Post-Tonsillectomy Bleeding and Analgesic Use Before and After the FDA Boxed Warning Against Codeine.

OBJECTIVE: The aim of this study was to investigate the trends in post-tonsillectomy analgesic utility and incidence of post-tonsillectomy hemorrhage before and after the 2013 FDA Boxed Warning against codeine use after pediatric tonsillectomy. METHODS: A retrospective study was conducted using TriNetX. A search for patients up to 18 years from 2008 to 2022 within the US Collaborative Network identified 15,648,542 subjects. CPT and ICD-10 codes were used to identify children who experienced post-tonsillectomy hemorrhage within 14 days of a tonsillectomy. Analgesics given within 14 days of tonsillectomy were tabulated annually from 2008 to 2022, including codeine, ibuprofen, acetaminophen, oxycodone, ketorolac, and hydrocodone. Bleeding percentage and analgesic utility were grouped into events before and after 2013. RESULTS: Mean age at tonsillectomy was 5.6 years (SD = 3.0). Before 2013, the median percentage of children who experienced postoperative bleeding was 1.8% with 0.73% returning to the OR for bleeding control. After 2013, the median percentage of children who experienced postoperative bleeding was 2.4% (p = 0.029), and 0.99% returned to the OR (p = 0.008). Use of post-tonsillectomy codeine fell from 10.4% to 0.5% (p = 0.003) whereas ibuprofen rose from 2.0% to 63.9% (p = <0.001), acetaminophen from 42.8% to 77.2% (p = <0.001), ketorolac from 1.2% to 9.2% (p = <0.001), and oxycodone from 2.0% to 30.9% (p = <0.001). No change was detected in use of hydrocodone. CONCLUSION: Analgesics used post-tonsillectomy in children have changed since the FDA Boxed Warning against codeine. There has been a small but statistically significant increase in post-tonsillectomy bleeding. LEVEL OF EVIDENCE: IV Laryngoscope, 2024.

Microbiome and Otic Quinolone Levels Following Tympanoplasty Assessed by Gelatin Sponge Analysis.

OBJECTIVE: To determine if absorbable gelatin sponge (AGS) can be used to assess the posttympanoplasty microbiome and otic antibiotic exposure. STUDY DESIGN: Prospective. SETTING: Tertiary hospital. METHODS: Patients undergoing tympanoplasty were prospectively enrolled. Intraoperatively, AGS was applied to the medial ear canal/tympanic membrane (TM) for 1 minute after canal incision, then saved for analysis. Ear canals were packed with AGS at the end of surgery. Otic ofloxacin was administered until the first postoperative visit, when AGS was collected. Microbial presence was assessed by culture. Ofloxacin levels were assessed by liquid-chromatography mass-spectrometry. RESULTS: Fifty-three patients were included. AGS was collected in 92.9% of patients seen within 21 days compared to 70.8% of those seen at 22 to 35 days. At surgery, AGS yielded bacteria and fungi in 81% and 11%, respectively, including Staphylococcus species (55%) and Pseudomonas species (25%). Postoperatively, AGS yielded bacteria in 71% and fungi in 21% at the meatus, (staphylococci 57% and pseudomonas 25%). TM samples yielded bacteria in 69%, fungi in 6%, staphylococci in 53%, and pseudomonas in 19%. Ofloxacin concentration at the meatus was 248 µg/mL (95% confidence interval [CI]: 119-377) and at the TM was 126 µg/mL (95% CI: 58-194). Ofloxacin-resistant colonies were found in 75% of patients. CONCLUSION: Analysis of AGS is a viable technique for noninvasively studying healing metrics posttympanoplasty, including the microbiome and otic antibiotic exposure. Despite exposure to a high concentration of quinolones, the tympanoplasty wound is far from sterile, which may impact healing outcomes.

Acute Intratonsillar Abscess in an Adult: A Case Report and Literature Review.

Intratonsillar abscess (ITA) is rarely reported. Here, we present an uncommon case of acute ITA in an adult, discuss the evaluation and treatment plan, and review the ITA literature.  The abscess reported in the present study was diagnosed through a combination of clinical findings and computed tomography imaging, and treatment included drainage, intravenous (IV) clindamycin, and IV dexamethasone. The literature reports 72 ITA cases with specified treatments: 21 (29.2%) in adults, 19 (26.4%) in children, and 32 (44.4%) in patients of unspecified ages. Among them, 25 (34.7%) responded to antibiotics alone, 11 (15.3%) to needle aspiration and antibiotics, and 36 (50.0%) needed further intervention. Based on the presented case and literature review, we suggest the use of IV antibiotics with needle aspiration as the primary treatment for acute ITA. Incision and drainage (I&D) with antibiotics should be reserved for cases unresponsive to initial measures, and tonsillectomy is recommended for recurrent post-I&D cases.

Evaluation of an Artificial Intelligence System for Detection of Invasive Lobular Carcinoma on Digital Mammography.

Introduction Early breast cancer detection with screening mammography has been shown to reduce mortality and improve breast cancer survival. This study aims to evaluate the ability of an artificial intelligence computer-aided detection (AI CAD) system to detect biopsy-proven invasive lobular carcinoma (ILC) on digital mammography. Methods This retrospective study reviewed mammograms of patients who were diagnosed with biopsy-proved ILC between January 1, 2017, and January 1, 2022. All mammograms were analyzed using cmAssist® (CureMetrix, San Diego, California, United States), which is an AI CAD for mammography. The AI CAD sensitivity for detecting ILC on mammography was calculated and further subdivided by lesion type, mass shape, and mass margins. To account for the within-subject correlation, generalized linear mixed models were implemented to investigate the association between age, family history, and breast density and whether the AI detected a false positive or true positive. Odds ratios, 95% confidence intervals, and p-values were also calculated. Results A total of 124 patients with 153 biopsy-proven ILC lesions were included. The AI CAD detected ILC on mammography with a sensitivity of 80%. The AI CAD had the highest sensitivity for detecting calcifications (100%), masses with irregular shape (82%), and masses with spiculated margins (86%). However, 88% of mammograms had at least one false positive mark with an average number of 3.9 false positive marks per mammogram. Conclusion The AI CAD system evaluated was successful in marking the malignancy in digital mammography. However, the numerous annotations confounded the ability to determine its overall accuracy and this reduces its potential use in real-life practice.