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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 II Pattern of Unexpected Hospital Death (CO2 Narcosis).
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Figure 2: Type II Pattern of Unexpected Hospital Death (CO2 Narcosis).

Mentions: So in summary, (as illustrated in figure 2) the Type II PUHD comprises first a fall in Ve (the amount of air moved in or out of the lungs per minute) due to progressive falls in tidal volume and/or respiratory rate, both unpredictably variable. This pattern continues to devolve as the body, failing to rid itself of its excess CO2 mounting from inadequate ventilation, begins to suffer from the effects of respiratory acidosis and CO2 narcosis. As the PaCO2 rises higher and higher, it competes with oxygen for space at the alveolar interface, seen reasonably early as a falling SPO2 in patients breathing room air (see figure 2). Because any acute rise in PaCO2 is also associated with falls in pH that shift the oxyhemoglobin disassociation curve to its right, monitored SPO2 declines are magnified by these pH/PaCO2/PaO2 shift effects on the SPO2. However, patients provided with supplemental oxygen can maintain SPO2 values in the 90-100% range with significantly advanced hypercarbia (see figure 2 dotted line), often the first hint of a problem coming from being discovered unarousable in near respiratory arrest or worse. Putting all this in a context of reliability and DFGP capability for early detection and rescue using our magical 90% threshold, pulse oximetry is moderately sensitive only when patients breathe room air, and extremely insensitive when supplemental oxygen is being deployed. Combining sedation scoring and threshold capnometry with pulse oximetry has been advocated by some experts, and this combination appears capable of providing an effective way to detect pure Type II PUHD [70,71], although such additions would be costly and less effective than imagined because of confounding circumstances. What confounds any reliable early detection of Type II patterns (Type I as well) by all threshold applications is our third PUHD, a clinically subtle yet exceedingly common process that only occurs during sleep, and just like the others is not amenable to reliable early detection with any form of threshold monitoring. Likewise, it remains indistinguishable by even the most meticulous sedation scoring. This Type III PUHD, which has been associated with silent, sudden death during sleep, is largely unknown to most clinicians, yet burdens the general care environments with extraordinarily common clinical and statistical mischief regarding any conventional attempts to reliably recognize it and its co-morbid associations. We'll have a look at this third PUHD now.


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

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

Type II Pattern of Unexpected Hospital Death (CO2 Narcosis).
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 2: Type II Pattern of Unexpected Hospital Death (CO2 Narcosis).
Mentions: So in summary, (as illustrated in figure 2) the Type II PUHD comprises first a fall in Ve (the amount of air moved in or out of the lungs per minute) due to progressive falls in tidal volume and/or respiratory rate, both unpredictably variable. This pattern continues to devolve as the body, failing to rid itself of its excess CO2 mounting from inadequate ventilation, begins to suffer from the effects of respiratory acidosis and CO2 narcosis. As the PaCO2 rises higher and higher, it competes with oxygen for space at the alveolar interface, seen reasonably early as a falling SPO2 in patients breathing room air (see figure 2). Because any acute rise in PaCO2 is also associated with falls in pH that shift the oxyhemoglobin disassociation curve to its right, monitored SPO2 declines are magnified by these pH/PaCO2/PaO2 shift effects on the SPO2. However, patients provided with supplemental oxygen can maintain SPO2 values in the 90-100% range with significantly advanced hypercarbia (see figure 2 dotted line), often the first hint of a problem coming from being discovered unarousable in near respiratory arrest or worse. Putting all this in a context of reliability and DFGP capability for early detection and rescue using our magical 90% threshold, pulse oximetry is moderately sensitive only when patients breathe room air, and extremely insensitive when supplemental oxygen is being deployed. Combining sedation scoring and threshold capnometry with pulse oximetry has been advocated by some experts, and this combination appears capable of providing an effective way to detect pure Type II PUHD [70,71], although such additions would be costly and less effective than imagined because of confounding circumstances. What confounds any reliable early detection of Type II patterns (Type I as well) by all threshold applications is our third PUHD, a clinically subtle yet exceedingly common process that only occurs during sleep, and just like the others is not amenable to reliable early detection with any form of threshold monitoring. Likewise, it remains indistinguishable by even the most meticulous sedation scoring. This Type III PUHD, which has been associated with silent, sudden death during sleep, is largely unknown to most clinicians, yet burdens the general care environments with extraordinarily common clinical and statistical mischief regarding any conventional attempts to reliably recognize it and its co-morbid associations. We'll have a look at this third PUHD now.

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