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Patterns of unexpected in-hospital deaths: a root cause analysis.

Lynn LA, Curry JP - Patient Saf Surg (2011)

Bottom Line: In contrast to the simplicity of the numeric threshold breach method of generating alerts, the actual patterns of evolving death are complex and do not share common features until near death.These patterns are too complex for early detection by any unifying numeric threshold.New methods and technologies which detect and identify the actual patterns of evolving death should be investigated.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Anesthesiology and Perioperative Care, Hoag Memorial Hospital Presbyterian, Newport Beach, CA 92658 USA. pcurry@hoaghospital.org.

ABSTRACT

Background: Respiratory alarm monitoring and rapid response team alerts on hospital general floors are based on detection of simple numeric threshold breaches. Although some uncontrolled observation trials in select patient populations have been encouraging, randomized controlled trials suggest that this simplistic approach may not reduce the unexpected death rate in this complex environment. The purpose of this review is to examine the history and scientific basis for threshold alarms and to compare thresholds with the actual pathophysiologic patterns of evolving death which must be timely detected.

Methods: The Pubmed database was searched for articles relating to methods for triggering rapid response teams and respiratory alarms and these were contrasted with the fundamental timed pathophysiologic patterns of death which evolve due to sepsis, congestive heart failure, pulmonary embolism, hypoventilation, narcotic overdose, and sleep apnea.

Results: In contrast to the simplicity of the numeric threshold breach method of generating alerts, the actual patterns of evolving death are complex and do not share common features until near death. On hospital general floors, unexpected clinical instability leading to death often progresses along three distinct patterns which can be designated as Types I, II and III. Type I is a pattern comprised of hyperventilation compensated respiratory failure typical of congestive heart failure and sepsis. Here, early hyperventilation and respiratory alkalosis can conceal the onset of instability. Type II is the pattern of classic CO2 narcosis. Type III occurs only during sleep and is a pattern of ventilation and SPO2 cycling caused by instability of ventilation and/or upper airway control followed by precipitous and fatal oxygen desaturation if arousal failure is induced by narcotics and/or sedation.

Conclusion: The traditional threshold breach method of detecting instability on hospital wards was not scientifically derived; explaining the failure of threshold based monitoring and rapid response team activation in randomized trials. Furthermore, the thresholds themselves are arbitrary and capricious. There are three common fundamental pathophysiologic patterns of unexpected hospital death. These patterns are too complex for early detection by any unifying numeric threshold. New methods and technologies which detect and identify the actual patterns of evolving death should be investigated.

No MeSH data available.


Related in: MedlinePlus

Type III SPO2 Cycling Pattern ("Sawtooth") Preceding Arousal Failure.
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Figure 5: Type III SPO2 Cycling Pattern ("Sawtooth") Preceding Arousal Failure.

Mentions: This Type III pattern architecture is comprised of repetitive reductions in airflow and SPO2 from sleep related cycling collapses of the upper airway [72,73]. This cycling figure 4, collapsing, and reopening of the upper airway produces a typical and very distinctive pattern of signal clusters shown in figure 5, that is reliably acquired only by higher resolution pulse oximetry (unlike many conventional pulse oximetry systems in use on hospital floors today). How this unique SPO2 pattern is produced will be discussed in a moment, but more contemporary bench research on how narcotics interact with our neuroaxis corroborates these important, newly appreciated patterns and their implied threats that include being capable of inducing a de novo form of sleep disordered breathing with repetitive airflow reductions very similar to that found in obstructive sleep apnea populations.


Patterns of unexpected in-hospital deaths: a root cause analysis.

Lynn LA, Curry JP - Patient Saf Surg (2011)

Type III SPO2 Cycling Pattern ("Sawtooth") Preceding Arousal Failure.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3045877&req=5

Figure 5: Type III SPO2 Cycling Pattern ("Sawtooth") Preceding Arousal Failure.
Mentions: This Type III pattern architecture is comprised of repetitive reductions in airflow and SPO2 from sleep related cycling collapses of the upper airway [72,73]. This cycling figure 4, collapsing, and reopening of the upper airway produces a typical and very distinctive pattern of signal clusters shown in figure 5, that is reliably acquired only by higher resolution pulse oximetry (unlike many conventional pulse oximetry systems in use on hospital floors today). How this unique SPO2 pattern is produced will be discussed in a moment, but more contemporary bench research on how narcotics interact with our neuroaxis corroborates these important, newly appreciated patterns and their implied threats that include being capable of inducing a de novo form of sleep disordered breathing with repetitive airflow reductions very similar to that found in obstructive sleep apnea populations.

Bottom Line: In contrast to the simplicity of the numeric threshold breach method of generating alerts, the actual patterns of evolving death are complex and do not share common features until near death.These patterns are too complex for early detection by any unifying numeric threshold.New methods and technologies which detect and identify the actual patterns of evolving death should be investigated.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Anesthesiology and Perioperative Care, Hoag Memorial Hospital Presbyterian, Newport Beach, CA 92658 USA. pcurry@hoaghospital.org.

ABSTRACT

Background: Respiratory alarm monitoring and rapid response team alerts on hospital general floors are based on detection of simple numeric threshold breaches. Although some uncontrolled observation trials in select patient populations have been encouraging, randomized controlled trials suggest that this simplistic approach may not reduce the unexpected death rate in this complex environment. The purpose of this review is to examine the history and scientific basis for threshold alarms and to compare thresholds with the actual pathophysiologic patterns of evolving death which must be timely detected.

Methods: The Pubmed database was searched for articles relating to methods for triggering rapid response teams and respiratory alarms and these were contrasted with the fundamental timed pathophysiologic patterns of death which evolve due to sepsis, congestive heart failure, pulmonary embolism, hypoventilation, narcotic overdose, and sleep apnea.

Results: In contrast to the simplicity of the numeric threshold breach method of generating alerts, the actual patterns of evolving death are complex and do not share common features until near death. On hospital general floors, unexpected clinical instability leading to death often progresses along three distinct patterns which can be designated as Types I, II and III. Type I is a pattern comprised of hyperventilation compensated respiratory failure typical of congestive heart failure and sepsis. Here, early hyperventilation and respiratory alkalosis can conceal the onset of instability. Type II is the pattern of classic CO2 narcosis. Type III occurs only during sleep and is a pattern of ventilation and SPO2 cycling caused by instability of ventilation and/or upper airway control followed by precipitous and fatal oxygen desaturation if arousal failure is induced by narcotics and/or sedation.

Conclusion: The traditional threshold breach method of detecting instability on hospital wards was not scientifically derived; explaining the failure of threshold based monitoring and rapid response team activation in randomized trials. Furthermore, the thresholds themselves are arbitrary and capricious. There are three common fundamental pathophysiologic patterns of unexpected hospital death. These patterns are too complex for early detection by any unifying numeric threshold. New methods and technologies which detect and identify the actual patterns of evolving death should be investigated.

No MeSH data available.


Related in: MedlinePlus