Mortality burden from variation in provision of surgical care in emergency general surgery: a cohort study using the National Inpatient Sample.

Background: The decision to undertake a surgical intervention for an emergency general surgery (EGS) condition (appendicitis, diverticulitis, cholecystitis, hernia, peptic ulcer, bowel obstruction, ischemic bowel) involves a complex consideration of factors, particularly in older adults. We hypothesized that identifying variability in the application of operative management could highlight a potential pathway to improve patient survival and outcomes. Methods: We included adults aged 65+ years with an EGS condition from the 2016-2017 National Inpatient Sample. Operative management was determined from procedure codes. Each patient was assigned a propensity score (PS) for the likelihood of undergoing an operation, modeled from patient and hospital factors: EGS diagnosis, age, gender, race, presence of shock, comorbidities, and hospital EGS volumes. Low and high probability for surgery was defined using a PS cut-off of 0.5. We identified two model-concordant groups (no surgery-low probability, surgery-high probability) and two model-discordant groups (no surgery-high probability, surgery-low probability). Logistic regression estimated the adjusted OR (AOR) of in-hospital mortality for each group. Results: Of 375 546 admissions, 21.2% underwent surgery. Model-discordant care occurred in 14.6%; 5.9% had no surgery despite a high PS and 8.7% received surgery with low PS. In the adjusted regression, model-discordant care was associated with significantly increased mortality: no surgery-high probability AOR 2.06 (1.86 to 2.27), surgery-low probability AOR 1.57 (1.49 to 1.65). Model-concordant care showed a protective effect against mortality (AOR 0.83, 0.74 to 0.92). Conclusions: Nearly one in seven EGS patients received model-discordant care, which was associated with higher mortality. Our study suggests that streamlined treatment protocols can be applied in EGS patients as a means to save lives. Level of evidence: III.

Heath status, frailty, and multimorbidity in patients with emergency general surgery conditions.

BACKGROUND: Although nearly 1 million older adults are admitted for emergency general surgery conditions yearly, the extent to which baseline health influences the development and treatment of emergency general surgery conditions is unknown. We evaluated baseline health and older patients with and without emergency general surgery conditions. METHODS: We used the prospectively collected Medicare Current Beneficiary Survey with Medicare claims and 2 validated health frameworks: (1) Deficit Accumulation Frailty Score and (2) Complex Multimorbidity. Self-reported health and function items were used to derive pre-emergency general surgery conditions Deficit Accumulation Frailty Score and Complex Multimorbidity scores. Deficit Accumulation Frailty Score ranges from 0 (no frailty deficits) to 100 (all possible deficits present). Complex Multimorbidity is a 3-point categorical rank based on the presence of chronic conditions, functional limitations, and geriatric syndromes. Specific survey factors were also examined to determine association with development of emergency general surgery conditions or use of operative management. RESULTS: Of 54,417 individuals, 1,960 had emergency general surgery conditions (median age 79 [interquartile range 73-84]). Patients with emergency general surgery conditions had significantly higher Deficit Accumulation Frailty Score (19 [interquartile range 11-31] vs 14 [8-24]) and were more likely to be in the most severe Complex Multimorbidity category (38% vs 29%). Emergency general surgery conditions patients had higher proportions of nearly every health category, with the most striking differences in functional limitations. Patients who were treated nonoperatively had the poorest overall baseline health. CONCLUSION: Patients who developed emergency general surgery conditions had more severe health burden than patients who did not, particularly in functional status. Clinicians must better understand the interaction between baseline health vulnerability and emergency surgical disease to improve prognostication and ensure alignment of patient goals and treatment strategies.

Two distinct Do-Not-Resuscitate protocols leaving less to the imagination: an observational study using propensity score matching.

BACKGROUND: Do-Not-Resuscitate (DNR) patients tend to receive less medical care after the order is written. To provide a clearer approach, the Ohio Department of Health adopted the Do-Not-Resuscitate law in 1998, indicating two distinct protocols of DNR orders that allow DNR patients to choose the medical care: DNR Comfort Care (DNRCC), implying DNRCC patients receive only comfort care after the order is written; and DNR Comfort Care-Arrest (DNRCC-Arrest), implying that DNRCC-Arrest patients are eligible to receive aggressive interventions until cardiac or respiratory arrest. The aim of this study was to examine the medical care provided to patients with these two distinct protocols of DNR orders. METHODS: Data were collected from August 2002 to December 2005 at a medical intensive care unit in a university-affiliated teaching hospital. In total, 188 DNRCC-Arrest patients, 88 DNRCC patients, and 2,051 non-DNR patients were included. Propensity score matching using multivariate logistic regression was used to balance the confounding variables between the 188 DNRCC-Arrest and 2,051 non-DNR patients, and between the 88 DNRCC and 2,051 non-DNR patients. The daily cost of intensive care unit (ICU) stay, the daily cost of hospital stay, the daily discretionary cost of ICU stay, six aggressive interventions, and three comfort care measures were used to indicate the medical care patients received. The association of each continuous variable and categorical variable with having a DNR order written was analyzed using Student's t-test and the χ2 test, respectively. The six aggressive interventions and three comfort care measures performed before and after the order was initiated were compared using McNemar's test. RESULTS: DNRCC patients received significantly fewer aggressive interventions and more comfort care after the order was initiated. By contrast, for DNRCC-Arrest patients, the six aggressive interventions provided were not significantly decreased, but the three comfort care measures were significantly increased after the order was initiated. In addition, the three medical costs were not significantly different between DNRCC and non-DNR patients, or between DNRCC-Arrest and non-DNR patients. CONCLUSIONS: When medical care provided to DNR patients is clearly indicated, healthcare professionals will provide the medical care determined by patient/surrogate decision-makers and healthcare professionals, rather than blindly decreasing medical care.

Factors associated with two different protocols of do-not-resuscitate orders in a medical ICU*.

OBJECTIVE: The State of Ohio in the United States has the legislation for two different protocols of do-not-resuscitate orders. The objective of this study was to examine the clinical/demographic factors and outcomes associated with the two different do-not-resuscitate orders. DESIGN: Data were concurrently and retrospectively collected from August 2002 to December 2005. The clinical/demographic factors of do-not-resuscitate patients were compared with those of non-do-not-resuscitate patients, and the clinical/demographic factors of do-not-resuscitate comfort care-arrest patients were compared with those of do-not-resuscitate comfort care patients. SETTING: An ICU in a university-affiliated hospital located at Northeast Ohio in the United States. PATIENTS: A sample of 2,440 patients was collected: 389 patients were do-not-resuscitate; and 2,051 patients were non-do-not-resuscitate. Among the 389 do-not-resuscitate patients, 194 were do-not-resuscitate comfort care-arrest patients and 91 were do-not-resuscitate comfort care patients. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The factors associated with do-not-resuscitate were older age, race and ethnicity with white race, more severe clinical illness at admission to the ICU, and longer stay before admission to the ICU. Comparing do-not-resuscitate comfort care-arrest patients with do-not-resuscitate comfort care patients, those with more severe clinical illness, longer ICU stay before making a do-not-resuscitate decision, and being cared for by only one intensivist during ICU stay were significantly associated with do-not-resuscitate comfort care decisions. For 149 do-not-resuscitate patients who eventually survived to hospital discharge and 86 do-not-resuscitate patients who eventually did not, only eight (5.4%) and 23 (26.7%) had the order written within 48 hours before the end of ICU stay, respectively. CONCLUSIONS: Our study showed that some clinical/demographic factors predicted do-not-resuscitate comfort care orders. This study also suggested that Ohio's Do-Not-Resuscitate Law, clearly indicating two different protocols of do-not-resuscitate orders, facilitated early do-not-resuscitate decision.

Optimal timing of transfer out of the intensive care unit.

BACKGROUND: Little other than subjective judgment is available to help clinicians determine when a patient should be transferred out of the intensive care unit. OBJECTIVE: To assess whether remaining in the intensive care unit longer than judged to be medically necessary is associated with increased 30-day mortality. METHODS: This prospective, observational cohort study was performed in a 13-bed, closed-model, adult medical intensive care unit of a county-owned, university-affiliated hospital that often has difficulty transferring patients to general care areas because of a lack of available beds. Analysis included all 2401 survivors of intensive care from the study period. Delay in discharge from the intensive care unit was defined as time elapsed between the request for transfer and the actual transfer. Logistic regression was used to assess the association of discharge delay with 30-day mortality, adjusting for demographics, comorbid conditions, type and severity of acute illness, care limitations in the unit, and other potential confounding variables. Nonlinear relationships with continuous variables were modeled with restricted cubic splines. RESULTS: Overall, 30-day mortality was 10.1%. Mean discharge delay was 9.6 (SD, 11.7) hours; 9.9% had a discharge delay exceeding 24 hours. The relationship of 30-day mortality to discharge delay was statistically significant and U-shaped, with the nadir at 20 hours. CONCLUSIONS: These data indicate an optimal time window for patients to leave the intensive care unit, with increased mortality not only if they leave earlier but also if they leave later than this optimal timing.

The effect of pulmonary artery catheter use on costs and long-term outcomes of acute lung injury.

BACKGROUND: The pulmonary artery catheter (PAC) remains widely used in acute lung injury (ALI) despite known complications and little evidence of improved short-term mortality. Concurrent with NHLBI ARDS Clinical Trials Network Fluid and Catheters Treatment Trial (FACTT), we conducted a prospectively-defined comparison of healthcare costs and long-term outcomes for care with a PAC vs. central venous catheter (CVC). We explored if use of the PAC in ALI is justified by a beneficial cost-effectiveness profile. METHODS: We obtained detailed bills for the initial hospitalization. We interviewed survivors using the Health Utilities Index Mark 2 questionnaire at 2, 6, 9 and 12 m to determine quality of life (QOL) and post-discharge resource use. Outcomes beyond 12 m were estimated from federal databases. Incremental costs and outcomes were generated using MonteCarlo simulation. RESULTS: Of 1001 subjects enrolled in FACTT, 774 (86%) were eligible for long-term follow-up and 655 (85%) consented. Hospital costs were similar for the PAC and CVC groups ($96.8k vs. $89.2k, p = 0.38). Post-discharge to 12 m costs were higher for PAC subjects ($61.1k vs. 45.4k, p = 0.03). One-year mortality and QOL among survivors were similar in PAC and CVC groups (mortality: 35.6% vs. 31.9%, p = 0.33; QOL [scale: 0-1]: 0.61 vs. 0.66, p = 0.49). MonteCarlo simulation showed PAC use had a 75.2% probability of being more expensive and less effective (mean cost increase of $14.4k and mean loss of 0.3 quality-adjusted life years (QALYs)) and a 94.2% probability of being higher than the $100k/QALY willingness-to-pay threshold. CONCLUSION: PAC use increased costs with no patient benefit and thus appears unjustified for routine use in ALI. TRIAL REGISTRATION: www.clinicaltrials.gov NCT00234767.

Lack of comprehension of common prostate cancer terms in an underserved population.

PURPOSE: To assess the comprehension of common medical terms used in prostate cancer in patient education materials to obtain informed consent, and to measure outcomes after prostate cancer treatment. We address this issue among underserved, African-American men because of the increased cancer incidence and mortality observed in this population. PATIENTS AND METHODS: We reviewed patient education materials and prostate-specific quality-of-life instruments to identify technical terms describing sexual, urinary, and bowel function. Understanding of these terms was assessed in face-to-face interviews of 105, mostly African-American men, age > or = 40, from two low-income clinics. Comprehension was evaluated using semiqualitative methods coded by two independent investigators. Demographics were collected and literacy was measured. RESULTS: Fewer than 50% of patients understood the terms "erection" or "impotent." Only 5% of patients understood the term "incontinence" and 25% understood the term "bowel habits." More patients recognized word roots than related terms or compound words (eg, "rectum" v "rectal urgency," "intercourse" v "vaginal intercourse"). Comprehension of terms from all domains was statistically significantly correlated with reading level (P < .001). Median literacy level was fourth to sixth grade. Prostate cancer knowledge was poor. Many patients had difficulty locating key anatomic structures. CONCLUSION: Limited comprehension of prostate cancer terms and low literacy create barriers to obtaining informed consent for treatment and to measuring prostate cancer outcomes accurately in our study population. In addition, the level of prostate cancer knowledge was poor. These results highlight the need for prostate cancer education efforts and outcomes measurements that consider literacy and use nonmedical language.

Glucose variability and mortality in patients with sepsis.

OBJECTIVE: Treatment and prevention of hyperglycemia has been advocated for subjects with sepsis. Glucose variability, rather than the glucose level, has also been shown to be an important factor associated with in-hospital mortality, in general, critically ill patients. Our objective was to determine the association between glucose variability and hospital mortality in septic patients and the expression of glucose variability that best reflects this risk. DESIGN: Retrospective, single-center cohort study. SETTING: Academic, tertiary care hospital. PATIENTS: Adult subjects hospitalized for >1 day, with a diagnosis of sepsis were included. INTERVENTIONS: None. MEASUREMENTS: Glucose variability was calculated for all subjects as the average and standard deviation of glucose, the mean amplitude of glycemic excursions, and the glycemic lability index. Hospital mortality was the primary outcome variable. Logistic regression was used to determine the odds of hospital death in relation to measures of glucose variability after adjustment for important covariates. MAIN RESULTS: Of the methods used to measure glucose variability, the glycemic lability index had the best discrimination for mortality (area under the curve = 0.67, p < 0.001). After adjustment for confounders, including the number of organ failures and the occurrence of hypoglycemia, there was a significant interaction between glycemic lability index and average glucose level, and the odds of hospital mortality. Higher glycemic lability index was not independently associated with mortality among subjects with average glucose levels above the median for the cohort. However, subjects with increased glycemic lability index, but lower average glucose values had almost five-fold increased odds of hospital mortality (odds ratio = 4.73, 95% confidence interval = 2.6-8.7) compared with those with lower glycemic lability index. CONCLUSIONS: Glucose variability is independently associated with hospital mortality in septic patients. Strategies to reduce glucose variability should be studied to determine whether they improve the outcomes of septic patients.

Acquired weakness, handgrip strength, and mortality in critically ill patients.

RATIONALE: ICU-acquired paresis (ICUAP) is common in survivors of critical illness. There is significant associated morbidity, including prolonged time on the ventilator and longer hospital stay. However, it is unclear whether ICUAP is independently associated with mortality, as sicker patients are more prone and existing studies have not adjusted for this. OBJECTIVES: To test the hypothesis that ICUAP is independently associated with increased mortality. Secondarily, to determine if handgrip dynamometry is a concise measure of global strength and is independently associated with mortality. METHODS: A prospective multicenter cohort study was conducted in intensive care units (ICU) of five academic medical centers. Adults requiring at least 5 days of mechanical ventilation without evidence of preexisting neuromuscular disease were followed until awakening and were then examined for strength. MEASUREMENTS AND MAIN RESULTS: We measured global strength and handgrip dynamometry. The primary outcome was in-hospital mortality and secondary outcomes were hospital and ICU-free days, ICU readmission, and recurrent respiratory failure. Subjects with ICUAP (average MRC score of < 4) had longer hospital stays and required mechanical ventilation longer. Handgrip strength was lower in subjects with ICUAP and had good test performance for diagnosing ICUAP. After adjustment for severity of illness, ICUAP was independently associated with hospital mortality (odds ratio [OR], 7.8; 95% confidence interval [CI], 2.4-25.3; P = 0.001). Separately, handgrip strength was independently associated with hospital mortality (OR, 4.5; 95% CI, 1.5-13.6; P = 0.007). CONCLUSIONS: ICUAP is independently associated with increased hospital mortality. Handgrip strength is also independently associated with poor hospital outcome and may serve as a simple test to identify ICUAP. Clinical trial registered with www.clinicaltrials.gov (NCT00106665).

Veterans Affairs intensive care unit risk adjustment model: validation, updating, recalibration.

BACKGROUND: A valid metric is critical to measure and report intensive care unit (ICU) outcomes and drive innovation in a national system. OBJECTIVES: To update and validate the Veterans Affairs (VA) ICU severity measure (VA ICU). RESEARCH DESIGN: A validated logistic regression model was applied to two VA hospital data sets: 36,240 consecutive ICU admissions to a stratified random sample of moderate and large hospitals in 1999-2000 (cohort 1) and 81,964 cases from 42 VA Medical Centers in fiscal years 2002-2004 (cohort 2). The model was updated by adding diagnostic groups and expanding the source of admission variables. MEASURES: C statistic, Hosmer-Lemeshow goodness-of-fit statistic, and Brier's score measured predictive validity. Coefficients from the 1997 model were applied to predictors (fixed) in a logistic regression model. A 10 x 10 table compared cases with both VA ICU and National Surgical Quality Improvement Performance metrics. The standardized mortality ratios divided observed deaths by the sum of predicted mortality. RESULTS: The fixed model in both cohorts had predictive validity (cohort 1: C statistic = 0.874, Hosmer-Lemeshow goodness-of-fit C statistic chi-square = 72.5; cohort 2: 0.876, 307), as did the updated model (cohort 2: C statistic = 0.887, Hosmer-Lemeshow goodness-of-fit C statistic chi-square = 39). In 7,411 cases with predictions in both systems, the standardized mortality ratio was similar (1.04 for VA ICU, 1.15 for National Surgical Quality Improvement Performance), and 92% of cases matched (+/-1 decile) when ordered by deciles of mortality. The VA ICU standardized mortality ratio correlates with the National Surgical Quality Improvement Performance standardized mortality ratio (r2 = .74). Variation in discharge and laboratory practices may affect performance measurement. CONCLUSION: The VA ICU severity model has face, construct, and predictive validity.

Effect of decisions to withhold life support on prolonged survival.

BACKGROUND: The effect on long-term mortality of decisions made to withhold life-supporting therapies (LST) for critically ill patients is unclear. We hypothesized that mortality 60 days after ICU admission is not influenced by a decision to withhold use of LST in the context of otherwise providing all indicated care. METHODS: We studied 2,211 consecutive, initial admissions to the adult, medical ICU of a university-affiliated teaching hospital. To achieve balanced groups for comparing outcomes, we created a multivariable regression model for the probability (propensity score [PS]) of having an order initiated in the ICU to withhold LST. Each of the 201 patients with such an order was matched to the patient without such an order having the closest PS; mortality rates were compared between the matched pairs. Cox survival analysis was performed to extend the main analysis. RESULTS: The matched pairs were well balanced with respect to all of the potentially confounding variables. Sixty days after ICU admission, 50.5% of patients who had an order initiated in the ICU to withhold life support had died, compared to 25.8% of those lacking such orders (risk ratio, 2.0; 95% confidence interval, 1.5 to 2.6). Survival analysis indicated that the difference in mortality between the two groups continued to increase for approximately 1 year. CONCLUSION: Contrary to our hypothesis, decisions made in the ICU to withhold LST were associated with increased mortality rate to at least 60 days after ICU admission.

Physicians' influence over decisions to forego life support.

OBJECTIVE: To quantify the association between individual physicians and decisions to limit use of life supporting therapies for critically ill patients. STUDY DESIGN: Prospective, observational data collected 2002-2005 in the adult medical intensive care unit (ICU) of a publicly owned teaching hospital. Nine intensivists staff this closed-model ICU; in rotating 2 week blocks of time one intensivist is responsible for directing all care. In order to uniquely associate care with individual physicians, eligible patients were cared for by a single intensivist throughout their ICU stay. Life support decisions were identified as orders to withhold or withdraw any form of life supporting medical therapy, including cardiopulmonary resuscitation (CPR), defibrillation, invasive mechanical ventilation, vasoactive drugs, and renal replacement therapy. We used multivariable Cox modeling to identify variables associated with decisions to limit use of life support. The association with the individual physicians was assessed as the hazard ratios of indicator variables representing the individual physicians. RESULTS: A decision to limit use of life support was made in 191 (14.0%) of 1363 ICU admissions. The hazard ratios associated with individual intensivists spanned a 15-fold range (0.069-1.042; p = 0.0003). Decisions to limit life support were more strongly related to the identity of the intensivist than to comorbid conditions, acute diagnostic category, and the source of ICU admission. CONCLUSIONS: We have, for the first time, quantified the association between individual physicians and decisions made to limit life support for critically ill patients. More research is needed to understand the nature and implications of this association.

Which hospitals have significantly better or worse than expected mortality rates for acute myocardial infarction patients? Improved risk adjustment with present-at-admission diagnoses.

BACKGROUND: Public reports that compare hospital mortality rates for patients with acute myocardial infarction are commonly used strategies for improving the quality of care delivered to these patients. Fair comparisons of hospital mortality rates require thorough adjustments for differences among patients in baseline mortality risk. This study examines the effect on hospital mortality rate comparisons of improved risk adjustment methods using diagnoses reported as present-at-admission. METHODS AND RESULTS: Logistic regression models and related methods originally used by California to compare hospital mortality rates for patients with acute myocardial infarction are replicated. These results are contrasted with results obtained for the same hospitals by patient-level mortality risk adjustment models using present-at-admission diagnoses, using 3 statistical methods of identifying hospitals with higher or lower than expected mortality: indirect standardization, adjusted odds ratios, and hierarchical models. Models using present-at-admission diagnoses identified substantially fewer hospitals as outliers than did California model A for each of the 3 statistical methods considered. CONCLUSIONS: Large improvements in statistical performance can be achieved with the use of present-at-admission diagnoses to characterize baseline mortality risk. These improvements are important because models with better statistical performance identify different hospitals as having better or worse than expected mortality.

Present-at-admission diagnoses improved mortality risk adjustment among acute myocardial infarction patients.

OBJECTIVE: Hospital mortality outcomes for acute myocardial infarction (AMI) patients are a focus of quality improvement programs conducted by government agencies. AMI mortality risk-adjustment models using administrative data typically adjust for baseline differences in mortality risk with a limited set of common and definite comorbidities. In this study, we present an AMI mortality risk-adjustment model that adjusts for comorbid disease and for AMI severity using information from secondary diagnoses reported as present at admission for California hospital patients. STUDY DESIGN AND SETTING: AMI patients were selected from California hospital administrative data for 1996 through 1999 according to criteria used by the California Hospital Outcomes Project Report on Heart Attack Outcomes, a state-mandated public report that compares hospital mortality outcomes. We compared results for the new model to two mortality risk-adjustment models used to assess hospital AMI mortality outcomes by the state of California, and to two other models used in prior research. RESULTS: The model using present-at-admission diagnoses obtained substantially better discrimination between predicted survival and inpatient death than the other models we considered. CONCLUSION: AMI mortality risk-adjustment methods can be meaningfully improved using present-at-admission diagnoses to identify comorbid disease and conditions related closely to AMI.

Physician-attributable differences in intensive care unit costs: a single-center study.

RATIONALE: Variation in practice and outcomes, not explained by patient or illness characteristics, is common in health care, including in intensive care units (ICUs). OBJECTIVE: To quantify within-ICU, between-physician variation in resource use in a single medical ICU. METHODS: This was a prospective, noninterventional study in a medical ICU where nine intensivists provide care in 14-d rotations. Consecutive sample consisted of 1,184 initial patient admissions whose care was provided by a single intensivist. Multivariate models were constructed for average daily discretionary costs, ICU length of stay, and hospital mortality, adjusting for patient and illness characteristics, and workload. MEASUREMENTS AND MAIN RESULTS: The identity of the intensivist was a significant predictor for average daily discretionary costs (p < 0.0001), but not ICU length of stay (p = 0.33) or hospital mortality (p = 0.83). The intensivists had more influence on costs than all other variables except the severity and type of acute illness. Average daily discretionary costs varied by 43% across the different intensivists, equating to a mean difference of 1,003 dollars per admission between the highest and lowest terciles of intensivists. CONCLUSIONS: There are large differences among intensivists in the amount of resources they use to manage critically ill patients. Higher resource use was not associated with lower length of stay or mortality.

Do patient preferences influence decisions on treatment for patients with steroid-refractory ulcerative colitis?

BACKGROUND & AIMS: Patients with steroid-refractory ulcerative colitis face a difficult treatment decision between colectomy and therapy with infliximab or cyclosporine. The aim of this study was to understand how individual patient preferences for the various treatment outcomes influence the optimal treatment decision for a given patient. METHODS: A Markov model was used to simulate treatment with total colectomy with an ileo pouch-anal anastomosis (TC/IPAA), cyclosporine (CSA), infliximab (INFLX), and infliximab followed by cyclosporine for treatment failures (INFLX-->CSA). Utility weights for treatment outcomes were elicited from 48 patients using both time trade-off and visual rating scale methods. Preference sets were applied to the model to identify the therapy that maximized quality-adjusted life years (QALYs) for each patient. Sensitivity analyses were performed to assess model robustness. RESULTS: Optimal treatment was highly variable among patients (INFLX-->CSA = 42%, 20/48; TC/IPAA = 37%, 18/48; CSA = 21%, 10/48; INFLX = 0%, 0/48). However, when average preference weights from our sample were applied to the model, medical treatments were superior to TC (CSA = .26 QALYs gained vs TC/IPAA; INFLX-->CSA = .25 QALYs gained vs TC/IPAA). CONCLUSIONS: Patient preferences have a clear impact on the optimal treatment for steroid-refractory ulcerative colitis. Although averaged preferences support the use of medical interventions, a third of individual patients may benefit most from proceeding directly to colectomy. Failure to fully assess individual preferences may result in suboptimal treatment for these patients.

Pulmonary-artery versus central venous catheter to guide treatment of acute lung injury.

BACKGROUND: The balance between the benefits and the risks of pulmonary-artery catheters (PACs) has not been established. METHODS: We evaluated the relationship of benefits and risks of PACs in 1000 patients with established acute lung injury in a randomized trial comparing hemodynamic management guided by a PAC with hemodynamic management guided by a central venous catheter (CVC) using an explicit management protocol. Mortality during the first 60 days before discharge home was the primary outcome. RESULTS: The groups had similar baseline characteristics. The rates of death during the first 60 days before discharge home were similar in the PAC and CVC groups (27.4 percent and 26.3 percent, respectively; P=0.69; absolute difference, 1.1 percent; 95 percent confidence interval, -4.4 to 6.6 percent), as were the mean (+/-SE) numbers of both ventilator-free days (13.2+/-0.5 and 13.5+/-0.5; P=0.58) and days not spent in the intensive care unit (12.0+/-0.4 and 12.5+/-0.5; P=0.40) to day 28. PAC-guided therapy did not improve these measures for patients in shock at the time of enrollment. There were no significant differences between groups in lung or kidney function, rates of hypotension, ventilator settings, or use of dialysis or vasopressors. Approximately 90 percent of protocol instructions were followed in both groups, with a 1 percent rate of crossover from CVC- to PAC-guided therapy. Fluid balance was similar in the two groups, as was the proportion of instructions given for fluid and diuretics. Dobutamine use was uncommon. The PAC group had approximately twice as many catheter-related complications (predominantly arrhythmias). CONCLUSIONS: PAC-guided therapy did not improve survival or organ function but was associated with more complications than CVC-guided therapy. These results, when considered with those of previous studies, suggest that the PAC should not be routinely used for the management of acute lung injury. (ClinicalTrials.gov number, NCT00281268.).