title: Computerize anesthesia record keeping in thoracic surgery--suitability of electronic anesthesia records in evaluating predictors for hypoxemia during one-lung ventilation.
abstract: OBJECTIVE
  The aim of this retrospective study was to assess the suitability of routine data gathered with a computerized anesthesia record keeping system in investigating predictors for intraoperative hypoxemia (SpO2 < 90%) during one-lung ventilation (OLV) in pulmonary surgery.
  
  
  METHODS
  Over a four-year period data of 705 patients undergoing thoracic surgery (pneumonectomy: 78; lobectomy: 292; minor pulmonary resections: 335) were recorded online using an automated anesthesia record-keeping system. Twenty-six patient-related, surgery-related and anesthesia-related variables were studied for a possible association with the occurrence of intraoperative hypoxemia during OLV. Data were analyzed using univariate and multivariate (logistic regression) analysis (p < 0.05). The model's discriminative power on hypoxemia was checked with a receiver operating characteristic (ROC) curve. Calibration was tested using the Hosmer-Lemeshow goodness-of-fit test.
  
  
  RESULTS
  An intraoperative incidence of hypoxemia during OLV was found in 67 patients (9.5%). Using logistic regression with a forward stepwise algorithm, body-mass-index (BMI, p = 0.018) and preoperative existing pneumonia (p = 0.043) could be detected as independent predictors having an influence on the incidence of hypoxemia during OLV. An acceptable goodness-of-fit could be observed using cross validation for the model (C = 8.21, p = 0.370, degrees of freedom, df 8; H = 3.21, p = 0.350, df 3), the discriminative power was poor with an area under the ROC curve of 0.58 [0.51-0.66].
  
  
  CONCLUSIONS
  In contrast to conventional performed retrospective studies, data were directly available for analyses without any manual intervention. Due to incomplete information and imprecise definitions of parameters, data of computerized anesthesia records collected in routine are helpful but not satisfactory in evaluating risk factors for hypoxemia during OLV.
authors.affiliation: Department of Anaesthesiology, Intensive Care, and Pain Management, University Hospital Giessen, Germany.
authors.forename: Jochen
authors.initials: J
authors.lastname: Sticher
authors.forename: Axel
authors.initials: A
authors.lastname: Junger
authors.forename: Bernd
authors.initials: B
authors.lastname: Hartmann
authors.forename: Matthias
authors.initials: M
authors.lastname: Benson
authors.forename: Andreas
authors.initials: A
authors.lastname: Jost
authors.forename: Martin
authors.initials: M
authors.lastname: Golinski
authors.forename: Stefan
authors.initials: S
authors.lastname: Scholz
authors.forename: Gunter
authors.initials: G
authors.lastname: Hempelmann
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D000768:Anesthesia, General; D015992:Body Mass Index; D002138:Calibration; D001330:Electronic Data Processing; D005260:Female; D006801:Humans; D000860:Hypoxia / Q000209:etiology*; D008297:Male; D008875:Middle Aged; D008991:Monitoring, Physiologic; D015999:Multivariate Analysis; D009716:Numerical Analysis, Computer-Assisted; D011237:Predictive Value of Tests; D012121:Respiration, Artificial; D012189:Retrospective Studies; D012307:Risk Factors; D019616:Thoracic Surgical Procedures