“From prediction to practice in surgery: Why risk stratification and outcome models still fail to deliver consistent real-world impact—insights from recent evidence in emergency and elective surgical care”

Letter to the Editor

Dear Editor,

I read with interest the recent correspondence, “From prediction to action—making emergency laparotomy risk scores clinically usable,” which brings attention to a familiar but unresolved issue in surgical care—the gap between what we can predict and what we do in practice [1]. Along similar lines, recent work from this journal examining predictors of complications after thyroid surgery highlights that identifying risk factors does not automatically translate into better outcomes at the bedside [2].

Taken together, these contributions point to a broader challenge. Surgical risk models have become increasingly sophisticated, yet their day-to-day clinical impact often feels limited. In many settings, these tools remain peripheral consulted occasionally but not consistently embedded in decision-making. The reasons are likely multifactorial: time pressures, workflow interruptions, and sometimes a lack of confidence in how best to apply numerical risk estimates to individual patients.

What seems increasingly clear is that accuracy alone is not enough. A well-performing model that sits outside the clinical workflow is unlikely to change practice. For risk prediction to matter, it needs to be available at the right moment, presented in a usable format, and linked—explicitly or implicitly—to clinical decisions. Without this, prediction risks remaining informative rather than influential.

There is also a tendency to evaluate these tools based on statistical performance while giving less attention to whether they alter decisions or outcomes. A shift in focus may be needed. Instead of asking how well a model predicts complications, we might also ask whether it changes what we do, and whether that change benefits patients.

The discussion initiated by recent articles in this journal is therefore timely. Moving from prediction to practice will likely require not only better models, but better integration—into systems, workflows, and clinical thinking itself.

In that sense, the next step for surgical research may be less about developing new tools and more about making existing one’s work where it matters most: in everyday care.

Yours sincerely,

Dr Rita Sangtani

Ethical approval and consent to participate

Not applicable. This article does not involve human participants, patient data, or animal subjects.

Consent for publication

Not applicable.

Availability of Data and Materials: No datasets were generated or analysed for this study.

Funding

No funding was received for this work.

CRediT authorship contribution statement

Rita Sangtani: Conceptualization, Writing – original draft, Writing – review & editing.

Declaration of competing interest

The author declares that there are no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.