Patient-ventilator asynchronies during mechanical ventilation: current knowledge and research priorities

Intensive Care Medicine Experimental

Volumn 7, Issue , 2019, Pages

  de Haro, Candelaria ^a,b,d   Ochagavia, Ana ^a,b,d   López Aguilar, Josefina ^a,b,d   Fernandez Gonzalo, Sol ^a,b   Navarra Ventura, Guillem ^a   Magrans, Rudys ^a,b,d   Montanyà, Jaume ^c   Blanch, Lluís ^a,b,d   Fernández Gonzalo, Sol ^d   Gomà, Gemma ^d   Chacón, Encarna ^d   Montanya, Jaume ^d   Sales, Bernat ^d   Lena, Enrico ^d   Lucangelo, Umberto ^d   Fernández, Rafael ^d   Subirà, Carles ^d   Albaiceta, Guillermo M ^d   Murias, Gastón ^d   Kacmarek, Robert M ^d  

^a PARC TAULÍ HOSPITAL UNIVERSITARI   (Spain)

^b INSTITUTO DE SALUD CARLOS III   (Spain)

^c Better Care   (Spain)

^d NONE

Author keywords

Asynchronies; Big data; Cognitive; Critically ill; Heart lung interaction; ICU; Mechanical ventilation; Outcome; Patient ventilator interaction; Psychological disorders

Indexed keywords

ACCURACY; AIRWAY PRESSURE; ANXIETY DISORDER; ARTIFICIAL VENTILATION; BREATHING MUSCLE; BREATHING PATTERN; CLINICAL OUTCOME; COMPUTER ASSISTED TOMOGRAPHY; CRITICALLY ILL PATIENT; DEPRESSION; FEAR; HEART OUTPUT; HEMODYNAMICS; HOSPITAL MORTALITY; HUMAN; INSPIRATORY CAPACITY; INTENSIVE CARE; KNOWLEDGE; LUNG INJURY; MACHINE LEARNING; MEAN ARTERIAL PRESSURE; PALLIATIVE THERAPY; PREDICTIVE VALUE; PRESSURE SUPPORT VENTILATION; PRIORITY JOURNAL; PROGNOSIS; QUALITY OF LIFE; RECEIVER OPERATING CHARACTERISTIC; REVIEW; SENSITIVITY AND SPECIFICITY; SYSTOLIC BLOOD PRESSURE; TIDAL VOLUME;

EID: 85132495089     PISSN: None     EISSN: 2197425X     Source Type: Journal    
DOI: 10.1186/s40635-019-0234-5     Document Type: Review

References (74)

1. Mehta AB, Syeda SN, Wiener RS, Walkey AJ (2015) Epidemiological trends in invasive mechanical ventilation in the United States: a population-based study. J Crit Care 30:1217–1221
2. Jackson JC, Mitchell N, Hopkins RO (2015) Cognitive functioning, mental health, and quality of life in ICU survivors: an overview. Psychiatr Clin North Am 38:91–104
3. Jackson JC, Pandharipande PP, Girard TD, Brummel NE, Thompson JL, Hughes CG, Pun BT, Vasilevskis EE, Morandi A, Shintani AK, Hopkins RO, Bernard GR, Dittus RS, Ely EW (2014) Depression, post-traumatic stress disorder, and functional disability in survivors of critical illness in the BRAIN-ICU study: a longitudinal cohort study. Lancet Respir Med 2:369–379
4. Blanch L, Villagra A, Sales B, Montanya J, Lucangelo U, Lujan M, Garcia-Esquirol O, Chacon E, Estruga A, Oliva JC, Hernandez-Abadia A, Albaiceta GM, Fernandez-Mondejar E, Fernandez R, Lopez-Aguilar J, Villar J, Murias G, Kacmarek RM (2015) Asynchronies during mechanical ventilation are associated with mortality. Intensive Care Med 41:633–641
5. Subira C, de Haro C, Magrans R, Fernandez R, Blanch L (2018) Minimizing asynchronies in mechanical ventilation: current and future trends. Respir Care 63:464–478
6. Pham T, Telias I, Piraino T, Yoshida T, Brochard LJ (2018) Asynchrony consequences and management. Crit Care Clin 34:325–341
7. Thille AW, Rodriguez P, Cabello B, Lellouche F, Brochard L (2006) Patient-ventilator asynchrony during assisted mechanical ventilation. Intensive Care Med 32:1515–1522
8. Gilstrap D, MacIntyre N (2013) Patient-ventilator interactions. Implications for clinical management. Am J Respir Crit Care Med 188:1058–1068
9. Spieth PM, Guldner A, Huhle R, Beda A, Bluth T, Schreiter D, Ragaller M, Gottschlich B, Kiss T, Jaber S, Pelosi P, Koch T, Gama de Abreu M (2013) Short-term effects of noisy pressure support ventilation in patients with acute hypoxemic respiratory failure. Crit Care 17:R261
10. Kondili E, Prinianakis G, Georgopoulos D (2003) Patient-ventilator interaction. Br J Anaesth 91:106–119
11. Colombo D, Cammarota G, Alemani M, Carenzo L, Barra FL, Vaschetto R, Slutsky AS, Della Corte F, Navalesi P (2011) Efficacy of ventilator waveforms observation in detecting patient-ventilator asynchrony. Crit Care Med 39:2452–2457
12. de Wit M (2011) Monitoring of patient-ventilator interaction at the bedside. Respir Care 56:61–72
13. Figueroa-Casas JB, Montoya R (2016) Effect of tidal volume size and its delivery mode on patient-ventilator dyssynchrony. Ann Am Thorac Soc 13:2207–2214
14. Telias I, Brochard L, Goligher EC (2018) Is my patient’s respiratory drive (too) high? Intensive Care Med 44(11):1936–1939
15. Evans KC, Banzett RB, Adams L, McKay L, Frackowiak RS, Corfield DR (2002) BOLD fMRI identifies limbic, paralimbic, and cerebellar activation during air hunger. J Neurophysiol 88:1500–1511
16. MacIntyre NR, McConnell R, Cheng KC, Sane A (1997) Patient-ventilator flow dyssynchrony: flow-limited versus pressure-limited breaths. Crit Care Med 25:1671–1677
17. Kallet RH, Alonso JA, Luce JM, Matthay MA (1999) Exacerbation of acute pulmonary edema during assisted mechanical ventilation using a low-tidal volume, lung-protective ventilator strategy. Chest 116:1826–1832
18. Yoshida T, Amato MBP, Kavanagh BP (2018) Understanding spontaneous vs. ventilator breaths: impact and monitoring. Intensive Care Med 44(12):2235–2238
19. Akoumianaki E, Lyazidi A, Rey N, Matamis D, Perez-Martinez N, Giraud R, Mancebo J, Brochard L, Richard JM (2013) Mechanical ventilation-induced reverse-triggered breaths: a frequently unrecognized form of neuromechanical coupling. Chest 143:927–938
20. Murias G, de Haro C, Blanch L (2016) Does this ventilated patient have asynchronies? Recognizing reverse triggering and entrainment at the bedside. Intensive Care Med 42:1058–1061
21. de Haro C, Lopez-Aguilar J, Magrans R, Montanya J, Fernandez-Gonzalo S, Turon M, Goma G, Chacon E, Albaiceta GM, Fernandez R, Subira C, Lucangelo U, Murias G, Rue M, Kacmarek RM, Blanch L (2018) Double cycling during mechanical ventilation: frequency, mechanisms, and physiologic implications. Crit Care Med 46:1385–1392
22. Delisle S, Charbonney E, Albert M, Ouellet P, Marsolais P, Rigollot M, Savary D, Richard JM, Serri K (2016) Patient-ventilator asynchrony due to reverse triggering occurring in brain-dead patients: clinical implications and physiological meaning. Am J Respir Crit Care Med 194:1166–1168
23. Yoshida T, Nakamura MAM, Morais CCA, Amato MBP, Kavanagh BP (2018) Reverse triggering causes an injurious inflation pattern during mechanical ventilation. Am J Respir Crit Care Med 198(8):1096–1099
24. Beitler JR, Sands SA, Loring SH, Owens RL, Malhotra A, Spragg RG, Matthay MA, Thompson BT, Talmor D (2016) Quantifying unintended exposure to high tidal volumes from breath stacking dyssynchrony in ARDS: the BREATHE criteria. Intensive Care Med 42:1427–1436
25. Pohlman MC, McCallister KE, Schweickert WD, Pohlman AS, Nigos CP, Krishnan JA, Charbeneau JT, Gehlbach BK, Kress JP, Hall JB (2008) Excessive tidal volume from breath stacking during lung-protective ventilation for acute lung injury. Crit Care Med 36:3019–3023
26. Pinsky MR (2018) Cardiopulmonary interactions: physiologic basis and clinical applications. Ann Am Thorac Soc 15:S45–S48
27. Feihl F, Broccard AF (2009) Interactions between respiration and systemic hemodynamics. Part I: basic concepts. Intensive Care Med 35:45–54
28. Pinsky MR (2012) Heart lung interactions during mechanical ventilation. Curr Opin Crit Care 18:256–260
29. Pinsky MR (2014) Functional haemodynamic monitoring. Curr Opin Crit Care 20:288–293
30. Katira BH, Engelberts D, Otulakowski G, Giesinger RE, Yoshida T, Post M, Kuebler WM, Connelly KA, Kavanagh BP (2018) Abrupt deflation after sustained inflation causes lung injury. Am J Respir Crit Care Med 198(9):1165–1176
31. Monnet X, Marik PE, Teboul JL (2016) Prediction of fluid responsiveness: an update. Ann Intensive Care 6:111
32. Messina A, Colombo D, Cammarota G, De Lucia M, Cecconi M, Antonelli M, Corte FD, Navalesi P (2015) Patient-ventilator asynchrony affects pulse pressure variation prediction of fluid responsiveness. J Crit Care 30:1067–1071
33. Bosma K, Ferreyra G, Ambrogio C, Pasero D, Mirabella L, Braghiroli A, Appendini L, Mascia L, Ranieri VM (2007) Patient-ventilator interaction and sleep in mechanically ventilated patients: pressure support versus proportional assist ventilation. Crit Care Med 35:1048–1054
34. de Wit M, Pedram S, Best AM, Epstein SK (2009) Observational study of patient-ventilator asynchrony and relationship to sedation level. J Crit Care 24:74–80
35. de Wit M, Miller KB, Green DA, Ostman HE, Gennings C, Epstein SK (2009) Ineffective triggering predicts increased duration of mechanical ventilation. Crit Care Med 37:2740–2745
36. Bodi M, Blanch L, Maspons R (2017) Clinical information systems: an opportunity to measure value, investigate and innovate from the real world. Med Int 41:316–318
37. Blanch L, Sales B, Montanya J, Lucangelo U, Garcia-Esquirol O, Villagra A, Chacon E, Estruga A, Borelli M, Burgueno MJ, Oliva JC, Fernandez R, Villar J, Kacmarek R, Murias G (2012) Validation of the Better Care(R) system to detect ineffective efforts during expiration in mechanically ventilated patients: a pilot study. Intensive Care Med 38:772–780
38. Vaporidi K, Babalis D, Chytas A, Lilitsis E, Kondili E, Amargianitakis V, Chouvarda I, Maglaveras N, Georgopoulos D (2017) Clusters of ineffective efforts during mechanical ventilation: impact on outcome. Intensive Care Med 43:184–191
39. Rue M, Andrinopoulou ER, Alvares D, Armero C, Forte A, Blanch L (2017) Bayesian joint modeling of bivariate longitudinal and competing risks data: an application to study patient-ventilator asynchronies in critical care patients. Biom J 59:1184–1203
40. Chanques G, Kress JP, Pohlman A, Patel S, Poston J, Jaber S, Hall JB (2013) Impact of ventilator adjustment and sedation-analgesia practices on severe asynchrony in patients ventilated in assist-control mode. Crit Care Med 41:2177–2187
41. Gonzalez-Lopez A, Garcia-Prieto E, Batalla-Solis E, Amado-Rodriguez L, Avello N, Blanch L, Albaiceta GM (2012) Lung strain and biological response in mechanically ventilated patients. Intensive Care Med 38:240–247
42. Blanch L, Quintel M (2017) Lung-brain cross talk in the critically ill. Intensive Care Med 43:557–559
43. Quilez ME, Fuster G, Villar J, Flores C, Marti-Sistac O, Blanch L, Lopez-Aguilar J (2011) Injurious mechanical ventilation affects neuronal activation in ventilated rats. Crit Care 15:R124
44. Breckenridge SJ, Chlan L, Savik K (2014) Impact of tracheostomy placement on anxiety in mechanically ventilated adult ICU patients. Heart Lung 43:392–398
45. Schmidt M, Banzett RB, Raux M, Morelot-Panzini C, Dangers L, Similowski T, Demoule A (2014) Unrecognized suffering in the ICU: addressing dyspnea in mechanically ventilated patients. Intensive Care Med 40:1–10
46. Tate JA, Devito Dabbs A, Hoffman LA, Milbrandt E, Happ MB (2012) Anxiety and agitation in mechanically ventilated patients. Qual Health Res 22:157–173
47. Bergbom-Engberg I, Haljamae H (1989) Assessment of patients’ experience of discomforts during respirator therapy. Crit Care Med 17:1068–1072
48. Schmidt M, Demoule A, Polito A, Porchet R, Aboab J, Siami S, Morelot-Panzini C, Similowski T, Sharshar T (2011) Dyspnea in mechanically ventilated critically ill patients. Crit Care Med 39:2059–2065
49. Jubran A, Lawm G, Kelly J, Duffner LA, Gungor G, Collins EG, Lanuza DM, Hoffman LA, Tobin MJ (2010) Depressive disorders during weaning from prolonged mechanical ventilation. Intensive Care Med 36:828–835
50. Davydow DS, Desai SV, Needham DM, Bienvenu OJ (2008) Psychiatric morbidity in survivors of the acute respiratory distress syndrome: a systematic review. Psychosom Med 70:512–519
51. McKinley S, Aitken LM, Alison JA, King M, Leslie G, Burmeister E, Elliott D (2012) Sleep and other factors associated with mental health and psychological distress after intensive care for critical illness. Intensive Care Med 38:627–633
52. Wolters AE, Peelen LM, Welling MC, Kok L, de Lange DW, Cremer OL, van Dijk D, Slooter AJ, Veldhuijzen DS (2016) Long-term mental health problems after delirium in the ICU. Crit Care Med 44:1808–1813
53. Davydow DS, Gifford JM, Desai SV, Needham DM, Bienvenu OJ (2008) Posttraumatic stress disorder in general intensive care unit survivors: a systematic review. Gen Hosp Psychiatry 30:421–434
54. Jackson JC, Hart RP, Gordon SM, Hopkins RO, Girard TD, Ely EW (2007) Post-traumatic stress disorder and post-traumatic stress symptoms following critical illness in medical intensive care unit patients: assessing the magnitude of the problem. Crit Care 11:R27
55. Parker AM, Sricharoenchai T, Raparla S, Schneck KW, Bienvenu OJ, Needham DM (2015) Posttraumatic stress disorder in critical illness survivors: a metaanalysis. Crit Care Med 43:1121–1129
56. Davydow DS, Gifford JM, Desai SV, Bienvenu OJ, Needham DM (2009) Depression in general intensive care unit survivors: a systematic review. Intensive Care Med 35:796–809
57. Vandenbroucke JP (2008) Observational research, randomised trials, and two views of medical science. PLoS Med 5:e67
58. Big, intensive data. http://news.mit.edu/2016/big-intensive-data-thomas-heldt-0331. Accessed 26 Nov 2018
59. Celi LA, Mark RG, Stone DJ, Montgomery RA (2013) “Big data” in the intensive care unit. Closing the data loop. Am J Respir Crit Care Med 187:1157–1160
60. Dres M, Rittayamai N, Brochard L (2016) Monitoring patient-ventilator asynchrony. Curr Opin Crit Care 22:246–253
61. Bauer M (2016) Big data, technology, and the changing future of medicine. Medicographia 38:401–409
62. Cooke CR, Iwashyna TJ (2013) Using existing data to address important clinical questions in critical care. Crit Care Med 41:886–896
63. Murdoch TB, Detsky AS (2013) The inevitable application of big data to health care. JAMA 309:1351–1352
64. Serpa Neto A, Deliberato RO, Johnson AEW, Bos LD, Amorim P, Pereira SM, Cazati DC, Cordioli RL, Correa TD, Pollard TJ, Schettino GPP, Timenetsky KT, Celi LA, Pelosi P, Gama de Abreu M, Schultz MJ (2018) Mechanical power of ventilation is associated with mortality in critically ill patients: an analysis of patients in two observational cohorts. Intensive Care Med 44:1914–1922
65. Potential benefits of adopting AEGLE analytics to improve patient-ventilator interaction. http.//www.aegle-uhealth.eu/blog/potential-benefits-of-adopting-aegle-analytics-to-improve-patient-ventilator-interaction. Accessed 26 Nov 2018
66. Looking at the ICU ventilator with AEGLE’s eyes - using big data analytics to improve mechanical ventilation in ICU. http://www.aegle-uhealth.eu/blog/icu-with-aegle-eyes. Accessed 26 Nov 2018
67. Marchuk Y, Magrans R, Sales B, Montanya J, López-Aguilar J, de Haro C, Gomà G, Subirà C, Fernández R, Kacmarek RM, Blanch L (2018) Predicting patient-ventilator asynchronies with Hidden Markov Models. Sci Rep 8:17614
68. Sanchez-Pinto LN, Luo Y, Churpek MM (2018) Big data and data science in critical care. Chest 154:1239–1248
69. Gholami B, Phan TS, Haddad WM, Cason A, Mullis J, Price L, Bailey JM (2018) Replicating human expertise of mechanical ventilation waveform analysis in detecting patient-ventilator cycling asynchrony using machine learning. Comput Biol Med 97:137–144
70. Adams JY, Lieng MK, Kuhn BT, Rehm GB, Guo EC, Taylor SL, Delplanque JP, Anderson NR (2017) Development and validation of a multi-algorithm analytic platform to detect off-target mechanical ventilation. Sci Rep 7:14980
71. Sinderby C, Liu S, Colombo D, Camarotta G, Slutsky AS, Navalesi P, Beck J (2013) An automated and standardized neural index to quantify patient-ventilator interaction. Crit Care 17:R239
72. Gutierrez G, Ballarino GJ, Turkan H, Abril J, De La Cruz L, Edsall C, George B, Gutierrez S, Jha V, Ahari J (2011) Automatic detection of patient-ventilator asynchrony by spectral analysis of airway flow. Crit Care 15:R167
73. Mulqueeny Q, Ceriana P, Carlucci A, Fanfulla F, Delmastro M, Nava S (2007) Automatic detection of ineffective triggering and double triggering during mechanical ventilation. Intensive Care Med 33:2014–2018
74. Younes M, Brochard L, Grasso S, Kun J, Mancebo J, Ranieri M, Richard JC, Younes H (2007) A method for monitoring and improving patient: ventilator interaction. Intensive Care Med 33:1337–1346