)
81 (10.4)
696 (89.6)
748 (100.0)
548 (73.3)
200 (26.7)
Ventilation and vital signs
Ventilatory mode, n (%)
0.000
0.376
0.452
Volume controlled
494 (63.8)
259 (70.2)
235 (58.0)
488 (63.5)
50 (64.1)
438 (63.5)
467 (63.2)
341 (62.9)
126 (64.0)
Pressure controlled
149 (19.3)
42 (11.4)
107 (26.4)
149 (19.4)
20 (25.6)
129 (18.7)
146 (19.8)
112 (20.7)
34 (17.3)
Pressure support
3 (0.4)
2 (0.5)
1 (0.2)
3 (0.4)
0 (0.0)
3 (0.4)
3 (0.4)
1 (0.2)
2 (1.0)
Spontaneous
64 (8.3)
21 (5.7)
43 (10.6)
64 (8.3)
4 (5.1)
60 (8.7)
60 (8.1)
42 (7.7)
18 (9.1)
Other
64 (8.3)
45 (12.2)
19 (4.7)
64 (8.3)
4 (5.1)
60 (8.7)
63 (8.5)
46 (8.5)
17 (8.6)
VT, ml, median (IQR)
510 (475; 575)
511 (475; 584)
506 (471; 562)
0.183
510 (475; 575)
500 (458; 560)
513 (475; 575)
0.096
510 (475; 572)
506 (475; 565)
525 (480; 590)
0.142
VT, (ml/kg PBW), median (IQR)
8.0 (7.3; 9.0)
8.2 (7.3; 9.1)
8.0 (7.2; 8.9)
0.150
8.0 (7.3; 9.0)
7.7 (7.0; 8.8)
8.1 (7.3; 9.0)
0.060
8.0 (7.3; 9.0)
8.0 (7.3; 9.0)
8.0 (7.3; 9.1)
0.420
PPeak, cmH2O, median (IQR)
18 (15; 21)
18 (15; 21)
18 (16; 21)
0.225
18 (15; 21)
18 (16; 21)
18 (15; 21)
0.183
18 (15; 21)
18 (15; 21)
18 (16; 21)
0.061
PPlateau, cmH2O, median (IQR)
16 (14; 19)
16 (14; 19)
16 (14; 18)
0.201
16 (14; 19)
17 (14; 19)
16 (14; 19)
0.150
16 (14; 19)
16 (14; 18)
17 (15; 19)
0.012
PEEP, cmH2O, median (IQR)
5.0 (3.0; 5.0)
5.0 (4.0; 5.0)
5.0 (3.0; 5.0)
0.669
5.0 (3.0; 5.0)
5.0 (4.0; 5.0)
5.0 (3.0; 5.0)
0.225
5.0 (3.0; 5.0)
5.0 (3.0; 5.0)
5.0 (3.3; 5.0)
0.156
DP, cmH2O, median (IQR)
12 (11; 15)
13 (11; 15)
12 (10; 16)
0.585
12 (11; 15)
13 (11; 15)
12 (11; 15)
0.201
12 (11; 15)
12 (11; 15)
14 (11; 17)
0.009
RR, bpm, mean (SD)
12.0 (1.5)
12.1 (1.5)
12.0 (1.4)
0.237
12.0 (1.5)
12.1 (1.7)
12.0 (1.4)
0.669
12.0 (1.4)
12.1 (1.3)
11.9 (1.7)
0.188
FiO2, %, median (IQR)
50 (43; 65)
50 (40; 60)
50 (44; 68)
0.021
50 (43; 64)
50 (46; 65)
50 (42; 63)
0.585
50 (43; 65)
50 (43; 70)
50 (45; 60)
0.143
SpO2, %, median (IQR)
99 (98; 100)
99 (99; 100)
99 (98; 100)
0.169
99 (98; 100)
99 (98; 100)
99 (98; 100)
0.237
99 (98; 100)
99 (99; 100)
99 (98; 100)
0.069
ETCO2, mmHg, mean (SD)
33 (4)
32 (4)
33 (5)
0.001
33 (4)
33 (4)
33 (5)
0.554
33 (4)
33 (4)
33 (5)
0.549
MP, J/min, median (IQR)
6.6 (4.9; 9.2)
6.9 (5.0; 10.3)
6.2 (4.8; 7.8)
0.058
6.6 (4.9; 9.2)
6.1 (4.8; 10.5)
6.6 (4.9; 9.1)
0.856
6.6 (4.9; 9.3)
6.6 (4.9; 8.6)
6.7 (5.1; 10.8)
0.230
MAP, mmHg, mean (SD)
80 (12)
79 (12)
80 (13)
0.083
79 (12)
78 (11)
80 (13)
0.021
79 (12)
79 (12)
80 (13)
0.212
Heart rate, bpm, mean (SD)
71 (12)
69 (12)
72 (12)
0.004
71 (12)
68 (12)
71 (12)
0.169
70 (12)
71 (12)
70 (13)
0.355
RM, n (%)
54 (6.9)
29 (7.8)
25 (6.1)
0.365
54 (6.9)
29 (7.8)
25 (6.1)
0.365
51 (6.8)
36 (6.6)
15 (7.5)
0.664
Anesthesia characteristics
Opioids, n (%)
No
2 (0.3)
0 (0.0)
2 (0.5)
2 (0.3)
0 (0.0)
2 (0.5)
90 (12.0)
65 (11.9)
25 (12.5)
Yes
782 (99.7)
376 (100.0)
406 (99.5)
0.174
782 (99.7)
376 (100.0)
406 (99.5)
0.629
746 (99.7)
546 (99.6)
200 (100.0)
0.392
Opioids type, n (%)
0.000
0.055
0.836
Short acting
221 (28.2)
137 (36.4)
84 (20.6)
220 (28.3)
20 (24.7)
200 (28.7)
2 (0.3)
2 (0.4)
0 (0.0)
Long acting
466 (59.4)
189 (50.3)
277 (67.9)
460 (59.2)
43 (53.1)
417 (59.9)
212 (28.3)
154 (28.1)
58 (29.0)
Total fluids, ml, median (IQR)
1500 (1000; 2000)
1500 (1000; 2000)
1500 (1000; 2000)
0.022
1500 (1000; 2000)
1800 (1200; 2125)
1500 (1000; 2000)
0.001
1500 (1000; 2000)
1300 (1000; 2000)
2000 (1100; 3000)
0.000
Cristalloids
1175 (1000; 2000)
1200 (1000; 2000)
1000 (1000; 1500)
0.012
1200 (1000; 2000)
1500 (1000; 2050)
1000 (1000; 2000)
0.000
1200 (1000; 2000)
1000 (1000; 1500)
1725 (1000; 2475)
0.000
Colloids
0.0 (0.0; 500.0)
0.0 (0.0; 500.0)
0.0 (0.0; 500.0)
0.649
0.0 (0.0; 500.0)
0.0 (0.0; 500.0)
0.0 (0.0; 500.0)
0.719
0.0 (0.0; 500.0)
0.0 (0.0; 125.0)
0.0 (0.0; 500.0)
0.649
P-value refers to the between-groups difference with Fisher-Freeman-Halton Exact test, Mann Whitney u-test, or Kruskal Wallis test, as appropriate. N Number; IQR Interquartile range, SD Standard deviation, PPC Postoperative pulmonary complications, PBW Predicted body weight, VT Tidal volume, PPeak Peak pressure, PPlateau Plateau pressure, PEEP Positive end-expiratory pressure, DP Driving pressure, RR Respiratory rate, FiO2 Fraction of inspired oxygen, SpO2 Blood oxygen saturation, ETCO2 End-tidal carbon dioxide, MP Mechanical power, MAP Mean arterial pressure, HR Heart rate, RM Recruitment maneuvers
Anzeige
Routine RMs were performed in 54 patients (6.9%). Unplanned RMs occurred in 1.4% of cases. No statistical difference was found between the spine and brain surgery group or regarding the ventilator settings (Table 2, ESM Figure S1). EtCO2 values were significantly lower in the brain surgery group compared with the spine surgery group (p = 0.001). Patients who developed PPCs received a higher amount of fluids compared to those with no PPCs (Table 2), but no differences were found in the ventilator settings between the two groups (Fig. 1).
Fig. 1
Ventilation parameters in patients who developed and who did not develop PPCs. Cumulative distribution of Tidal Volume (VT) (upper left panel); Cumulative distribution of peak pressure (Ppeak) (upper right panel); Cumulative distribution of plateau pressure (Pplat) (lower left panel); Cumulative frequency distribution of positive end expiratory pressure (PEEP) (lower right panel)
×
Scatter plots showing the combinations of VT with PEEP, driving pressure, Ppeak, and respiratory rate in patients who developed versus patients who did not develop PPCs, between the spine and brain group, and in patients with low risk [ARISCAT < 26] vs. moderate-to-high risk [ARISCAT ≥26] are shown in Fig. 2, ESM Figures S2, S3.
Fig. 2
Combinations of ventilator settings in patients who developed or not developed PPCs. Scatterplots showing distribution of tidal volume with positive end expiratory pressure combinations (upper left panel); tidal volume with Peak pressure (upper right panel); tidal volume with Driving pressure (lower left panel); tidal volume and respiratory rate (lower right panel). Scatter and the fitted line for each of the bivariate plots are shown in blue
×
Occurrence of PPCs, intraoperative complications and outcomes
Among the 784 patients included in the analysis, 81 (10.4%) developed PPCs (Table 2). PPCs occurred mainly on day 3. No differences between the surgical groups were found as for probability of PPCs occurrence and hospital length of stay (ESM Figure S4).
Patients with ARISCAT≥26 showed an increased probability of PPCs occurrence compared to patients at lower risk (HR 2.50; 95% CI 1.61–3.58, p < 0.000), and of longer hospital length of stay (HR 0.81; 95% CI 0.69.0.97, p = 0.019) (ESM Figure S4).
Anzeige
Intraoperative episodes of hypotension and the need for vasoactive drugs during the procedure were frequent, especially in the spine group compared to the brain group (38.7% vs 31.2% for hypotension; p = 0.028 and 34.6% vs 27.7% for vasoactive drugs, p = 0.04, respectively) (Table 3). The incidence of desaturation was less frequent than hypotension or need of vasoactive drugs. No differences were found in terms of mortality or hospital length of stay in patients who developed and did not develop PPCs or the type of surgery. Patients with ARISCAT≥26 compared to those with ARISCAT< 26, had longer LOS and higher hospital mortality (Table 3).
Table 3
Outcomes According to Subgroups
All Patients
Brain
Spine
p value
All patients
PPC
No PPC
p value
All patients
ARISCAT < 26
ARISCAT ≥ 26
p value
n (%)
784 (100.0)
376 (48.0)
408 (52.0)
777 (100.0)
81 (10.4)
696 (89.6)
748 (100.0)
548 (73.3)
200 (26.7)
PPCs, n (%)
PPCs
81 (10.4)
46 (12.4)
35 (8.6)
0.085
777 (100.0)
81 (10.4)
696 (89.6)
0.000
80 (10.8)
43 (7.9)
37 (18.6)
0.000
Need of oxygen
69 (8.9)
38 (10.2)
31 (7.6)
0.202
81 (10.4)
81 (100.0)
0 (0.0)
0.000
68 (9.2)
39 (7.2)
29 (14.6)
0.002
Respiratory failure
14 (1.8)
8 (2.2)
6 (1.5)
0.478
69 (8.9)
69 (85.2)
0 (0.0)
0.000
14 (1.9)
6 (1.1)
8 (4.0)
0.010
NIV
9 (1.2)
4 (1.2)
5 (1.2)
0.963
14 (1.8)
14 (17.3)
0 (0.0)
0.000
9 (1.3)
7 (1.3)
2 (1.1)
0.801
ARDS
1 (0.1)
1 (0.3)
0 (0.0)
0.295
9 (1.2)
5 (6.3)
4 (0.6)
0.003
1 (0.1)
0 (0.0)
1 (0.5)
0.098
Pneumothorax
1 (0.1)
1 (0.3)
0 (0.0)
0.295
1 (0.1)
1 (1.2)
0 (0.0)
0.003
1 (0.1)
0 (0.0)
1 (0.5)
0.098
Secondary outcomes, n (%)
Severe PPCs
19 (2.4)
13 (3.5)
6 (1.5)
0.068
19 (2.4)
19 (23.5)
0 (0.0)
0.000
19 (2.6)
6 (1.1)
13 (6.5)
0.000
Intra-operative complications
344 (43.9)
154 (41.1)
190 (46.6)
0.121
342 (44.1)
46 (56.8)
296 (42.6)
0.015
336 (44.9)
237 (43.2)
99 (49.5)
0.128
Desaturation
38 (4.9)
23 (6.1)
15 (3.7)
0.110
37 (4.8)
11 (13.6)
26 (3.7)
0.000
36 (4.8)
21 (3.8)
15 (7.5)
0.038
Unplanned RMs
25 (3.2)
15 (4.0)
10 (2.5)
0.220
24 (3.1)
5 (6.2)
19 (2.7)
0.091
22 (2.9)
12 (2.2)
10 (5.0)
0.043
Pressure reduction
25 (3.2)
11 (2.9)
14 (3.4)
0.692
25 (3.2)
3 (3.7)
22 (3.2)
0.795
22 (2.9)
17 (3.1)
5 (2.5)
0.666
Flow limitation
5 (0.6)
3 (0.8)
2 (0.5)
0.590
4 (0.5)
1 (1.3)
3 (0.4)
0.322
4 (0.5)
2 (0.4)
2 (1.0)
0.289
Hypotension
275 (35.1)
117 (31.2)
158 (38.7)
0.028
274 (35.3)
34 (42.0)
240 (34.5)
0.185
270 (36.1)
197 (35.9)
73 (36.5)
0.890
Vasopressors
245 (31.3)
104 (27.7)
141 (34.6)
0.040
244 (31.4)
37 (45.7)
207 (29.8)
0.004
242 (32.4)
168 (30.7)
74 (37.0)
0.101
New arrhythmias
9 (1.1)
6 (1.6)
3 (0.7)
0.257
9 (1.2)
0 (0.0)
9 (1.3)
0.303
9 (1.2)
5 (0.9)
4 (2.0)
0.227
Hospital LOS, days, median (IQR)
2 (1; 5)
2 (1; 5)
2 (1; 5)
0.993
2 (1; 5)
3 (1; 5)
2 (1; 5)
0.447
2 (1; 5)
2 (1; 5)
3 (1; 5)
0.033
Hospital mortality
5 (0.7)
4 (1.2)
1 (0.3)
0.145
5 (0.7)
1 (1.3)
4 (0.6)
0.500
5 (0.7)
1 (0.2)
4 (2.2)
0.006
n Number, IQR Interquartile range, PPCs Postoperative pulmonary complications, NIV Non-invasive ventilation, ARDS Acute respiratory distress syndrome, LOS Length of hospital stay, RMs Recruitment maneuvers, ARISCAT Assess respiratory risk in surgical patients in Catalonia
Risk factors for PPCs
Multivariable logistic regression was used to identify the predictors of PPCs. Duration of anaesthesia was independently associated for the development of PPCs. Analysing the predictors for type of neurosurgery, for age we found a significantly effect in the brain group (the omnibus p-value for the neurosurgery-age interaction was p = 0.031), but not in the spine group. (Table ESM S7, ESM Figure S5, Fig. 3). The effect of age on PPC in the brain group was significant at age above 62 (ESM Figure S5).
Fig. 3
Interaction between type of neurosurgery and age continuous on PPC as outcome. Odds ratio (per 1-unit change in age) is depicted along the continuum of age (years) with its median (53 years) as reference point. Analysis adjusted by duration of anaesthesia, desaturation, and ARISCAT risk score. Indeed, the prognostic effect of age on PPC varies according to neurosurgery subpopulations, with no effect on the spine group, and a significant crescendo effect on the brain group as patient aged
×
Discussion
Our results show that: 1) Neurosurgical patients are ventilated with low VT and low PEEP levels, while recruitment manoeuvres are seldom applied. No clinically significant differences exist between the intraoperative ventilator settings and the incidence of PPCs between the subgroups analysed, and in patients undergoing brain and spine surgery. ETCO2 levels are generally medium-low, especially in the brain surgery group; 2) PPCs are common, with similar incidence in the spine- and the brain surgical groups; 3) Intraoperative complications occur in a large number of patients (44% of the total population); of these, hypotension and the need for vasopressors are common; 4) Increasing age (for the brain group) and long surgical procedures are independently associated with development of PPCs.
To our knowledge, this is the first prospective observational study in neurosurgical patients specifically focusing on the prevalence of PPCs and the effects of intraoperative mechanical ventilation settings on PPCs development. Our study is a sub-analysis of the LAS VEGAS study [10], a large international observational study describing the ventilator settings and PPCs occurrence in the perioperative period across different countries, and can therefore be considered representative for the current clinical practice in this population.
Anzeige
Ventilator strategies in patients undergoing neurosurgical interventions
Currently applied lung-protective ventilation strategies have shown to reduce PPCs [13, 14]. In patients undergoing spine surgery, the prone position has various effects on pulmonary function, including a decreased dynamic lung compliance and increased peak inspiratory pressure [13]; however, no large observational studies or randomized controlled trials are available regarding protective ventilator settings and their effect on PPCs in the prone position in non-ARDS patients.
In brain injured patients, lung-protective ventilation could be deleterious [7]; in particular, possible high intra-thoracic pressures when using high PEEP levels and permissive hypercapnia can have detrimental effects on cerebral perfusion pressure (CPP) and intracranial pressure (ICP). Therefore, brain injury patients are traditionally ventilated with tidal volumes approximating 9 ml/kg of PBW [5]. However, recent studies suggest that high VT is a risk factor for acute lung injury even in patients with neurological disorders [4]. Indeed, our results suggest that the use of low VT is increasingly applied also in neurosurgical patients. Similarly, the application of PEEP in brain injured patients has been traditionally considered detrimental for ICP, by reducing venous outflow [15]. However, recent evidence demonstrates that PEEP application might not compromise ICP, provided that arterial blood pressure is preserved [16, 17].
In our cohort, neurosurgical patients were ventilated with low PEEP levels and no differences in PEEP levels were detected between the brain and spine groups. No data is available on the effects of RM in neurosurgical patients and their role within the intraoperative protective ventilation bundle remains unclear. In brain injured patients, RMs can have a dangerous effect on ICP by impairment of jugular blood outflow, and increase of intra-thoracic pressure with impediment of cerebral venous return to the right atrium [8]. Although pressure-control recruitment manoeuvres improve oxygenation without impairing ICP or CPP, there is still concern regarding their application in neurosurgical patients, and therefore are rarely performed [8]. Indeed, our results show that recruitment manoeuvres are seldom applied in neurosurgical patients.
To date, no clinical studies comparing pressure-controlled ventilation (PCV) and VCV in brain injured patients are published. In obese [18], ARDS [19], and thoracic patients [20], research suggests no difference in outcome between the modes of ventilation (PCV and VCV). In a trial [21] including patients undergoing spinal surgery, PCV decreased intraoperative surgical bleeding compared with the VCV group (p < 0.001), possibly by lowering peak inspiratory pressures. A recent randomized controlled trial during lumbar spine surgery demonstrated that hemodynamic variables and arterial blood gas results did not differ significantly between the VCV and PCV with volume guaranteed (PCV-VG) mode groups [13]. Also, a recent large observational study suggested that PCV is associated with increase of PPC compared to VCV [22]. This association is not confirmed by our results. In our cohort, patients undergoing spinal surgery were more frequently ventilated with VCV than the brain injured group. However, despite the pathophysiological differences of prone vs supine ventilation, we did not find any other differences in the ventilator settings between the two groups.
In our cohort, ETCO2 levels were generally medium-low, with significantly lower values in the brain surgery group compared to the spinal surgery group. This result suggests that patients undergoing brain surgery are more likely to be hyperventilated. This is most likely out of concern for potential increased intracranial pressure.
Although the subgroup with ARISCAT ≥26 shows higher values of driving pressure and plateau pressure (plateau pressure (17 vs 16 cmH2O, p = 0.012), and higher driving pressure (14 vs 12 cmH2O; p = 0.009), these values still remain within the recommended ranges for protective ventilation [22, 23]. In general, in the whole population, a low total energy was applied to the respiratory system [23] (median mechanical power (6.2 J/min)), with values which remain far from the threshold of 12 J/min suggested as increased risk of lung injury [23].
Post- operative pulmonary complications
Clinical studies suggest that the application of protective ventilation can reduce PPCs [24, 25], with high VT identified as an independent predictor of PPCs development [26, 27]. Trials in obese [27] and non-obese [28] patients undergoing abdominal surgery demonstrated that the intraoperative application of high level of PEEP and RMs did not reduce PPCs, when compared with lower PEEP level without RMs.
In our neurosurgical population, 10.3% of patients developed PPCs, similar to the results from the whole population of the LAS VEGAS [8]. No clinically significant differences exist in the incidence of PPCs when comparing the different intraoperative ventilator settings in the subgroups analysed.
Patients who developed PPCs had worse preoperative conditions (age, ARISCAT score, ASA status), longer duration of anaesthesia (thus suggesting a more complicated surgical procedure), intraoperative complications (in particular hypotension) and the administration of higher volumes of fluid. This latter point is of extreme importance as cerebral and spinal perfusion pressures are generally maintained by the administration of vasopressors and a large amount of fluids; however, a positive fluid balance can increase the risk for pulmonary damage and complications [28]. Finally, increasing age in the brain surgical group was associated with PPCs occurrence, thus making preoperative assessment extremely important in the management of this group of patients in order to optimize hospital resources and empathetically begin discussions with patients and their carers.
Intraoperative complications and outcomes
In our cohort, intraoperative complications occurred in a large number of patients (44% of our total population). Moreover, we found an increased prevalence of intraoperative hemodynamic deterioration as compared to respiratory impairment in the intraoperative settings. According to our results, patients undergoing spine surgery have commonly episodes of intraoperative hypotension requiring the use of vasoactive drugs, probably related to the effects of prone position on cardiac function, including a decreased cardiac index [13].
Our results suggest that in neurosurgical patients, the most common intraoperative complications are related to hemodynamic rather than respiratory function. The fact that hypotension and hemodynamic impairment are common might suggest that limited levels of PEEP could be beneficial in this type of patients by having less negative impact on hemodynamic. These results are in accordance with recently published literature [24, 29], suggesting that the use of high PEEP can negatively impact the hemodynamic system, thus challenging the traditional concept of “open lung approach”, and avoiding repeated alveolar collapse and expansion and keeping the lung partially at rest [30].
Limitations
Several limitations need to be mentioned. First, the manuscript derives from a secondary analysis from the LAS VEGAS study. Thus, the results represent an observation of associations and do not allow to draw causality conclusions, considering that there exist unaccounted confounding factors.
Second, this is an unplanned secondary analysis from the main study, and even though we built a meticulous statistical model, there could still be confounding factors affecting our results.
Third, as the design of the original study focused on intraoperative settings and variables in the general population, limited information was available regarding specific perioperative data in neurosurgical patients, in particular on the use neuro-monitoring and type of brain and spine surgery.
Conclusions
The main findings of this study are that MV settings in neurosurgical patients are characterized by low VT and low PEEP with seldom use of RMs. PPCs are frequent in this population and not associated with intraoperative ventilator setting. Further studies are warranted to assess the effect of ventilation strategies on the outcome of this cohort of patients.
We would like to acknowledge the medical and nursing staff of the operating rooms involved for their support in the completion of this study.
Contributors
Las Vegas Investigators:
Austria
LKH Graz, Graz: Wolfgang Kroell, Helfried Metzler, Gerd Struber, Thomas Wegscheider
AKH Linz, Linz: Hans Gombotz
Medical University Vienna: Michael Hiesmayr, Werner Schmid, Bernhard Urbanek
Belgium
UCL - Cliniques Universitaires Saint Luc Brussels: David Kahn, Mona Momeni, Audrey Pospiech, Fernande Lois, Patrice Forget, Irina Grosu
Universitary Hospital Brussels (UZ Brussel): Jan Poelaert, Veerle van Mossevelde, Marie-Claire van Malderen
Het Ziekenhuis Oost Limburg (ZOL), Genk: Dimitri Dylst, Jeroen van Melkebeek, Maud Beran
Ghent University Hospital, Gent: Stefan de Hert, Luc De Baerdemaeker, Bjorn Heyse, Jurgen Van Limmen, Piet Wyffels, Tom Jacobs, Nathalie Roels, Ann De Bruyne
Maria Middelares, Gent: Stijn van de Velde
European Society of Anaesthesiology, Brussels:Brigitte Leva, Sandrine Damster, Benoit Plichon
Bosnia and Herzegovina
General Hospital “prim Dr Abdulah Nakas” Sarajevo: Marina Juros-Zovko, Dejana Djonoviċ- Omanoviċ
Croatia
General Hospital Cakovec, Cakovec: Selma Pernar
General Hospital Karlovac, Karlovac: Josip Zunic, Petar Miskovic, Antonio Zilic
University Clinical Hospital Osijek, Osijek: Slavica Kvolik, Dubravka Ivic, Darija Azenic-Venzera, Sonja Skiljic, Hrvoje Vinkovic, Ivana Oputric
University Hospital Rijeka, Rijeka: Kazimir Juricic, Vedran Frkovic
General Hospital Dr J Bencevic, Slavonski Brod: Jasminka Kopic, Ivan Mirkovic
University Hospital Center Split, Split: Nenad Karanovic, Mladen Carev, Natasa Dropulic
University Hospital Sveti Duh, Zagreb: Branka Mazul-Sunko, Anna Marija Pavicic, Tanja Goranovic
University Hospital, Medical school, “Sestre milosrdnice” (Sister of Charity), Zagreb: Branka Maldini, Tomislav Radocaj, Zeljka Gavranovic, Inga Mladic-Batinica, Mirna Sehovic
Czech Republic
University Hospital Brno, Brno: Petr Stourac, Hana Harazim, Olga Smekalova, Martina Kosinova, Tomas Kolacek, Kamil Hudacek, Michal Drab
University Hospital Hradec Kralove, Hradec Kralove: Jan Brujevic, Katerina Vitkova, Katerina Jirmanova
University Hospital Ostrava, Ostrava: Ivana Volfova, Paula Dzurnakova, Katarina Liskova
Azienda Ospedaliera – Universitaria Sant’Anna, Ferrara: Carlo Alberto Volta, Savino Spadaro, Marco Verri, Riccardo Ragazzi, Roberto Zoppellari
Ospedali Riuniti Di Foggia - University of Foggia, Foggia: Gilda Cinnella, Pasquale Raimondo, Daniela La Bella, Lucia Mirabella, Davide D’antini
IRCCS AOU San Martino IST Hospital, University of Genoa, Genoa: Paolo Pelosi, Alexandre Molin, Iole Brunetti, Angelo Gratarola, Giulia Pellerano, Rosanna Sileo, Stefano Pezzatto, Luca Montagnani
IRCCS San Raffaele Scientific Institute, Milano: Laura Pasin, Giovanni Landoni, Alberto Zangrillo, Luigi Beretta, Ambra Licia Di Parma, Valentina Tarzia, Roberto Dossi, Marta Eugenia Sassone
Istituto europeo di oncologia – ieo, Milano: Daniele Sances, Stefano Tredici, Gianluca Spano, Gianluca Castellani, Luigi Delunas, Sopio Peradze, Marco Venturino
Ospedale Niguarda Ca’Granda Milano, Milano: Ines Arpino, Sara Sher
Ospedale San Paolo - University of Milano, Milano: Concezione Tommasino, Francesca Rapido, Paola Morelli
University of Naples “Federico II” Naples: Maria Vargas, Giuseppe Servillo
Medical University Hospital, Hospital of Lithuanian University of Health Sciences, Kaunas: Aurika Karbonskiene, Ruta Aukstakalniene, Zivile Teberaite, Erika Salciute
Vilnius University Hospital - Institute of Oncology, Vilnius: Renatas Tikuisis, Povilas Miliauskas
Vilnius University Hospital - Santariskiu Clinics, Vilnius: Sipylaite Jurate, Egle Kontrimaviciute, Gabija Tomkute
Malta
Mater Dei Hospital, Msida: John Xuereb, Maureen Bezzina, Francis Joseph Borg
Netherlands
Academic Medical Centre, University of Amsterdam: Sabrine Hemmes, Marcus Schultz, Markus Hollmann, Irene Wiersma, Jan Binnekade, Lieuwe Bos
VU University Medical Center, Amsterdam: Christa Boer, Anne Duvekot
MC Haaglanden, Den Haag: Bas in ‘t Veld, Alice Werger, Paul Dennesen, Charlotte Severijns
Westfriesgasthuis, Hoorn: Jasper De Jong, Jens Hering, Rienk van Beek
Norway
Haukeland University Hospital, Bergen: Stefan Ivars, Ib Jammer
Førde Central Hospital /Førde Sentral Sykehus, Førde: Alena Breidablik
Martina Hansens Hospital, Gjettum: Katharina Skirstad Hodt, Frode Fjellanger, Manuel Vico Avalos
Bærum Hospital, Vestre Viken, Rud: Jannicke Mellin-Olsen, Elisabeth Andersson
Stavanger University Hospital, Stavanger: Amir Shafi-Kabiri
Panama
Hospital Santo Tomás, Panama: Ruby Molina, Stanley Wutai, Erick Morais
Portugal
Hospital do Espírito Santo - Évora, E.P.E, Évora.: Glória Tareco, Daniel Ferreira, Joana Amaral
Centro Hospitalar de Lisboa Central, E.P.E, Lisboa.: Maria de Lurdes Goncalves Castro, Susana Cadilha, Sofia Appleton
Centro Hospitalar de Lisboa Ocidental, E.P.E. Hospital de S. Francisco Xavier, Lisboa: Suzana Parente, Mariana Correia, Diogo Martins
Santarem Hospital, Santarem: Angela Monteirosa, Ana Ricardo, Sara Rodrigues
Reanimatology Research Institute n.a. Negovskij RAMS, Moscow: Valery Likhvantsev, Sergei Fedorov
Serbia
Clinical Center of Vojvodina, Emergency Center, Novisad: Aleksandra Lazukic, Jasmina Pejakovic, Dunja Mihajlovic
Slovakia
National Cancer Institute, Bratislava: Zuzana Kusnierikova, Maria Zelinkova
F.D. Roosevelt teaching Hospital, Banská Bystrica: Katarina Bruncakova, Lenka Polakovicova
Faculty Hospital Nové Zámky, Nové Zámky: Villiam Sobona
Slovenia
Institute of Oncology Ljubljana, Ljubljana: Barbka Novak-Supe, Ana Pekle-Golez, Miroljub Jovanov, Branka Strazisar
University Medical Centre Ljubljana, Ljubljana: Jasmina Markovic-Bozic, Vesna Novak-Jankovic, Minca Voje, Andriy Grynyuk, Ivan Kostadinov, Alenka Spindler-Vesel
Spain
Hospital Sant Pau, Barcelona: Victoria Moral, Mari Carmen Unzueta, Carlos Puigbo, Josep Fava
Hospital Universitari Germans Trias I Pujol, Barcelona: Jaume Canet, Enrique Moret, Mónica Rodriguez Nunez, Mar Sendra, Andrea Brunelli, Frederic Rodenas
University of Navarra, Pamplona: Pablo Monedero, Francisco Hidalgo Martinez, Maria Jose Yepes Temino, Antonio Martínez Simon, Ana de Abajo Larriba
Dokuz Eylül Universitesi Tip Fakültesi, Izmir: Bahar Kuvaki, Ferim Gunenc, Semih Kucukguclu, Şule Ozbilgin
Şifa University Hospital, İzmir: Jale Maral, Seyda Canli
Selcuk University faculty of medicine, Konya: Oguzhan Arun, Ali Saltali, Eyup Aydogan
Fatih Sultan Mehmet Eğitim Ve Araştirma Hastanesi, Istanbul: Fatma Nur Akgun, Ceren Sanlikarip, Fatma Mine Karaman
Ukraine
Institute Of Surgery And Transplantology, Kiev: Andriy Mazur
Zaporizhzhia State Medical University, Zaporizhzhia: Sergiy Vorotyntsev
United Kingdom
SWARM Research Collaborative: for full list of SWARM contributors please see www.ukswarm.com
Northern Devon Healthcare NHS Trust, Barnstaple: Guy Rousseau, Colin Barrett, Lucia Stancombe
Golden Jubilee National Hospital, Clydebank, Scotland: Ben Shelley, Helen Scholes
Darlington Memorial Hospital, County Durham and Darlington Foundation NHS Trust, Darlington: James Limb, Amir Rafi, Lisa Wayman, Jill Deane
Royal Derby Hospital, Derby: David Rogerson, John Williams, Susan Yates, Elaine Rogers
Dorset County Hospital, Dorchester: Mark Pulletz, Sarah Moreton, Stephanie Jones
The Princess Alexandra NHS Hospital Trust, Essex: Suresh Venkatesh, Maudrian Burton, Lucy Brown, Cait Goodall
Royal Devon and Exeter NHS Foundation Trust, Exeter: Matthew Rucklidge, Debbie Fuller, Maria Nadolski, Sandeep Kusre
Hospital James Paget University Hospital NHS Foundation Trust, Great Yarmouth: Michael Lundberg, Lynn Everett, Helen Nutt
Royal Surrey County Hospital NHS Foundation Trust, Guildford: Maka Zuleika, Peter Carvalho, Deborah Clements, Ben Creagh-Brown
Kettering General Hospital NHS Foundation Trust, Kettering: Philip Watt, Parizade Raymode
Barts Health NHS Trust, Royal London Hospital, London: Rupert Pearse, Otto Mohr, Ashok Raj, Thais Creary
Newcastle Upon Tyne Hospitals NHS Trust The Freeman Hospital High Heaton, Newcastle upon Tyne: Ahmed Chishti, Andrea Bell, Charley Higham, Alistair Cain, Sarah Gibb, Stephen Mowat
Derriford Hospital Plymouth Hospitals NHS Trust, Plymouth: Danielle Franklin, Claire West, Gary Minto, Nicholas Boyd
Royal Hallamshire Hospital, Sheffield: Gary Mills, Emily Calton, Rachel Walker, Felicity Mackenzie, Branwen Ellison, Helen Roberts
Mid Staffordshire NHS, Stafford: Moses Chikungwa, Clare Jackson
Musgrove Park Hospital, Taunton: Andrew Donovan, Jayne Foot, Elizabeth Homan
South Devon Healthcare NHS Foundation Trust /Torbay Hospital, Torquay, Torbay: Jane Montgomery, David Portch, Pauline Mercer, Janet Palmer
Royal Cornwall Hospital, Truro: Jonathan Paddle, Anna Fouracres, Amanda Datson, Alyson Andrew, Leanne Welch
Mayo Clinic, Rochester: Juraj Sprung, Toby Weingarten, Daryl Kor, Federica Scavonetto, Yeo Tze
Ethics approval and consent to participate
Ethic approval is in accordance with the Declaration of Helsinki and the study was first approved by the ethical committee of the Academic Medical Center, Amsterdam, the Netherlands (W12_190#12.17.0227). Each participating centre obtained the approval from the local ethical review board, and written informed consent was obtained from patients or next of kin, according to ethical requirements.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Intraoperative ventilator settings and their association with postoperative pulmonary complications in neurosurgical patients: post-hoc analysis of LAS VEGAS study
verfasst von
Chiara Robba Sabrine N. T. Hemmes Ary Serpa Neto Thomas Bluth Jaume Canet Michael Hiesmayr M. Wiersma Hollmann Gary H. Mills Marcos F. Vidal Melo Christian Putensen Samir Jaber Werner Schmid Paolo Severgnini Hermann Wrigge Denise Battaglini Lorenzo Ball Marcelo Gama de Abreu Marcus J. Schultz Paolo Pelosi FERS for the LAS VEGAS investigators the PROtective VEntilation Network and the Clinical Trial Network of the European Society of Anaesthesiology
Wer sich an einem Essensrest verschluckt und um Luft ringt, benötigt vor allem rasche Hilfe. Dass Umstehende nur in jedem zweiten Erstickungsnotfall bereit waren, diese zu leisten, ist das ernüchternde Ergebnis einer Beobachtungsstudie aus Japan. Doch es gibt auch eine gute Nachricht.
In einer Leseranfrage in der Zeitschrift Journal of the American Academy of Dermatology möchte ein anonymer Dermatologe bzw. eine anonyme Dermatologin wissen, ob er oder sie einen Patienten behandeln muss, der eine rassistische Tätowierung trägt.
Extreme Arbeitsverdichtung und kaum Supervision: Dr. Andrea Martini, Sprecherin des Bündnisses Junge Ärztinnen und Ärzte (BJÄ) über den Frust des ärztlichen Nachwuchses und die Vorteile des Rucksack-Modells.
Akute Brustschmerzen sind ein Alarmsymptom par exellence, schließlich sind manche Auslöser lebensbedrohlich. Auch Kinder klagen oft über Schmerzen in der Brust. Ein Studienteam ist den Ursachen nachgegangen.
Update AINS
Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.
