In Defense of Lawyers

Conservative judge challenges Quayle statistics

A Fine-Grid Model for the ASRM Aft Segment with Gimballed Nozzle

Results from computational fluid dynamic analyses for complex three-dimensional internal flows in the Advanced Solid Rocket Motor (ASRM) are presented. In particular, flow visualization and tabulated results from a fine-grid model consisting of 1.5 M grid points for the ASRM Aft Segment at the l9-second burn time with an 8-degree nozzle gimbal angle are shown. The results from this model will enable characterization of various aspects of the ASRM internal environment, and in particular will allow an assessment of the heat transfer and stresses exerted on the submerged nozzle, casing insulation, and nozzle case joint

Risk for Clostridium difficile infection after allogeneic hematopoietic cell transplant remains elevated in the postengraftment period

BACKGROUND: Clostridium difficile infection (CDI) is a frequent cause of diarrhea among allogeneic hematopoietic cell transplant (HCT) recipients. It is unknown whether risk factors for CDI vary by time posttransplant. METHODS: We performed a 3-year prospective cohort study of CDI in allogeneic HCT recipients. Participants were enrolled during their transplant hospitalizations. Clinical assessments were performed weekly during hospitalizations and for 12 weeks posttransplant, and monthly for 30 months thereafter. Data were collected through patient interviews and chart review, and included CDI diagnosis, demographics, transplant characteristics, medications, infections, and outcomes. CDI cases were included if they occurred within 1 year of HCT and were stratified by time from transplant. Multivariable logistic regression was used to determine risk factors for CDI. RESULTS: One hundred eighty-seven allogeneic HCT recipients were enrolled, including 63 (34%) patients who developed CDI. 38 (60%) CDI cases occurred during the preengraftment period (days 0-30 post-HCT) and 25 (40%) postengraftment (day >30). Lack of any preexisting comorbid disease was significantly associated with lower risk of CDI preengraftment (odds ratio [OR], 0.3; 95% confidence interval [CI], 0.1-0.9). Relapsed underlying disease (OR, 6.7; 95% CI, 1.3-33.1), receipt of any high-risk antimicrobials (OR, 11.8; 95% CI, 2.9-47.8), and graft-versus-host disease (OR, 7.8; 95% CI, 2.0-30.2) were significant independent risk factors for CDI postengraftment. CONCLUSIONS: A large portion of CDI cases occurred during the postengraftment period in allogeneic HCT recipients, suggesting that surveillance for CDI should continue beyond the transplant hospitalization and preengraftment period. Patients with continued high underlying severity of illness were at increased risk of CDI postengraftment

ICD-9 Codes and Surveillance for Clostridium difficile–associated Disease

We conducted a retrospective cohort study to compare Clostridium difficile–associated disease rates determined by C. difficile–toxin assays and International Classification of Diseases, 9th Revision (ICD-9) codes. The correlation between toxin assay results and ICD-9 codes was good (κ = 0.72, p<0.01). The sensitivity of the ICD-9 codes was 78% and the specificity was 99.7%

Randomized controlled trial to determine the impact of probiotic administration on colonization with multidrug-resistant organisms in critically ill patients

This was a randomized controlled pilot study of Lactobacillus rhamnosus GG versus standard of care to prevent gastrointestinal multidrug-resistant organism (MDRO) colonization in ICU patients. Seventy subjects were included in analyses. There were no significant differences in acquisition or loss of any MDROs (p>0.05). There were no probiotic-associated adverse events

Correlation of lung collapse and gas exchange

Background: Atelectasis can provoke pulmonary and non-pulmonary complications after general anaesthesia. Unfortunately, there is no instrument to estimate atelectasis and prompt changes of mechanical ventilation during general anaesthesia. Although arterial partial pressure of oxygen (PaO2) and intrapulmonary shunt have both been suggested to correlate with atelectasis, studies yielded inconsistent results. Therefore, we investigated these correlations. Methods: Shunt, PaO2 and atelectasis were measured in 11 sheep and 23 pigs with otherwise normal lungs. In pigs, contrasting measurements were available 12 hours after induction of acute respiratory distress syndrome (ARDS). Atelectasis was calculated by computed tomography relative to total lung mass (Mtotal). We logarithmically transformed PaO2 (lnPaO2) to linearize its relationships with shunt and atelectasis. Data are given as median (interquartile range). Results: Mtotal was 768 (715–884) g in sheep and 543 (503–583) g in pigs. Atelectasis was 26 (16–47)% in sheep and 18 (13–23) % in pigs. PaO2 (FiO2 = 1.0) was 242 (106–414) mmHg in sheep and 480 (437–514) mmHg in pigs. Shunt was 39 (29–51)% in sheep and 15 (11–20) % in pigs. Atelectasis correlated closely with lnPaO2 (R2 = 0.78) and shunt (R2 = 0.79) in sheep (P-values<0.0001). The correlation of atelectasis with lnPaO2 (R2 = 0.63) and shunt (R2 = 0.34) was weaker in pigs, but R2 increased to 0.71 for lnPaO2 and 0.72 for shunt 12 hours after induction of ARDS. In both, sheep and pigs, changes in atelectasis correlated strongly with corresponding changes in lnPaO2 and shunt. Discussion and Conclusion: In lung-healthy sheep, atelectasis correlates closely with lnPaO2 and shunt, when blood gases are measured during ventilation with pure oxygen. In lung-healthy pigs, these correlations were significantly weaker, likely because pigs have stronger hypoxic pulmonary vasoconstriction (HPV) than sheep and humans. Nevertheless, correlations improved also in pigs after blunting of HPV during ARDS. In humans, the observed relationships may aid in assessing anaesthesia-related atelectasis

Development and validation of a Clostridium difficile infection risk prediction model

OBJECTIVE: The purpose of this study was to develop and validate a risk prediction model that could identify patients at high risk for Clostridium difficile infection (CDI) before they develop disease. DESIGN: Retrospective cohort. SETTING: Tertiary care medical center. PATIENTS: Patients admitted to the hospital for ≥48 hours from 1-1-2003 through 12-31-2003. METHODS: Data were collected electronically from the hospital’s Medical Informatics database and analyzed with logistic regression to determine variables that best predicted patients’ risk for development of CDI. Model discrimination and calibration were calculated. The model was bootstrapped 500 times to validate the predictive accuracy. A receiver operating characteristic (ROC) curve was calculated to evaluate potential risk cut-offs. RESULTS: 35,350 admissions with 329 CDI cases were included. Variables in the risk prediction model were age, CDI pressure, admissions in previous 60 days, modified Acute Physiology Score, days on high risk antibiotics, low albumin, admission to an ICU, and receipt of laxatives, gastric acid suppressors, or antimotility drugs. The calibration and discrimination of the model were very good to excellent (C index=0.88; Brier score 0.009). CONCLUSIONS: The CDI risk prediction model performed well. Further study is needed to determine if it could be used in a clinical setting to prevent CDI-associated outcomes and reduce costs