Clinical Performance of an Interactive Clinical Decision Support System for Assessment of Plasma Lactate in Hospitalized Patients with Organ Dysfunction

Robert A. Raschke, MD MS

Hargobind Khurana, MD 

Huw Owen-Reece, MBBS 

Robert H. Groves Jr, MD

Steven C. Curry, MD

Mary Martin, PharmD

Brenda Stoffer, RN BSN

Banner University Medical Center Phoenix

Phoenix, AZ USA

Abstract

Purpose: Elevated plasma lactate concentration can be a useful measure of tissue hypo-perfusion in acutely deteriorating patients, focusing attention on the need for urgent resuscitation. But lactate is not always assessed in a timely fashion in patients who have deteriorating vital signs. We hypothesized that an electronic medical record (EMR)-based decision support system could interact with clinicians to prompt assessment of plasma lactate in appropriate clinical situations in order to risk stratify a population of inpatients and identify those who are acutely deteriorating in real-time.

Methods: All adult patients admitted to our hospital over a three month period were monitored by an EMR-based lactate decision support system (lactate DSS) programmed to detect patients exhibiting acute organ dysfunction and engage the clinician in the decision to order a plasma lactate concentration. Inpatient mortality was determined for the five risk categories that this system generated, and chart review was performed on a high-risk subgroup to describe the spectrum of bedside events that triggered the system logic.

Results: The lactate DSS segregated inpatients into five strata with mortality rates of 0.8% (95%CI:0.6-1.0%); 2.7% (95%CI:1.0-4.4%); 7.9% (95%CI: 6.0-10.1%), 13.0% (95%CI: 9.0-17.8%) and 42.1% (95%CI: 32.0-52.4%), achieving a discriminant accuracy of 80% (95%CI:76-84%) by AUROC for predicting inpatient mortality. Classification into the two highest risk strata had a positive predictive value for detecting acute life-threatening clinical events of 54% (95%CI: 41.5-66.5%).

Conclusions: Our lactate decision support system is different than previously-described computerized “early warning systems”, because it engages the clinician in decision-making and incorporates clinical judgment in risk stratification. Our system has favorable operating characteristics for the prediction of inpatient mortality and real-time detection of acute life-threatening deterioration.

Introduction

Over 700,000 deaths occur annually in U.S. hospitals (1). Sepsis accounts directly for 37% and indirectly for 56% of these deaths (2). Other common causes of inpatient mortality such as acute hemorrhage and venous thromboembolism (3) share certain early clinical findings with sepsis, in that they may present with deterioration of vital signs and biochemical variables before life-threatening manifestations become obvious (4). Recognition of these findings provides an opportunity for early intervention, which has been shown to improve mortality (5,6). Studies have shown that failure to rapidly recognize acute clinical deterioration is one of the most common root causes of preventable inpatient mortality (4,8).

Early warning systems (EWSs) are a type of clinical decision support system (CDSS) utilized to provide surveillance of hospitalized patients in order to alert clinicians when a patient has findings associated with acute deterioration (19). These typically monitor for abnormal vital signs or laboratory evidence of organ dysfunction, but have included many other types of clinical and laboratory variables (20-23). Modern EWSs utilize logistic regression to weight up to 36 different independent variables and yield highly stratified risk scores (24-26).

We had previous experience developing a simple EWS that triggered when at least two systemic inflammatory response syndrome (SIRS) criteria plus at least one of 14 acute organ dysfunction (OD) parameters was detected. Although this system references SIRS it was found to be nonspecific for sepsis (27), and was subsequently employed in our healthcare system to identify patients deteriorating in real-time regardless of the cause. Subsequent research showed that our SIRS/OD alert system was triggered during the course of 19% of admissions, and that patients who triggered the alert had an odds ratio of 30.1 (95% CI: 26.1-34.5) for inpatient mortality (28). We hypothesized that this SIRS/OD alert system could be used to identify high risk patients who might be further risk-stratified by obtaining a plasma lactate concentration.

Elevated plasma lactate concentration is a particularly useful biochemical marker of acute decompensation. Hyperlactemia is pathophysiologically associated with acute tissue hypoperfusion, and clinically associated with organ dysfunction and mortality (7-11). Hyperlactemia is also associated with the need for urgent clinical interventions such as transfusion and urgent surgery in trauma patients (13,14), and resuscitation of medical patients with sepsis or other life-threatening illnesses (5,15). Lactate assessment is integral to the definition of sepsis (7,16), and an essential component of the Surviving Sepsis Campaign sepsis resuscitation bundle (6). Lactate assessment is integral to achieving sepsis bundle compliance as defined by the Centers for Medicare and Medicaid Services (CMS), which has mandated participating hospitals to report as a measure of quality of care. However, lactate is only ordered about half the time that it ought to be in patients with severe sepsis and septic shock (17,18). To our knowledge, only one previously reported EWS incorporates lactate assessment (29), but this system passively utilized lactate concentration results obtained on admission from the emergency room and was not used for surveillance during hospitalization.

We sought to use our SIRS/OD alert system to actively trigger lactate assessment to identify patients suffering from sepsis or any other life-threatening disease process requiring immediate intervention during hospitalization. We hypothesized that the resulting “lactate decision support system” (lactate DSS) would provide inpatient mortality risk stratification with high discriminant accuracy, and detect acute life-threatening events with high positive predictive value compared to contemporary EWSs.

A lactate DSS with these favorable characteristics could theoretically be used to guide emergent interventions in an effort to save lives, although it was not our aim at this time to perform an interventional trial. The specific aims of this study were to pilot an interactive lactate DSS in our healthcare system, and to calculate its discriminant accuracy for mortality risk stratification, and its positive predictive value as a real-time early warning system.

Methods

We prospectively studied a cohort of all adult inpatients admitted to Banner-University Medical Center - Phoenix, a 650-bed academic hospital in Phoenix Arizona, during the first quarter of 2014. Our research was part of an ongoing system-level patient safety project and was approved by our Institutional Review Board.

The decision support logic was developed at Banner Health using Discern Expert^® (Cerner Corporation, North Kansas City MO, USA). The lactate decision support system (lactate DSS) monitored each patient in our EMR for vital signs and laboratory results consistent with SIRS and organ dysfunction, using criteria derived from the standard definition of sepsis (5-7) (Table 1).

Table 1. Lactate DSS trigger logic

If criteria for SIRS and organ dysfunction overlapped in any eight-hour window, the lactate DSS was triggered to respond. An electronic notification was generated to the patient’s nurse and physician alerting them to the possibility of acute clinical deterioration suggested by SIRS and organ dysfunction, and recommending evaluation and resuscitation if appropriate. Decision support included automatic generation of an order for a STAT plasma lactate if one was not previously ordered by the clinician, interactively prompting the clinician to cancel it if they felt it was unnecessary.

Adult admissions during the three-month study period and subsequent inpatient mortality were enumerated using our hospital’s general financial database: MedSeries4^® (Siemens Corporation, Washington DC). Although some patients triggered the lactate DSS multiple times over the course of their hospital stay, only the first trigger event was included in our analysis.

Inpatient mortality rates with ninety-five percent confidence intervals were calculated for each of five subgroups: 1) patients who did not exhibit SIRS and organ dysfunction during their hospitalization and therefore did not trigger a lactate DSS response; 2) patients who triggered a lactate DSS response, for whom a DSS-generated lactate order was cancelled by their clinician; 3) patients who triggered the lactate DSS and had a lactate concentration <2.2 mmol/L (normal for our laboratory); 4) patients who triggered the lactate DSS and had an elevated lactate of 2.2-3.9 mmol/L; and 5) patients who triggered the lactate DSS and had a highly elevated lactate >4.0 mmol/L.

It was our hypothesis that mortality in patients who triggered the lactate DSS logic would be equivalent whether the clinician chose not to cancel a DSS-generated lactate order, or the clinician had already entered a lactate order themselves. Therefore, we classified patients into the subgroups above regardless of whether their lactate order was DSS-generated or entered independently by the clinician. In order to confirm the validity of this hypothesis, the mortality rate of all patients with any lactate concentration result (the sum of groups 3, 4 and 5 above), and mortality rates within each lactate concentration strata, were separately analyzed to determine if mortality depended on the method of lactate order entry.

Stratified likelihood ratios and the area under the receiver operating curve (AUROC) generated using the five subgroups described above were calculated to determine the discriminant accuracy of the lactate DSS for the outcome of inpatient mortality.

A subgroup analysis was performed of all study patients with an elevated lactate >2.2 mmol/L (above the upper limit of normal range at our laboratory) detected by a DSS-generated lactate order during the first six weeks of the study. These patients’ charts were reviewed in order to characterize the acute clinical events that triggered a lactate DSS response in this subgroup of patients. A physician researcher reviewed progress notes, laboratory and microbiology results at the time of system activation, and for 72 hours afterwards to make this determination. Patient were determined to be suffering an acute life-threatening clinical event if a new-onset or rapidly-progressive disease process was present at the time the lactate DSS was triggered that required emergent treatment with any one of the following: >1 L intravenous fluid resuscitation, vasopressor infusion, >2 units of packed red blood cell transfusion, endotracheal intubation, advanced cardiac life support, or emergent surgical intervention. Minor clinical events included any diagnosis that required initiation of treatment not included in the definition of acute life threatening clinical events above. False alerts were said to have occurred when no evidence was found that the patient was clinically deteriorating in temporal relationship to lactate DSS activation, or within 72 hours. The positive predictive value of the system was calculated for the real-time detection of acute life-threatening clinical events. Microsoft Research and VassarStats^® on-line statistical software were used for statistical calculations.

Results

8,867 adult patients were admitted during our three-month study period. One hundred and ninety-six of 8867 patients (2.2% 95%CI: 1.9-2.5%) died while in the hospital. Seventy percent (138/196) of these inpatient deaths occurred in the 16% (1400/8867) of patients who triggered a lactate DSS response.

Four hundred seventy-nine of 1400 patients who triggered the lactate DSS already had a clinician-ordered lactate. A DSS-generated order for plasma lactate was entered for the remaining 921 patients, but clinicians cancelled 337 of these. DSS-generated lactate orders were resulted for the remaining 584 patients. These patients were merged with 479 patients who had clinician –ordered lactates for the purposes of further analysis after confirmation that mortality did not depend on how the lactate was ordered (Figure 1).

Figure 1. Stratification of inpatients into five subgroups by the lactate DSS.

Patients who did not trigger the lactate DSS logic (n=7467) had a mortality rate of 0.78% (95%CI: 0.58-0.98). Patients who triggered the lactate DSS and for whom a DSS-generated lactate order was cancelled by the clinician (n=337) had mortality of 2.7% (95%CI: 1.0-4.4%). Patients who triggered the lactate DSS and had a lactate concentration in the normal range (< 2.2 mmol/L; n=721) had mortality of 7.9% (95%CI: 6.0-10.1%), and those with elevated lactates of 2.2-3.9 and >4.0 mmol/L (n=247 and n=95) had mortality rates of 13.0% (95%CI: 9.0-17.8%) and 42.1% (95%CI: 32.0-52.4%) respectively (Figure 2).

Figure 2. Inpatient mortality rates (Y-axis: Percent mortality) with 95% confidence intervals for five subgroups of patients stratified by lactate DSS.

The mortality of patients who triggered a lactate DSS response and for whom a lactate concentration was resulted did not depend on whether the order was DSS-generated or entered by the clinician (13.0% versus 12.1% (P=0.71)). Clinician-entered lactate orders were closely temporally related to the onset of organ dysfunction, preceding lactate DSS triggering by < six hours in 52%, <12 hours in 64%, and <24 hours in 75% of cases. Likelihood ratios for mortality in subgroups of patients with lactates <2.2, 2.2-3.9, and >4.0 mmol/L were 6.1 (95%CI: 5.4-6.9), 11.8 (95%CI: 9.5-14.7), and 32.4 (95%CI: 22.0-47.1) respectively.

Five-strata of mortality risk generated by the lactate DSS yielded an AUROC of 0.80 (95% CI: 0.76-0.84) (Figure 3).

Figure 3. Receiver-operating characteristic curve for mortality risk stratification by the lactate DSS.  

Focused chart review was performed on 61 patients who had elevated lactate (>2.2 mmol/L) detected by a DSS-generated lactate order. Thirty-three (54%) were experiencing acute life-threatening clinical events at the time the lactate DSS was triggered. These included 18 episodes of sepsis. Sepsis was due to pneumonia in nine patients, catheter-associated blood stream infection, bowel perforation, cellulitis, ascending cholangitis, endocarditis, liver abscess, cholecystitis, perianal abscess, or an unidentified source. Other acute life threatening clinical events included five cases of acute gastrointestinal hemorrhage, three of acute respiratory failure, and one each of post-operative bleeding, cardiogenic shock, acute liver failure, retroperitoneal bleeding, acute myocardial infarction, subdural hematoma, and cerebral dural sinus thrombosis. Twenty-one (64%) of these events occurred outside the intensive care unit. The positive predictive value of the detection of SIRS, organ dysfunction and elevated lactate by the lactate DSS for acute life-threatening clinical events was 54% (95%CI: 41.5-66.5%).

Ten minor clinical events included anemia, atrial fibrillation, post-op third spacing, transient mild hypotension associated with end stage liver disease, sedation related to narcotics, and dialysis disequilibrium. There were 18 false alerts among patients with SIRS, organ dysfunction and elevated lactate detected by the system. (18/61=29%).

Discussion

Our lactate DSS effectively segregated a population of adult inpatients into five subgroups with increasing inpatient mortality. Clinician engagement was critically important in achieving this result. About a quarter (337/1400) of patients who triggered the lactate DSS (simultaneously exhibited SIRS and organ dysfunction) were doing well enough in their clinician’s opinion that the DSS-generated lactate order was cancelled. Clinicians exercised good judgment in this regard, identifying a subgroup of patients with inpatient mortality rate not significantly higher than the overall mortality of all patients admitted during the study. This supports our decision to incorporate clinician judgment in our risk stratification method.

Approximately half of patients (721/1400) who triggered the lactate DSS turned out to have a normal lactate concentration, yet suffered inpatient mortality ten-times higher than patients who did not trigger the system. This likely represents the independent association between SIRS and organ dysfunction with the risk for mortality (27, 31,32).

One hundred twenty-nine patients over 3 months (14.5 per 1000 patient admissions) triggered the lactate DSS and were found to have an elevated lactate concentration because of a DSS-generated lactate order. These patients had >50% probability of experiencing an acute life-threatening clinical event at the time the lactate DSS was triggered, and subsequently suffered 50% inpatient mortality.

Our lactate DSS is consistent with the new definition of sepsis because it uses organ dysfunction in addition to SIRS criteria (7). As stated in the new definition of sepsis, “Nonspecific SIRS criteria such as pyrexia or neutrophilia will continue to aid in the general diagnosis of infection” (7). Although these criteria are nonspecific, they appear to be relatively sensitive for sepsis (7,27). Our lactate DSS has excellent discriminant accuracy for predicting inpatient mortality (AUROC=0.80). It is comparable to other criteria such SOFA (AUROC = 0.74) and the Logistic Organ Dysfunction System (AUROC=0.75).The five strata into which it segregates patients could further translate into a decision support-guided treatment protocol, directing appropriate real-time interventions such as those proposed in Table 2.

Table 2. Proposed stratified clinical response to lactate DSS.

* Our data indicate that RRT activation would occur about twice a week at our hospital.

Our lactate DSS is different than EWSs because it specifically prompts assessment of plasma lactate in patients exhibiting SIRS and organ dysfunction, rather than simply generating a warning. But a discussion of the operating characteristics of previously reported EWSs is useful for purposes of comparison. A review of 33 EWSs has reported AUROCs ranging from 0.66-0.78 (19). Several more recent EWSs reported AUROCs of 0.81-0.88 (23,24,26,33), but AUROC comparisons are confounded by lack of consensus regarding which clinical outcome to analyze. Authors have variously chosen 24-hour mortality, ICU transfer, and cardiac arrest, among other outcomes (20,23,24). Many EWSs yield highly stratified results, which may increase the AUROC by adding detail to the shape of the ROC curve, but this will not improve clinical discrimination unless each resulting strata has a distinct clinical response. If a EWS is simply used to activate a rapid response team (RRT), the clinically-achievable discriminant accuracy is best described by a polygonal AUROC derived from a single cutoff with two resulting strata (activate the RRT, or do not activate the RRT). This two-strata AUROC will invariably be lower than the highly stratified AUROC that many authors report (23,24,26,33). Our AUROC analysis is based on 5 strata, each of which could reasonably trigger a distinct clinical response (Table 2).

Our lactate decision support system has a positive predictive value (PPV) for acute life-threatening clinical events that is superior to that of our previous “sepsis alert” (27) and to those reported in several reviews of EWSs. One review of 39 EWSs reported PPVs ranging from 13.5-26.1% (34), and another review of 25 systems reported a median PPV of 36.7% with interquartile range 29.3-43.8% (34). PPV was not reported for several of the most elegant and well-studied EWSs (22,23,25,32). From the perspective of bedside clinicians and rapid response team members, the efficiency of an alert system is strongly influenced by the PPV, because a poor PPV translates to frequent false alerts. The PPV is of particularly concern when the pretest probability of the outcome of interest is low, as in the case of inpatient mortality (2% at our hospital). Bayes theory indicates that a test with relatively good AUROC will have a poor PPV if the pretest probability is low enough.

Our study has several limitations. Our sample size is small compared to many contemporary EWS studies. We did not have the resources to perform focused chart reviews on all study patients and therefore had to limit individual case analysis to a subgroup of study patients. Our simple treatment of vital sign abnormalities as markers of SIRS is not as elaborate as in many EWSs. Our study is only hypothesis-generating, whereas several EWSs are well validated (25,32). We cannot provide data on how our alert might change bedside interventions by clinicians. To our knowledge, no study to date has proven that using a computerized decision support system or EWS to trigger rapid clinical intervention actually improves patient outcomes.

Conclusions

We developed an automated decision-support system that prompts assessment of plasma lactate concentration in patients exhibiting SIRS and organ dysfunction. Our lactate decision support system is different than previously-described EWSs because it engages the clinician in decision-making and incorporates clinical judgment into risk stratification. This system has favorable operating characteristics for the prediction of inpatient mortality and for detecting acute life-threatening events in real time. We have proposed a stratified clinical response based on classification of patients into five subgroups by this system that requires further testing, but our current study was not designed to demonstrate a benefit on clinical outcomes. Our lactate DSS has the potential to improve sepsis bundle compliance by helping clinicians appropriately order lactate concentrations in patients deteriorating due to the onset of sepsis – a hypothesis we are currently investigating. It also has potential for easy generalizability, particularly to other healthcare systems that share the same EMR as ours, but requires further refinement and validation.

Author Contributions

All authors were involved in conceptualization, design and implementation of the decision support system described in this manuscript, and in preparation of the manuscript, and all approve of the content of the manuscript and vouch for the validity of the data. We list below additional contributions from several of the authors:

RAR: data analysis and interpretation, main author of initial draft of the manuscript.

HOW: data analysis and interpretation, contribution to discussion/conclusions

HK: directly in charge of design and pilot implementation team for the decision support system, data interpretation, contribution to discussion, conclusions

RHG: data interpretation, contribution to discussion, conclusions

SCC: data analysis and interpretation, contribution to discussion, conclusions. Manuscript editing.

MM: data collection and analysis

BS: data collection and analysis

References

1. Center for Disease Control. Trends in inpatient hospital deaths: National Hospital Discharge Survey: 2000:2010. NCHS Data Brief 118; 2013. [PubMed]
2. Liu V, Escobar G, Greene JD, Soule J, et al. Hospital deaths in patients with sepsis from two independent cohorts. JAMA. 2014;312:90-92. [CrossRef] [PubMed]
3. Nichols L, Chew B. Causes of sudden unexpected death of adult hospital patients. J Hosp Med. 2012;7:706-8. [CrossRef] [PubMed]
4. McGloin H, Adam SK, Singer M. Unexpected deaths and referrals to intensive care of patients on general wards. Are some cases potentially avoidable? J R Coll Physicians Lond. 1999;33:255-9. [PubMed]
5. Rivers E, Nguyen B, Havstad S, Ressler J, et al. Early goal-directed therapy in the treatment of severe sepsis and septic shock. NEJM. 2001;345:1368-77. [CrossRef] [PubMed]
6. Dellinger RP, Levy MM, Rhodes A, Annane D, et al. Surviving sepsis campaign: International guidelines for management of severe sepsis and septic shock: 2012. Crit Care Med. 2013;41:580. [CrossRef] [PubMed]
7. Singer M, Deutschman CS, Seymour CW, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016 Feb 23;315(8):801-10. [CrossRef] [PubMed]
8. National Patient Safety Agency. Safer care for the acutely ill patient: learning from serious incidents. 2007;Report # PSO/5. Available online at: http://www.nrls.npsa.nhs.uk/resources/?EntryId45=59828 (accessed 5/9/17).
9. Gultepe E, Green JP, Nguyen H, Adams J, et al. From vital signs to clinical outcomes for patients with sepsis: a machine learning basis for a clinical decision support system. J Am Med Inform Assoc. 2014;21:315-325. [CrossRef] [PubMed]
10. Jansen TC, van Bommel J, Woodward R, Mulder PG, Bakker J. Association between blood lactate levels, sequential organ failure assessment sub-scores, and 28-day mortality during early and late intensive care unit stay: a retrospective observational study. Crit Care Med. 2009;37:2369-74. [CrossRef] [PubMed]
11. Bakker J, Gris P, Coffernils M, Kahn RJ, Vincent JL. Serial blood lactate levels can predict the development of multiple organ failure following septic shock. Am J Surg. 1996;171:221-6. [CrossRef] [PubMed]
12. Jansen TC, van Bommel J, Bakker J. Blood lactate monitoring in critically ill patients: a systematic health technology assessment. Crit Care Med. 2009;37:2827-39. [CrossRef] [PubMed]
13. Guyette F, Suffoletto B, Castillo JL, Quintero J, Callaway C, Puyana JC. Prehospital serum lactate as a predictor of outcomes in trauma patients: A retrospective observational study. J Trauma. 2011;70:782–6. [CrossRef] [PubMed]
14. Vandromme MJ, Griffin RL, Weinberg JA, Rue LW 3rd, Kerby JD. Lactate is a better predictor than systolic blood pressure for determining blood requirement and mortality: Could prehospital measures improve trauma triage? J Am Coll Surg. 2010;210:861–9. [CrossRef] [PubMed]
15. Jansen TC, van Bommel J, Schoonderbeek FJ, Sleeswijk Visser SL, et al. Early lactate-guided therapy in intensive care unit patients: a multicenter, open-label, randomized controlled trial. Am J Respir Crit Care Med. 2010;182:752-61. [CrossRef] [PubMed]
16. Levy MM, Fink MP, Marshall JC, Abraham E, et al. International Sepsis Definitions Conference. Crit Care Med. 2003;31(4):1250. [CrossRef] [PubMed]
17. Gao R, Melody T, Daniels DF, Giles S and Fox S. The impact of compliance with 6-hour and 24-hour sepsis bundles on hospital mortality in patients with severe sepsis: a prospective observational study. Crit Care. 2005;9:R764–R770. [CrossRef] [PubMed]
18. Levy MM, Dellinger RP, Townsend SR, et al. The Surviving Sepsis Campaign: results of an international guideline-based performance improvement program targeting severe sepsis. Intensive Care Med. 2010; 36: 222–31. [CrossRef] [PubMed]
19. Smith GB, Prytherch DR, Schmidt PE, Featherstone PI. Review and performance evaluation of aggregate weighted "track and trigger" systems. Resuscitation. 2008;77:170-9. [CrossRef] [PubMed]
20. Hodgetts TJ, Kenward G, Vlachonikolis IG, Payne S, Castle N. The identification of risk factors for cardiac arrest and formulation of activation criteria to alert a medical emergency team. Resuscitation. 2002;54:125-31. [CrossRef] [PubMed]
21. Kho A, Rotz D, Alrahi K, Cardenas W, et al. Utility of commonly captured data from an HER to identify hospitalized patients at risk for clinical deterioration. AMIA 2007 symposium proceedings. 404-8.[CrossRef]
22. Howell MD, Donnino M, Clardy P, Talmor D, Shapiro NI. Occult hypoperfusion and mortality in patients with suspected infection. Intensive Care Med. 2007;33:1892-9. [CrossRef] [PubMed]
23. Escobar GJ, LaGuardia JC, Turk BJ, Ragins A, et al. Early detection of impending physiological deterioration among patients who are not in intensive care: Development of predictive models using data from an automated electronic medical record. J Hosp Med. 2012;7:388-95. [CrossRef] [PubMed]
24. Prytherch DR, Smith GB, Schmidt P, Featherstone PI. ViEWS – towards a national early warning score for detecting adult inpatient deterioration. Resuscitation. 2010;81:932-7. [CrossRef] [PubMed]
25. Bailey TC, Yixin C, Mao Y, Lu C, et al. A trial of a real-time alert for clinical deterioration in patients hospitalized on general medical wards. J Hosp Med. 2013;8:236-42. [CrossRef] [PubMed]
26. Churpek MM, Yuen TC, Winslow C, Robicsek AA, et al. Multicenter development and validation of a risk stratification tool for ward patients. Am J Resp Crit Care Med. 2014;190:649-55. [CrossRef] [PubMed]
27. Raschke RA, Owen-Reece H, Khurana H, Groves RH Jr, et al. Clinical performance of an automated systemic inflammatory response syndrome (SIRS)/organ dysfunction alert: a system-based patient safety project. Southwest J Pulm Crit Care. 2014;9:223-9. [CrossRef]
28. Khurana, H, Groves RH, Simons MP, Martin M, Stoffer B, et al. Real-time automated continuous sampling of electronic medical records predicts hospital mortality. Am J Med. 2016 Jul;129(7):688-698.e2. [CrossRef] [PubMed]
29. Jo S, Lee JB, Jin YH, Jeong TO, et al. Modified early warning score with rapid lactate level in critically ill medical patients: the ViEWS-L score. Emerg Med J. 2013;30:123-9. [CrossRef] [PubMed]
30. Rangel-Frausto MS, Pittet, D, Costigan M, et al. The natural history of the Systemic Inflammatory Response Syndrome (SIRS): A prospective study. JAMA. 1995;273:117-123. [CrossRef] [PubMed]
31. Matthew M, Churpek F, Zadravecz J, et al. Incidence and prognostic value of the Systemic Inflammatory Response Syndrome and organ dysfunctions in ward patients. Am J Resp Crit Care Med. 2015;192:958-64. [CrossRef] [PubMed]
32. Pittet D, Range-Frausto S, Tarara LN, Lin N, et al. Systemic inflammatory response syndrome, sepsis, severe sepsis and septic shock: incidence, morbidities and outcomes in surgical ICU patients. Intensive Care Med. 1995;21:302-9. [CrossRef] [PubMed]
33. Kellett J, Kim A. Validation of an abbreviated Vitalpac early warning score (ViEWS) in 75,419 consecutive admission to a Canadian regional hospital. Resuscitation. 2012;83:297-302. [CrossRef] [PubMed]
34. Smith GB, Prytherch DR, Schmidt PE, Featherstone PI, et al. A review and performance evaluation of single-parameter "track and trigger" systems. Resuscitation. 2008;79:11-21. [CrossRef] [PubMed]
35. Gao H, McDonnell A, Harrison DA, Moore T, et al. Systemic review and evaluation of physiological track and trigger warning systems for identifying at-risk patients on the ward. Intensive Care Med. 2007;33:667-79. [CrossRef] [PubMed]

Cite as: Raschke RA, Khurana H, Owen-Reece H, Groves RH Jr, Curry SC, Martin M, Stoffer B. Clinical performance of an interactive clinical decision support system for assessment of plasma lactate in hospitalized patients with organ dysfunction. Southwest J Pulm Crit Care. 2017;14:241-52. doi: https://doi.org/10.13175/swjpcc058-17 PDF 

May 2017 Critical Care Case of the Month

Sapna Bhatia, MD

David Ling, DO

Michel Boivin, MD

Division of Pulmonary, Critical Care and Sleep Medicine

University of New Mexico School of Medicine

Albuquerque, NM USA

History of Present Illness

A 54-year-old Hispanic male who was incarcerated 3 days prior to hospital admission was brought into the emergency room from prison for alcohol related withdrawal seizures.

Physical Examination

Upon arrival to the ER, the patient was noted to be hypoxic with copious thick secretions in his mouth. He was intubated for airway protection, started on propofol and fentanyl drips as well as intravenous thiamine and folic acid.

Radiography

A chest radiograph was performed (Figure 1).

Figure 1. Portable anterior-posterior (AP) radiograph of the chest.

Which of the following are true regarding management of this patient?

1. Phenytoin should be administered for prevention of seizures
2. Prophylactic antibiotics for aspiration pneumonia should be administered
3. Thiamine and folic acid should be administered
4. 1 and 3
5. All of the above

Cite as: Bhatia S, Ling D, Boivin M. May 2017 critical care case of the month. Southwest J Pulm Crit Care. 2017;14(5):192-8. doi: https://doi.org/10.13175/swjpcc051-17 PDF

Management of Life Threatening Post-Partum Hemorrhage with HBOC-201 in a Jehovah’s Witness

Andrea Mytinger, DO¹

Elyce Sheehan, MD¹

Nathan Blue, MD²

Kendall P. Crookston, MD, PhD³

Ali I. Saeed, MD ⁴

¹Department of Internal Medicine, ²Department of Maternal and Fetal Medicine, ³Departments of Pathology of Transfusion Medicine, and ⁴Divisions of Pulmonary, Sleep and Critical Care Medicine

University of New Mexico School of Medicine

Albuquerque, NM USA

Abstract

Background: Post-partum hemorrhage remains the leading cause of maternal mortality worldwide. The obstetrician and critical care physician should be aware of local alternative treatment options for symptomatic anemia secondary to post-partum hemorrhage in patients who cannot receive red blood cell transfusion. Transfusion may not be an option due to strong personal belief, lack of compatible blood, or blood shortage.

Case: A 21-year-old woman, gravida 1 para 1001, was transferred to a tertiary care center for management of severe post-partum hemorrhage (hemoglobin 4.2 g/dL). She had undergone emergent dilation and curettage followed by Bakri tamponade balloon placement at an outside facility. As a member of the Jehovah’s Witness faith, she refused red blood cell transfusion. HBOC-201, a bovine hemoglobin based oxygen carrier, was successfully used to reverse symptomatic, life-threatening anemia.

Conclusion:  HBOC-201 can act as a means to reverse severe end-organ damage for patients with severe post-partum hemorrhage and should be considered when no other treatment options are available.

Teaching Points

1. HBOC-210 (Hemopure®) is a bovine hemoglobin-based oxygen carrier (HBOC), used as a means to reverse severe anemia in those patients who cannot receive RBC transfusion.
2. The current generation of HBOCs carry fewer side effects than their predecessors. Common side effects include transient hypertension, abdominal complaints, jaundice, elevated liver and pancreatic enzymes and decreased urine output.
3. The teratogenic effects of HBOC-201 remains unknown in humans.

Introduction

Worldwide, there are an estimated 14 million pregnancy-related hemorrhages each year and 25% of maternal mortality can be attributed to post-partum hemorrhage (1). While the majority of post-partum hemorrhage leading to acute blood loss anemia is treated with red blood cell (RBC) transfusion, there remains a significant subset of patients who are unable to receive this life-saving modality. In instances where RBC transfusion is not an option due to lack of compatible blood, blood shortage, or strong patient personal beliefs, there remain alternative options for management. We report the case of a young Jehovah’s Witness who presented with symptomatic anemia secondary to severe post-partum hemorrhage, treated successfully with an experimental protocol using HBOC-201 (Hemopure®).

Case

A 21-year-old female, gravida 1 para 1001, Jehovah’s Witness was transferred to a tertiary care hospital for management of post-partum hemorrhage after spontaneous vaginal delivery at 40 weeks of gestation. The patient received 3 boluses of intravenous oxytocin, 800mcg of misoprostol and 1 dose of intramuscular (IM) carboprost trimethamine. She then underwent a dilation and curettage for presumed retained products of conception. A Bakri tamponade balloon catheter (Figure 1) was placed vaginally and the patient was transferred for a higher level of care.

Figure 1.  An example illustration of the Bakri vaginal tamponade balloon, placed in the uterus in attempt to apply pressure to bleeding vessels.

Prior to delivery, the patient’s hemoglobin (Hb) and hematocrit (Hct) were initially 12.4 g/dL and 36.4 %, respectively, which decreased to 5.5 g/dL and 16.4%.

On arrival, the patient ‘s heart rate was 148 beats per minute while on 2L of oxygen. The blood pressure was 93/36 mmHg. She was pale and tired-appearing with conjunctival pallor.  Her abdomen exhibited generalized mild tenderness to palpation. The Bakri balloon was in place with 100 mL of drainage noted. Laboratory results revealed Hb of 4.2 g/dL, lactate of 1.2 mmol/L and troponin I of 1.820 ng/mL. The patient refused transfusion of RBC, and the other major blood products, citing her faith. After a prolonged discussion, the patient consented to the use of HBOC-201.

The patient received 2 units of HBOC-201 along with 1,000 mg of ascorbic acid. Her Hb increased from 4.2 g/dL to 4.8 g/dL, much less than the anticipated 1 g/dL increase with each unit of HBOC-201 raising concern for ongoing hemorrhage. An ultrasound was performed which revealed ongoing bleeding from the lower uterine segment behind the balloon. Methylergonovine 0.2mg IM every 6 hours was started and the patient received two additional units of HBOC-201 however, during infusion of the second unit her oxygen requirement increased from 2L by nasal cannula to 15L high flow mask at 80% FiO2. The transfusion was stopped and a chest radiograph revealed diffuse parenchymal opacities with prominent interstitial markings and small bilateral pleural effusions suggestive if fluid overload / pulmonary edema. The patient then underwent gel foam uterine artery embolization by Interventional Radiology for definitive management.

On hospital day 2 the patient’s heart rate was 114 beats per minute and Hb was 5.2 g/dL, prompting infusion of an additional 2 units of HBOC-201. Due to continued hypoxia and radiographic evidence of fluid overload, diuretic therapy was administered. Her oxygen requirement decreased to 5L by nasal cannula, however did not improve from there despite a negative fluid balance, so a CT scan of the chest was performed which revealed significant bilateral basal atelectasis. The patient’s oxygen requirement resolved with incentive spirometry. The Bakri vaginal balloon was removed and minimal bleeding was observed.

On hospital day 3 the patient’s blood pressure increased to 176/78 mmHg. This, in the setting of proteinuria, peripheral edema and elevated aspartate aminotransferase (AST) to 104 unit/L (6-58 Unit/L) raised a suspicion for post-partum preeclampsia with severe features. Intravenous magnesium sulfate was briefly initiated for seizure prophylaxis, however it was discontinued after her blood pressure stabilized and the hypertension was attributed to a possible side effect of HBOC-201.

The patient received a total of 7.5 units of HBOC-201 over the course of 4 days in the MICU. Her troponin peaked on hospital day 2 at 2.930 ng/mL, and continued to downtrend with multiple infusions of HBOC-201. The patient’s own hematocrit began rising on hospital day 5 (Figure 2).

Figure 2.  Illustration of the hemoglobin and hematocrit over the course of the patient’s hospitalization and at her first out-patient follow up visit. The arrows indicate when HBOC-201 was infused.  Troponin I is also depicted on this graph to illustrate the resolution of severe end-organ damage due to the severe anemia.

The patient was transferred to the obstetrics floor on hospital day 7. In accordance with recent post-partum hemorrhage recommendations, she received 1025 mg of IV iron dextran. She was discharged home in stable condition on hospital day 8 with a Hb of 6.7 g/dL and Hct of 21%. Outpatient follow-up revealed significant improvement in anemia with a Hb of 9.2 g/dL and Hct of 30% one week after discharge.

Discussion

Acute post-partum hemorrhage leading to severe anemia remains the leading cause of maternal death worldwide (2). While the majority of post-partum hemorrhage leading to acute blood loss anemia is treated with transfusion of packed RBC or other blood products, there are certain subsets of patients who are unable to accept these products. This case demonstrates the use of a bovine hemoglobin-based oxygen carrier in a Jehovah’s Witness patient with severe post-partum hemorrhage who refused blood products. There have been multiple case reports regarding the use of HBOC-201 in severely anemic Jehovah’s Witness patients; however, there is no published report to our knowledge on the use of HBOC-201 in patients with symptomatic post-partum hemorrhage.

Hemoglobin-based oxygen carriers were developed in response to the infectious issues associated with donor RBC and in an attempt to come up with an alternative treatment in those situations where RBC transfusion was not an option. The first generation of these products was known to cause renal toxicity and coagulopathy (3,4). HBOC-201 is a second generation HBOC that is a cell-free, stroma-free, polymerized version of bovine hemoglobin. Because it contains no cell membrane, it is compatible with all blood types (no cross matching is needed).  The shelf life is 36 months at room temperature (5) (no refrigeration or sophisticated supply network is needed). A number of randomized control trials have been done to evaluate HBOC-201 (and other similar products) as a potential RBC replacement.  However, after infusion the short 24-hour half-life and statistical increase in adverse events associated with administration made it apparent that these HBOCs were not interchangeable with RBC for routine transfusion. While they are not interchangeable, many clinicians feel that the risk-benefit profile is favorable in severely anemic patients who cannot receive RBC. HBOC-201 is not yet approved for use in the United States, and therefore cannot be used outside of clinical trials. Several compassionate use studies are available in the United States to treat patients with life-threatening anemia when no other treatment option is available. Worldwide only a few countries have approved the use of HBOC-201 (6).

The side effect profile of the second generation HBOC’s is much preferable to that of the first (4). Reported class effects of HBOC use include hypertension, esophageal dysmotility and increased risk for myocardial infarction, all of which are related to vasoconstriction secondary to increased nitric oxide scavenging in these products (5). HBOC-201 in particular, has not been reported to increase risk of myocardial infarction. Rather, it has been reported that HBOC-201 reduces cardiac hypoxia in the setting of severe anemia (7). Mongan et al. (8) found that, while HBOC-201 causes transient systemic and pulmonary hypertension in swine, blood flow to 8 major organs, including the heart, was unchanged compared to controls. Serruys et al. (9) found no significant change in coronary blood flow and no vasoconstriction in humans pre-oxygenated with HBOC-201 prior to Percutaneous Coronary Intervention for coronary artery disease. In this case, the patient presented with troponinemia, indicating type 2 demand ischemia in the setting of severe anemia. Troponin levels began to down-trend after HBOC-201 infusion.

Common side effects of HBOC-201 in particular include transient hypertension, abdominal complaints, jaundice, elevated liver and pancreatic enzymes (10) and bovine methemoglobinemia (11). To prevent the increased oxidation of infused HBOC-201 to methemoglobin, ascorbic acid is co-administered; methemoglobin levels should be monitored and treated with methylene blue should they become significantly elevated (5).

This patient did experience increased hypoxia while receiving a unit of HBOC-201 which resulted in concern for transfusion reaction and transient discontinuation of the HBOC-201 infusion. It must be noted that HBOC-201 contains no cellular or plasma components, thus many transfusion reactions such as Transfusion Related Acute Lung Injury (TRALI) are an impossibility. HBOC-201 has been associated with volume overload; as it is a colloid this is a known complication (12). Volume overload was suspected, however, the patient did not improve with diuresis, and a chest CT revealed profound atelectasis. Given that her hypoxia greatly improved with incentive spirometry and ambulation, this was deemed unlikely to be a reaction associated with HBOC-201, but rather related to being bed-bound and critically ill.

One unit of HBOC-201 will raise serum Hb from 0.5g/dL to 2g/dL (12). One to two units of HBOC-201 are typically given for Hb levels <6 g/Dl, with additional units provided to maintain a goal Hemoglobin greater than 6g/dL (11, 12). With a half-life of 19-24 hours (5, 13), HBOC-201 must be infused regularly until the patient’s bone marrow production of RBC is sufficient, as evidenced by increases in hematocrit. It should be noted that HBOC-201 will only increase serum hemoglobin and not hematocrit; an initial decrease in hematocrit may be seen after infusion secondary to hemodilution (12).

The patient presented above experienced both transient hypertension and an increase in her serum AST, raising concern for post-partum preeclampsia. She was started on treatment for severe preeclampsia, however these affects were later attributed to the HBOC-201.

HBOC-201 is currently not recommended during pregnancy. One animal study in rats indicated that HBOC-201 infusion during organogenesis resulted in decreased litter size and increased incidence of external fetal malformations. This was thought to be related to decreased function of an inverted yolk sac, the primary nutritive organ for rat pups in utero (14). Holson et al. (15) performed a similar study on dogs which did not reveal a statistically significant difference in fetal malformations or other study end-points when compared to control. Canines and humans do not have an inverted yolk sac. Thus, it has been hypothesized that teratogenic effects of HBOC-201 do not apply to humans, however, more studies are needed. At least one US expanded access study allows pregnant women with the potential of massive blood loss (e.g. those with placenta accreta, placenta percreta) to consent to the study while still pregnant. However, HBOC-201 cannot be given until after delivery.

HBOC-201 in this case was utilized as a means to reverse severe end-organ damage due to anemia. This Jehovah’s Witness patient refused blood products, citing religious beliefs. Jehovah’s Witnesses in general will not receive “primary” blood components which include red blood cells, platelets and plasma. Other components, including albumin, clotting factors and HBOCs are considered “conscience items” through the church, where-in the individual can decide for themselves if they wish to receive them (5). With an estimated 1.2 million Jehovah’s Witnesses in the United States alone, alternative treatment options for this patient population are imperative (5).

While transfusion of allogeneic blood products remains the standard of care for treatment of severe post-partum hemorrhage, there are certain situations where this is not available. These might include lack of resources in a rural setting, blood product shortages, and inability to cross-match blood products given patient antibodies or patient denial of blood products due to personal or religious beliefs. HBOC’s are currently not approved for use in the United States, however they can be used on a limited compassionate use basis with FDA IND and local IRB approval, either as part of a planned expanded use study or on an emergency approval basis. Referral to a center with an expanded use protocol should be considered for a woman with the potential for massive bleeding who cannot receive RBC.

References

1. Enakpene CA, Morhason-Bello IO, Enakpene EO, Arowojolu AO, Omigbodun AO. Oral misoprostol for the prevention of primary post-partum hemorrhage during third stage of labor. J Obstet Gynaecol Res. 2007 Dec;33(6):810-7. [CrossRef] [PubMed]
2. Say L, Chou D, Gemmill A, Tunçalp Ö, Moller AB, Daniels J, et al. Global causes of maternal death: a WHO systematic analysis. Lancet Glob Health. 2014 2(6):e323–e333.[CrossRef] [PubMed]
3. Creteur J, Vincent JL. Hemoglobin solutions. Crit Care Med. 2003 Dec;31(12 Suppl):S698-707. [CrossRef] [PubMed]
4. Marinaro J, Smith J, Tawil I, Billstrand M, Crookston KP. HBOC-201 use in traumatic brain injury: case report and review of literature. Transfusion. 2009 Oct;49(10):2054-9. [CrossRef] [PubMed]
5. Epperla N, Strouse C, VanSandt AM, Foy P. Difficult to swallow: warm autoimmune hemolytic anemia in a Jehovah's Witness treated with hemoglobin concentrate complicated by achalasia. Transfusion. 2016 Jul;56(7):1801-6. [CrossRef] [PubMed]
6. Greenburg AG, Kim HW. Hemoglobin-based oxygen carriers. Crit Care. 2004;8 Suppl 2:S61-4. [CrossRef] [PubMed]
7. Fitzgerald MC, Chan JY, Ross AW, Liew SM, Butt WW, Baguley D, et al. A synthetic haemoglobin-based oxygen carrier and the reversal of cardiac hypoxia secondary to severe anaemia following trauma. Med J Aust. 2011 May;194(9):471-3. [PubMed]
8. Mongan PD, Moon-Massat PF, Rentko V, Mihok S, Dragovich A, Sharma P. Regional blood flow after serial normovolemic exchange transfusion with HBOC-201 (Hemopure®) in anesthetized swine. J Trauma. 2009 Jul;67(1):51-60. [CrossRef] [PubMed]
9. Serruys PW, Vranckx P, Slagboom T, Regar E, Meliga E, de Winter RJ, et al. Haemodynamic effects, safety, and tolerability of haemoglobin-based oxygen carrier-201 in patients undergoing PCI for CAD. EuroIntervention. 2008 Mar;3(5):600-9. [CrossRef] [PubMed]
10. Van Hemelrijck J, Levien LJ, Veeckman L, Pitman A, Zafirelis Z, Standl T. A safety and efficacy evaluation of hemoglobin-based oxygen carrier HBOC-201 in a randomized, multicenter red blood cell controlled trial in noncardiac surgery patients. Anesth Analg. 2014 Oct;119(4):766-76. [CrossRef] [PubMed]
11. Jordan SD, Alexander E. Bovine hemoglobin: a nontraditional approach to the management of acute anemia in a Jehovah's Witness patient with autoimmune hemolytic anemia. J Pharm Pract. 2013 Jun;26(3):257-60. [CrossRef] [PubMed]
12. Mer M, Hodgson E, Wallis L, Jacobson B, Levien L, Snyman J, et al. Hemoglobin glutamer-250 (bovine) in South Africa: consensus usage guidelines from clinician experts who have treated patients. Transfusion. 2016 Sep. [CrossRef] [PubMed]
13. Donahue LL, Shapira I, Shander A, Kolitz J, Allen S, Greenburg G. Management of acute anemia in a Jehovah's Witness patient with acute lymphoblastic leukemia with polymerized bovine hemoglobin-based oxygen carrier: a case report and review of literature. Transfusion. 2010 Jul;50(7):1561-7. [CrossRef]  [PubMed]
14. Stump DG, Holson JF, Harris C, Pearce LB, Watson RE, DeSesso JM. Developmental toxicity in rats of a hemoglobin-based oxygen carrier results from impeded function of the inverted visceral yolk sac. Reprod Toxicol. 2015 Apr;52:108-17. [CrossRef] [PubMed]
15. Holson JF, Stump DG, Pearce LB, Watson RE, DeSesso JM. Absence of developmental toxicity in a canine model after infusion of a hemoglobin-based oxygen carrier: Implications for risk assessment. Reprod Toxicol. 2015 Apr;52:101-7. [CrossRef] [PubMed] 

Cite as: Mytinger A, Sheehan E, Blue N, Crookston KP, Saeed AI. Management of life threatening post-partum hemorrhage with HBOC-201 in a Jehovah’s witness. Southwest J Pulm Crit Care. 2017;14(4):177-84. doi: https://doi.org/10.13175/swjpcc031-17 PDF

Tracheal Stoma Necrosis: A Case Report

Stella Pak, MD

Arjan Flora, MD 

Young-Sook Yoon, MD

Department of Medicine

University of Toledo Medical Center

Toledo, OH, USA

Abstract

Acute tracheal dilatation, due to an overinflated cuff, has been reported early in the course of mechanical ventilation through an endotracheal tube. Tracheal stoma necrosis is a rare complication, but such can accompany acute tracheal dilation. Herein, we report a case of tracheal necrosis 9 days following tracheostomy placement in a 71-year old woman associated with overinflation of the tracheal tube cuff. This case report aims to 1) add to the scant body of knowledge about the diagnosis and management for the patients with tracheal stoma necrosis and 2) raise awareness for error-traps in interpreting diagnostic images, specifically satisfaction of search error, inattentional blindness error, and alliterative error.

Case Report

A 71-year-old woman with a history of chronic respiratory failure on mechanical ventilation presented to the emergency department for bleeding around the tracheostomy site. The tracheostomy was recently inserted 9 days prior to admission. A chest radiograph demonstrated left lower lobe atelectasis, pleural effusion, and cardiomegaly that was consistent with pre-existing congestive heart failure (Figure 1).

Figure 1. Chest radiograph (AP) performed during first admission.

The cuff overinflation was demonstrated as a spherical shaped hypolucent region surrounding the trachea. However, the lesion escaped attention possibly because the focus of attention was limited to the thoracic compartment. A CT of the soft tissue in the neck ruled out the possibility of hematoma or infection. However, the features suggestive of overinflation of tracheostomy tube once again escaped attention. The spherical shaped hypolucent area, representing the cuff, was 3.9 cm in the anterior-posterior axis and 3.8 cm along the right-left axis.

A fiberoptic bronchoscopy through the tracheostomy tube revealed a large blood clot obstructing the distal end of the tube. A necrotic lesion around the stoma was also found. Careful observation via the bronchoscope during the procedure revealed no tearing or rupture. The patient was conservatively treated with vancomycin and cefepime for treatment of a ventilator-associated pneumonia. The oozing of blood from the tracheostomy stopped on with conservative wound care, including cleaning and dressing. She returned back to her baseline and was subsequently discharged on 3^rd day of admission. During this first admission, a tracheostomy tube exchange was not done due to bleeding from the stoma.

The patient was readmitted 12 days after discharge for an episode of hematemesis of approximately 400 mL of bright red blood. A chest radiograph showed satisfactory position of tracheotomy tube and cardiomegaly at baseline (Figure 2).

Figure 2.  Chest radiograph (AP) after readmission.

For the third time, the features suggestive of cuff-overinflation went unnoticed, delaying accurate diagnosis and proper treatment.

As a part of the patient’s evaluation, a CT of the chest with intravenous contrast was done, revealing the overinflated cuff of the trachea tube into the soft tissue of the neck (Figure 3).

Figure 3. Thoracic CT scan showing the overinflated tracheostomy cuff in the (A) coronal, (B) sagittal, and (C) axial views.

The ovoid shaped hypolucent area, representing the cuff, was 5.3 cm in the anterior-posterior axis and 4.6 cm along the right-left axis.

The Shiley proximal tracheal tube was urgently replaced with a portex Bivona tracheal tube. The new tracheostomy tube is more extensible, soft, and longer in distal length. Postoperatively, the patient was kept ventilated in the ICU. Repeated chest CT showed the new tracheostomy tube in satisfactory position and normalization of trachea shape. She made an uneventful recovery and was discharged 8 days after the tracheotomy tube replacement.

Discussion

A case of nonfatal hemorrhage due to innominate artery erosion with soft tissue necrosis at the stoma site of a tracheostomy is presented. In this ventilator-dependent patient with a recent tracheotomy stoma creation, an overinflated cuff of a tracheotomy tube was the key culprit in the pathology. Tracheal tube cuff pressure should be monitored so that it does not exceed a reasonable estimate of capillary perfusion pressure. Cuffs with pressure over 25 mmHg can compress the surrounding soft tissue, including delicate vascular structures. The damage to the vasculature in contact with the tube can result in ischemic necrosis in the soft tissue. If left untreated, these necrotic regions can develop infection or undergo fibrosis, leading to progressive stenosis (1).

A number of cognitive errors led to multiple episodes of misdiagnosis in this patient. Satisfaction of search error is a type of false negative error caused by premature termination of search after an abnormality has been detected (2). In this patient, we readily detected several abnormalities—cardiomegaly, pulmonary atelectasis, and pleural effusion. These initial findings likely led us to subconsciously neglect later findings.

Inattentional blindness error is a false negative error caused by the psychological lack of attention on an unexpected stimulus (3). In the present case, none of the diagnostic imaging was taken to check for cuff-overinflation. The images from the first admission were ordered for a concern of NG tube malposition, infection, and hematoma. The images ordered during the second admission were ordered to check the tracheotomy tube position. The thoracic compartment (the area for the expected abnormalities) received a disproportionately large amount of attention, whereas only a scant amount of attention was paid to the neck compartment.

Alliterative error is an error caused by a preconceived notion from a previous interpretation by a colleague or oneself (4). The negative finding in the previous reports could have affected the subsequent interpretative performance.

To the best of our knowledge, there are only 3 other cases of soft tissue necrosis caused by cuff overinflation. In two of these cases, the extended trachea did not recoil back to the previous size (5, 6). In the presented case, the stretched trachea recoiled back, similar to the case described by Sachdeva and his colleagues (7). The prognostic value of this difference in recovery is unknown, but might have a significant clinical implication. To explore the clinical relevance of this finding, more data on this condition is needed.

Teaching Points

1. Careful attention should be paid to cuff inflation pressure in patients presenting with bleeding at the tracheostomy site.
2. Conscious efforts to avoid well-known errors in diagnostic image interpretation, such as satisfaction of search error, and inattentional blindness error, should be made to improve diagnostic accuracy.

References

1. De Leyn P, Bedert L, Delcroix M, et al. Tracheotomy: clinical review and guidelines. Eur J Cardiothorac Surg. 2007 Sep;32(3):412-21. [CrossRef] [PubMed]
2. Ashman CJ, Yu JS, Wolfman D. Satisfaction of search in osteoradiology. AJR Am J Roentgenol. 2000 Aug;175(2):541-4. [CrossRef] [PubMed]
3. Richards A, Hannon EM, Derakshan N. Predicting and manipulating the incidence of inattentional blindness. Psychol Res. 2010 Nov;74(6):513-23. [CrossRef] [PubMed]
4. Berlin L. Malpractice issues in radiology. Alliterative errors. AJR Am J Roentgenol. 2000 Apr;174(4):925-31. [CrossRef] [PubMed]
5. Rhodes A, Lamb FJ, Grounds RM, Bennett ED. Tracheal dilatation complicating tracheal intubation. Anaesthesia. 1997 Jan;52(1):70-2. [CrossRef] [PubMed]
6. Honig EG, Francis PB. Persistent tracheal dilatation: onset after brief mechanical ventilation with a "soft-cuff" endotracheal tube. South Med J. 1979 Apr;72(4):487-90. [CrossRef] [PubMed]
7. Sachdeva A, Pickering EM, Reed RM, Shanholtz CB. Ice cream cone sign: reversible ballooning of the trachea due to tracheostomy tube cuff overinflation. BMJ Case Rep. 2016 May 4;2016. [CrossRef] [PubMed]

Cite as: Pak S, Flora A, Yoon Y-S. Tracheal stoma necrosis: a case report. Southwest J Pulm Crit Care. 2017;14(4):172-6. doi: https://doi.org/10.13175/swjpcc032-17 PDF 

April 2017 Critical Care Case of the Month

Robert A. Raschke, MD

Banner University Medical Center-Phoenix

Phoenix, AZ USA

History of Present Illness

A 20-year-old woman was transferred from another medical center for care. She was pregnant and initially presented with a one day history of crampy abdominal pain with nausea and vomiting after eating old, bad tasting chicken two days previously. She had pain of her right arm and a non-displaced humeral fracture was seen on x-ray. The etiology of the fracture was unclear. Her illness rapidly progressed to respiratory distress requiring intubation. The fetus had deceleration of heart tones leading to a cesarean section and delivery of a non-viable infant. Subsequently, she had rapid progression of shock and anuria.

Past Medical History

She had a previous history of a seizure disorder which was managed with levetiracetam, clonazepam, and folic acid. There was a previous intentional opiate overdose 2 years earlier. One month prior to admission she had visited her husband in Iraq. After returning to the US 3 weeks prior to admission, she developed a sore throat and was treated with penicillin. She smokes tobacco hookah and marijuana. There is a positive family history of gout.

Physical Examination

• Vital signs: heart rate 109, blood pressure 102/78 mm Hg while on norepinephrine, respiratory rate 22, temperature 36.5º C.
• General: She was sedated and intubated. She had a splint on her right arm.
• Lungs: clear anteriorly
• Heart: regular rhythm without murmur
• Abdomen: firm without palpable organomegaly or masses.
• Neurological examination: There was movement of all extremities. Muscle tone was normal. Deep tendon reflexes were normal. Plantar reflexes were down going.
• Skin: diffuse erythematous macular popular rash on the trunk and back (Figure 1).

Figure 1. Photograph of patient’s back showing rash.

Initial Laboratory Evaluation

• CBC: hemoglobin 14.5 gm/dL, platelet count 299,000 cells/mcL, WBC 41,000 cells/mcL, vacuolated polymorphonuclear leukocytes were noted
• Electrolytes: Na⁺ 135 mmol/L, K⁺ 4.9 mmol/L, Cl^- 95 mmol/L, HCO3^- 18 mmol/L
• Renal function: creatinine 3.9 mg/dL, blood urea nitrogen (BUN) 59 mg/dL
• Liver enzymes: AST 294 (normal 8-48 U/L), ALT 303 (normal 7-55 U/L), ALP 187 (normal 45-115 U/L).       
• Glucose: 58

Which of the following should be done immediately? (Click on the correct answer to proceed to the second of five pages)

1. Bedside echocardiography
2. Liver biopsy
3. Urine drug screen
4. 1 and 3
5. All of the above

Cite as: Raschke RA. April 2017 critical care case of the month. Southwest J Pulm Crit Care. 2017;14(4):134-40. doi: https://doi.org/10.13175/swjpcc039-17 PDF