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George J. Stukenborg - One of the best experts on this subject based on the ideXlab platform.
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Trauma centre patient volume and inpatient Mortality Risk reconsidered.
Injury, 2016Co-Authors: J. Forrest Calland, George J. StukenborgAbstract:Abstract Background Several studies have examined the relationship between injury volumes and trauma centre outcomes, with varying results attributable to differences in the measurement of volume's effect on Mortality and differences in how characteristics are addressed as potential confounders. Methods This analysis includes all trauma cases reported to the NTDB 2012. The effect of trauma centre volume on patient Mortality Risk was measured in three different contexts: as a linear function of trauma centre volume, as a dichotomous function comparing patients in trauma centres with and without 1200 or more cases, and as a non-linear function of trauma centre volume. Multivariable weighted Hierarchical Generalized Linear Models were used to account for the combined effects of facility level and patient level covariates. Patient level Mortality Risk was assessed using the ACS Trauma Quality Improvement Programme methodology. Results Trauma centre volume was not a statistically significant predictor (at the α = 0.01 level) of patient Mortality Risk, in any of the three models. Comprehensive adjustments for patient level Risk were obtained, with excellent discrimination between survivor and decedent cases. The addition of trauma volume to baseline patient Mortality Risk yielded no improvement in the accuracy of any model. These results were not sensitive to the inclusion of Level II trauma centres. Equivalent results were obtained by repeating the analysis for the Level I subpopulation only. Conclusions Case volume may be a reasonable standard for determining whether adequate numbers of injured patients are available to support training needs and experience requirements of a Level I trauma centre. However, case volume is not a useful predictor of patient Mortality in individual facilities. Trauma centre volume has no independent effect, after accounting for the patient level characteristics that predominantly influence Mortality.
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Effects of leading Mortality Risk factors among trauma patients vary by age.
The journal of trauma and acute care surgery, 2013Co-Authors: J. Forrest Calland, Wenjun Xin, George J. StukenborgAbstract:BACKGROUND: Patient age is well recognized as a factor that contributes to increased Mortality Risk among trauma patients. Less well recognized is the potential that the strength of the effects of other Risk factors that increase Mortality Risk may depend on a patient's age. This study examines whether the statistical relationship between trauma patient survival and key Mortality Risk factors varies significantly by patient age in years, across mechanisms of injury. METHODS: The statistical interaction between age and values of key Risk factors included in the Trauma Quality Improvement Program Mortality Risk adjustment model is assessed using patient data included in the 2008 National Trauma Data Bank National Sample Program. Multivariable logistic regression analysis is used to assess the statistical significance of the interaction effect on patient morality Risk for key Mortality Risk factors and patient age in years, across mechanisms of injury. RESULTS: Statistically significant interactions (p Language: en
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Present-at-admission diagnoses improve Mortality Risk adjustment and allow more accurate assessment of the relationship between volume of lung cancer operations and Mortality Risk.
Surgery, 2005Co-Authors: George J. Stukenborg, Kerry L. Kilbridge, Douglas P. Wagner, Frank E. Harrell, M. Norman Oliver, Jason A. Lyman, Jonathan S. Einbinder, Alfred F. ConnorsAbstract:Background Mortality Risk adjustment is a key component of studies that examine the statistical relationship between hospital lung cancer operation volume and in-hospital Mortality. Previous studies of this relationship have used different methods of adjusting for factors that influence Mortality Risk, but none have adjusted for differences in comorbid disease using only diagnoses identified as present-at-admission. Methods This study uses adjustments for conditions identified as present-at-admission to examine the statistical relationship between the volume of lung cancer operations and Mortality among 14,456 California hospital patients, and compares these results to other methods of Risk adjustment similar to those used in previous studies. Results Mortality Risk adjustment using present-at-admission diagnoses yielded better discrimination and explained more of the variability in observed deaths. Large increases in hospital procedure volume were associated with much smaller decreases in Mortality Risk than those estimated using comparable Risk-adjustment models. Conclusions Present-at-admission diagnoses can be used to improve Mortality Risk adjustment and may allow a more accurate assessment of the relationship between procedure volume and Mortality Risk.
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Original communications Present-at-admission diagnoses improve Mortality Risk adjustment and allow more accurate assessment of the relationship between volume of lung cancer operations and Mortality Risk
2005Co-Authors: George J. Stukenborg, Kerry L. Kilbridge, Douglas P. Wagner, Frank E. Harrell, M. Norman Oliver, Jason A. Lyman, Jonathan S. Einbinder, Alfred F. ConnorsAbstract:Background. Mortality Risk adjustment is a key component of studies that examine the statistical relationship between hospital lung cancer operation volume and in-hospital Mortality. Previous studies of thisrelationshiphaveuseddifferentmethodsofadjustingfor factors thatinfluenceMortalityRisk,butnone have adjusted for differences in comorbid disease using only diagnoses identified as present-at-admission. Methods. This study uses adjustments for conditions identified as present-at-admission to examine the statistical relationship between the volume of lung cancer operations and Mortality among 14,456 California hospital patients, and compares these results to other methods of Risk adjustment similar to those used in previous studies. Results. Mortality Risk adjustment using present-at-admission diagnoses yielded better discrimination and explained more of the variability in observed deaths. Large increases in hospital procedure volume were associated with much smaller decreases in Mortality Risk than those estimated using comparable Riskadjustment models. Conclusions. Present-at-admission diagnoses can be used to improve Mortality Risk adjustment and may allow a more accurate assessment of the relationship between procedure volume and Mortality Risk. (Surgery 2005;138:498-507.)
Eric J Demaria - One of the best experts on this subject based on the ideXlab platform.
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validation of the obesity surgery Mortality Risk score in a multicenter study proves it stratifies Mortality Risk in patients undergoing gastric bypass for morbid obesity
Annals of Surgery, 2007Co-Authors: Eric J Demaria, Michel M Murr, Karl T Byrne, Robin Blackstone, John Grant, Amanda R Budak, Luke G WolfeAbstract:Background: A scoring system for clinical assessment of Mortality Risk has been previously proposed for bariatric surgery (Demaria EJ, Portenier D, Wolfe L, Surg Obes Relat Dis. 2007;3:34-40.). The Obesity Surgery Mortality Risk Score (OS-MRS) was developed from a single institution experience of 2075 patients. The current study provides multicenter validation of the value of the OS-MRS. The OS-MRS assigns 1 point to each of 5 preoperative variables, including body mass index≥50 kg/m 2 , male gender, hypertension, known Risk factors for pulmonary embolism (previous thromboembolism, preoperative vena cava filter, hypoventilation, pulmonary hypertension), and age≥45 years. Patients with total score of 0 to 1 are classified as 'A' (lowest) Risk group, score 2 to 3 as 'B' (intermediate) Risk group, and score 4 to 5 as 'C' (high) Risk group. Methods: Prospectively-collected data from 4431 consecutive patients undergoing a primary gastric bypass at 4 bariatric programs recruited to validate the proposed system were analyzed to assess OS-MRS as a means of stratifying surgical Mortality Risk. Results: There were 33 total deaths for an overall Mortality for the validation cohort of 0.7% consistent with published standards. Mortality for 2164 class A patients was 0.2%, for 2142 class B patients was 1.1%, and for 125 class C patients was 2.4%. Mortality was significantly different between each of the class A, B, and C groupings (P < 0.05, X 2 ). Mortality was 5-fold greater in the class B group than in class A. Only 6 patients with all 5 Risk factors were identified. Class C patients (n = 125, 3% of total cohort) were characterized by a 12-fold greater Mortality than the lowest Risk group (A) and a disproportionate 9% of all mortalities. Conclusion: The OS-MRS was found to stratify Mortality Risk in 4431 patients from 4 validation centers that were nonparticipants in the original defining cohort study. The score represents the first validated scoring system for Risk stratification in bariatric surgery and is anticipated to aid informed consent discussions, guide surgical decision-making, and allow standardization of outcome comparisons between treatment centers.
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obesity surgery Mortality Risk score proposal for a clinically useful score to predict Mortality Risk in patients undergoing gastric bypass
Surgery for Obesity and Related Diseases, 2007Co-Authors: Eric J Demaria, Dana Portenier, Luke G WolfeAbstract:Abstract Background Currently, no clinically useful scoring system is available to stratify the Mortality Risk for patients undergoing gastric bypass (GBP). We propose the obesity surgery Mortality Risk score as a clinically useful score system to predict the Mortality Risk for patients undergoing GBP. Methods Prospectively collected data from 2075 consecutive patients undergoing GBP at a single university from 1995 to 2004 were analyzed to determine the preoperative factors correlating with 90-day Mortality. Results Four independent variables correlated with Mortality using multivariate analysis, including body mass index ≥50 kg/m 2 (odds ratio [OR] 3.60, 95% confidence interval [CI] 1.44–8.99), male gender (OR 2.80, 95% CI 1.32–5.92), hypertension (OR 2.78, 95% CI 1.11–7.00), and a novel variable pulmonary embolus Risk, that included previous thrombosis, pulmonary embolus, inferior vena cava filter, right heart failure, and obesity hypoventilation (OR 2.62, 95% CI 1.12–6.12). A fifth variable, patient age ≥45 years (OR 1.64, 95% CI 0.78–3.48), significant on univariate analysis, was added to the ultimate scoring system because of its significance in other studies. A scoring system was developed by arbitrarily scoring the presence of each independent variable as equal to 1 point, resulting in an overall score of 0–5 points for each patient. The factors were grouped into 3 Risk classes (A, B, or C) to increase the evaluable cases in each class (e.g., Conclusion The analysis reveals that Mortality Risk for gastric bypass can be stratified based upon independent variables that can be identified before surgery. The OS-MRS, a simple, clinically relevant scoring system, is proposed, which stratifies Mortality Risk into low (Class A), intermediate (Class B), and high (Class C) Risk groups in the current study population. This Risk assessment scoring system may contribute to surgical decision making in bariatric surgery if its ability to stratify Risk is validated in subsequent studies.
Luke G Wolfe - One of the best experts on this subject based on the ideXlab platform.
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validation of the obesity surgery Mortality Risk score in a multicenter study proves it stratifies Mortality Risk in patients undergoing gastric bypass for morbid obesity
Annals of Surgery, 2007Co-Authors: Eric J Demaria, Michel M Murr, Karl T Byrne, Robin Blackstone, John Grant, Amanda R Budak, Luke G WolfeAbstract:Background: A scoring system for clinical assessment of Mortality Risk has been previously proposed for bariatric surgery (Demaria EJ, Portenier D, Wolfe L, Surg Obes Relat Dis. 2007;3:34-40.). The Obesity Surgery Mortality Risk Score (OS-MRS) was developed from a single institution experience of 2075 patients. The current study provides multicenter validation of the value of the OS-MRS. The OS-MRS assigns 1 point to each of 5 preoperative variables, including body mass index≥50 kg/m 2 , male gender, hypertension, known Risk factors for pulmonary embolism (previous thromboembolism, preoperative vena cava filter, hypoventilation, pulmonary hypertension), and age≥45 years. Patients with total score of 0 to 1 are classified as 'A' (lowest) Risk group, score 2 to 3 as 'B' (intermediate) Risk group, and score 4 to 5 as 'C' (high) Risk group. Methods: Prospectively-collected data from 4431 consecutive patients undergoing a primary gastric bypass at 4 bariatric programs recruited to validate the proposed system were analyzed to assess OS-MRS as a means of stratifying surgical Mortality Risk. Results: There were 33 total deaths for an overall Mortality for the validation cohort of 0.7% consistent with published standards. Mortality for 2164 class A patients was 0.2%, for 2142 class B patients was 1.1%, and for 125 class C patients was 2.4%. Mortality was significantly different between each of the class A, B, and C groupings (P < 0.05, X 2 ). Mortality was 5-fold greater in the class B group than in class A. Only 6 patients with all 5 Risk factors were identified. Class C patients (n = 125, 3% of total cohort) were characterized by a 12-fold greater Mortality than the lowest Risk group (A) and a disproportionate 9% of all mortalities. Conclusion: The OS-MRS was found to stratify Mortality Risk in 4431 patients from 4 validation centers that were nonparticipants in the original defining cohort study. The score represents the first validated scoring system for Risk stratification in bariatric surgery and is anticipated to aid informed consent discussions, guide surgical decision-making, and allow standardization of outcome comparisons between treatment centers.
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obesity surgery Mortality Risk score proposal for a clinically useful score to predict Mortality Risk in patients undergoing gastric bypass
Surgery for Obesity and Related Diseases, 2007Co-Authors: Eric J Demaria, Dana Portenier, Luke G WolfeAbstract:Abstract Background Currently, no clinically useful scoring system is available to stratify the Mortality Risk for patients undergoing gastric bypass (GBP). We propose the obesity surgery Mortality Risk score as a clinically useful score system to predict the Mortality Risk for patients undergoing GBP. Methods Prospectively collected data from 2075 consecutive patients undergoing GBP at a single university from 1995 to 2004 were analyzed to determine the preoperative factors correlating with 90-day Mortality. Results Four independent variables correlated with Mortality using multivariate analysis, including body mass index ≥50 kg/m 2 (odds ratio [OR] 3.60, 95% confidence interval [CI] 1.44–8.99), male gender (OR 2.80, 95% CI 1.32–5.92), hypertension (OR 2.78, 95% CI 1.11–7.00), and a novel variable pulmonary embolus Risk, that included previous thrombosis, pulmonary embolus, inferior vena cava filter, right heart failure, and obesity hypoventilation (OR 2.62, 95% CI 1.12–6.12). A fifth variable, patient age ≥45 years (OR 1.64, 95% CI 0.78–3.48), significant on univariate analysis, was added to the ultimate scoring system because of its significance in other studies. A scoring system was developed by arbitrarily scoring the presence of each independent variable as equal to 1 point, resulting in an overall score of 0–5 points for each patient. The factors were grouped into 3 Risk classes (A, B, or C) to increase the evaluable cases in each class (e.g., Conclusion The analysis reveals that Mortality Risk for gastric bypass can be stratified based upon independent variables that can be identified before surgery. The OS-MRS, a simple, clinically relevant scoring system, is proposed, which stratifies Mortality Risk into low (Class A), intermediate (Class B), and high (Class C) Risk groups in the current study population. This Risk assessment scoring system may contribute to surgical decision making in bariatric surgery if its ability to stratify Risk is validated in subsequent studies.
J. Forrest Calland - One of the best experts on this subject based on the ideXlab platform.
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Trauma centre patient volume and inpatient Mortality Risk reconsidered.
Injury, 2016Co-Authors: J. Forrest Calland, George J. StukenborgAbstract:Abstract Background Several studies have examined the relationship between injury volumes and trauma centre outcomes, with varying results attributable to differences in the measurement of volume's effect on Mortality and differences in how characteristics are addressed as potential confounders. Methods This analysis includes all trauma cases reported to the NTDB 2012. The effect of trauma centre volume on patient Mortality Risk was measured in three different contexts: as a linear function of trauma centre volume, as a dichotomous function comparing patients in trauma centres with and without 1200 or more cases, and as a non-linear function of trauma centre volume. Multivariable weighted Hierarchical Generalized Linear Models were used to account for the combined effects of facility level and patient level covariates. Patient level Mortality Risk was assessed using the ACS Trauma Quality Improvement Programme methodology. Results Trauma centre volume was not a statistically significant predictor (at the α = 0.01 level) of patient Mortality Risk, in any of the three models. Comprehensive adjustments for patient level Risk were obtained, with excellent discrimination between survivor and decedent cases. The addition of trauma volume to baseline patient Mortality Risk yielded no improvement in the accuracy of any model. These results were not sensitive to the inclusion of Level II trauma centres. Equivalent results were obtained by repeating the analysis for the Level I subpopulation only. Conclusions Case volume may be a reasonable standard for determining whether adequate numbers of injured patients are available to support training needs and experience requirements of a Level I trauma centre. However, case volume is not a useful predictor of patient Mortality in individual facilities. Trauma centre volume has no independent effect, after accounting for the patient level characteristics that predominantly influence Mortality.
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Effects of leading Mortality Risk factors among trauma patients vary by age.
The journal of trauma and acute care surgery, 2013Co-Authors: J. Forrest Calland, Wenjun Xin, George J. StukenborgAbstract:BACKGROUND: Patient age is well recognized as a factor that contributes to increased Mortality Risk among trauma patients. Less well recognized is the potential that the strength of the effects of other Risk factors that increase Mortality Risk may depend on a patient's age. This study examines whether the statistical relationship between trauma patient survival and key Mortality Risk factors varies significantly by patient age in years, across mechanisms of injury. METHODS: The statistical interaction between age and values of key Risk factors included in the Trauma Quality Improvement Program Mortality Risk adjustment model is assessed using patient data included in the 2008 National Trauma Data Bank National Sample Program. Multivariable logistic regression analysis is used to assess the statistical significance of the interaction effect on patient morality Risk for key Mortality Risk factors and patient age in years, across mechanisms of injury. RESULTS: Statistically significant interactions (p Language: en
Joseph Feldman - One of the best experts on this subject based on the ideXlab platform.
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Association of serum albumin and Mortality Risk
Journal of clinical epidemiology, 1997Co-Authors: Philip Goldwasser, Joseph FeldmanAbstract:Reduced levels of serum albumin concentration, a routine blood test, within the "normal" range have been reported to be associated with Mortality Risk. The literature is reviewed, with a focus on cohort studies meeting specified criteria, and findings are summarized. In studies of many populations, comprising healthy subjects and patients with acute or chronic illness, serum albumin concentration is inversely related to Mortality Risk in a graded manner over its entire range; the estimated increase in the odds of death ranges from 24% to 56% for each 2.5 g/l decrement in serum albumin concentration. The association predicts overall and cause-specific Mortality including cardiovascular Mortality. It is likely that albumin concentration is a highly sensitive indicator of preclinical disease and disease severity. A direct protective effect of the albumin molecule is suggested by the persistence of the association after adjustment for other known Risk factors and preexisting illness, and after exclusion of early Mortality. Although biologically plausible, there is no direct evidence for this hypothesis. Serum albumin concentration is an independent predictor of Mortality Risk and could be useful in the quantification of Risk in a broad range of clinical and research settings.