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PERSPECTIVE article

Front. Med., 12 November 2021
Sec. Intensive Care Medicine and Anesthesiology
This article is part of the Research Topic Insights in Intensive Care Medicine and Anesthesiology: 2021 View all 41 articles

Tools Are Needed to Promote Sedation Practices for Mechanically Ventilated Patients

\nTao WangTao Wang1Dongxu ZhouDongxu Zhou1Zhongheng ZhangZhongheng Zhang2Penglin Ma
Penglin Ma1*
  • 1Critical Care Medicine Department, Guiqian International General Hospital, Guiyang, China
  • 2Department of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China

Suboptimal sedation practices continue to be frequent, although the updated guidelines for management of pain, agitation, and delirium in mechanically ventilated (MV) patients have been published for several years. Causes of low adherence to the recommended minimal sedation protocol are multifactorial. However, the barriers to translation of these protocols into standard care for MV patients have yet to be analyzed. In our view, it is necessary to develop fresh insights into the interaction between the patients' responses to nociceptive stimuli and individualized regulation of patients' tolerance when using analgesics and sedatives. By better understanding this interaction, development of novel tools to assess patient pain tolerance and to define and predict oversedation or delirium may promote better sedation practices in the future.

Introduction

Mechanically ventilated (MV) patients can have a wide variety of discomforts resulting from multiple sources, including pathophysiological abnormalities (such as fever, hypoxia, and shock), emotional alterations (anxiety or fear), and intensive care procedures as well (such as non-physical ventilation, immobilization, frequent puncturing, and turning over, etc.) (14). Analgesics and sedatives are often used to maintain MV patients' comfort (5). In the last two decades, it has been observed that MV patients were deeply sedated very frequently in intensive care units (ICU) (68). Significantly, this behavior has been associated with poor outcomes, including prolonged duration of mechanical ventilation, increased incidence of ventilator associated pneumonia decline in cognitive ability, and even increased long-term mortality (610). Therefore, it has been strongly recommended to optimize sedation practices, such as implementing a light sedation protocol and the eCASH concept (early Comfort using Analgesia, minimal Sedatives and maximal Humane care) in MV patients (11, 12). Recently, more days without occurrence of coma or delirium were demonstrated in the patients receiving no sedation protocol than in those who were maintained at even light levels of sedation during the stay in the ICUs (13). These findings indicated that the lighter the level of sedation, the better outcomes would be for MV patients.

However, the frequency of deep sedation remains high in clinical practice based on recently published data from various studies (1315), although a strong recommendation of minimizing sedation for MV patients has been published in the updated guidelines for several years. For instance, the mean depth of sedation was below RASS−2 (mean RASS = −2.3) on day 1 in the sedation group (i.e., the usual care arm) of Olsen's randomized control trial in ICUs where no sedation strategy was initiated 10 years ago (13, 16). It was previously recognized that the low adherence to a minimal sedation protocol was multifactorial, including inadequate assessments because of shortage of nurses, lack of multidisciplinary cooperation, and even misperception as well (1720). However, the barriers to translating a minimal sedation protocol into standard care for MV patients are not well-defined. It is necessary to reveal fresh insight into the fact that the outcome favored minimal sedation protocol was poorly implemented in MV patients.

Lightly Sedated Patients' Tolerance to Mechanical Ventilation

Lack of knowledge on patient intolerance to MV has been an important barrier to implementing a minimal sedation protocol in MV patients. Among the common signs of patient intolerance, agitation affected nearly half of ICU MV patients in previous reports (21, 22). Moreover, accumulating evidence has demonstrated that the risks of agitation or agitation-associated events were significantly increased while maintaining MV patients at light levels of sedation (usually defined as at levels of RASS from −2 to 1) (16, 23, 24). Notably, severe agitation has been associated with unplanned self-extubation, removal of important intralumenal tubes and vascular catheters, poor patient–ventilator synchrony, and increased morbidity, including PTSD (2528). Accordingly, agitation or agitated adverse events have been of serious concern in most ICU nurses and physicians, which in turn has affected their willingness to implement light sedation practices in their routine clinical care (18, 29). In a nationwide cross-sectional survey, we also found that ICU physicians' perception of patients' tolerance to the support levels of ventilation with light sedation was highly varied across institutions. Importantly, their perceptions were largely translated into clinical practices (14). In addition, bolus administration of sedatives was usually given as a rescue intervention for agitation, which often led to unjustified deep sedation (18).

Actually, measurement of MV patients' tolerance (who are unable to communicate) remains problematic. Tools to evaluate patient tolerance or sedation depth in mechanical ventilation have evolved since the Ramsay sedation scale first used in 1974 as shown on Table 1. RASS offers broader discrimination in the mild-to-moderate sedation range. It is the most commonly used tool in clinical practice (41), and has demonstrated greater inter-rater reliability between clinical staff (37, 38, 42, 44). Therefore, frequent assessment of RASS has been strongly recommended to optimize the depth of sedation for MV patients and has been associated with improvement in outcomes (56). However, RASS, like other tools, is actually a transient result of patient tolerance to nociceptive stimuli as regulated by the infused analgesics and sedatives in MV. It is not a scale to directly assess the intensity of stimuli that patients experience instantaneously. Being complementary to RASS, the pain assessment tools such as Behavioral Pain Score (BPS) or Clinical Pain Observation Tool (CPOT) were suggested to improve the overall assessment of comfort of critically ill patients. However, the intensity of nociceptive stimuli might change over time because of occurrence of fever, thirst, drainage tube pain, or intestinal colic, etc., that would raise the risk of patient intolerance to MV (or vice versa). No matter how frequent the RASS assessment is, titration of analgesics and sedatives always lags behind patient intolerance (or oversedation), which partially at least accounts for frequent and unpredictable agitation. In fact, there is a lack of reliable criteria to scale responses to the stimuli that patients experience during MV. Accordingly, it is difficult for ICU physicians to properly estimate the intensity of patients' responses as well as their tolerance when patients are lightly sedated, which might be an important source of suboptimal sedation practices.

TABLE 1
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Table 1. Tools for assessment of sedation depth or pain in mechanically ventilated patients.

Burk et al. (26) previously reported several predictors of agitation within 24 h in adult critically ill patients, including Sequential Organ Failure Assessment score, PaO2/FiO2 <200 mmHg, receiving MV, using restraints, etc. Based on the variables relating to fever, ventilator settings, alterations in respiratory physiology, and dosage of sedatives and analgesics, our study group recently developed an ensemble model for the prediction of agitation in invasive MV patients under light sedation (57). The model showed good calibration and discrimination in an independent dataset. However, the effectiveness of interventions based on the prediction model need to be investigated in further experimental trials. These findings indicate that agitation (i.e., severe patient intolerance in MV) is predictable by evaluating variables related to nocioceptive stimuli. Thus, development of a tool for evaluating the balance between the intensity of stimuli and patient tolerance when analgesics and sedatives are used is needed to implement a minimal sedation protocol in the future.

Recognition, Estimation, and Prevention of Oversedation in MV Patients

Suboptimal sedation practices include both oversedation and undersedation. In the literature, numerous studies have shown that deep sedation continues to be common in the ICU (8, 9, 1315). Generally, it has been recognized that deep sedation (below RASS−2) remains relevant only for the management of some situations in MV patients, such as severe acute respiratory distress syndrome with ventilator–patient asynchrony or with use of neuromuscular blocking agents, severe brain injury with intracranial hypertension, status epilepticus, etc. (5861). For the vast majority of ICU MV patients, deep sedation is unnecessary and should be avoided (62). Oversedation is therefore suspected when MV patients are sedated at the depths below RASS−2. However, this concept is mainly based on expert opinions rather than empirical evidence, which is misleading for appropriate sedation practices. For instance, sedatives could be overused while maintaining the level of sedation at RASS−2 for MV patients ready for weaning. On the other hand, the sedation depth at RASS−3 (or even the deeper levels) might be necessary for acute critically ill patients with multiple organ dysfunction caused by aggressive inflammatory responses (63, 64). In fact, no consensus on the definitions of deep sedation and oversedation is available because of gaps in the evidence. There is a dearth of information regarding the interaction among sedative choice, sedation depth, and patient-specific factors that affect outcomes (65). Therefore, determining optimal sedation and oversedation in MV patients remains challenging.

Ambiguity in definition is an important barrier to the development of protocols to prevent oversedation in practice. Previously, the ABCDEF bundle (Assess, prevent, and manage pain; Both spontaneous awakening and breathing trials; Choice of analgesia and sedation; Delirium assess, prevent, and manage; Early mobility and exercise; Family engagement/empowerment) was developed to promote appropriate sedation practices by creating a safe and comfortable environment for MV patients (66). Although reduction in the rate of deep sedation and improvement in outcomes were demonstrated in patients who did receive more of the bundle elements each day, the major limitation was low adherence in clinical practice because of too many unresolved issues involved in this protocol (67). A novel sedation-monitoring technology (the Responsiveness Index, RI) based on facial electromyography was developed to provide an alert for possible deep sedation. Results showed that use of the monitor increased optimal sedation-analgesia quality but just by 7% (68). Results from the AWARE study (69) revealed that by decreasing use of intravenous hypnotics, the oversedation prevention protocol was feasible in clinical practice and resulted in a significantly earlier time to spontaneous breathing trial and reduced duration of mechanical ventilation (69). However, mortality was not significantly different between the study group and the control group. It should be interpreted with caution that the rate of oversedation or deep sedation was prevented in this study. Therefore, a precision definition is fundamental for development of a reliable scale for estimation as well as an effective protocol for prevention of oversedation in MV patients.

Delirium Prediction

Delirium is a well-established syndrome in the ICU that is considered to be an acute onset of brain dysfunction (70). There are two motor subtypes of delirium that are categorized according to its clinical presentation, namely, the hyperactive and hypoactive subtypes (71, 72). The primary presentation of hyperactive delirium is agitation, which is reported to occur in many ICU patients (26). Although agitated delirium is found to be less harmful than the hypoactive type with respect to 12-month mortality (72, 73), potential serious consequences of agitation as opposed to its hypoactive counterpart, mentioned above included medical device removal (such as urinary catheter, venous or arterial line, or surgical drain), falling out of bed, immobilization device removal, or self-aggression or aggression toward medical staff (2528, 74). Thus, the prediction and appropriate prevention of agitated delirium is of paramount importance in the management of MV patients.

The mechanism of delirium remains unclear (75). Risk factors for delirium include illness-related acute pathophysiological abnormalities (e.g., hypotension, acidosis, hypoxia, and sepsis), environmental factors (e.g., lighting, alarm sounds, and noise); and iatrogenic harm (e.g., frequent suctions, puncture, immobilization, and even use of analgesic and sedative drugs) (7679). Among these, there are potentially modifiable risk factors, for example, minimizing sedation and benzodiazepine use (80). Significantly, numerous studies have reported that patients receiving deep sedation were more susceptible to post-traumatic stress disorder syndrome, ICU memory disorder, and delirium (81, 82). On the other hand, two recently published meta-analyses revealed that delirium occurred more frequently in the light than in the deep sedation group of MV patients (24, 83). Because of multiple etiologies, therefore, prediction and prevention of delirium remains problematic.

Some prediction models have been developed for delirium, but limitations remain. For example, the prediction model for delirium (PRE-DELIRIC) and early prediction model for delirium (E-PRE-DELIRIC) were initially developed in a single hospital and validated in four hospitals (84). However, the discriminatory ability of these models in an external dataset was less than satisfactory (area under curve: 0.68–0.79, respectively) (8587). These studies are limited in several aspects. First, previous studies typically used variables collected on the day of ICU admission, and the delirium event may happen several days later. Some physiological variables change significantly in this interval. Second, there is no model to specifically predict hypoactive delirium. Third, previous models were usually developed in a single center, which partly explains the models' suboptimal performance in an external dataset. Foruth, the previous models were developed as generalized linear models that failed to capture higher- order and interaction terms between predictors. Therefore, a novel delirium prediction model is needed for MV patients.

Conclusion

Suboptimal sedation practices are common, which are largely attributable to the evidence gaps concerning the intensity of nociceptive stimuli that patients experience and patients' tolerance and its treatment by using analgesics and sedatives. Development of novel tools to assess patient tolerance and to define and predict oversedation or delirium are needed to implement better sedation practices in the future.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.

Author Contributions

TW and PM were the major contributors in writing the manuscript. DZ and ZZ helped to revise the manuscript. PM critically reviewed the manuscript and agreed with the final version. All authors read and approved the submitted manuscript.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

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References

1. Ma P, Liu J, Xi X, Du B, Yuan X, Lin H, et al. Practice of sedation and the perception of discomfort during mechanical ventilation in chinese intensive care units. J Crit Care. (2010) 3:451–7. doi: 10.1016/j.jcrc.2009.11.006

PubMed Abstract | CrossRef Full Text | Google Scholar

2. Puntillo KA, Max A, Timsit JF, Vignoud L, Chanques G, Robleda G, et al. Determinants of procedural pain intensity in the intensive care unit. the Europain® study. Am J Respir Crit Care Med. (2014) 189:39–47. doi: 10.1164/rccm

PubMed Abstract | CrossRef Full Text | Google Scholar

3. Samuelson KA, Lundberg D, Fridlund B. Stressful experiences in relation to depth of sedation in mechanically ventilated patients. Nurs Crit Care. (2007) 12:93–104. doi: 10.1111/j.1478-5153.2006.00199.x

PubMed Abstract | CrossRef Full Text | Google Scholar

4. Weinert CR, Calvin AD. Epidemiology of sedation and sedation adequacy for mechanically ventilated patients in a medical and surgical intensive care unit. Crit Care Med. (2007) 35:393–401. doi: 10.1097/01.CCM.0000254339.18639.1D

PubMed Abstract | CrossRef Full Text | Google Scholar

5. Jacobi J, Fraser GL, Coursin DB, Riker RR, Fontaine D, Wittbrodt ET, et al. Clinical practice guidelines for the sustained use of sedatives and analgesics in the critically ill adult. Crit Care Med. (2002) 30:119–41. doi: 10.1097/00003246-200201000-00020

PubMed Abstract | CrossRef Full Text | Google Scholar

6. Shehabi Y, Chan L, Kadiman S, Alias A, Ismail WN, Tan MA, et al. Sedation depth and long-term mortality in mechanically ventilated critically ill adults: a prospective longitudinal multicentre cohort study. Intensive Care Med. (2013) 39:910–8. doi: 10.1007/s00134-013-2830-2

PubMed Abstract | CrossRef Full Text | Google Scholar

7. Tanaka LM, Azevedo LC, Park M, Schettino G, Nassar AP, Réa-Neto A, et al. Early sedation and clinical outcomes of mv patients: a prospective multicenter cohort study. Crit Care. (2014) 18:R156. doi: 10.1186/cc13995

PubMed Abstract | CrossRef Full Text | Google Scholar

8. Balzer F, Weiß B, Kumpf O, Treskatsch S, Spies C, Wernecke KD, et al. Early deep sedation is associated with decreased in-hospital and two-year follow-up survival. Crit Care. (2015) 19:197. doi: 10.1186/s13054-015-0929-2

PubMed Abstract | CrossRef Full Text | Google Scholar

9. Shehabi Y, Bellomo R, Kadiman S, Ti LK, Howe B, Reade MC, et al. Sedation intensity in the first 48 hours of mechanical ventilation and 180-day mortality: a multinational prospective longitudinal cohort study. Crit Care Med. (2018) 46:850–9. 03071. doi: 10.1097/CCM.0000000000003071

PubMed Abstract | CrossRef Full Text | Google Scholar

10. Girard TD, Kress JP, Fuchs BD, Thomason JW, Schweickert WD, Pun BT. Efficacy and safety of a paired sedation and ventilator weaning protocol for MV patients in intensive care (awakening and breathing controlled trial): a randomised controlled trial. Lancet. (2008) 371:126–34. doi: 10.1016/S0140-6736(08)60105-1

PubMed Abstract | CrossRef Full Text | Google Scholar

11. Barr J, Fraser GL, Puntillo K, Ely EW, Gélinas C, Dasta JF, et al. Clinical practice guidelines for the management of pain, agitation, and delirium in adult patients in the intensive care unit. Crit Care Med. (2013) 41:263–306. doi: 10.1097/CCM.0b013e3182783b72

PubMed Abstract | CrossRef Full Text | Google Scholar

12. Vincent JL, Shehabi Y, Walsh TS, Pandharipande PP, Ball JA, Spronk P. Comfort and patient-centred care without excessive sedation: the ecash concept. Intensive Care Med. (2016) 42:962–71. doi: 10.1007/s00134-016-4297-4

PubMed Abstract | CrossRef Full Text | Google Scholar

13. Olsen HT, Nedergaard HK, Strøm T, Oxlund J, Wian KA, Ytrebø LM, et al. Nonsedation or light sedation in critically ill, mechanically ventilated patients. N Engl J Med. (2020) 382:1103–11. doi: 10.1056/NEJMoa1906759

PubMed Abstract | CrossRef Full Text | Google Scholar

14. Gong Y, Yang H, Xie J, Liu J, Zhou J, Ma P. ICU physicians' perception of patients' tolerance levels in light sedation impacts sedation practice for mechanically ventilated patients. Front Med. (2019) 6:226. doi: 10.3389/fmed.2019.00226

PubMed Abstract | CrossRef Full Text | Google Scholar

15. Fuller BM, Roberts BW, Mohr NM, Knight WA 4th, Adeoye O, Pappal RD, et al. The ED-SED study: a multicenter, prospective cohort study of practice patterns and clinical outcomes associated with emergency department sedation for mechanically ventilated patients. Crit Care Med. (2019) 47:1539–48. doi: 10.1097/CCM.0000000000003928

PubMed Abstract | CrossRef Full Text | Google Scholar

16. Strom T, Martnussen T, Toft P. A protocol of no sedation for critically ill patients receiving mechanical ventilation: a randomised trial. Lancet. (2010) 375:475–80. doi: 10.1016/S0140-6736(09)62072-9

PubMed Abstract | CrossRef Full Text | Google Scholar

17. Jackson DL, Proudfoot CW, Cann KF, Walsh TS. The incidence of sub-optimal sedation in the ICU: a systematic review. Crit Care. (2009) 13:R204. doi: 10.1186/cc8212

PubMed Abstract | CrossRef Full Text | Google Scholar

18. Mehta S, McCullagh Burry L. Current sedation practices: lessons learned from international surveys. Anesthesiol Clin. (2011) 29:607–24. doi: 10.1016/j.anclin.2011.09.003

PubMed Abstract | CrossRef Full Text | Google Scholar

19. Peitz GJ, Balas MC, Olsen KM, Pun BT, Ely EW. Top 10 myths regarding sedation and delirium in the ICU. Crit Care Med. (2013) 41(Suppl. 1):S46–56. doi: 10.1097/CCM.0b013e3182a168f5

PubMed Abstract | CrossRef Full Text | Google Scholar

20. Sneyers B, Laterre PF, Perreault MM, Wouters D, Spinewine A. current practices and barriers impairing physicians' and nurses' adherence to analgo-sedation recommendations in the intensive care unit–a national survey. Crit Care. (2014) 18:655. doi: 10.1186/s13054-014-0655-1

PubMed Abstract | CrossRef Full Text | Google Scholar

21. Jaber S, Chanques G, Altairac C, Sebbane M, Vergne C, Perrigault PF, et al. A prospective study of agitation in a medical-surgical ICU: incidence, risk factors, and outcomes. Chest. (2005) 128:2749–57. doi: 10.1378/chest.128.4.2749

PubMed Abstract | CrossRef Full Text | Google Scholar

22. Woods JC, Mion LC, Connor JT, Viray F, Jahan L, Huber C, et al. Severe agitation among ventilated medical intensive care unit patients: frequency, characteristics and outcomes. Intensive Care Med. (2004) 30:1066–72. doi: 10.1007/s00134-004-2193-9

PubMed Abstract | CrossRef Full Text | Google Scholar

23. Long L, Ren S, Gong Y, Zhao H, He C, Shen L, et al. Different depths of sedation versus risk of delirium in adult mechanically ventilated patients: a systematic review and meta-analysis. PLoS ONE. (2020) 15:e0236014. doi: 10.1371/journal.pone.0236014

PubMed Abstract | CrossRef Full Text | Google Scholar

24. Shehabi Y, Bellomo R, Reade MC, Bailey M, Bass F, Howe B. Early goal-directed sedation versus standard sedation in MV critically Ill patients: a pilot study. Crit Care Med. (2013) 41:1983–91. doi: 10.1097/CCM.0b013e31828a437d

PubMed Abstract | CrossRef Full Text | Google Scholar

25. Carrión MI, Ayuso D, Marcos M, Paz Robles M, de la Cal MA, Alía I, et al. Accidental removal of endotracheal and nasogastric tubes and intravascular catheters. Crit Care Med. (2000) 28:63–6. doi: 10.1097/00003246-200001000-00010

PubMed Abstract | CrossRef Full Text | Google Scholar

26. Burk RS, Grap MJ, Munro CL, Schubert CM, Sessler CN. Predictors of agitation in critically ill adults. Am J Crit Care. (2014) 23:414–23. doi: 10.4037/ajcc2014714

PubMed Abstract | CrossRef Full Text | Google Scholar

27. Chevrolet JC, Jolliet P. Clinical review: agitation and delirium in the critically ill–significance and management. Crit Care. (2007) 11:214. doi: 10.1186/cc5787

PubMed Abstract | CrossRef Full Text | Google Scholar

28. De Bels D, Honore PM, Redant S. Nonsedation or light sedation in critically ill, mechanically ventilated patients. N Engl J Med. (2020) 382:e107. doi: 10.1056/NEJMc2011055

PubMed Abstract | CrossRef Full Text | Google Scholar

29. Rose L, Fitzgerald E, Cook D, Kim S, Steinberg M, Devlin JW, et al. Clinician perspectives on protocols designed to minimize sedation. J Crit Care. (2015) 30:348–52. doi: 10.1016/j.jcrc.2014.10.021

PubMed Abstract | CrossRef Full Text | Google Scholar

30. Dawson R, von Fintel N, Nairn S. Sedation assessment using the Ramsay scale. Emerg Nurse. (2010) 18:18–20. doi: 10.7748/en2010.06.18.3.18.c7825

PubMed Abstract | CrossRef Full Text | Google Scholar

31. Némethy M, Paroli L, Williams-Russo PG, Blanck T. Assessing sedation with regional anesthesia [sic]: inter-rater agreement on a modified Wilson Sedation Scale. Anesth Analg. (2002) 94:723–8. doi: 10.1097/00000539-200203000-00045

PubMed Abstract | CrossRef Full Text | Google Scholar

32. Peck M, Down J. Use of sedatives in the critically ill. Anaesth Intensive Care Med. (2010) 11:12–15. doi: 10.1016/j.mpaic.2009.10.007

CrossRef Full Text | Google Scholar

33. De Jonghe B, Cook D, Appere-De-Vecchi C, Guyatt G, Meade M, Outin H. Using and understanding sedation scoring systems: a systematic review. Intensive Care Med. (2000) 26:275–85. doi: 10.1007/s001340051150

PubMed Abstract | CrossRef Full Text | Google Scholar

34. Mirski MA, LeDroux SN, Lewin JJ III, Thompson CB, Mirski KT, Griswold M. Validity and reliability of an intuitive conscious sedation scoring tool: the nursing instrument for the communication of sedation. Crit Care Med. (2010) 38:1674–84. doi: 10.1097/CCM.0b013e3181e7c73e

PubMed Abstract | CrossRef Full Text | Google Scholar

35. Riker R, Fraser G, Cox P. Continuous infusion of haloperidol controls agitation in critically ill patients. Crit Care Med. (1994) 22:433–40. doi: 10.1097/00003246-199403000-00013

PubMed Abstract | CrossRef Full Text | Google Scholar

36. Riker RR, Picard JT, Fraser GL. Prospective evaluation of the Sedation-Agitation Scale for adult critically ill patients. Crit Care Med. (1999) 27:1325–9. doi: 10.1097/00003246-199907000-00022

PubMed Abstract | CrossRef Full Text | Google Scholar

37. Ryder-Lewis M, Nelson K. Reliability of the Sedation-Agitation Scale between nurses and doctors. Intensive Crit Care Nurs. (2008) 24:211–7. doi: 10.1016/j.iccn.2007.11.004

PubMed Abstract | CrossRef Full Text | Google Scholar

38. Nassar Junior AP, Pires Neto RC, de Figueiredo WB, Park M. Validity, reliability and applicability of Portuguese versions of sedation-agitation scales among critically ill patients. Sáo Paulo Med J. (2008) 126:215–9. doi: 10.1590/S1516-31802008000400003

PubMed Abstract | CrossRef Full Text | Google Scholar

39. De Jonghe B, Cook D, Griffith L, Appere-de-Vecchi C, Guyatt G, Théron V, et al. Adaptation to the Intensive Care Environment (ATICE): development and validation of a new sedation assessment instrument. Crit Care Med. (2003) 31:2344–54. doi: 10.1097/01.CCM.0000084850.16444.94

PubMed Abstract | CrossRef Full Text | Google Scholar

40. Sessler CN, Grap MJ, Brophy GM. Multidisciplinary management of sedation and analgesia in critical care. Semin Respir Crit Care Med. (2001) 22:211–25. doi: 10.1055/s-2001-13834

PubMed Abstract | CrossRef Full Text | Google Scholar

41. Sessler CN, Gosnell MS, Grap MJ, Brophy GM, O'Neal PV, Keane KA, et al. The richmond agitation-sedation scale: validity and reliability in adult intensive care unit patients. Am J Respir Crit Care Med. (2002) 166:1338–44. doi: 10.1164/rccm.2107138

PubMed Abstract | CrossRef Full Text | Google Scholar

42. Ely EW, Truman B, Shintani A, Thomason JWW, Wheeler AP, Gordon S, et al. Monitoring sedation status over time in I.C.U. patients: reliability validity of the Richmond Agitation-Sedation Scale (RASS). JAMA. (2003) 289:2983–91. doi: 10.1001/jama.289.22.2983

PubMed Abstract | CrossRef Full Text | Google Scholar

43. Vincent JL, Takala J, Moreno RP, Sakr Y, Marshall JC. The Richmond Agitation-Sedation Scale should not be used to evaluate neurologic function. Crit Care Med. (2016) 44:e450. doi: 10.1097/CCM.0000000000001597

PubMed Abstract | CrossRef Full Text | Google Scholar

44. Brandl K, Langley K, Riker R, Dork L, Qualis C, Levy H. Confirming the reliability of the sedation-agitation scale administered by ICU nurses without experience in its use. Pharmcotherapy. (2001) 21:431–6. doi: 10.1592/phco.21.5.431.34487

PubMed Abstract | CrossRef Full Text | Google Scholar

45. Deogaonkar A, Gupta R, Degeorgia M, Sabharwal V, Gopakumaran B, Schubert A, et al. Bispectral Index monitoring correlates with sedation scales in brain-injure patients. Crit Care Med. (2004) 32:2403–6. doi: 10.1097/01.CCM.0000147442.14921.A5

PubMed Abstract | CrossRef Full Text | Google Scholar

46. Watson BD, Kane-Gill SL. Sedation assessment in critically ill adults: 2001–2004 update. Ann Pharmacother. (2004) 38:1898–906. doi: 10.1345/aph.1E167

PubMed Abstract | CrossRef Full Text | Google Scholar

47. Consales G, Chelazzi C, Rinaldi S, De Gaudio AR. Bispectral Index compared to Ramsay score for sedation monitoring in intensive care units. Minerva Anestesiol. (2006) 72:329–36. doi: 10.1111/mec.12739

PubMed Abstract | CrossRef Full Text | Google Scholar

48. Burjek NE, Wagner CE, Hollenbeck RD, Wang L, Yu C, McPherson JA, et al. Early bispectral index and sedation requirements during therapeutic hypothermia predict neurologic recovery following cardiac arrest. Crit Care Med. (2014) 42:1204–12. doi: 10.1097/CCM.0000000000000126

PubMed Abstract | CrossRef Full Text | Google Scholar

49. Devlin J, Boleski G, Mlynarek M, Narenz D, Peterson E, Jankowski M, et al. Motor activity assessment scale: a valid and reliable sedation scale for use with mechanically ventilated patients in an adult surgical intensive care unit. Crit Care Med. (1999) 27:1271–5. doi: 10.1097/00003246-199907000-00008

PubMed Abstract | CrossRef Full Text | Google Scholar

50. Varndell W, Elliott D, Fry M. The validity, reliability, responsiveness and applicability of observation sedation-scoring instruments for use with adult patients in the emergency department: a systematic literature review. Australas Emerg Nurs J. (2015) 18:1–23. doi: 10.1016/j.aenj.2014.07.001

PubMed Abstract | CrossRef Full Text | Google Scholar

51. Payen JF, Bru O, Bosson JL, Lagrasta A, Novel E, Deschaux I, et al. Assessing pain in critically ill sedated patients by using a behavioral pain scale. Crit Care Med. (2001) 29:2258–63. doi: 10.1097/00003246-200112000-00004

PubMed Abstract | CrossRef Full Text | Google Scholar

52. Rijkenberg S, Stilma W, Bosman RJ, van der Meer NJ, van der Voort PHJ. Pain measurement in mechanically ventilated patients after cardiac surgery: comparison of the Behavioral Pain Scale (BPS) and the Critical-Care Pain Observation Tool (CPOT). J Cardiothorac Vasc Anesth. (2017) 31:1227–34. doi: 10.1053/j.jvca.2017.03.013

PubMed Abstract | CrossRef Full Text | Google Scholar

53. Chanques G, Pohlman A, Kress JP, Molinari N, de Jong A, Jaber S, et al. Psychometric comparison of three behavioural scales for the assessment of pain in critically ill patients unable to self-report. Crit Care. (2014) 18:R160. doi: 10.1186/cc14000

PubMed Abstract | CrossRef Full Text | Google Scholar

54. Birkedal HC, Larsen MH, Steindal SA, Solberg MT. Comparison of two behavioural pain scales for the assessment of procedural pain: a systematic review. Nurs Open. (2021) 8:2050–60. doi: 10.1002/nop2.714

PubMed Abstract | CrossRef Full Text | Google Scholar

55. Gélinas C, Fillion L, Puntillo KA, Viens C, Fortier M. Validation of the critical-care pain observation tool in adult patients. Am J Crit Care. (2006) 15:420–7. doi: 10.4037/ajcc2006.15.4.420

PubMed Abstract | CrossRef Full Text | Google Scholar

56. Qi Z, Yang S, Qu J, Li M, Zheng J, Huang R, et al. Effect of nurse-led sedation protocols on mechanically ventilated intensive care adults: a systematic review and meta-analysis. Aust Crit Care. (2021) 34:278–86. doi: 10.1016/j.aucc.2020.07.013

PubMed Abstract | CrossRef Full Text | Google Scholar

57. Zhang Z, Liu J, Xi J, Gong Y, Zeng L, Ma P. Derivation and validation of an ensemble model for the prediction of agitation in mechanically ventilated patients maintained under light sedation. Crit Care Med. (2021) 49:e279–90. doi: 10.1097/CCM.0000000000004821

PubMed Abstract | CrossRef Full Text | Google Scholar

58. Papazian L, Forel JM, Gacouin A, Penot-Ragon C, Perrin G, Loundou A, et al. Neuromuscular blockers in early acute respiratory distress syndrome. N Engl J Med. (2010) 363:1107–16. doi: 10.1056/NEJMoa1005372

PubMed Abstract | CrossRef Full Text | Google Scholar

59. Luauté J, Plantier D, Wiart L, Tell L, SOFMER group. Care management of the agitation or aggressiveness crisis in patients with TBI. Systematic review of the literature and practice recommendations. Ann Phys Rehabil Med. (2016) 59:58–67. doi: 10.1016/j.rehab.2015.11.001

PubMed Abstract | CrossRef Full Text | Google Scholar

60. Brophy GM, Bell R, Claassen J, Alldredge B, Bleck TP, Glauser T, et al. Guidelines for the evaluation and management of status epilepticus. Neurocrit Care. (2012) 17:3–23. doi: 10.1007/s12028-012-9695-z

PubMed Abstract | CrossRef Full Text | Google Scholar

61. Devlin JW, Skrobik Y, Gélinas C, Needham DM, Slooter AJC, Pandharipande PP, et al. Clinical practice guidelines for the prevention and management of pain, agitation/sedation, delirium, immobility, and sleep disruption in adult patients in the ICU. Crit Care Med. (2018) 46:e825–73. doi: 10.1097/CCM.0000000000003299

PubMed Abstract | CrossRef Full Text | Google Scholar

62. Temesgen N, Chekol B, Tamirie T, Eshetie D, Simeneh N, Feleke A. Adult sedation and analgesia in a resource limited intensive care unit–a systematic review and evidence based guideline. Ann Med Surg. (2021) 66:102356. doi: 10.1016/j.amsu.2021.102356

PubMed Abstract | CrossRef Full Text | Google Scholar

63. Qiu HB. [Disease-specific analgesia and sedation in critically ill patients]. Zhonghua Nei Ke Za Zhi. (2013) 52:279–81. doi: 10.1157/13063183

PubMed Abstract | CrossRef Full Text | Google Scholar

64. Page V, McKenzie C. Sedation in the intensive care unit. Curr Anesthesiol Rep. (2021) 11:92–100. doi: 10.1007/s40140-021-00446-5

PubMed Abstract | CrossRef Full Text | Google Scholar

65. Shehabi Y, Howe B, Bellomo R, Arabi YM, Bailey M, Bass FE, et al. Early sedation with dexmedetomidine in critically ill patients. N Engl J Med. (2019) 380:2506–17. doi: 10.1056/NEJMoa1904710

PubMed Abstract | CrossRef Full Text | Google Scholar

66. Marra A, Ely EW, Pandharipande PP, Patel MB. The ABCDEF bundle in critical care. Crit Care Clin. (2017) 2:225–43. doi: 10.1016/j.ccc.2016.12.005

PubMed Abstract | CrossRef Full Text | Google Scholar

67. Pun BT, Balas MC, Barnes-Daly MA, Thompson JL, Aldrich JM, Barr J, et al. Caring for critically ill patients with the ABCDEF bundle: results of the ICU liberation collaborative in over 15,000 adults. Crit Care Med. (2019) 47:3–14. doi: 10.1097/CCM.0000000000003482

PubMed Abstract | CrossRef Full Text | Google Scholar

68. Walsh TS, Kydonaki K, Antonelli J, Stephen J, Lee RJ, Everingham K, et al. Development and Evaluation of Strategies to Improve Sedation Practice in Intensive Care (DESIST) study investigators. staff education, regular sedation and analgesia quality feedback, and a sedation monitoring technology for improving sedation and analgesia quality for critically ill, mechanically ventilated patients: a cluster randomised trial. Lancet Respir Med. (2016) 4:807–17. doi: 10.1016/S2213-2600(16)30178-3

PubMed Abstract | CrossRef Full Text | Google Scholar

69. SRLF Trial Group. Impact of oversedation prevention in ventilated critically ill patients: a randomized trial-the AWARE study. Ann Intensive Care. (2018) 8:93. doi: 10.1186/s13613-018-0425-3

PubMed Abstract | CrossRef Full Text | Google Scholar

70. Salluh JI, Soares M, Teles JM, Ceraso D, Raimondi N, Nava VS, et al. Delirium Epidemiology in Critical Care (DECCA): an international study. Crit Care. (2010) 14:R210. doi: 10.1186/cc9333

PubMed Abstract | CrossRef Full Text | Google Scholar

71. Krewulak KD, Stelfox HT, Leigh JP, Ely EW, Fiest KM. Incidence and prevalence of delirium subtypes in an adult ICU: a systematic review and meta-analysis. Crit Care Med. (2018) 46:2029–35. doi: 10.1097/CCM.0000000000003402

PubMed Abstract | CrossRef Full Text | Google Scholar

72. Krewulak KD, Stelfox HT, Ely EW, Fiest KM. Risk factors and outcomes among delirium subtypes in adult ICUs: a systematic review. J Crit Care. (2020) 56:257–64. doi: 10.1016/j.jcrc.2020.01.017

PubMed Abstract | CrossRef Full Text | Google Scholar

73. Avelino-Silva TJ, Campora F, Curiati JAE, Jacob-Filho W. Prognostic effects of delirium motor subtypes in hospitalized older adults: a prospective cohort study. PLoS ONE. (2018) 13:e0191092. doi: 10.1371/journal.pone.0191092

PubMed Abstract | CrossRef Full Text | Google Scholar

74. Vourc'h M, Feuillet F, Mahe PJ, Sebille V, Asehnoune K, BACLOREA trial group. Baclofen to prevent agitation in alcohol-addicted patients in the ICU: study protocol for a randomised controlled trial. Trials. (2016) 17:415. doi: 10.1186/s13063-016-1539-2

PubMed Abstract | CrossRef Full Text | Google Scholar

75. Reade MC, Finfer S. Sedation and delirium in the intensive care unit. N Engl J Med. (2014) 370:444–54. doi: 10.1056/NEJMra1208705

PubMed Abstract | CrossRef Full Text | Google Scholar

76. Hsieh SJ, Ely EW, Gong MN. Can intensive care unit delirium be prevented and reduced? lessons learned and future directions. Ann Am Thorac Soc. (2013) 10:648–56. doi: 10.1513/AnnalsATS.201307-232FR

PubMed Abstract | CrossRef Full Text | Google Scholar

77. Van Rompaey B, Elseviers MM, Schuurmans MJ, Shortridge-Baggett LM, Truijen S, Bossaert L. Risk factors for delirium in intensive care patients: a prospective cohort study. Crit Care. (2009) 13:R77. doi: 10.1186/cc7892

PubMed Abstract | CrossRef Full Text | Google Scholar

78. Zaal IJ, Spruyt CF, Peelen LM, van Eijk MM, Wientjes R, Schneider MM, et al. Intensive care unit environment may affect the course of delirium. Intensive Care Med. (2013) 39:481–8. doi: 10.1007/s00134-012-2726-6

PubMed Abstract | CrossRef Full Text | Google Scholar

79. Girard TD, Ware LB, Bernard GR, Pandharipande PP, Thompson JL, Shintani AK, et al. Associations of markers of inflammation and coagulation with delirium during critical illness. Intensive Care Med. (2012) 38:1965–73. doi: 10.1007/s00134-012-2678-x

PubMed Abstract | CrossRef Full Text | Google Scholar

80. Zaal IJ, Devlin JW, Peelen LM, Slooter AJ. A systematic review of risk factors for delirium in the ICU. Crit Care Med. (2015) 43:40–7. doi: 10.1097/CCM.0000000000000625

PubMed Abstract | CrossRef Full Text | Google Scholar

81. Treggiari MM, Romand JA, Yanez ND, Deem SA, Goldberg J, Hudson L, et al. Randomized trial of light versus deep sedation on mental health after critical illness. Crit Care Med. (2009) 37:2527–34. doi: 10.1097/CCM.0b013e3181a5689f

PubMed Abstract | CrossRef Full Text | Google Scholar

82. Sieber FE, Zakriya KJ, Gottschalk A, Blute MR, Lee HB, Rosenberg PB, et al. Sedation depth during spinal anesthesia and the development of postoperative delirium in elderly patients undergoing hip fracture repair. Mayo Clin Proc. (2010) 85:18–26. doi: 10.4065/mcp.2009.0469

PubMed Abstract | CrossRef Full Text | Google Scholar

83. Stephens RJ, Dettmer MR, Roberts BW, Ablordeppey E, Fowler SA, Kollef MH, et al. Practice patterns and outcomes associated with early sedation depth in mechanically ventilated patients: a systematic review and meta-analysis. Crit Care Med. (2018) 46:471–9. doi: 10.1097/CCM.0000000000002885

PubMed Abstract | CrossRef Full Text | Google Scholar

84. van den Boogaard M, Pickkers P, Slooter AJ, Kuiper MA, Spronk PE, van der Voort PH, et al. Development and validation of PRE-DELIRIC (PREdiction of DELIRium in ICu patients) delirium prediction model for intensive care patients: observational multicentre study. BMJ. (2012) 344:e420. doi: 10.1136/bmj.e420

PubMed Abstract | CrossRef Full Text | Google Scholar

85. Wassenaar A, Schoonhoven L, Devlin JW, van Haren FMP, Slooter AJC, Jorens PG, et al. Delirium prediction in the intensive care unit: comparison of two delirium prediction models. Crit Care. (2018) 22:114. doi: 10.1186/s13054-018-2037-6

PubMed Abstract | CrossRef Full Text | Google Scholar

86. van den Boogaard M, Schoonhoven L, Maseda E, Plowright C, Jones C, Luetz A, et al. Recalibration of the delirium prediction model for ICU patients (PRE-DELIRIC): a multinational observational study. Intensive Care Med. (2014) 40:361–9. doi: 10.1007/s00134-013-3202-7

PubMed Abstract | CrossRef Full Text | Google Scholar

87. Linkaite G, Riauka M, Bunevičiute I, Vosylius S. Evaluation of PRE-DELIRIC (PREdiction of DELIRium in ICu patients) delirium prediction model for the patients in the intensive care unit. Acta Med Litu. (2018) 25:14–22. doi: 10.6001/actamedica.v25i1.3699

PubMed Abstract | CrossRef Full Text | Google Scholar

Keywords: mechanical ventilation, suboptimal sedation, patient tolerability, assessment tools, sedation depth

Citation: Wang T, Zhou D, Zhang Z and Ma P (2021) Tools Are Needed to Promote Sedation Practices for Mechanically Ventilated Patients. Front. Med. 8:744297. doi: 10.3389/fmed.2021.744297

Received: 20 July 2021; Accepted: 20 October 2021;
Published: 12 November 2021.

Edited by:

Ata Murat Kaynar, University of Pittsburgh, United States

Reviewed by:

Abele Donati, Marche Polytechnic University, Italy
Francesco Forfori, University of Pisa, Italy

Copyright © 2021 Wang, Zhou, Zhang and Ma. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Penglin Ma, mapenglin1@163.com

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