Propofol-containing sedatives increase levels of parathyroid hormone

OBJECTIVE

To evaluate the effects of propofol and propofol containing disodium edetate (ethylenediaminetetraacetic acid [EDTA]) on the parathyroid-calcium axis in normal subjects.

DESIGN

Randomised, double-blind, age-stratified, crossover trial.

SETTING

Single centre.

PATIENTS

A total of 50 healthy subjects.

INTERVENTIONS

Each subject was randomised to receive propofol or propofol containing EDTA on day 1 and the alternate treatment between days 15 and 29, with a 2-week wash-out period in between. On the day of treatment, subjects received a bolus of trial medication (1 or 2 mg/kg) followed by a 60-minute observation period. At the end of 60 minutes, subjects received trial medication infused for 60 minutes at 1 of 4 randomised infusion rates (25, 50, 100, or 200 microg/kg per min). Subjects were monitored for an additional 60 minutes following the infusion.

MEASUREMENTS AND RESULTS

Blood pressure, heart rate, respiratory rate, oxygen saturation, blood ionised calcium concentration, serum total magnesium concentration, serum intact parathyroid hormone (PTH) level, and plasma EDTA level were assessed at periodic intervals during and following the bolus and continuous infusion of trial medication. Mean arterial pressure significantly decreased (p < 0.05) following the bolus injection of both trial medications and returned to baseline at 60 minutes; it significantly decreased again during the continuous infusion and returned to baseline during recovery. Heart rate and respiratory rate fluctuated in both groups with significant increases and decreases throughout the study period following the bolus injection; both returned to baseline during the recovery period in each group. Ionised calcium and total magnesium concentrations remained within normal limits and were unchanged in response to both study medications. PTH levels significantly increased following the bolus injection of both study drugs. The increase in PTH levels was greater with higher doses of study medication during the infusion period. There was no difference in the response of blood pressure, heart rate, respiratory rate, or PTH levels between propofol and propofol with EDTA. EDTA levels increased significantly during the infusion of propofol with EDTA, reaching mean levels of 240 ng/mL.

CONCLUSIONS

The results of this study indicate that propofol increases PTH levels in normal subjects; however, propofol with EDTA does not alter ionised calcium or total magnesium concentrations.

Trace element homeostasis during continuous sedation with propofol containing EDTA versus other sedatives in critically ill patients

OBJECTIVE

To evaluate changes in serum and urinary zinc, cobalt, copper, iron, and calcium concentrations in critically ill patients receiving propofol containing disodium edetate (disodium ethylenediaminetetraacetic acid [EDTA]) versus sedative agents without EDTA.

DESIGN

This was a randomised, open-label, parallel-group study with randomisation stratified by baseline Acute Physiology and Chronic Health Evaluation (APACHE II) scores.

SETTING

Intensive care units (ICU) in 23 medical centres.

PATIENTS

Medical, surgical, or trauma ICU patients 17 years of age or older who required mechanical ventilator support and sedation.

INTERVENTIONS

A total of 106 patients received propofol containing 0.005 % EDTA (propofol EDTA), and 104 received other sedative agents without EDTA (non-EDTA). Only the first 108 patients were assessed for urinary trace metal excretion. Twenty-four-hour urine samples were collected on days 2, 3, and 7 and every 7 days thereafter for determination of zinc, cobalt, copper, iron, and calcium excretion; EDTA levels; urine osmolality; albumin levels; and glucose levels. The first 143 patients were assessed for serum concentration of zinc, cobalt, copper, iron, and calcium; creatinine; blood urea nitrogen; and albumin at baseline and once during each 24-hour urine collection.

MEASUREMENTS AND RESULTS

For the assessment of trace metals, patients receiving propofol EDTA demonstrated increased mean urinary excretion of zinc, copper, and iron compared with the normal range. All patients receiving sedatives demonstrated increased urinary excretion of zinc and copper above normal reference values. Compared with the non-EDTA sedative group, the propofol EDTA group demonstrated increased urinary excretion of zinc and iron. Mean serum concentrations of zinc and total calcium were decreased in both patient groups. Serum zinc concentrations increased from baseline to day 3 in the non-EDTA sedative group but not in the propofol EDTA group. Renal function, measured by blood urea nitrogen, serum creatinine, and creatinine clearance, did not deteriorate during ICU sedation with either regimen.

CONCLUSION

This study showed that critical illness is associated with increased urinary losses of zinc, copper, and iron. Propofol EDTA-treated patients had greater urinary losses of zinc and iron and lower serum zinc concentrations compared with the non-EDTA sedative group. No adverse events indicative of trace metal deficiency were observed in either group. The clinical significance of trace metal losses during critical illness is unclear and requires further study.

Safety and efficacy of propofol with EDTA when used for sedation of surgical intensive care unit patients

OBJECTIVE

To compare propofol with disodium edetate (EDTA) and propofol without EDTAwhen used for the sedation of critically ill surgical intensive care unit (ICU) patients.

DESIGN

Prospective, randomised, multicentre trial.

PATIENTS

A total of 122 surgical ICU patients who required intubation and mechanical ventilation.

INTERVENTIONS

Patients were randomised to receive either propofol or propofol plus EDTA (propofol EDTA) by continuous infusion for sedation.

MEASUREMENTS AND RESULTS

The addition of EDTA to propofol had no effect on calcium or magnesium homeostasis, renal function, haemodynamic function, or efficacy when used for the sedation of surgical patients in the ICU. The most common adverse events were hypotension, atrial fibrillation, and hypocalcaemia. In this trial, a greater number of serious adverse events and adverse events leading to withdrawal occurred in the propofol group relative to the propofol EDTA group. There was a significantly lower crude mortality rate at 7 and 28 days for the propofol EDTA group compared with the propofol group. There were no statistically significant differences between groups with respect to depth of sedation.

CONCLUSION

The propofol EDTA formulation had no effect on calcium or magnesium homeostasis, renal function, or sedation efficacy compared with propofol alone when used for sedation in critically ill surgical ICU patients. There was a significant decrease in mortality in the propofol EDTA group compared with the propofol group. Further investigations are needed to validate this survival benefit and elucidate a possible mechanism.

Cation metabolism during propofol sedation with and without EDTA in patients with impaired renal function

OBJECTIVE

To compare the effects of propofol with and without disodium edetate (EDTA) on cation metabolism in intensive care unit (ICU) patients with renal insufficiency who received propofol or propofol plus EDTA (propofol EDTA) for sedation and mechanical ventilation.

DESIGN

Double-blind, randomised, multicentre study.

SETTING

Medical and surgical ICUs from 5 hospitals.

PATIENTS

Thirty-nine ICU patients with acute and chronic renal impairment expected to require at least 24 hours of continuous sedation and respiratory failure necessitating mechanical ventilation.

INTERVENTIONS

Propofol or propofol EDTA administered for sedation by continuous intravenous infusion.

MEASUREMENTS AND RESULTS

The depth of sedation, as measured by the Modified Ramsay Sedation Scale, was similar in the 2 groups, when adjusted for dosing differences. The amount of propofol required to maintain adequate sedation was decreased in both groups compared to propofol requirements in ICU patients with normal renal function. EDTA levels were elevated at baseline in both groups. In the propofol EDTA group, the EDTA levels increased further by 20 % but decreased to below baseline EDTA levels at 48 hours after sedation. In the propofol group, EDTA levels decreased during sedation and remained below baseline levels at 48 hours after sedation. PATIENTS in both groups were hypocalcaemic and hyperphosphataemic at baseline with low levels of 1,25-dihydroxyvitamin D and elevated parathyroid hormone (PTH) levels. Other than a slight difference in ionised serum calcium levels at 4 h after the start of sedation, there were no significant differences observed in serum calcium levels between the two groups. There were no significant differences in 1,25-dihydroxyvitamin D or PTH levels over time between the two groups. There was no significant effect on renal function in either group.

CONCLUSIONS

The results of this study suggest that adding EDTA to propofol does not adversely affect cation homeostasis or renal function when used for sedation of ICU patients with renal insufficiency. Although EDTA levels increased over time from baseline levels in patients with renal insufficiency who receive propofol EDTA, this increase does not appear to be clinically significant, and EDTA levels return to below baseline levels within 48 hours of discontinuing the propofol EDTA infusion. The efficacy of propofol with and without EDTA also appears comparable in these patients.

Patient characteristics and ICU organizational factors that influence frequency of pulmonary artery catheterization

CONTEXT

Hemodynamic monitoring of patients with a pulmonary artery catheter is controversial because there are few data confirming its effectiveness, and patient and intensive care unit (ICU) organizational factors associated with its use are unknown.

OBJECTIVE

To determine pulmonary artery catheter use in relationship to type of ICU organization and staffing, and patient characteristics, including severity of illness and insurance coverage.

DESIGN, SETTING, AND PATIENTS

Retrospective database study of 10,217 nonoperative patients who received treatment at 34 medical, mixed medical and surgical, and surgical ICUs at 27 hospitals during 1998 (patients were enrolled in Project IMPACT).

MAIN OUTCOME MEASURES

Pulmonary artery catheter use based on severity of illness measured by the Simplified Acute Physiology Score, resuscitation status at ICU admission, and ICU organizational variables, including type, size, and model.

RESULTS

A pulmonary artery catheter was used for 831 patients (8.1%) in the ICU. In multivariate analysis adjusted for severity of illness, age, diagnosis, and do-not-resuscitate status, full-time ICU physician staffing was associated with a two-thirds reduction in the probability of catheter use (odds ratio [OR], 0.36; 95% confidence interval [CI], 0.28-0.45). Higher catheter use was associated with white race (OR, 1.38; 95% CI, 1.10-1.72) and private insurance coverage (OR, 1.33; 95% CI, 1.10-1.60). Admission to a surgical ICU was associated with a 2-fold increase in probability of catheter use (OR, 2.17; 95% CI, 1.70-2.76) compared with either medical or mixed medical and surgical ICUs.

CONCLUSION

Organizational characteristics of ICUs, insurance reimbursement, and race, as well as clinical variables, are associated with variation in practice patterns regarding pulmonary artery catheter use. Understanding such influences, combined with studies measuring clinical and economic outcomes, can contribute to the development of policies for the rational use of pulmonary artery catheters. JAMA. 2000;283:2559-2567

Use of flexible intermediate and intensive care to reduce multiple transfers of patients

OBJECTIVE

To test an alternative flexible approach to traditional fixed intermediate and intensive care to minimize transfers of patients.

METHODS

Patients admitted to a 28-bed nursing unit with intermediate care potential and a 12-bed intensive care unit at a 300-bed teaching community hospital were studied. The group included 524 patients with a discharge diagnosis code for mechanical ventilation. During eight 3-week cycles, 1073 transfers of patients were tabulated. A plan-do-study-act method was used to improve weaning from mechanical ventilation and reduce the number of inappropriate days in intensive care. Admissions and transfers to the 2 units for all patients during the eight 3-week cycles were compared over time. Length of stay and mortality were noted for all patients treated with conventional and noninvasive ventilation.

RESULTS

Direct admissions to the flexible intermediate unit increased with no overall change in admissions to the intensive care unit. Fewer patients needed conventional ventilation, and more in both units were treated with noninvasive ventilation. The median number of transfers per patient treated with mechanical ventilation decreased from 1.94 to 1.20. Length of stay and mortality also decreased among such patients. Some cost savings were attributable to the decrease in the number of transfers. Transfers out of the hospital directly from the intensive care unit increased from 2.24% to 4.43%.

CONCLUSIONS

In a community teaching hospital, flexible care policies decreased the number of in-hospital transfers of patients treated with mechanical ventilation.

Use of flexible intermediate and intensive care to reduce multiple transfers of patients

OBJECTIVE: To test an alternative flexible approach to traditional fixed intermediate and intensive care to minimize transfers of patients. METHODS: Patients admitted to a 28-bed nursing unit with intermediate care potential and a 12-bed intensive care unit at a 300-bed teaching community hospital were studied. The group included 524 patients with a discharge diagnosis code for mechanical ventilation. During eight 3-week cycles, 1073 transfers of patients were tabulated. A plan-do-study-act method was used to improve weaning from mechanical ventilation and reduce the number of inappropriate days in intensive care. Admissions and transfers to the 2 units for all patients during the eight 3-week cycles were compared over time. Length of stay and mortality were noted for all patients treated with conventional and noninvasive ventilation. RESULTS: Direct admissions to the flexible intermediate unit increased with no overall change in admissions to the intensive care unit. Fewer patients needed conventional ventilation, and more in both units were treated with noninvasive ventilation. The median number of transfers per patient treated with mechanical ventilation decreased from 1.94 to 1.20. Length of stay and mortality also decreased among such patients. Some cost savings were attributable to the decrease in the number of transfers. Transfers out of the hospital directly from the intensive care unit increased from 2.24% to 4.43%. CONCLUSIONS: In a community teaching hospital, flexible care policies decreased the number of in-hospital transfers of patients treated with mechanical ventilation.

Effect of local standards on the implementation of national guidelines for asthma: primary care agreement with national asthma guidelines

OBJECTIVE

To assess the level of modification by local primary care doctors of key aspects of the National Asthma Education Program (NAEP) Guidelines for the Diagnosis and Management of Asthma.

DESIGN

A random sample of primary care physicians participating in local asthma guideline development.

SETTING

Two hospital systems, one based in an urban environment, and a second in a community and rural environment.

PARTICIPANTS

Primary care physicians.

INTERVENTION

Design of consensus-based local asthma guidelines using a modified Delphi approach.

MEASUREMENTS AND MAIN RESULTS

A total of 42 physicians participated in the local guideline development. With few exceptions, the primary care physicians modified in major ways the NAEP Guidelines regarding the role of pulmonary function testing and spirometry. Specifically, the local guidelines did not require peak flow and spirometry measurements as the basis for initiating inhaled steroids as did the national guidelines. All 42 physicians emphasized a clinical diagnosis versus one based on a pulmonary function. Peak flow monitoring was recommended by 35 (83%) of physicians in selected patients only, in contrast to the national guidelines, which emphasized monitoring for all patients routinely and during exacerbations. There was strong agreement with the national guidelines on the role and importance of patient education, and on the indications for the use of inhaled steroids.

CONCLUSIONS

Disagreement by primary care doctors with parts of the NAEP guideline is a potential cause for poor compliance and lack of influence on patient care. Recognizing the need to modify or customize guidelines through field testing with local primary care physicians will improve acceptance of national guidelines.

Economic implications of the timing of do-not-resuscitate orders for ICU patients

Healthcare reform continues to move forward, with the influence of managed care increasing in most areas of the United States. Strategies for cost containment are being considered to limit marginally beneficial health care, including futile-care policies, capitation, preset limits on health care, and guidelines for writing do-not-resuscitate (DNR) orders. Recent studies which attempted to improve communication between patients and physicians have failed to improve the quality of end-of-life care offered by healthcare providers. In other recent works, the timing of when DNR orders are written has been associated with shortening needed hospital and ICU care, as well as effecting significant reductions in resources utilized. This study reviews the current literature with respect to the timing of when DNR orders are written. We present a conservative estimate that for each ICU patient moved from late DNR to early DNR status, approximately $10,000 per patient could be saved. Moreover, approximately 0.5% of all ICU care could be limited should DNR orders be written earlier in a patient's hospital or ICU stay. In addition, a shift from open-format ICUs to semiclosed units managed by qualified critical care physician directors would reduce the number of patients with futile or failed cardiopulmonary resuscitation, and increase the number of patients having care withheld or withdrawn after failed ICU therapy. Such a change would result in more substantial savings.

Effect of changing patient mix on the performance of an intensive care unit severity-of-illness model: how to distinguish a general from a specialty intensive care unit

OBJECTIVE

To analyze the effects of patient mix diversity on performance of an intensive care unit (ICU) severity-of-illness model.

DESIGN

Multiple patient populations were created using computer simulations. A customized version of the Mortality Probability Model (MPM) II admission model was used to ascertain probabilities of hospital mortality. Performance of the model was assessed using discrimination (area under the receiver operating characteristic curve) and calibration (goodness-of-fit testing).

SETTING

Intensive care units.

PATIENTS

Data were collected from 4,224 ICU patients from two Massachusetts hospitals (Baystate Medical Center, Springfield, MA; University of Massachusetts Medical Center, Worcester, MA) and two New York hospitals (Albany Medical Center, Albany, NY; Ellis Hospital, Schenectady, NY).

INTERVENTIONS

Random samples were taken from a database. The percentage of patients with each model disease characteristic was varied by assigning weights (ranging from 0 to 10) to patients with a disease characteristic. Three simulations were run for each of 15 model variables at each of 16 weights, totaling 720 simulations.

MEASUREMENTS AND MAIN RESULTS

The area under the receiver operating characteristic curve and model fit were assessed in each random sample. Removing patients with a given disease characteristic did not affect discrimination or calibration. Increasing frequency of patients with each disease characteristic above the original frequency caused discrimination and calibration to deteriorate. Model fit was more robust to increases in less frequently occurring patient conditions. From the goodness-of-fit test, a critical percentage for each admission model variable was determined for each disease characteristic, defined as the percentage at which the average p value for the test over the three replications decreased to < .10.

CONCLUSIONS

The concept of critical percentages is potentially clinically important. It might provide an easy first step in checking applicability of a given severity-of-illness model and in defining a general medical-surgical ICU. If the critical percentages are exceeded, as might occur in a highly specialized ICU, the model would not be accurate. Alternative modeling approaches might be to customize the model coefficients to the population for more accurate probabilities or to develop specialized models. The MPM approach remained robust for a large variation in patient mix factors.

The Logistic Organ Dysfunction system. A new way to assess organ dysfunction in the intensive care unit. ICU Scoring Group

OBJECTIVE

To develop an objective method for assessing organ dysfunction among intensive care unit (ICU) patients on the first day of the ICU stay.

DESIGN AND SETTING

Physiological variables defined dysfunction in 6 organ systems. Logistic regression techniques were used to determine severity levels and relative weights for the Logistic Organ Dysfunction (LOD) score and for conversion of the LOD score to a probability of mortality.

PATIENTS

A total of 13 152 consecutive admission to 137 adult medical/surgical ICUs in 12 countries from the European/North American Study of Severity Systems.

OUTCOME MEASURES

Patient vital status at hospital discharge.

RESULTS

The LOD System identified from 1 to 3 levels of organ dysfunction for 6 organ systems: neurologic, cardiovascular, renal, pulmonary, hematologic, and hepatic. From 1 to 5 LOD points were assigned to the levels of severity, and the resulting LOD scores ranged from 0 to 22 points. Model calibration was very good in the developmental and validation samples (P=.21 and P=.50, respectively), as was model discrimination (area under the receiver operating characteristic curves of 0.843 and 0.850, respectively).

CONCLUSION

The LOD System provides an objective tool for assessing severity levels for organ dysfunction in the ICU, a critical component in the conduct of clinical trials. Neurologic, cardiovascular, and renal dysfunction were the most severe organ dysfunctions, followed by pulmonary and hematologic dysfunction, with hepatic dysfunction the least severe. The LOD System takes into account both the relative severity among organ systems and the degree of severity within an organ system.

The Logistic Organ Dysfunction system. A new way to assess organ dysfunction in the intensive care unit. ICU Scoring Group

OBJECTIVE

To develop an objective method for assessing organ dysfunction among intensive care unit (ICU) patients on the first day of the ICU stay.

DESIGN AND SETTING

Physiological variables defined dysfunction in 6 organ systems. Logistic regression techniques were used to determine severity levels and relative weights for the Logistic Organ Dysfunction (LOD) score and for conversion of the LOD score to a probability of mortality.

PATIENTS

A total of 13 152 consecutive admission to 137 adult medical/surgical ICUs in 12 countries from the European/North American Study of Severity Systems.

OUTCOME MEASURES

Patient vital status at hospital discharge.

RESULTS

The LOD System identified from 1 to 3 levels of organ dysfunction for 6 organ systems: neurologic, cardiovascular, renal, pulmonary, hematologic, and hepatic. From 1 to 5 LOD points were assigned to the levels of severity, and the resulting LOD scores ranged from 0 to 22 points. Model calibration was very good in the developmental and validation samples (P=.21 and P=.50, respectively), as was model discrimination (area under the receiver operating characteristic curves of 0.843 and 0.850, respectively).

CONCLUSION

The LOD System provides an objective tool for assessing severity levels for organ dysfunction in the ICU, a critical component in the conduct of clinical trials. Neurologic, cardiovascular, and renal dysfunction were the most severe organ dysfunctions, followed by pulmonary and hematologic dysfunction, with hepatic dysfunction the least severe. The LOD System takes into account both the relative severity among organ systems and the degree of severity within an organ system.

The relationship between age and the use of DNR orders in critical care patients. Evidence for age discrimination

OBJECTIVE

To determine whether a relationship exists between the use of do-not-resuscitate (DNR) orders in the intensive care unit and the age of the patient after controlling for the severity of illness.

METHODS

Patients from the Mortality Probability Model database, which includes 6103 patients in 4 large hospitals, and from a second database, which includes 3226 additional patients in 25 hospitals, were analyzed through logistic regression seeking a relationship between age and DNR use. Adult medical and surgical intensive care units from 27 hospitals in the United States were included.

RESULTS

In the Mortality Probability Model database, 11.4% of the patients had DNR orders written. In the group of patients younger than 65 years, 8% had DNR orders. This percentage climbed rapidly with age. For age ranges of 65 to younger than 75 years, 75 to younger than 85 years, and 85 years or older, the percentage of patients who had a DNR order was 11.2%, 18.9%, and 32.6%, respectively. Similar results were found in the second database: 5.4% of patients had DNR orders and, again, the rise in the use of DNR orders was associated with increased age. For patients younger than 75 years, 4.2% had DNR orders. For the older groups, 75 to younger than 85 years and 85 years and older, the rates were 8.8% and 15.4%, respectively. Logistic regression was used to control for severity of illness; when compared with patients younger than 65 years, patients 75 to younger than 85 years were 50% more likely to have DNR orders written and patients 85 years or older were 140% more likely to have DNR orders written.

CONCLUSIONS

Older patients (> or = 75 years old) are significantly more likely than younger patients to have DNR orders written even after the severity of illness is controlled as a confounding variable. This association suggests age discrimination and becomes stronger as patient age increases.

Resource use implications of do not resuscitate orders for intensive care unit patients

This study describes the use of do not resuscitate (DNR) orders for ICU patients in four northeastern U.S. teaching hospitals and investigates the relationship between DNR orders and length of stay. The use of detailed data from the mortality probability model (MPM II) study on 6,290 consecutive ICU admissions to general adult medical and surgical ICUs during 1989 through 1991 allows us to control for severity of illness and the time during the ICU stay at which the DNR order was entered. About 12.8% of patients were DNR during their ICU stay, including more than half of nonsurvivors. The percentage of patients with DNR was higher for older and more severely ill patients. Most DNR orders were issued after 72 h in the ICU, but many were issued during the first ICU day. Nonsurvivors with early (first 24 h) DNR had shorter mean and median ICU and hospital stays than the comparison group of non-DNR patients. The percentage of patients with very long ICU (> 30 d) and hospital (> 60 d) stays was smaller among DNR patients. The use of DNR orders, particularly early in the ICU stay, may be associated with significant resource use reduction for an identifiable group of patients.

Factors affecting the performance of the models in the Mortality Probability Model II system and strategies of customization: a simulation study

OBJECTIVES

To examine the impact of hospital mortality and intensive care unit (ICU) size on the performance of the Mortality Probability Model II system for use in quality assessment, and to examine the ability of model customization to produce accurate estimates of hospital mortality to characterize patients by severity of illness for clinical trials.

DESIGN

Prospective evaluation of model performance, using retrospective data.

SETTING

Data for the simulation were assembled from six adult medical and surgical ICUs in Massachusetts and New York.

PATIENTS

Consecutive admissions (n = 4,224) to the Massachusetts and New York ICUs were studied. The mortality rate in the database was 18.7%.

INTERVENTIONS

A computer simulation of several different hospital mortality rates and ICU sample sizes, using a multicenter database of consecutive ICU admissions, was utilized. We simulated 20 different mortality rates by randomly changing the outcomes at hospital discharge from "survived" to "deceased" and from "deceased" to "survived". Four sample size simulations used 75%, 50%, 25%, and 10% of the database. Ten replications of each mortality rate and samples size were constructed, and model calibration and discrimination were assessed for each replication. Model coefficients were customized, using logistic regression.

MEASUREMENTS AND MAIN RESULTS

Vital status at hospital discharge was the outcome measure among the ICU patient population. Model performance was assessed using the Hosmer-Lemeshow C statistic for calibration, and the area under the receiver operating characteristic curve for discrimination. Goodness-of-fit tests and receiver operating characteristic curve areas demonstrated that the models were sensitive to differences in hospital mortality, indicating that they are useful quality assurance tools. Goodness-of-fit tests were more sensitive than the receiver operating characteristic curve areas. The further the hospital mortality rate diverged from the original rate, the worse the performance of the model. Sample size had an impact on these results. The smaller the sample size, the less likely the model was to perform poorly. Model coefficients were successfully customized to demonstrate that improved model performance can be achieved when necessary for clinical trial stratification.

CONCLUSION

Mortality Probability Model II models can be used to assess quality of care in ICUs, but the size of the sample should be considered when assessing calibration and discrimination.

Outcome prediction for individual intensive care patients: useful, misused, or abused?

Probabilities of hospital mortality provide meaningful information in many contexts, such as in discussions of patient prognosis by intensive care physicians, in patient stratification for analysis of clinical trial data by researchers, and in hospital reimbursement analysis by insurers. Use of probabilities as binary predictors based on a cut point can be misleading for making treatment decisions for individual patients, however, even when model performance is good overall. Alternative models for estimating severity of illness in intensive care unit (ICU) patients, while demonstrating good agreement for describing patients in the aggregate, are shown to differ considerably for individual patients. This suggests that identifying patients unlikely to benefit from ICU care by using models must be approached with considerable caution.

A comparison of intensive care unit utilization in Alberta and western Massachusetts

OBJECTIVE

To analyze differences in intensive care unit (ICU) utilization between a Canadian province and a U.S. area.

DESIGN

Retrospective data analysis of hospital discharge data and existing data from an international study of severity of illness in ICU patients.

SETTING

Administrative data for the province of Alberta and the four counties of western Massachusetts for the years 1990 to 1991 were used. Detailed data on consecutive ICU admissions from two Alberta hospitals, one western Massachusetts hospital, and 24 other U.S. hospitals for 3 months in 1991 were used.

MEASUREMENTS AND MAIN RESULTS

ICU use and hospital mortality rates were compared for 50,030 hospital admissions divided into 11 patient groups. ICU days per million population were two to three times as great in western Massachusetts as in Alberta. The primary reason was higher ICU incidence (percent of hospitalized patients treated in the ICU) rather than a difference in hospital admission rate or length of ICU stay. ICU incidence in western Massachusetts was significantly higher in ten of 11 patient groups--for the coronary bypass surgery group, there was no difference. The hospital mortality rate in western Massachusetts was similar to, or higher than, the mortality rate in Alberta. In Alberta, a much higher proportion of ICU patients received mechanical ventilation. For elective surgery patients, the ICU severity of illness was lower in western Massachusetts and in other U.S. hospitals than in Alberta.

CONCLUSIONS

Western Massachusetts hospitalized patients are more likely to be treated in an ICU than are similar patients in Alberta. There is no evidence that the greater ICU utilization in western Massachusetts led to a lower hospital mortality rate.

Customized probability models for early severe sepsis in adult intensive care patients. Intensive Care Unit Scoring Group

OBJECTIVE

To develop customized versions of the Simplified Acute Physiology Score II (SAPS II) and the 24-hour Mortality Probability Model II (MPM II) to estimate the probability of mortality for intensive care unit patients with early severe sepsis.

DESIGN AND SETTING

Logistic regression models developed for patients with severe sepsis in a database of adult medical and surgical intensive care units in 12 countries.

PATIENTS

Of 11,458 patients in the intensive care unit for at least 24 hours, 1130 had severe sepsis based on criteria of the American College of Chest Physicians and the Society of Critical Care Medicine (systemic inflammatory response syndrome in response to infection, plus hypotension, hypoperfusion, or multiple organ dysfunction).

RESULTS

In patients with severe sepsis, mortality was higher (48.0% vs 19.6% among other patients) and 28-day survival was lower. The customized SAPS II was well calibrated (P = .92 for the goodness-of-fit test) and discriminated well (area under the receiver operating characteristic [ROC] curve, 0.78). Performance in the validation sample was equally good (P = .85 for the goodness-of-fit test; area under the ROC curve, 0.79). The customized MPM II was well calibrated (P = .92 for the goodness-of-fit test) and discriminated well (area under the ROC curve, 0.79). Performance in the validation sample was equally good (P = .52 for the goodness-of-fit test; area under the ROC curve, 0.75). The models are independent of each other; either can be used alone to estimate the probability of mortality of patients with severe sepsis.

CONCLUSIONS

Customization provides a simple technique to apply existing models to a subgroup of patients. Accurately assessing the probability of hospital mortality is a useful adjunct for clinical trials.

Mortality probability models for patients in the intensive care unit for 48 or 72 hours: a prospective, multicenter study

OBJECTIVE

To develop models in the Mortality Probability Model (MPM II) system to estimate the probability of hospital mortality at 48 and 72 hrs in the intensive care unit (ICU), and to test whether the 24-hr Mortality Probability Model (MPM24), developed for use at 24 hrs in the ICU, can be used on a daily basis beyond 24 hrs.

DESIGN

A prospective, multicenter study to develop and validate models, using a cohort of consecutive admissions.

SETTING

Six adult medical and surgical ICUs in Massachusetts and New York adjusted to reflect 137 ICUs in 12 countries.

PATIENTS

Consecutive admissions (n = 6,290) to the Massachusetts/New York ICUs were studied. Of these patients, 3,023 and 2,233 patients remained in the ICU and had complete data at 48 and 72 hrs, respectively. Patients < 18 yrs of age, burn patients, coronary care patients, and cardiac surgical patients were excluded.

OUTCOME MEASURE

Vital status at the time of hospital discharge.

RESULTS

The models consist of five variables measured at the time of ICU admission and eight variables ascertained at 24-hr intervals. The 24-hr model demonstrated poor calibration and discrimination at 48 and 72 hrs. The newly developed 48- and 72-hr models--MPM48 and MPM72--contain the same 13 variables and coefficients as the MPM24. The models differ only in their constant terms, which increase in a manner that reflects the increasing probability of mortality with increasing length of stay in the ICU. These constant terms were adjusted by a factor determined from the relationship between the data from the six Massachusetts and New York ICUs and a more extensive data set, from which the ICU admission Mortality Probability Model (MPM0) and MPM24 were developed. This latter data set was assembled from ICUs in 12 countries. The MPM48 and MPM72 calibrated and discriminated well, based on goodness-of-fit tests and area under the receiver operating characteristic curve.

CONCLUSIONS

Models developed for use among ICU patients at one time period are not transferable without modification to other time periods. The MPM48 and MPM72 calibrated well to their respective time periods, and they are intended for use at specific points in time. The increasing constant terms and associated increase in the probability of hospital mortality exemplify a common clinical adage that if a patient's clinical profile stays the same, he or she is actually getting worse.

A method for assessing the clinical performance and cost-effectiveness of intensive care units: a multicenter inception cohort study

OBJECTIVES

To present an approach for assessing intensive care unit (ICU) performance which takes into account both economic and clinical performance while adjusting for severity of illness. To present a graphic display which permits comparisons among a group of hospitals.

DESIGN

A multicenter, inception cohort study.

SETTING

Twenty-five ICUs in U.S. hospitals that participated in the European and North American Study of Severity Systems for ICU Patients.

PATIENTS

Consecutive patients (n = 3,397) admitted to ICUs in participating hospitals between September 30, 1991 and December 27, 1991. Excluded were coronary care patients, burn patients, cardiac surgery patients and patients aged < 18 yrs.

MEASUREMENTS AND MAIN RESULTS

The clinical performance index is the difference between observed hospital survival rate and survival rate predicted by the Mortality Probability Model measuring severity of illness at ICU admission. The economic performance (resource use) measure is a length of stay index, Weighted Hospital Days, which weights ICU days more heavily than non-ICU days. The economic performance index is the difference between actual mean resource use and the resource use predicted by a regression including severity of illness and percent of surgical patients. Both the clinical and economic performance indices are standardized to show how far a particular hospital is from the overall mean and are graphed together. Most of the 25 hospitals lie within 1 SD of the mean on both clinical and economic performance scales. The graph makes it easy to identify those hospitals that are outside this range. There is no evidence of a trade-off between high clinical performance and high economic performance; i.e., it is possible to achieve both.

CONCLUSIONS

Cross-indexing of clinical and economic ICU performance is easy to calculate. It has potential as a research and evaluation tool used by physicians, hospital administrators, payers, and others.

Why severity models should be used with caution

There are now two validated time points for predicting hospital mortality of ICU patients--at admission and at 24 hours. The best purposes include evaluation of high clinical performance ICUs and for patients being enrolled in clinical trials. For the latter purpose, the model must be calibrated in the individual hospital to ensure that the model is applicable. This can be estimated by using goodness-of-fit testing. There are fewer uses for physiology scores and increased emphasis on converting scores to probabilities. For individual patient application, the model should be demonstrated to have high discrimination, as measured by the area under the receiver operating characteristic curve, and high calibration, as defined by goodness-of-fit testing. Although models have improved substantially and are now based on much larger databases, there is considerable uncertainty in their application for insurance purposes, triage, regulatory applications, sanctions against individual physicians, and cost containment. Current models may not adequately describe important ICU conditions such as adult respiratory distress syndrome and multi-organ dysfunction occurring after 24 hours into ICU care. For family discussions regarding prognosis of individual patients, ICU severity models must be used cautiously at admission or after 24 hours, with the understanding of the strengths and weakness of estimating probabilities of hospital mortality. The mathematical link between physiology score and estimation of hospital mortality is established only for the time point of 24 hours after ICU admission. Calibration and discrimination of the admission and 24-hour models also must be performed within each hospital in which individual probabilities are presented to families. It may be possible to customize a probability model such as MPM to achieve a high level of calibration at the individual hospital level.

Nosocomial pneumonia during stress ulcer prophylaxis with cimetidine and sucralfate

BACKGROUND

Recent studies have questioned the use of histamine (H2) receptor antagonist in stress ulcer prophylaxis because of an increased incidence of nosocomial pneumonia and subsequent death.

DESIGN

This prospective randomized study compared prophylaxis with cimetidine vs sucralfate.

SETTING

Medical/surgical intensive care unit in Springfield, Mass.

PATIENTS

One hundred fourteen patients were enrolled.

INTERVENTIONS

Cimetidine, administered as a primed continuous infusion using a 300-mg bolus followed by 37.5 mg/h, was compared with sucralfate, administered via nasogastric tube, at a dosage of 1 g every 6 hours suspended in 20 mL of sterile water.

MAIN OUTCOME MEASURES

End points of the study included nosocomial pneumonia, gastrointestinal hemorrhage, and death.

RESULTS

Fifty-six patients were randomized to receive cimetidine and their rate of pneumonia was 12.5%; upper gastrointestinal hemorrhage, 3.6%; and mortality, 33.9%. Fifty-eight patients were given sucralfate, and their rate of pneumonia was 13.8%; upper gastrointestinal hemorrhage, 3.4%; and mortality, 37.9%. There were no significant differences between these study end points. In patients who had pneumonia, 80% of isolates were aerobic gram-negative bacilli.

CONCLUSIONS

These observations suggest that the rate of nosocomial pneumonia is not increased in patients in the intensive care unit who receive prophylaxis with cimetidine to prevent stress ulcer bleeding.

Mortality Probability Models (MPM II) based on an international cohort of intensive care unit patients

OBJECTIVE

To revise and update models in the Mortality Probability Model (MPM II) system to estimate the probability of hospital mortality among 19,124 intensive care unit (ICU) patients that can be used for quality assessment within and among ICUs.

DESIGN AND SETTING

Models developed and validated on consecutive admissions to adult medical and surgical ICUs in 12 countries.

PATIENTS

A total of 12,610 patients for model development, 6514 patients for model validation. Patients younger than 18 years and burn, coronary care, and cardiac surgery patients were excluded.

OUTCOME MEASURE

Vital status at hospital discharge.

RESULTS

The admission model, MPM0, contains 15 readily obtainable variables. In developmental and validation samples it calibrated well (goodness-of-fit tests: P = .623 and P = .327, respectively, where a high P value represents good fit between observed and expected values) and discriminated well (area under the receiver operating characteristic curve = 0.837 and 0.824, respectively). The 24-hour model, MPM24 (developed on 10,357 patients still in the ICU at 24 hours), contains five of the admission variables and eight additional variables easily ascertained at 24 hours. It also calibrated well (P = .764 and P = .231 in the developmental and validation samples, respectively) and discriminated well (area under the receiver operating characteristic curve = 0.844 and 0.836 in the developmental and validation samples, respectively).

CONCLUSIONS

Among severity systems for intensive care patients, the MPM0 is the only model available for use at ICU admission. Both MPM0 and MPM24 are useful research tools and provide important clinical information when used alone or together.

Using severity measures to describe high performance intensive care units

This article describes the use of various scores and probabilities to clinically categorize patients in the adult intensive care unit. Some of the limitations of these severity measures are reviewed including variable definitions, timing of measurements, and whether models can be used for individual patients. Also, this article discusses how probability models may be used to compare similar types of intensive care units using standardized clinical and cost performance indices.

Trends from the United States with end of life decisions in the intensive care unit

OBJECTIVE

To describe the changes that have occurred in the United States since medicine has moved away from a paternalistic model to one that promotes patient autonomy and self-determination. To discuss the implications for cardiopulmonary resuscitation (CPR) and the increasing use of when not to perform CPR and other life-sustaining therapies. To describe the various interpretations of the ritual term Do-Not-Resuscitate (DNR) and to introduce the concept of futility in the context of non-beneficial over-treatment and discriminatory under-treatment.

SETTING

Selected clinical, philosophical and public policy literature and two illustrative case examples.

RESULTS

1. There is no longer a mandate to perform CPR on all dying patients, even though the Council on Ethical and Judicial Affairs of the American Medical Association in 1991 said that the only restrictions should be in patients with an irreversible terminal condition or when the physician writes the order, DNR. 2. The DNR order usually requires the informed refusal of CPR by the patient or family. There is only minimal support for a unilateral decision even for patients with far advanced disease. 3. DNR is often the first step in the negotiated process of forgoing care in the ICU. There are multiple interpretations of DNR both in and outside of the ICU. 4. Health Proxy is the latest attempt to have a person clarify his/her wishes and preferences by naming a decision maker, if the individual losses mental capacity. 5. Although ethical principles seem well established, there are inconsistent interpretations and practices at the bedside in the United States in part due to the restructuring of the relationship between physicians and patients, providers and consumers/clients. 6. Objective severity scores such as Apache III, SAPS II, MPM II are generally not applicable for individual patient end-of-life decisions.

CONCLUSIONS

Although Health Proxy in its current formulation has been disappointing, there is a clear trend for wider application of DNR and for more active discussions about withholding or forgoing other life-sustaining therapies. DNR has a different interpretation late into the ICU course (> 72 h) than when applied at or shortly after ICU admission. Late in the ICU course, it has been decided by the medical team and family or surrogate decision maker/Health Proxy that the patient has failed or is in the process of failing aggressive ICU therapy. Early use of DNR may be related to limitations based on pre-existing chronic or subacute disease burden or an unwillingness to proceed with a full ICU course of therapy. It is unclear how Ethics Committees, risk management and hospital administrators, national practice guidelines, governmental sponsored health care reform will interface with the highly complex individual patient--physician--family--Health Proxy interface as practiced in the United States. Dialogue between the Society of Critical Care Medicine and the European Society of Critical Care Medicine and among interested physicians could provide a format for a multi-cultural context to discuss end of life issues in the ICU setting.

Civilian triage in the intensive care unit: the ritual of the last bed

OBJECTIVE

To evaluate the numerous problems that exist when there is an acute shortage of trained critical care nurses, no triage officer is available or designated, there is no cooperation among intensive care units (ICUs) or alternative sites, or there is excessive political or financial pressure applied to maintain a referral practice or to fill all the beds, or limited ability to divert ambulances to other hospitals. The Joint Commission on Accreditation of Health Care organizations now mandates a written policy: "when patient load exceeds optimal operational capacity" (1992).

DATA SOURCES/STUDY SELECTION

Selected clinical, philosophical, and public policy literature on the subject of triage. DATA SYNTHESIS/DATA EXTRACTION: 1) An ICU medical director, designee, or supervisory nurse should be empowered as the gatekeeper/triage officer. 2) The basis for regulating admission, discharge, or triage from the special care unit should be medical suitability (from a utilitarian or egalitarian point of view). During high-level triage when all ICU patients are receiving active therapy, these decisions should override the individual primary physician-patient relationship. 3) The guidelines should follow the "congestive heart failure" treatment analogy: a) preload reduction: hold high-risk patients in the postanesthesia care unit or Emergency Room, postpone surgery, hold transfers in outlying ICUs; b) improve cardiac performance: increase efficiency and decrease workload per patient by performing fewer invasive procedures and transporting fewer patients for abdominal computed tomography scans; c) afterload reduction: keep unstable patients in the postanesthesia care unit, send sicker patients to intermediate care units, send "stable" ventilator-dependent patients to general medical/surgical units, and transfer or resolve issues regarding "hopeless" patients.

CONCLUSIONS

It is necessary to have public disclosure of the broader issues related to high-level triage. The first issue is recognition that there are periods of time when ICU capacity is exceeded or skilled critical care nurse availability is reduced. The next issue is the decision of who is best suited to make complex and dynamic triage decisions and what kind of oversight should be provided. Other issues relate to whether there should be patient or family consent, and what to do about patients receiving marginal benefit or who are considered hopeless or unsalvageable, yet the family or surrogate decision maker (or perhaps one of the consultants) wants to continue active care in the ICU. In the conflict between individual and community rights and benefits, there should be a nonlitigious approach when a patient is harmed during these periods of high census or limited capacity. In recognition of these complex issues (including potential conflicts among ICUs, hospital administration, individual physicians, and the various medical and surgical programs feeding patients into special care units), the Society of Critical Care Medicine has organized a Task Force on the legal and ethical justification for triage.

Therapeutic impact of pulmonary artery catheterization in a medical/surgical ICU

The objective of this study was to determine the following: (1) if standard clinical evaluation is sufficient to provide an accurate estimate of hemodynamic status of unstable ICU patients; (2) the impact of pulmonary artery catheterization (PAC) on diagnosis and treatment plan; and (3) whether therapy provided after PAC was appropriate as judged by an expert panel of senior ICU physicians. A descriptive analysis of utilization of pulmonary artery catheters in a medical/surgical ICU population was performed in a university-affiliated hospital (24-bed medical/surgical ICU). The subjects included 154 medical/surgical patients judged by ICU residents and attendings to require PAC. All 154 patients underwent PAC with four patients having more than one catheterization. Prior to insertion of the catheter, a questionnaire was completed by medical/surgical residents and attendings indicating reasons for PAC insertion and estimate of hemodynamics. Following PAC, residents/attendings indicated their evaluation of hemodynamics and planned therapy. An expert panel rated performance of the house staff regarding treatment plan on a scale of 1 to 5 (5 indicating optimal therapy). The overall proportion correct classification for pulmonary artery wedge pressure (PAWP), CO, and systemic vascular resistance (SVR) were 47 percent, 51 percent, and 36 percent, respectively. In 45 percent of PAC, information obtained resulted in a major change in therapy. Major change in therapy occurred more often when prediction of PAWP by residents proved inaccurate. The expert panel judged appropriate scores of 3, 4 and 5 in 84 percent of the cases. Prediction of hemodynamics in ICU patients by clinical evaluation alone is inaccurate and unreliable. There is a positive correlation between inaccurate prediction of hemodynamics and major therapeutic changes after PAC. Most resident/attending performance was judged appropriate. Results of this study suggest that PAC was instrumental to the management scheme in many patients unresponsive to initial therapy. However, a subset of ICU patients were judged to have been managed favorably, yet had treatment based on inaccurate hemodynamic assessment.

Timing of intensive care unit admission in relation to ICU outcome

This study assessed the relationship between admission time (from hospital admission to ICU admission) and mortality predicted by the Mortality Prediction Model (MPM), actual mortality, and resource use. All admissions, except elective surgery patients, to the general medical/surgical ICU of a tertiary care hospital during a 24-month period were studied (n = 1,889). Patients admitted to the ICU within 1 day of hospital admission had lower predicted and actual mortality, and used fewer resources than patients admitted later. Predicted mortality was higher than actual mortality for patients admitted to the ICU early and was lower than actual mortality for later ICU admissions. Transfers had higher predicted and actual mortality, and used more resources than nontransfer patients. Time from hospital admission to ICU admission can be a potentially useful variable in models of ICU outcome.

Nursing perception of the availability of the intensive care unit medical director for triage and conflict resolution

The Joint Commission on the Accreditation of Healthcare Organizations and the Society of Critical Care Medicine call on the physician medical director of the intensive care unit (ICU) to play an important role in admission and discharge decision-making. To assess nursing perception of the medical director's involvement in this decision-making, we analyzed data from a questionnaire administered at an annual ICU management conference to ICU nursing supervisors representing 101 hospitals and 137 ICUs. We asked nurses if the medical director or his or her designee (excluding residents) was available at night for triage, admission decision-making, and conflict resolution. In 21% (29) of the ICUs, nurses perceived no medical director at all. In the 54 ICUs with full-time medical directors, nurses in approximately 30% of the units said that there was no nighttime availability of the medical director or designee. The data suggest that many ICUs lack physician leadership in ICU management and resource allocation.

Clinical assessment of hemodynamic values in two surgical intensive care units. Effects on therapy

A prospective study of 126 surgical patients from two institutions was undertaken to assess the impact of pulmonary artery catheterization in surgical intensive care units. Before catheterization, surgical residents were asked to predict pulmonary artery wedge pressure, cardiac output, systemic vascular resistance, and plan of therapy. After catheterization, each chart was reviewed by a panel of intensive care specialists and a general surgeon. Correct classification for the hemodynamic variables ranged from 47% to 55%. Catheterization results prompted a major change in therapy in 50% of patients. The data suggest that hemodynamic variables obtained from pulmonary artery catheterization improve the accuracy of bedside evaluation and lead to alteration in therapy, particularly in patients whose pulmonary artery wedge pressure predictions were poor.

Explaining variability of cost using a severity-of-illness measure for ICU patients

Factors related to hospital resource use by intensive care unit (ICU) patients, including severity of illness at admission and intensity of therapy during the first 24 ICU hours were explored in this study. Analysis was based on 2,749 patients admitted to the general medical-surgical ICU at Baystate Medical Center, Springfield, Massachusetts, between February 1, 1983 and January 10, 1985. Resource use was indexed by hospital length of stay (LOS) adjusted for differences between ICU and other hospital days. Severity of illness was measured by the Mortality Prediction Model (MPM0), a validated predictor of outcome but not previously used to analyze resource consumption. Intensity of therapy was measured using the Therapeutic Intervention Scoring System (TISS). The 10% of patients with longest ICU stays were significantly different from the other 90% with respect to previous ICU use, MPM probability, and TISS score. Variability in resource use was analyzed using four diagnosis-related groups (DRGs) accounting for large numbers of ICU patients. The relationship between severity of illness and resource was nonlinear: as severity increased from low levels, resource use increased at a decreasing rate, reached a plateau, and eventually declined. Within each DRG, MPM0 explained a statistically significant percentage of the variability in resource use.