Expansion of the surgical Apgar score across all surgical subspecialties as a means to predict postoperative mortality.

BACKGROUND: A surgical scoring system, akin to the obstetrician's Apgar score, has been developed to assess postoperative risk. To date, evaluation of this scoring system has been limited to general and vascular services. The authors attempt to externally validate and expand the Surgical Apgar Score across a wide breadth of surgical subspecialties. METHODS: Intraoperative data for 123,864 procedures including all surgical subspecialties were collected and associated with Surgical Apgar Scores (created by the summation of point values associated with the lowest mean arterial pressure, lowest heart rate, and estimated blood loss). Patients' death records were matched to the corresponding score, and logistic regression models were created in which mortality within 7, 30, and 90 days was regressed on the Apgar score. RESULTS: Lower Surgical Apgar Scores were associated with an increased risk of death. The magnitude of this association varied by subspecialty. Some subspecialties exhibited higher odds ratios, suggesting that the score is not as useful for them. For most of the subspecialties the association between the Apgar score and mortality decreased as the time since surgery increased, suggesting that predictive ability ceases to be helpful over time. After adjusting for the patient's American Society of Anesthesiologists classification, Apgar scores remained associated with death among most of the subspecialties. CONCLUSION: A previously published methodology for calculating risk among general and vascular surgical patients can be applied across many surgical services to provide an objective means of predicting and communicating patient outcomes in surgery as well as planning potential interventions.

Derivation and validation of Spo2/Fio2 ratio to impute for Pao2/Fio2 ratio in the respiratory component of the Sequential Organ Failure Assessment score.

OBJECTIVE: The Sequential Organ Failure Assessment (SOFA) score is validated to measure severity of organ dysfunction in critically ill patients. However, in some practice settings, daily arterial blood gas data required to calculate the respiratory component of the SOFA score are often unavailable. The objectives of this study were to derive Spo2/Fio2 (SF) ratio correlations with the Pao2/Fio2 (PF) ratio to calculate the respiratory parameter of the SOFA score, and to validate the respiratory SOFA obtained using SF ratios against clinical outcomes. PATIENTS AND MEASUREMENTS: We obtained matched measurements of Spo2 and Pao2 from two populations: group 1-patients undergoing general anesthesia and group 2-patients from the acute respiratory distress syndrome network-low-vs. high-tidal volume for the acute respiratory management of acute respiratory distress syndrome database. Using a linear regression model, we first determined SF ratios corresponding to PF ratios of 100, 200, 300, and 400. Second, we evaluated the contribution of positive end-expiratory pressure (PEEP) on the relationship between SF and PF, for patients on PEEP in centimeters of water (cm H2O) of <8, 8-12, and >12. Third, we calculated the SOFA scores in a separate cohort of intensive care unit patients using the derived SF ratios and validated them against clinical outcomes. RESULTS: The total SOFA scores calculated using SF ratios and PF ratios were highly correlated (Spearman's rho 0.85, p < 0.001) in all patients and in the three stratified PEEP categories (<8 cm H2O, Spearman's rho 0.87, p < 0.001; PEEP 8-12 cm H20, Spearman's rho 0.85, p < 0.001; PEEP >12 cm H2O, Spearman's rho 0.85, p < 0.001). The respiratory SOFA scores based on SF ratios and PF ratios correlated similarly with intensive care unit length of stay and ventilator-free days, when validated in a cohort of critically ill patients. CONCLUSION: The total and respiratory SOFA scores obtained with imputed SF values correlate with the corresponding SOFA score using PF ratios. Both the derived and original respiratory SOFA scores similarly predict outcomes.

Pain drawing scoring is not improved by inclusion of patient-reported pain sensation.

STUDY DESIGN: This is a retrospective study of 250 patients who describe low back pain with pain drawings. A computer application using artificial neural networks was designed to analyze pain drawings and evaluate the contribution of pain sensation to drawing classification. OBJECTIVE: The primary goal of this study was to assess the contribution of patient recorded pain sensation marks in classifying pain drawings into one of five broadly defined categories. The hypothesis was that including pain sensation would improve classification. SUMMARY OF BACKGROUND DATA: With no perfect diagnostic test for patients with low back pain, many approaches have been proposed and are used. One common diagnostic tool is the pain drawing. Several quantitative methods have been proposed to score the drawings. Some methods use pain sensation in the scoring; however, the contribution of pain sensation has not been defined. METHODS: A custom computer application classified the pain drawing. Data consisted of 250 pain drawings from patients with low back pain. RESULTS: Patient recorded pain sensation is not necessary in computer-based scoring of pain drawings. CONCLUSION: Patient-reported pain sensation does not improve classification when quantitatively scoring pain drawings.