A worse ECOG-PS is associated with 30-day mortality among patients over 90 years old in non-cardiac surgeries: A single-center retrospective study

Predictive value of a novel digital risk calculator to determine early patient outcomes after major surgery: a proof-of-concept pilot study

BACKGROUND

A structured risk assessment of patients with validated and evidence-based tools can help to identify modifiable factors before major surgeries. The Protego Maxima trial investigated the value of a new digitized risk assessment tool that combines tools which can be easily used and implemented in the clinical workflow by doctors and qualified medical staff. The hypothesis was that the structured assessment and risk-grouping is predictive of short-term surgical quality reflected by complications and overall survival.

METHODS

The Protego Maxima Trial was a prospective cohort analysis of patients undergoing major surgery (visceral, thoracic, urology, vascular and gynecologic surgeries) as key inclusion criterion and the absence of an acute or acute on chronically decompensated pulmo-cardiovascular decompensation. Patients were risk-scored with the software (The Prehab App) that includes a battery of evidence-based risk assessment tools that allow a structured risk assessment. The data were grouped to predefined high and low risk groups and aggregate and individual scores. The primary outcome was to validate the predictive value of the RAI score and the TUG for overall survival in the high and low risk groups. Secondary outcomes were surgical outcomes at 90-days after surgery (overall survival, Clavien-Dindo (CD) 1-5 (all complications), and CD 3-5 (major complications)). The study was carried out in accordance with the DIN ISO 14,155, and the medical device regulation (MDR) at Frankfurt University Hospital between March 2022 and January 2023.

RESULTS

In total 267 patients were included in the intention to treat analysis. The mean age was 62.1 ± 12.4 years. Patients with a RAI score > 25 and/or a timed up and go (TUG) > 8 s had a higher risk for mortality at 90 days after surgery. The low-risk group predicted beneficial outcome and the high-risk group predicted adverse outcome in the ROC analysis (Area Under the Curve Receiver Operator Characteristics: AUROC > 0.800; p = 0.01). Risk groups (high vs. low) showed significant differences for 90-day survival (99.4% vs. 95.5%; p = 0.04) and major complications (16.4% vs. 32.4%; p < 0.001).

CONCLUSION

The proof-of-concept trial showed that a risk assessment with 'The Prehab App' may be viable to estimate the preoperative risk for mortality and major complications before major surgeries. The overall performance in this initial set of data indicated a certain reliability of the scoring and risk grouping, especially of the RAI score and the TUG. A larger data set will be required to proof the generalizability of the risk scoring to every subgroup and may be fostered by artificial intelligence approaches.

TRIAL REGISTRATION

Ethics number: 2021-483-MDR/MPDG-zuständig monocentric; The Federal Institute for Pharmaceuticals and Medical Devices/BfArM, reference number: 94.1.04-5660-13655; Eudamed: CIV-21-07-0307311; German Clinical Trial Registry: DRKS 00026985.

A systematic review of predictive accuracy via c-statistic of preoperative frailty tests for extended length of stay, post-operative complications, and mortality

Frailty, as an age-related syndrome of reduced physiological reserve, contributes significantly to post-operative outcomes. With the aging population, frailty poses a significant threat to patients and health systems. Since 2012, preoperative frailty assessment has been recommended, yet its implementation has been inhibited by the vast number of frailty tests and lack of consensus. Since the anesthesiologist is the best placed for perioperative care, an anesthesia-tailored preoperative frailty test must be simple, quick, universally applicable to all surgeries, accurate, and ideally available in an app or online form. This systematic review attempted to rank frailty tests by predictive accuracy using the c-statistic in the outcomes of extended length of stay, 3-month post-operative complications, and 3-month mortality, as well as feasibility outcomes including time to completion, equipment and training requirements, cost, and database compatibility. Presenting findings of all frailty tests as a future reference for anesthesiologists, Clinical Frailty Scale was found to have the best combination of accuracy and feasibility for mortality with speed of completion and phone app availability; Edmonton Frailty Scale had the best accuracy for post-operative complications with opportunity for self-reporting. Finally, extended length of stay had too little data for recommendation of a frailty test. This review also demonstrated the need for changing research emphasis from odds ratios to metrics that measure the accuracy of a test itself, such as the c-statistic.

Evaluation of Agreement Among Frailty Assessment Tools in Head and Neck Surgery

OBJECTIVE

To evaluate intertest agreement among hand grip strength (HGS), the modified Frailty Index (mFI), and the Edmonton Frail Scale (EFS) in patients presenting for presurgical assessment in a head and neck surgery clinic.

STUDY DESIGN

Prospective observational study.

SETTING

Academic tertiary medical center.

METHODS

Prospective data relating to 3 frailty measurements were collected for 96 consecutive adults presenting for presurgical counseling at a single high-volume head and neck surgical oncology clinic. Frailty was determined with previously validated thresholds for the mFI (≥3) and EFS (>7). The highest of 2 HGS measurements performed for the dominant hand was used to determine frail status based on previously validated sex- and body mass index-specific thresholds. Baseline characteristics were identified to determine the association of such variables to each tool. Agreement among frailty assessment tools was examined.

RESULTS

The frequency of frailty in the cohort varied among tools, ranging from 29.2% (28/96) for HGS to 12.5% (12/96) for the mFI and 4.2% (4/96) for the EFS. The overall agreement among the 3 frailty tools via the Fleiss index was poor (kappa, 0.088; 95% CI, -0.028 to 0.203).

CONCLUSION

Assessment of frailty is complex, and established frailty assessment tools may not agree on which patients are frail. When assessing a patient as frail, clinicians must be vigilant to the influence of frailty assessment tools on such determinations, which may contribute critical input during shared decision making for patients considering head and neck surgery or nonsurgical alternatives.