Biomedical subjects

Turner M Osler

Publications and source records attributed to Turner M Osler.

25 records · Page 2Linked to original sources

PubMed2002

Complications in surgical patients.

HYPOTHESIS: Complications are common in hospitalized surgical patients. Provider error contributes to a significant proportion of these complications. DESIGN: Surgical patients were concurrently observed for the development of explicit complications. All complications were reviewed by the attending surgeon and other members of the service and evaluated for the severity of sequelae (major or minor) and for whether the complication resulted from medical error (avoidable) or not. SETTING: University teaching hospital with a level I trauma designation. PATIENTS: All inpatients (operative or nonoperative) from 4 different surgical services: general surgery, combined general surgery and trauma, vascular surgery, and cardiothoracic surgery. MAIN OUTCOME MEASURES: Total complication rate (number of complications divided by the number of patients) and the number of patients with complications. Complications were separated into those with major or minor sequelae and the proportion of each type that were due to medical error (avoidable). Rates of complications in a recent Institute of Medicine report were used as a criterion standard. RESULTS: The data for the respective groups (general surgery, vascular surgery, combined general surgery and trauma, and cardiothoracic surgery) are as follows. The number of patients was 1363, 978, 914, and 1403; number of complications, 413, 409, 295, and 378; total complication rate, 30.3%, 42.4%, 32.3%, and 26.9%; minor complication rate, 13.3%, 19.9%, 13.5%, and 13.0% (percentage of minor complications that were avoidable, 37.4%, 59.0%, 51.2%, and 49.5%); major complication rate, 16.2%, 21.1%, 18.1%, and 12.9% (percentage of major complications that were avoidable, 53.4%, 60.7%, 38.8%, and 38.7%); and mortality rate, 1.83%, 3.33%, 2.28%, and 3.34% (percentage of mortality that was avoidable, 28.0%, 44.1%, 19.0%, and 25.0%). CONCLUSIONS: Despite mortality rates that compare favorably with national benchmarks, a prospective examination of surgical patients reveals complication rates that are 2 to 4 times higher than those identified in an Institute of Medicine report. Almost half of these adverse events were judged contemporaneously by peers to be due to provider error (avoidable). Errors in care contributed to 38 (30%) of 128 deaths. Recognition that provider error contributes significantly to adverse events presents significant opportunities for improving patient outcomes.

Cardiac Surgical Procedures↗

PubMed2002

Synergistic effect of genistein and BCNU on growth inhibition and cytotoxicity of glioblastoma cells.

OBJECTIVE: Recent experiments have shown that dietary soy isoflavones such as genistein can significantly suppress invasiveness and growth of a number of human malignancies. This study examined whether genistein, at a concentration typical of plasma levels following soy diet intake, in combination with 1,3-bis(2-chloroethyl)-1-nitrosourea (BCNU, carmustine) exhibited an additive or synergistic inhibitory effect on the growth of glioma cells. METHODS: The human glioblastoma multiforme (GBM) cell line U87 and the rodent C6 glioma were treated with genistein at 4 microM, combined with BCNU (0-50 microM). Monolayer cell growth and cytotoxicity, as measured by colonigenic survival in soft agarose, were then compared in control and drug-treated cultures. Presence of apoptosis, using the DNA ladder assay and laser scanning cytometry (LSC), was investigated in all cell lines at those concentrations where an enhancement of antiproliferative effect of BCNU in presence of genistein was observed. RESULTS: A 32-41% increase in monolayer growth inhibition and a 28-42% increase in colony cytotoxicity in the U87 cell line were observed when genistein (4 microM) was added to BCNU in the 0-10 microM dose range. In the C6 cell line, a 30-36% increase in monolayer growth inhibition and a 39-54% increase in colony cytotoxicity were observed with the BCNU dose range of 0-50 microM. All experiments showed a significant increase in growth inhibition and a decrease in colonogenic survival (P < 0.05). We were unable to detect apoptosis in any of the lines when genistein was combined with BCNU. CONCLUSION: These results indicate that genistein at typical adult dietary plasma levels can significantly enhance the antiproliferative and cytotoxic action of BCNU. The implication for treatment of GBM may be a reduction in the chemotherapeutic dose recommendations of these agents and subsequently a decrease in the risk of treatment sequelae for these patients.

Animals↗

PubMed2002

Rating the quality of intensive care units: is it a function of the intensive care unit scoring system?

OBJECTIVE: Intensive care units (ICUs) use severity-adjusted mortality measures such as the standardized mortality ratio to benchmark their performance. Prognostic scoring systems such as Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score II, and Mortality Probability Model II0 permit performance-based comparisons of ICUs by adjusting for severity of disease and case mix. Whether different risk-adjustment methods agree on the identity of ICU quality outliers within a single database has not been previously investigated. The objective of this study was to determine whether the identity of ICU quality outliers depends on the ICU scoring system used to calculate the standardized mortality ratio. DESIGN, SETTING, PATIENTS: Retrospective cohort study of 16,604 patients from 32 hospitals based on the outcomes database (Project IMPACT) created by the Society of Critical Care Medicine. The ICUs were a mixture of medical, surgical, and mixed medical-surgical ICUs in urban and nonurban settings. Standardized mortality ratios for each ICU were calculated using APACHE II, Simplified Acute Physiology Score II, and Mortality Probability Model II. ICU quality outliers were defined as ICUs whose standardized mortality ratio was statistically different from 1. Kappa analysis was used to determine the extent of agreement between the scoring systems on the identity of hospital quality outliers. The intraclass correlation coefficient was calculated to estimate the reliability of standardized mortality ratios obtained using the three risk-adjustment methods. MEASUREMENTS AND MAIN RESULTS: Kappa analysis showed fair to moderate agreement among the three scoring systems in identifying ICU quality outliers; the intraclass correlation coefficient suggested moderate to substantial agreement between the scoring systems. The majority of ICUs were classified as high-performance ICUs by all three scoring systems. All three scoring systems exhibited good discrimination and poor calibration in this data set. CONCLUSION: APACHE II, Simplified Acute Physiology Score II, and Mortality Probability Model II0 exhibit fair to moderate agreement in identifying quality outliers. However, the finding that most ICUs in this database were judged to be high-performing units limits the usefulness of these models in their present form for benchmarking.

APACHE↗

PubMed2002

Identifying quality outliers in a large, multiple-institution database by using customized versions of the Simplified Acute Physiology Score II and the Mortality Probability Model II0.

OBJECTIVE: To assess whether customized versions of the Simplified Acute Physiology Score (SAPS) II and the Mortality Probability Model (MPM) II0 agree on the identity of intensive care unit quality outliers within a multiple-center database. DESIGN: Retrospective database analysis. SETTING AND PATIENTS: Patient subset of the Project IMPACT database consisting of 39,617 adult patients admitted to surgical, medical, and mixed surgical-medical intensive care units at 54 hospitals between 1995 and 1999 who met inclusion criteria for SAPS II and MPM II0. INTERVENTIONS: Customized versions of SAPS II and MPM II0 were obtained by fitting new logistic regressions to the data by using the risk score as the independent variable and outcome at hospital discharge as the dependent variable. The data set was divided randomly into a training set and a validation set. Each model was customized by using the training set; model performance was then assessed in the validation set by using the area under the receiver operating characteristic curve and the Hosmer-Lemeshow statistic. The final models were based on the entire data set. The level of agreement between the customized models on the identity of quality outliers was evaluated by using kappa analysis. MEASUREMENTS AND MAIN RESULTS: Both customized models exhibited good discrimination and good calibration in this database. The area under the receiver operating characteristic curve was 0.83 for MPM II0 and 0.872 for SAPS II following model customization. The Hosmer-Lemeshow statistic was 12.3 ( >.14) for MPM II0, and 8.17 (p >.42) for SAPS II, after customization. Kappa analysis showed only fair agreement between the two customized models with regard to the identity of the quality outliers: kappa = 0.44 (95% confidence interval, 0.24, 0.65). CONCLUSIONS: Customization of SAPS II and MPM II0 to the Project IMPACT database resulted in well-calibrated models. Despite this, the models exhibited only a moderate level of agreement in which hospitals were designated as quality outliers. Seventeen of the 54 hospitals were categorized differently depending on which of the two scoring systems was used. Therefore, the rating of quality of care appears, in part, to be a function of the prediction model used.

APACHE↗

PubMed2002

A simple mathematical modification of TRISS markedly improves calibration.

BACKGROUND: TRISS has reigned as the preeminent trauma outcome prediction model for 20 years. Despite this endorsement, the calibration of TRISS has been poor in most data sets where it has been examined. We hypothesized that the lack of calibration of TRISS was because of the inappropriate mathematical specification of the model that TRISS is based on, rather than the predictors in the model. In particular, we hypothesized that the nonlinearity of the Injury Severity Score (ISS) in the log odds of death was responsible for the poor calibration of TRISS, and further, that this nonlinearity could be corrected by the simple addition of an ISS squared term to the TRISS model. METHODS: We examined ISS in the log odds of mortality for linearity in one large trauma data set, the National Pediatric Trauma Registry (NPTR) (n = 53,113 from 1985-1996; mortality, 1.3%); and two small data sets, the University of New Mexico (UNM) (n = 3,142 from 1991-1995; mortality, 8.6%) and Portland, Oregon (PORT) (n = 2,916 from 1990-1994; mortality, 1.75%). In addition, in the NPTR we compared the calibration of TRISS models with and without linearity in the log odds of death. RESULTS: In the NPTR, ISS was profoundly nonlinear in the log odds of death for both blunt and penetrating trauma (p < 0.001). Moreover, the overall calibration of the TRISS model for the NPTR data was significantly improved when the nonlinearity of ISS was corrected by the addition of a quadratic ISS term as demonstrated by a 70% reduction (improvement) in the Hosmer-Lemeshow statistic. Interestingly, the addition of the ISS squared term did not affect the discrimination of the model. The log odds of survival in the UNM and PORT data sets were also better modeled when an ISS squared term was added (UNM, p = 0 0.052; PORT, p = 0.014), but improvements in the Hosmer-Lemeshow statistic were smaller, possibly because of the small size of these data sets. CONCLUSION: The TRISS model for outcome prediction currently uses ISS in a mathematically inappropriate way that impairs the calibration, but not the discrimination, of its predictions. If TRISS is to continue as the prediction standard for trauma, a quadratic ISS term must be added to the model. In the future, outcome prediction models should undergo thorough statistical modeling and evaluation before being released. Injury severity descriptors other than ISS (such as ASCOT, ICISS, or NISS) may require other modeling techniques to optimize the calibration of survival models that use these injury scores.

Adolescent↗

PubMed2002

"Shock" bowel.

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Accidents, Traffic↗

PubMed2002

Pulmonary embolism.

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Costs and Cost Analysis↗