BACKGROUND: Patient-associated co-morbidities are a potential cause of postoperative complications. The National Surgical Quality Improvement Project (NSQIP) collects data on patient outcomes to provide risk-adjusted outcomes data to participating hospitals. However, operations which may have a high distribution of technically-related complications, such as pancreatic operations, may not be adequately assessed using such predictive models. METHODS: A combined data set of NSQIP Public Use files (PUF) from 2005 to 2008 was created. Using this database, multiple logistic regression analyses were used to generate a predictive model of 30-day postoperative morbidity and mortality for pancreatic operations and all other operations recorded in NSQIP. Receiver-operator characteristic curves were generated and the area under those curves (AUROC) used to generate a c-statistic to assess the model's discriminatory ability. Observed-to-expected (O/E) ratios of for mortality and morbidity using not only patient-associated co-morbidities, but operation-associated information, such as work relative-value units and Current Procedural Terminology codes, were generated. Data were analyzed in SPSS. RESULTS: In the 4-year period analyzed, there were 7,097 complex pancreatic procedures done which were compared to 568,371 procedures that were not. For postoperative mortality, the AUROC was less for pancreatic operations (0.741) compared to all other operation (0.947) and all other inpatient operations (0.927). Similarly for postoperative morbidity, the AUROC was less for pancreatic operations (0.598) compared to all other operations (0.764) and all other inpatient operations (0.817). However, the O/E ratios were similar in both groups for mortality (all other operations, 0.94 vs. pancreatic operations, 0.92) and morbidity (0.98 for both). CONCLUSIONS: These data imply that the factors used to assess postoperative mortality and morbidity may not completely explain postoperative outcomes in pancreatic operations. These procedures are technically demanding and can have morbidities not related to pre-existing co-morbid conditions; therefore, preoperative prediction based on pre-existing co-morbidities may have limitations in these types of operations.
BACKGROUND:Patient-associated co-morbidities are a potential cause of postoperative complications. The National Surgical Quality Improvement Project (NSQIP) collects data on patient outcomes to provide risk-adjusted outcomes data to participating hospitals. However, operations which may have a high distribution of technically-related complications, such as pancreatic operations, may not be adequately assessed using such predictive models. METHODS: A combined data set of NSQIP Public Use files (PUF) from 2005 to 2008 was created. Using this database, multiple logistic regression analyses were used to generate a predictive model of 30-day postoperative morbidity and mortality for pancreatic operations and all other operations recorded in NSQIP. Receiver-operator characteristic curves were generated and the area under those curves (AUROC) used to generate a c-statistic to assess the model's discriminatory ability. Observed-to-expected (O/E) ratios of for mortality and morbidity using not only patient-associated co-morbidities, but operation-associated information, such as work relative-value units and Current Procedural Terminology codes, were generated. Data were analyzed in SPSS. RESULTS: In the 4-year period analyzed, there were 7,097 complex pancreatic procedures done which were compared to 568,371 procedures that were not. For postoperative mortality, the AUROC was less for pancreatic operations (0.741) compared to all other operation (0.947) and all other inpatient operations (0.927). Similarly for postoperative morbidity, the AUROC was less for pancreatic operations (0.598) compared to all other operations (0.764) and all other inpatient operations (0.817). However, the O/E ratios were similar in both groups for mortality (all other operations, 0.94 vs. pancreatic operations, 0.92) and morbidity (0.98 for both). CONCLUSIONS: These data imply that the factors used to assess postoperative mortality and morbidity may not completely explain postoperative outcomes in pancreatic operations. These procedures are technically demanding and can have morbidities not related to pre-existing co-morbid conditions; therefore, preoperative prediction based on pre-existing co-morbidities may have limitations in these types of operations.
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