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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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Surgeons estimate of postoperative infection | All surgeons will be asked to fill in a questionnaire, containing 5 questions, pertaining to the estimated risk of postoperative infection (within 30days). Thus there is a single arm and no comparison. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Questionnaire | Behavioral | Surgeons will be asked to fill in a short questionnaire after surgery on risk of postoperative infection |
|
| Measure | Description | Time Frame |
|---|---|---|
| The discriminative predictive performance of surgeons with respect to estimating the risk of developing (any type) bacterial post-surgical within 30 days of surgery | The 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. | 30 days |
| The calibration properties of surgeons with respect to estimating the risk of developing (any type) bacterial post-surgical within 30 days of surgery | Calibration plots with slope and intercept | 30 days |
| Measure | Description | Time Frame |
|---|---|---|
| Relationship between the certainty in estimate and the predictive performance of surgeons | Surgeons are questioned on their certainty in the provided estimate | 30 days |
| Relationship between patient factors and predicted risk |
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Predictions are made for patients with the following inclusion and exclusion criteria:
Inclusion Criteria:
Exclusion Criteria:
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Adult, surgical population of different surgical subspecialties.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Sesmu Arbous | Leiden | South Holland | 2333 ZA | Netherlands |
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| ID | Term |
|---|---|
| D011795 | Surveys and Questionnaires |
| ID | Term |
|---|---|
| D003625 | Data Collection |
| D004812 | Epidemiologic Methods |
| D008919 | Investigative Techniques |
| D017531 | Health Care Evaluation Mechanisms |
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Surgeons are questioned to indicate for a list of patient factors whether they were of impact to the decision
| 30 days |
| Predictive performance per surgeons and patients subgroups | Surgeons 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. | 30 days |
| Relationship between predicted risk of surgeons and if they perform additional actions | Surgeons are asked to indicate whether they performed additional actions for this patient in the questionnaire. | 30 days |
| Comparison between the predicted risk of surgeons and an artificial intelligence algorithm | The performance of the physicians is compared to that of the artificial intelligence algorithm by means of AUROC | 30 days |
| D011787 | Quality of Health Care |
| D017530 | Health Care Quality, Access, and Evaluation |
| D011634 | Public Health |
| D004778 | Environment and Public Health |