Reproducibility and predictive value of three grading systems for intraoperative adverse events in a cohort of abdominal surgery

INTRODUCTION

Intraoperative adverse events (iAEs) are increasingly recognized for their impact on patient outcomes. The Kaafarani classification and Surgical Apgar Score (SAS) were developed to assess the intraoperative course; however, both have their drawbacks. ClassIntra was validated for iAEs of any origin. This study compares the Kaafarani and SAS to ClassIntra considering predictive value and interrater reliability in a cohort of abdominal surgery to support implementation of a classification in clinical practice.

METHODS

The authors made use of the LAParotomy or LAParoscopy and ADhesiolysis (LAPAD) study database of elective abdominal surgery. Detailed descriptions on iAEs were collected in real-time by a researcher. For the current research aim, all iAEs were graded according ClassIntra, Kaafarani, and SAS (score ≤4). The predictive value was assessed using univariable and multivariable linear regression and the area under the receiver operating curve (AUROC). Two teams graded ClassIntra and Kaafarani to assess the interrater reliability using Cohen's Kappa.

RESULTS

A total of 755 surgeries were included, in which 335 (44%) iAEs were graded according to ClassIntra, 228 (30%) to Kaafarani, and 130 (20%) to SAS. All classifications were significantly correlated to postoperative complications, with an AUROC of 0.67 (95% CI: 0.62-0.72), 0.64 (0.59-0.70), and 0.71 (0.56-0.76), respectively. For the secondary endpoint, the interrater reliability of ClassIntra with κ 0.87 (95% CI: 0.84-0.90) and Kaafarani 0.90 (95% CI: 0.87-0.93) was both strong.

CONCLUSION

ClassIntra, Kaafarani, and SAS can be used for reporting of iAEs in abdominal surgery with good predictive value for postoperative complications, with strong reliability. ClassIntra, compared with Kaafarani and SAS, included the most iAEs and has the most comprehensive definition suitable for uniform reporting of iAEs in clinical practice and research.

Predicting Major Complications Following Laparotomy for Gastrointestinal Conditions Using Surgical Apgar Score: A Prospective Analysis in a Nigerian Population

BACKGROUND

Surgical Apgar score (SAS) is one of the risk assessment tools used in predicting postoperative complications. It is a simple and inexpensive tool composed of three intra-operative variables; lowest heart rate, lowest mean arterial blood pressure, and estimated blood loss, which are scored with a total of 10 points, based on which patients are risk stratified for developing post-operative complications. SAS was found to have good predictive accuracy for post-operative morbidity and mortality. The main objective of this study was to determine the efficacy of SAS in predicting major complications following laparotomy for gastrointestinal conditions.

MATERIALS AND METHODS

The study was a prospective observational study, conducted in Aminu Kano Teaching Hospital, Kano, Nigeria. Eighty-three adult patients, who required laparotomy for gastrointestinal conditions were recruited. Data was collected using proforma, and patients were followed up for 30 days. The intra-operative parameters for SAS were scored, and according to the scores, patients were risk stratified for developing post-operative complications. The data were analyzed; sensitivity, specificity, and accuracy of the SAS were determined.

RESULTS

A total of 83 patients were recruited in the study. About half (44.6%) of the patients developed major post-operative complications and a mortality rate of 7.2%. Most of the patients that died had low SAS. The sensitivity, specificity, accuracy, and AUC of SAS found were: 83.8%. 47.8%, 63.9% and 0.74 (95% CI; 0.63-0.84, P < 0.001) respectively.

CONCLUSION

This study revealed that SAS is efficacious in predicting major complications following laparotomy for gastrointestinal conditions.

Utility of the Surgical Apgar Score in Kidney Transplantation: Is it Feasible to Predict ICU Admission, Hospital Readmission, Length of Stay, and Cost in This Patient Population?

BACKGROUND

This study analyzed the utility of the Surgical Apgar Scoring (SAS) system in predicting morbidity in kidney transplantation. Recipient comorbidities were evaluated for any effect on the SAS and then globally assessed for any relationship with intensive care unit (ICU) admission, need for dialysis, creatinine at discharge, length of stay, incremental, and total cost of transplantation. The hypothesis for this study is that a low SAS will be a statistically significant predictor of postoperative morbidity and associated costs.

METHODS

This was an institutional review board (IRB)-approved retrospective longitudinal cohort study on 204 solitary kidney transplant recipients (2009-2011). Patients were divided into 2 groups: low to moderate = SAS ≤ 7 and high = SAS ≥ 8. These groups were then analyzed against a host of variables.

RESULTS

Sixty-five percent of patients had an SAS of 7 or lower, while 35% had an SAS of 8 and higher. Recipients with a history of stroke were 88% more likely to be in the low-moderate SAS group (P = .017). Patients with lower SASs trended toward having less extended criteria donors (0.097) but were more likely to be admitted to the ICU (P = .043), leading to significantly higher transplant event hospitalization costs. Higher SASs were more likely to be readmitted to the hospital within 30 days of discharge (P = .027), leading to higher 30-day postdischarge costs (P = .014). Readmission rates, however, and 30-day follow-up costs were similar between SAS groups after controlling for donor characteristics, specifically donor marginality and recipient estimated glomerular filtration rate (eGFR).

CONCLUSION

The findings of this study suggest that a history of stroke in the recipient may lend to a lower SAS and that a low SAS is associated with ICU admission following transplant, leading to higher hospital costs.