The new timing in acute care surgery (new TACS) classification: a WSES Delphi consensus study.

BACKGROUND: Timely access to the operating room for emergency general surgery (EGS) indications remains a challenge across the globe, largely driven by operating room availability and staffing constraints. The "timing in acute care surgery" (TACS) classification was previously published to introduce a new tool to triage the timely and appropriate access of EGS patients to the operating room. However, the clinical and operational effectiveness of the TACS classification has not been investigated in subsequent validation studies. This study aimed to improve the TACS classification and provide further consensus around the appropriate use of the new TACS classification through a standardized Delphi approach with international experts. METHODS: This is a validation study of the new TACS by a selected international panel of experts using the Delphi method. The TACS questionnaire was designed as a web-based survey. The consensus agreement level was established to be ≥ 75%. The collective consensus agreement was defined as the sum of the percentage of the highest Likert scale levels (4-5) out of all participants. Surgical emergency diseases and correlated clinical scenarios were defined for each of the proposed classes. Subsequent rounds were carried out until a definitive level of consensus was reached. Frequencies and percentages were calculated to determine the degree of agreement for each surgical disease. RESULTS: Four polling rounds were carried out. The new TACS classification provides 6 colour-code classes correlated to a precise timing to surgery, defined scenarios and surgical condition. The WHITE colour-code class was introduced to rapidly (within a week) reschedule cancelled or postponed surgical procedures. Haemodynamic stability is the main tool to stratify patients for immediate surgery or not in the presence of sepsis/septic shock. Fifty-one surgical diseases were included in the different colour-code classes of priority. CONCLUSION: The new TACS classification is a comprehensive, simple, clear and reproducible triage system which can be used to assess the severity of the patient and the surgical disease, to reduce the time to access to the operating room, and to manage the emergency surgical patients within a "safe" timeframe. By including well-defined surgical diseases in the different colour-code classes of priority, validated through a Delphi consensus, the new TACS improves communication among surgeons, between surgeons and anaesthesiologists and decreases conflicts and waste and waiting time in accessing the operating room for emergency surgical patients.

Is it possible to predict the severity of acute appendicitis? Reliability of predictive models based on easily available blood variables.

INTRODUCTION: Recent evidence confirms that the treatment of acute appendicitis is not necessarily surgical, and selected patients with uncomplicated appendicitis can benefit from a non-operative management. Unfortunately, no cost-effective test has been proven to be able to effectively predict the degree of appendicular inflammation as yet, therefore, patient selection is too often left to the personal choice of the emergency surgeon. Our paper aims to clarify if basic and readily available blood tests can give reliable prognostic information to build up predictive models to help the decision-making process. METHODS: Clinical notes of 2275 patients who underwent an appendicectomy with a presumptive diagnosis of acute appendicitis were reviewed, taking into consideration basic preoperative blood tests and histology reports on the surgical specimens. Variables were compared with univariate and multivariate analysis, and predictive models were created. RESULTS: 18.2% of patients had a negative appendicectomy, 9.6% had mucosal only inflammation, 53% had transmural inflammation and 19.2% had gangrenous appendicitis. A strong correlation was found between degree of inflammation and lymphocytes count and CRP/Albumin ratio, both at univariate and multivariate analysis. A predictive model to identify cases of gangrenous appendicitis was developed. CONCLUSION: Low lymphocyte count and high CRP/Albumin ratio combined into a predictive model may have a role in the selection of patients who deserve appendicectomy instead of non-operative management of acute appendicitis.