Turner Osler

OBJECTIVES: The Injury Severity Score (ISS) has served as the standard summary measure of anatomic injury for more than 20 years. Nevertheless, the ISS has an idiosyncrasy that both impairs its predictive power and complicates its calculation. We present here a simple modification of the ISS called the New Injury Severity Score (NISS), which significantly outperforms the venerable but dated ISS as a predictor of mortality. DESIGN: Retrospective calculation of NISS and comparison of NISS with prospectively calculated ISS. MATERIALS AND METHODS: The NISS is defined as the sum of the squares of the Abbreviated Injury Scale scores of each of a patient's three most severe Abbreviated Injury Scale injuries regardless of the body region in which they occur. NISS values were calculated for every patient in two large independent data sets: 3,136 patients treated during a 4-year period at the American College of Surgeons' Level I trauma center in Albuquerque, New Mexico, and 3,449 patients treated during a 4-year period at the American College of Surgeons' Level I trauma center at the Emanuel Hospital in Portland, Oregon. The power of NISS to predict mortality was then compared with previously calculated ISS values for the same patients in each of the two data sets. MEASUREMENTS AND MAIN RESULTS: We find that NISS is not only simple to calculate but more predictive of survival as well (Albuquerque: receiver operating characteristic (ROC) ISS = 0.869, ROC NISS = 0.896, p < 0.001; Portland: ROC ISS = 0.896, ROC NISS = 0.907,p < 0.004). Moreover, NISS provides a better fit throughout its entire range of prediction (Hosmer Lemeshow statistic for Albuquerque ISS = 29.12, NISS = 8.88; Hosmer Lemeshow statistic for Portland ISS = 83.48, NISS = 19.86). CONCLUSION: NISS should replace ISS as the standard summary measure of human trauma.

PURPOSE: Anastomotic leaks are among the most dreaded complications after colorectal surgery. However, problems with definitions and the retrospective nature of previous analyses have been major limitations. We sought to use a prospective database to define the true incidence and presentation of anastomotic leakage after intestinal anastomosis. METHODS: A prospective database of two colorectal surgeons was reviewed over a 10-year period (1995-2004). The incidence of leak by surgical site, timing of diagnosis, method of detection, and treatment was noted. Complications were entered prospectively by a nurse practitioner directly involved in patient care. Standardized criteria for diagnosis were used. A logistic regression model was used to discriminate statistical variation. RESULTS: A total of 1223 patients underwent resection and anastomosis during the study period. Mean age was 59.1 years. Leaks occurred in 33 patients (2.7%). Diagnosis was made a mean of 12.7 days postoperatively, including four beyond 30 days (12.1%). There was no difference in leak rate by surgeon (3.6% vs. 2.2%; P = 0.08). The leak rate was similar by surgical site except for a markedly increased leak rate with ileorectal anastomosis (P = 0.001). Twelve leaks were diagnosed clinically versus 21 radiographically. Contrast enema correctly identified only 4 of 10 leaks, whereas CT correctly identified 17 of 19. A total of 14 of 33 (42%) patients had their leak diagnosed only after readmission. Fifteen patients required fecal diversion, whereas 18 could be managed nonoperatively. CONCLUSIONS: Anastomotic leaks are frequently diagnosed late in the postoperative period and often after initial hospital discharge, highlighting the importance of prospective data entry and adequate follow-up. CT scan is the preferred diagnostic modality when imaging is required. More than half of leaks can be managed without fecal diversion.

BACKGROUND: The impact of intraoperative erythrocyte transfusion on outcomes of anemic patients undergoing noncardiac surgery has not been well characterized. The objective of this study was to examine the association between blood transfusion and mortality and morbidity in patients with severe anemia (hematocrit less than 30%) who are exposed to one or two units of erythrocytes intraoperatively. METHODS: This was a retrospective analysis of the association of blood transfusion and 30-day mortality and 30-day morbidity in 10,100 patients undergoing general, vascular, or orthopedic surgery. We estimated separate multivariate logistic regression models for 30-day mortality and for 30-day complications. RESULTS: Intraoperative blood transfusion was associated with an increased risk of death (odds ratio [OR], 1.29; 95% CI, 1.03-1.62). Patients receiving an intraoperative transfusion were more likely to have pulmonary, septic, wound, or thromboembolic complications, compared with patients not receiving an intraoperative transfusion. Compared with patients who were not transfused, patients receiving one or two units of erythrocytes were more likely to have pulmonary complications (OR, 1.76; 95% CI, 1.48-2.09), sepsis (OR, 1.43; 95% CI, 1.21-1.68), thromboembolic complications (OR, 1.77; 95% CI, 1.32-2.38), and wound complications (OR, 1.87; 95% CI, 1.47-2.37). CONCLUSIONS: Intraoperative blood transfusion is associated with a higher risk of mortality and morbidity in surgical patients with severe anemia. It is unknown whether this association is due to the adverse effects of blood transfusion or is, instead, the result of increased blood loss in the patients receiving blood.

BACKGROUND: The Injury Severity Score (ISS) has served as the standard summary measure of human trauma for 20 years. Despite its stalwart service, the ISS has two weaknesses: it relies upon the consensus derived severity estimates for each Abbreviated Injury Scale (AIS) injury and considers, at most, only three of an individual patient's injuries, three injuries that often are not even the patient's most severe injuries. Additionally, the ISS requires that all patients have their injuries described in the AIS lexicon, an expensive step that is currently taken only at hospitals with a zealous commitment to trauma care. We hypothesized that a data driven alternative to ISS that used empirically derived injury severities and considered all of an individual patient's injuries would more accurately predict survival. METHODS: Survival risk ratios were derived for every International Classification of Disease 9th Edition (ICD-9) injury category (800-959.9) using the North Carolina State Discharge Database experience with 300,000 trauma patients over 5 years. An ICD-9 Injury Severity Score (ICISS) was then defined as the product of all survival risk ratios for an individual patient's traumatic ICD-9 codes. We compared the performance of ISS and ICISS in a group of 3,142 patients accrued at the University of New Mexico Trauma Center over 4 years. These patients had both AIS and ICD-9 descriptors meticulously assigned prospectively by designated trauma data base personnel. RESULTS: ICISS outperformed ISS at a level that was highly statistically significant (p < 0.0001) and may be clinically important: ISS misclassification rate 7.67%, ISS Receiver Operator Characteristic Curve area = 0.872; ICISS misclassification rate 5.95%, ICISS Receiver Operator Characteristic Curve area = 0.921. Moreover, these improvements are largely preserved when ICISS is used in a probability of survival model that includes age, mechanism, and revised trauma score. About half of ICISS's improvement in predictive power is because of its use of an individual patient's worst three injuries regardless of body region. The remainder is because of better modeling of individual injuries and allowing all injuries to contribute to the final score. CONCLUSIONS: We conclude that ICISS is a much better predictor of survival than ISS in injured patients. The use of the ICD-9 lexicon may avoid the need for AIS coding, and thus may add an economic incentive to the statistical appeal of ICISS. It is possible that a similar data driven revision of ISS using the AIS vocabulary might perform as well or better than ICISS. Indeed, the actual lexicon used to divide up the injury "landscape" into individual injuries may be of little consequence so long as all injuries are considered and empirically derived SRRs are used to calculate the final injury measure.

BACKGROUND: : Generations of clinicians have used the Baux score, defined as the sum of age in years and percent body burn, to predict percent mortality after trauma, but advances in burn care have rendered the predictions of this score too pessimistic. Additionally, this score does not include the effects of inhalation injury. METHODS: : We revised the Baux score to include inhalation injury and recalibrated its predictions using a single-term logistic regression model developed using data on 39,888 burned patients provided by the national burn repository. We compared this revised Baux score to a more complex logistic regression model derived from the same data set and predictors. RESULTS: : A preliminary logistic regression model showed that age and percent burn contribute almost equally to mortality and further that the presence of inhalation injury added the equivalent of 17 years (or 17% burn). These observations suggested a revised Baux Score:Age + Percent Burn + 17 * (Inhalation Injury, 1 = yes, 0 = no)A logistic model based on the Revised Baux Score performed well, but a more complex model obtained using modern statistical model building tools had better discrimination and calibration. CONCLUSIONS: : Our proposed revised Baux score is simple enough for mental calculation, and its inverse logit transformation (provided with a calculator or nomogram) can provide precise predictions of mortality. Better predictions can be obtained using our more complex statistical model. Burn surgeons and nurses accustomed to using the original Baux score may welcome an updated version.