We investigated the ability of large language models (LLMs) to answer anesthesia related queries prior to surgery from a patient′s point of view. In the study, we introduced textual data evaluation metrics, investigated ″hallucinations″ phenomenon, and evaluated feasibility of using LLMs at the patient-clinician interface. ChatGPT was found to be lengthier, intellectual, and effective in its response as compared to Bard. Upon clinical evaluation, no ″hallucination″ errors were reported from ChatGPT, whereas we observed a 30.3% error in response from Bard. ChatGPT responses were difficult to read (college level difficulty) while Bard responses were more conversational and about 8th grade level from readability calculations. Linguistic quality of ChatGPT was found to be 19.7% greater for Bard (66.16 ± 13.42 vs. 55.27 ± 11.76; p=0.0037) and was independent of response length. Computational sentiment analysis revelated that polarity scores of on a Bard was significantly greater than ChatGPT (mean 0.16 vs. 0.11 on scale of -1 (negative) to 1 (positive); p=0.0323) and can be classified as ″positive″′ whereas subjectivity scores were similar across LLM′s (mean 0.54 vs 0.50 on a scale of 0 (objective) to 1 (subjective), p=0.3030). Even though the majority of the LLM responses were appropriate, at this stage these chatbots should be considered as a versatile clinical resource to assist communication between clinicians and patients, and not a replacement of essential pre-anesthesia consultation. Further efforts are needed to incorporate health literacy that will improve patient-clinical communications and ultimately, post-operative patient outcomes.

The authors have declared no competing interest.

Funding was provided by Department of Anesthesiology and Pain Management, The University of Texas Southwestern Medical Center, Dallas, TX.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

All data produced in the present work in provided in the supplementary materials.