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Surgeon's Performance in Predicting Postoperative Infections

Surgeon's Performance in Predicting Postoperative Infections

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT05961930
Acronym
SPIRIT
Enrollment
594
Registered
2023-07-27
Start date
2023-02-01
Completion date
2023-09-10
Last updated
2025-04-04

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Postoperative Infection

Brief summary

Post-surgical (bacterial) infections are the most frequent post-surgical complications, including deep or superficial wound infections, urinary tract infections, pneumonia, and even sepsis. Approximately 6.5-25% of all surgical patients will develop any type of bacterial infection. To personalize surgical infection management, (Artificial Intelligence) models are in the making to predict which patients are at high or low risk of developing a post-surgical infection. In order to benchmark these prediction models to the predictive capabilities of surgeons, the investigators aim to investigate the performance of surgeons in predicting the risk of a patient developing (any type) of post-surgical infection within 30 days.

Detailed description

A prospective non-interventional study is performed to collect surgeons' predictions on the risk of a patient developing a postoperative infection within 30 days of surgery. Surgeons are asked to fill in a short questionnaire asking about the estimated infection risk. The actual outcome (infection \< 30 days of surgery) of a patient will be collected retrospectively after completion of the study. This study will have no effect on standard care: surgical interventions and postoperative care will be carried out according to standard clinical practice. Besides a one-time estimate of the surgeon, immediately after the surgical procedure, no other interventions will be performed and surgical specialists will carry out their normal post-surgical care, including screening and treating (if necessary) their patients for postoperative infections.

Interventions

BEHAVIORALQuestionnaire

Surgeons will be asked to fill in a short questionnaire after surgery on risk of postoperative infection

Sponsors

Leiden University Medical Center
Lead SponsorOTHER

Study design

Observational model
OTHER
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

Predictions are made for patients with the following inclusion and

Exclusion criteria

Inclusion Criteria: * Adult patients (\>18 years old) * Acute or elective surgery * Invasive or minimally invasive surgical procedures

Design outcomes

Primary

MeasureTime frameDescription
The discriminative predictive performance of surgeons with respect to estimating the risk of developing (any type) bacterial post-surgical within 30 days of surgery30 daysThe primary outcome measure of discrimination are area under the receiving operating characteristic curve (AUROC). Predictions are compared to the occurrence of a postoperative infection requiring treatment, surgical intervention or registration within 30 days of surgery.
The calibration properties of surgeons with respect to estimating the risk of developing (any type) bacterial post-surgical within 30 days of surgery30 daysCalibration plots with slope and intercept

Secondary

MeasureTime frameDescription
Predictive performance per surgeons and patients subgroups30 daysSurgeons subgroups are based on specialty, years of experience, level of experience, sex. Patient subgroups include, surgical specialty, age groups, type of surgical procedure, planned or emergency intervention.
Relationship between the certainty in estimate and the predictive performance of surgeons30 daysSurgeons are questioned on their certainty in the provided estimate
Comparison between the predicted risk of surgeons and an artificial intelligence algorithm30 daysThe performance of the physicians is compared to that of the artificial intelligence algorithm by means of AUROC
Relationship between predicted risk of surgeons and if they perform additional actions30 daysSurgeons are asked to indicate whether they performed additional actions for this patient in the questionnaire.
Relationship between patient factors and predicted risk30 daysSurgeons are questioned to indicate for a list of patient factors whether they were of impact to the decision

Countries

Netherlands

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026