Clinical laboratory findings associated with in-hospital mortality

Admission Laboratory Values Accurately Predict In-hospital Mortality: a Retrospective Cohort Study

BACKGROUND

The greater the severity of illness of a patient, the more likely the patient will have a poor hospital outcome. However, hospital-wide severity of illness scores that are simple, widely available, and not diagnosis-specific are still needed. Laboratory tests could potentially be used as an alternative to estimate severity of illness.

OBJECTIVE

To evaluate the ability of hospital laboratory tests, as measures of severity of illness, to predict in-hospital mortality among hospitalized patients, and therefore, their potential as an alternative method to severity of illness risk adjustment.

DESIGNS AND PATIENTS

A retrospective cohort study among 38,367 adult non-trauma patients admitted to the University of Maryland Medical Center between November 2015 and November 2017 was performed. Laboratory tests (hemoglobin, platelet count, white blood cell count, urea nitrogen, creatinine, glucose, sodium, potassium, and total bicarbonate (HCO₃)) were included when ordered within 24 h from the time of hospital admission. A multivariable logistic regression model to predict in-hospital mortality was constructed using a section of our cohort (n = 21,003).

MAIN MEASURES

Model performance was evaluated using the c-statistic and the Hosmer-Lemeshow (HL) test. In addition, a calibration belt was constructed to determine a confidence interval around the calibration curve with the purpose of identifying ranges of miscalibration.

KEY RESULTS

Patient age and all laboratory tests predicted mortality with good discrimination (c = 0.79). Patients with abnormal HCO₃ levels or leukocyte counts at admission were twice as likely to die during their hospital stay as patients with normal results. A good model calibration and fit were observed (HL = 13.9, p = 0.18).

CONCLUSIONS

Admission laboratory tests are able to predict in-hospital mortality with good accuracy, providing an objective and widely accessible approach to severity of illness risk adjustment.

Development and validation of a novel computer-aided score to predict the risk of in-hospital mortality for acutely ill medical admissions in two acute hospitals using their first electronically recorded blood test results and vital signs: a cross-sectional study

OBJECTIVES

There are no established mortality risk equations specifically for emergency medical patients who are admitted to a general hospital ward. Such risk equations may be useful in supporting the clinical decision-making process. We aim to develop and externally validate a computer-aided risk of mortality (CARM) score by combining the first electronically recorded vital signs and blood test results for emergency medical admissions.

DESIGN

Logistic regression model development and external validation study.

SETTING

Two acute hospitals (Northern Lincolnshire and Goole NHS Foundation Trust Hospital (NH)-model development data; York Hospital (YH)-external validation data).

PARTICIPANTS

Adult (aged ≥16 years) medical admissions discharged over a 24-month period with electronic National Early Warning Score(s) and blood test results recorded on admission.

RESULTS

The risk of in-hospital mortality following emergency medical admission was 5.7% (NH: 1766/30 996) and 6.5% (YH: 1703/26 247). The C-statistic for the CARM score in NH was 0.87 (95% CI 0.86 to 0.88) and was similar in an external hospital setting YH (0.86, 95% CI 0.85 to 0.87) and the calibration slope included 1 (0.97, 95% CI 0.94 to 1.00).

CONCLUSIONS

We have developed a novel, externally validated CARM score with good performance characteristics for estimating the risk of in-hospital mortality following an emergency medical admission using the patient's first, electronically recorded, vital signs and blood test results. Since the CARM score places no additional data collection burden on clinicians and is readily automated, it may now be carefully introduced and evaluated in hospitals with sufficient informatics infrastructure.

Laboratory alerts to guide early intensive care team review in surgical patients: A feasibility, safety, and efficacy pilot randomized controlled trial

AIM

Common blood tests can help identify patients at risk of death, unplanned intensive care unit (ICU) admission, or rapid response team (RRT) call. We aimed to test whether early ICU-team review triggered by such laboratory tests (lab alert) is feasible, safe, and can alter physiological variables, clinical management, and clinical outcomes.

METHODS

In prospective pilot randomized controlled trial in surgical wards of a tertiary hospital, we studied patients admitted for >24 h. We applied a previously validated risk assessment tool to each set of common laboratory tests to identify patients at risk and generate a "lab-alert". We randomly allocated such lab-alert patients to receive early ICU-team review (intervention) or usual care (control).

RESULTS

We studied 205 patients (males 54.1%; average age 79 years; 103 randomized to intervention and 102 to usual care). Intervention patients were more likely to trigger RRT activation during their first lab-alert (10.7 vs. 2.0%; P < 0.001) but less likely to receive an allied health referral (18.0% vs. 24.5%; p = 0.007). They were less likely to trigger RRT activation in the 24-h before subsequent alerts (18.4 vs. 22.4%; p = 0.008) and less likely to generate further alerts (204 vs. 320; p < 0.001), but more likely to receive a not for resuscitation or endotracheal intubation status in the 24-h before subsequent alerts (26.6 vs. 17.3%; p = 0.05). Mortality at 24 h was 1.9% for the intervention group vs. 2.9% in the control group (p = 0.63). Finally, overall mortality was 19.4% for intervention patients vs. 23.5% for control patients (p = 0.50).

CONCLUSION

Among surgical patients, lab alerts identify patients with a high mortality. Lab alert-triggered interventions are associated with more first alert-associated RRT activations; more changes in resuscitation status toward a more conservative approach; fewer subsequent alert-associated RRT activations; fewer subsequent alerts, and decreased allied health interventions (ANZCTRN12615000146594).

Predicting in-hospital mortality and unanticipated admissions to the intensive care unit using routinely collected blood tests and vital signs: Development and validation of a multivariable model

Aim

The National Early Warning System (NEWS) is based on vital signs; the Laboratory Decision Tree Early Warning Score (LDT-EWS) on laboratory test results. We aimed to develop and validate a new EWS (the LDTEWS:NEWS risk index) by combining the two and evaluating the discrimination of the primary outcome of unanticipated intensive care unit (ICU) admission or in-hospital mortality, within 24 h.

Methods

We studied emergency medical admissions, aged 16 years or over, admitted to Oxford University Hospitals (OUH) and Portsmouth Hospitals (PH). Each admission had vital signs and laboratory tests measured within their hospital stay. We combined LDT-EWS and NEWS values using a linear time-decay weighting function imposed on the most recent blood tests. The LDTEWS:NEWS risk index was developed using data from 5 years of admissions to PH, and validated on a year of data from both PH and OUH. We tested the risk index’s ability to discriminate the primary outcome using the c-statistic.

Results

The development cohort contained 97,933 admissions (median age = 73 years) of which 4723 (4.8%) resulted inhospital death and 1078 (1.1%) in unanticipated ICU admission. We validated the risk index using data from PH (n = 21,028) and OUH (n = 16,383). The risk index showed a higher discrimination in the validation sets (c-statistic value (95% CI)) (PH, 0.901 (0.898–0.905); OUH, 0.916 (0.911–0.921)), than NEWS alone (PH, 0.877 (0.873–0.882); OUH, 0.898 (0.893–0.904)).

Conclusions

The LDTEWS:NEWS risk index increases the ability to identify patients at risk of deterioration, compared to NEWS alone.

Predicting medical emergency team calls, cardiac arrest calls and re-admission after intensive care discharge: creation of a tool to identify at-risk patients

We aimed to develop a predictive model for intensive care unit (ICU)-discharged patients at risk of post-ICU deterioration. We performed a retrospective, single-centre cohort observational study by linking the hospital admission, patient pathology, ICU, and medical emergency team (MET) databases. All patients discharged from the Alfred Hospital ICU to wards between July 2012 and June 2014 were included. The primary outcome was a composite endpoint of any MET call, cardiac arrest call or ICU re-admission. Multivariable logistic regression analysis was used to identify predictors of outcome and develop a risk-stratification model. Four thousand, six hundred and thirty-two patients were included in the study. Of these, 878 (19%) patients had a MET call, 51 (1.1%) patients had cardiac arrest calls, 304 (6.5%) were re-admitted to ICU during the same hospital stay, and 964 (21%) had MET calls, cardiac arrest calls or ICU re-admission. A discriminatory predictive model was developed (area under the receiver operating characteristic curve 0.72 [95% confidence intervals {CI} 0.70 to 0.73]) which identified the following factors: increasing age (odds ratio [OR] 1.012 [95% CI 1.007 to 1.017] <i>P</i> <0.001), ICU admission with subarachnoid haemorrhage (OR 2.26 [95% CI 1.22 to 4.16] <i>P</i>=0.009), admission to ICU from a ward (OR 1.67 [95% CI 1.31 to 2.13] <i>P</i> <0.001), Acute Physiology and Chronic Health Evaluation (APACHE) III score without the age component (OR 1.005 [95% CI 1.001 to 1.010] <i>P</i>=0.025), tracheostomy on ICU discharge (OR 4.32 [95% CI 2.9 to 6.42] <i>P</i> <0.001) and discharge to cardiothoracic (OR 2.43 [95%CI 1.49 to 3.96] <i>P</i> <0.001) or oncology wards (OR 2.27 [95% CI 1.05 to 4.89] <i>P</i>=0.036). Over the two-year period, 361 patients were identified as having a greater than 50% chance of having post-ICU deterioration. Factors are identifiable to predict patients at risk of post-ICU deterioration. This knowledge could be used to guide patient follow-up after ICU discharge, optimise healthcare resources, and improve patient outcomes and service delivery.

Glucocorticoid receptor density and binding affinity in healthy horses and horses with systemic inflammatory response syndrome

BACKGROUND

Dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis occurs in horses with systemic inflammatory response syndrome (SIRS). Peripheral resistance to glucocorticoids has not been investigated in horses.

OBJECTIVE

To determine if glucocorticoid receptor (GR) function in horses can be measured using flow cytometry, and to use this information to evaluate HPA axis dynamics.

ANIMALS

Eleven healthy adult horses in parts 1 and 2. Ten horses with SIRS and 10 age and sex matched controls in part 3.

METHODS

Flow cytometry was used to evaluate GR density and binding affinity (BA) in 3 healthy horses in part 1. In part 2, exogenous ACTH was administered to eight healthy horses. Their cortisol response and GR properties were measured. In part 3, CBC, serum biochemistry, cortisol and ACTH, and GR properties were compared between controls without SIRS (n = 10) and horses with SIRS (n = 10), and between survivors and nonsurvivors (n = 4 and n = 6 respectively).

RESULTS

Flow cytometry can be used to measure GR properties in equine PBMCs. No correlation was observed between plasma cortisol concentration and GR density or BA in healthy horses (r = -0.145, P = .428 and r = 0.046, P = .802 respectively). Nonsurvivors with SIRS had significantly decreased GR BA (P = .008). Horses with triglyceride concentration > 28.5 mg/dL had increased odds of nonsurvival (OR=117; 95% CI, 1.94-7,060). GR BA <35.79% was associated with nonsurvival (OR = 30.33; 95% CI, 0.96-960.5).

CONCLUSIONS AND CLINICAL IMPORTANCE

Tissue resistance to glucocorticoids contributes to HPA axis dysfunction in adult horses with SIRS. These horses might benefit from treatment with exogenous glucocorticoids.

Laboratory tests to identify patients at risk of early major adverse events: a prospective pilot study

BACKGROUND/AIMS

To test whether commonly measured laboratory variables can identify surgical patients at risk of major adverse events (death, unplanned intensive care unit (ICU) admission or rapid response team (RRT) activation).

METHODS

We conducted a prospective observational study in a surgical ward of a university-affiliated hospital in a cohort of 834 surgical patients admitted for >24 h. We applied a previously validated multivariable model-derived risk assessment to each combined set of common laboratory tests to identify patients at risk. We compared the clinical course of such patients with that of control patients from the same ward who had blood tests but were identified as low risk.

RESULTS

We studied 7955 batches and 73,428 individual tests in 834 patients (males 55%; average age 65.8 ± 17.6 years). Among these patients, 66 (7.9%) were identified as 'high risk'. High-risk patients were older (75.9 vs 61.8 years of age; P < 0.0001), had much greater early (48 h) mortality (6/66 (9%) vs 4/768 (0.5%); P < 0.0001) and greater overall hospital mortality (11/66 (16.7%) vs 9/768 (1.2%); P < 0.0001). They also had more early (8/66 (12.1%) vs 14/768 (1.8%); P = 0.0001) and overall in-hospital unplanned ICU admissions (12/66 (18.2%) vs 18/768 (2.3%); P < 0.0001) and more early (26/66 (39.3%) vs 50/768 (6.5%); P < 0.0001) and overall in-hospital RRT calls (26/66 (39.4%) vs 55/768 (7.2%); P < 0.0001).

CONCLUSIONS

Commonly performed laboratory tests identify surgical ward patients at risk of early major adverse events. Further studies are needed to assess whether such identification system can be used to trigger interventions that help improve patient outcomes.

Serum value of procalcitonin as a marker of intestinal damages: type, extension, and prognosis

BACKGROUND

Ischemic and necrotic damages are complications of digestive diseases and require emergency management. Nevertheless, the decision to surgically manage could be delayed because of no sufficiently preoperative accurate marker of ischemia diagnosis, extension, and prognosis.

METHODS

The aim of this study was to assess the predictive value of serum procalcitonin (PCT) levels for diagnosing intestinal necrotic damages, their extension, and their prognosis in patients with ischemic disease including ischemic colitis and mesenteric infarction by a gray zone approach. Between January 2007 to June 2014, 128 patients with ischemic colitis and mesenteric infarction (codes K55.0 and K51.9) were operated, for whom data on PCT were available. We perform a retrospective, multicenter review of their medical records. Patients were divided into subgroups: ischemia (ID group) versus necrosis (ND group); the extension [focal (FD) vs. extended (ED)] and the vital status [deceased (D) vs. alive (A)].

RESULTS

PCT levels were higher in the ND (n = 94; p = 0.009); ED (n = 100; p = 0.02); and D (n = 70; p = 0.0003) groups. With a gray zone approach, the predictive thresholds were (i) for necrosis 2.473 ng/mL, (ii) for extension 3.884 ng/mL, and (iii) for mortality 7.87 ng/mL.

CONCLUSION

In our population, PCT could be used as a marker of necrosis; especially in case of extended damages and reflects the patient's prognosis.

Does repeat Hb measurement within 2 hours after a normal initial Hb in stable trauma patients add value to trauma evaluation?

Background

In our level I trauma center, it is considered common practice to repeat blood haemoglobin measurements in patients within 2 h after admission. However, the rationale behind this procedure is elusive and can be considered labour-intensive, especially in patients in whom haemorrhaging is not to be expected. The aim of this study was to assess the value of the repeated Hb measurement (r-Hb) within 2 h in adult trauma patients without evidence of haemodynamic instability.

Methods

The local trauma registry was used to identify all trauma patients without evidence of haemodynamic instability from January 2009 to December 2010. Patients in whom no initial blood Hb measurement (i-Hb) was done on admission, referrals, and patients without risk for traumatic injuries or haemorrhage based upon mechanism of injury (e.g. inhalation or drowning injury) were excluded.

Results

A total of 1,537 patients were included in the study, 1,246 of which did not present with signs of haemodynamic instability. Median Injury Severity Score (ISS) was 5 (interquartile range (IQR) 1 to 13), 22% of the patients were multitrauma patients (ISS > 15). A normal i-Hb was found in 914 patients (73%). Of the 914 patients with a normal i-Hb, 639 (70%) had a normal r-Hb, while in 127 patients (14%), an abnormal r-Hb was found. In none of these patients, the abnormal r-Hb led to new diagnoses. In 148 patients (16%), no repeated Hb measurement was done without clinical consequences.

Conclusion

We conclude that repeated blood Hb measurement within 2 h after admission in stable, adult trauma patients with a normal initial Hb concentration does not add value to a trauma patient's evaluation.

Index blood tests and national early warning scores within 24 hours of emergency admission can predict the risk of in-hospital mortality: a model development and validation study

BACKGROUND

We explored the use of routine blood tests and national early warning scores (NEWS) reported within ±24 hours of admission to predict in-hospital mortality in emergency admissions, using empirical decision Tree models because they are intuitive and may ultimately be used to support clinical decision making.

METHODOLOGY

A retrospective analysis of adult emergency admissions to a large acute hospital during April 2009 to March 2010 in the West Midlands, England, with a full set of index blood tests results (albumin, creatinine, haemoglobin, potassium, sodium, urea, white cell count and an index NEWS undertaken within ±24 hours of admission). We developed a Tree model by randomly splitting the admissions into a training (50%) and validation dataset (50%) and assessed its accuracy using the concordance (c-) statistic. Emergency admissions (about 30%) did not have a full set of index blood tests and/or NEWS and so were not included in our analysis.

RESULTS

There were 23248 emergency admissions with a full set of blood tests and NEWS with an in-hospital mortality of 5.69%. The Tree model identified age, NEWS, albumin, sodium, white cell count and urea as significant (p<0.001) predictors of death, which described 17 homogeneous subgroups of admissions with mortality ranging from 0.2% to 60%. The c-statistic for the training model was 0.864 (95%CI 0.852 to 0.87) and when applied to the testing data set this was 0.853 (95%CI 0.840 to 0.866).

CONCLUSIONS

An easy to interpret validated risk adjustment Tree model using blood test and NEWS taken within ±24 hours of admission provides good discrimination and offers a novel approach to risk adjustment which may potentially support clinical decision making. Given the nature of the clinical data, the results are likely to be generalisable but further research is required to investigate this promising approach.

Which is more useful in predicting hospital mortality--dichotomised blood test results or actual test values? A retrospective study in two hospitals

Background

Routine blood tests are an integral part of clinical medicine and in interpreting blood test results clinicians have two broad options. (1) Dichotomise the blood tests into normal/abnormal or (2) use the actual values and overlook the reference values. We refer to these as the “binary” and the “non-binary” strategy respectively. We investigate which strategy is better at predicting the risk of death in hospital based on seven routinely undertaken blood tests (albumin, creatinine, haemoglobin, potassium, sodium, urea, and white blood cell count) using tree models to implement the two strategies.

Methodology

A retrospective database study of emergency admissions to an acute hospital during April 2009 to March 2010, involving 10,050 emergency admissions with routine blood tests undertaken within 24 hours of admission. We compared the area under the Receiver Operating Characteristics (ROC) curve for predicting in-hospital mortality using the binary and non-binary strategy.

Results

The mortality rate was 6.98% (701/10050). The mean predicted risk of death in those who died was significantly (p-value <0.0001) lower using the binary strategy (risk = 0.181 95%CI: 0.193 to 0.210) versus the non-binary strategy (risk = 0.222 95%CI: 0.194 to 0.251), representing a risk difference of 28.74 deaths in the deceased patients (n = 701). The binary strategy had a significantly (p-value <0.0001) lower area under the ROC curve of 0.832 (95% CI: 0.819 to 0.845) versus the non-binary strategy (0.853 95% CI: 0.840 to 0.867). Similar results were obtained using data from another hospital.

Conclusions

Dichotomising routine blood test results is less accurate in predicting in-hospital mortality than using actual test values because it underestimates the risk of death in patients who died. Further research into the use of actual blood test values in clinical decision making is required especially as the infrastructure to implement this potentially promising strategy already exists in most hospitals.

Common laboratory tests predict imminent death in ward patients

OBJECTIVE

To estimate the ability of commonly measured laboratory variables to predict an imminent (within the same or next calendar day) death in ward patients.

DESIGN

Retrospective observational study.

SETTING

Two university affiliated hospitals.

PATIENTS

Cohort of 42,701 patients admitted for more than 24 hours and external validation cohort of 13,137 patients admitted for more than 24 hours.

INTERVENTION

We linked commonly measured laboratory tests with event databases and assessed the ability of each laboratory variable or combination of variables together with patient age to predict imminent death.

MEASUREMENTS AND MAIN RESULTS

In the inception teaching hospital, we studied 418,897 batches of tests in 42,701 patients (males 55%; average age 65.8 ± 17.6 years), for a total of >2.5 million individual measurements. Among these patients, there were 1596 deaths. Multivariable logistic modelling achieved an AUC-ROC of 0.87 (95% CI: 0.85-0.89) for the prediction of imminent death. Using an additional 105,074 batches from a cohort of 13,137 patients from a second teaching hospital, the multivariate model achieved an AUC-ROC of 0.88 (95% CI: 0.85-0.90).

CONCLUSIONS

Commonly performed laboratory tests can help predict imminent death in ward patients. Prospective investigations of the clinical utility of such predictions appear justified.

Risk factors for 90-day and 180-day mortality in hospitalised patients with pressure ulcers

An understanding of risk factors associated with mortality among pressure ulcer patients can inform prognostic counselling and treatment plans. This retrospective cohort study examined associations of comorbid illness, demographic characteristics and laboratory values with 90-day and 90- to 180-day mortality in adult hospitalised patients with pressure ulcers. Data were extracted from hospital databases at two academic urban hospitals. Covariates included mortality risk factors identified in other populations, including demographic and laboratory variables, DRG weight, 'systemic infection or fever' and comorbidity categories from the Charlson comorbidity index. In adjusted Cox proportional hazards models, diabetes, chronic renal failure, congestive heart failure and metastatic cancer were significantly associated with mortality in both time frames. There was no significant effect on mortality from dementia, hemiplegia/paraplegia, rheumatic disease, chronic pulmonary disease or peripheral vascular disease. Myocardial infarction, cerebrovascular disease, liver disease and human immunodeficiency virus/AIDS were associated with mortality in the 90-day time frame only. 'Systemic infection or fever' was associated with mortality in the 90-day time frame but did not show a confounding effect on other variables, and the only significant interaction term was with metastatic cancer. Albumin was the only studied laboratory value that was strongly associated with mortality. Understanding the context of comorbid illness in pressure ulcer patients sets the groundwork for more robust studies of patient- and population-level outcomes, as well as study of heterogeneity within this group.

Accuracy of procalcitonin for outcome prediction in unselected postoperative critically ill patients

The importance of postoperative procalcitonin (PCT) measurements for outcome prediction is currently controversial. Conflicting results have been obtained for patients after polytrauma, sepsis, peritonitis, or cardiac surgery and may result from incomplete adjustment for important confounders or from nonlinear PCT effects. We retrospectively analyzed the association of PCT concentration with postoperative mortality, morbidity, and length of stay in an unselected series of 220 consecutive patients who required postoperative intensive care unit therapy or surveillance. Biochemical markers were measured on the first day after intensive care unit admission. Results were adjusted for various confounding variables (Acute Physiology and Chronic Health Evaluation II score, underlying disease), and test accuracy was evaluated by receiver operating characteristic statistics. We found a significant nonlinear, logarithmic association between PCT concentration and outcome. After adjustment for relevant covariates, PCT was an independent determinant of mortality, combined mortality/morbidity, and postoperative hospital length of stay in survivors. At mortality analysis, the predictive power of PCT was superior to that of Acute Physiology and Chronic Health Evaluation II score and of IL-6 (optimal cutoff point, 1.44 ng/mL; sensitivity, 80.8%; specificity, 80.4%). The use of PCT was comparable to that of other prognostic markers when combined mortality/morbidity were examined. Our results suggest that PCT may deserve further testing as a prognostic tool in unselected, critically ill, surgical patients.

Serum procalcitonin at the time of admission to the ICU as a predictor of short-term mortality

OBJECTIVE

This purpose of this study was to determine if serum procalcitonin (PCT) concentration at the time of admission to the ICU is a predictor of all-cause short-term mortality.

DESIGN AND METHODS

This prospective cross-sectional study was conducted over a 16-month period with 86 consecutive critically ill patients. The semi-quantitative PCT-Q test was performed and APACHE II scores and C-reactive protein (CRP) concentrations were determined within 24 h of admission.

RESULTS

PCT-Q test value was a better predictor of all-cause short-term mortality than CRP value or APACHE II score. PCT > or = 10 ng/mL was highly and independently correlated with mortality. Use of PCT-Q > or = 10 ng/mL was superior to use of APACHE II > or = 25 or CRP > or = 10 mg/dL as a predictor of poor outcome.

CONCLUSIONS

A PCT-Q value > or = 10 ng/mL obtained at the time of admission to the ICU is a strong predictor of short-term mortality.

Measurement of serum free cortisol shows discordant responsivity to stress and dynamic evaluation

CONTEXT

Routinely available assays of adrenal function measure serum total cortisol (TC) and not the biologically active free cortisol (FC). However, there are few data on FC levels during surgical stress and in response to standard pharmacological tests.

OBJECTIVE

Our objective was to evaluate TC and FC levels in different states of physical stress.

DESIGN AND SETTING

We conducted a prospective observational study in a university hospital.

PARTICIPANTS AND MAIN OUTCOME MEASURES

We measured TC and FC levels in 64 patients: group A, 17 healthy controls without stress; group B, 23 medical patients with moderate stress; and group C, 24 surgical patients undergoing coronary bypass grafting. Cortisol levels in group C were measured basally and at several time points thereafter and were compared with responsivity to a pharmacological dose of ACTH. FC was measured using equilibrium dialysis.

RESULTS

In group C patients after extubation, the relative increase above basal FC was higher than the increase in TC levels (399 +/- 266 vs. 247 +/- 132% of initial values, respectively; mean +/- sd; P = 0.02) and then fell more markedly, FC levels falling to 67 +/- 49% and TC levels to 79 +/- 36% (P = 0.04). After ACTH stimulation, TC levels increased to 680 +/- 168 nmol/liter, which was similar to the increase with major stress (811 +/- 268 nmol/liter). In contrast, FC levels increased to 55 +/- 16 nmol/liter after ACTH stimulation but significantly greater with surgical stress to 108 +/- 56 nmol/liter (P < 0.001).

CONCLUSION

The more pronounced increase in FC seen during stress as compared with the ACTH test suggests that this test does not adequately anticipate the FC levels needed during severe stress.