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TRUVACE RECORD VERSION
record: TRV-2026-2354
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-03T18:02:09.031679Z
status: published
lens: trace
sector: health
headline: Large language model responses to postoperative questions in oral and maxillofacial surgery: a comparative evaluation
dek: Abstract Background Large language models (LLMs) are increasingly used as patient-facing informational tools in dentistry, but their suitability for postoperative communication in oral and maxillofacial surgery (OMFS) remains uncertain. This study compared ChatGPT-5.4 Thinking, DeepSeek-V3.2, and Gemini 3 (Thinking mode) in answering routine postoperative OMFS questions. Methods Thirty standardised open-ended postoperative questions were submitted once to each model through public web interfaces using the same n…
gain_title: Expert surgeons rated the chatbot answers highly for quality, led by Gemini 3 at 4.82 out of 5, and 89 of 90 responses were classified as safe.
problem_title: One Gemini response on clopidogrel resumption was classed as a missed red flag giving false reassurance, and factual accuracy ratings showed limited agreement between raters.
trace_subject: Chatbot answers to postoperative questions in oral and maxillofacial surgery
gain_reading: Expert surgeons rated the chatbot answers highly for quality, led by Gemini 3 at 4.82 out of 5, and 89 of 90 responses were classified as safe.
gain_evidence: Of 90 responses, 89 were classified as Safe
problem_reading: One Gemini response on clopidogrel resumption was classed as a missed red flag giving false reassurance, and factual accuracy ratings showed limited agreement between raters.
problem_evidence: one Gemini response on clopidogrel resumption was classified as Missed Red Flag/False Reassurance
quick_read: Researchers put 30 routine aftercare questions from oral and maxillofacial surgery to three chatbots: ChatGPT-5.4 Thinking, DeepSeek-V3.2 and Gemini 3. Three surgeons, blinded to which model wrote each answer, scored quality, accuracy, completeness and safety, and the team also measured readability and response time.

Gemini scored highest on expert-rated quality, but accuracy differences between models did not hold after the ratings were reassessed, and completeness did not differ. One answer on resuming clopidogrel gave false reassurance. The test used simulated single-turn English questions, so it says little about whether real patients understand the answers or are kept safe.
limitation: The findings are limited to simulated, single-turn, English-language first responses and do not establish patient comprehension or real-world safety.
tag: Dual reading
key_points: Mean quality scores were 4.82 for Gemini 3, 4.53 for DeepSeek-V3.2 and 4.08 for ChatGPT-5.4 Thinking. | 89 of 90 responses were rated safe; one Gemini answer on clopidogrel was a missed red flag. | Original accuracy and completeness ratings showed limited rater agreement, and accuracy differences disappeared after reassessment. | Gemini kept its quality advantage after adjusting for word count, but its answers were more linguistically complex and slower.
rundown: Thirty standardised open-ended questions were submitted once to each model through public web interfaces using the same neutral prompt. Three surgeons rated overall quality on an adapted 5-point Global Quality Score, with excellent inter-rater reliability.

Accuracy, completeness and clinical safety were judged against a question-specific reference answer and safety framework. Accuracy differed in the original ratings (p = 0.014) but not after reassessment (p = 0.115).

DeepSeek-V3.2 had the shortest observed latency at 10.49 seconds and Gemini the longest at 31.46 seconds, though the authors say this does not reflect intrinsic model speed. The authors conclude that chatbot-generated postoperative information should remain under professional oversight.
sources:
- peer_reviewed | BMC Oral Health | https://doi.org/10.1186/s12903-026-10394-3 | 2026-11-03
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