BiZact™ tonsillectomy: Predictive factors for post-tonsillectomy haemorrhage from a 1717 case series.

OBJECTIVE: To determine primary and secondary post-tonsillectomy haemorrhage (PTH) rates and identify predictive factors in a cohort of consecutive adult and paediatric BiZact™ tonsillectomy cases. SETTING: Retrospective cohort study. Patients from Flinders Medical Centre, Noarlunga Hospital and private otolaryngology practices who underwent BiZact™ tonsillectomy from 2017 to 2020. DATA COLLECTED: patient age, indication for tonsillectomy, surgeon experience, time and severity of PTH, including return to theatre. Each secondary PTH was graded using the Stammberger classification. Logistic regression was utilised to identify predictors of secondary PTH. RESULTS: One thousand seven hundred and seventeen patient medical records were assessed (658 adults and 1059 children). The primary PTH rate was 0.1%, and secondary PTH rate was 5.9%. The majority of secondary PTH cases were Stammberger grade A (80/102, 78.4%) requiring observation only. Few secondary PTH required medical intervention (grade B; 9/102, 8.8%), return to theatre (grade C; 12/102, 11.8%), or blood transfusion (grade D; 1/102, 1.0%), with no death reported (grade E; 0/102, 0.0%). Recurrent secondary PTH occurred in 8 patients (0.5%). Predictive factors of secondary PTH in children were surgeon experience with trainees having greater chance of PTH (OR 2.502, 95% CI 1.345-4.654; p = .004) and age of child (OR 1.095, 95% CI 1.025-1.170; p = .007). Surgeon experience was a predictive factor for adults (OR 3.804, 95% CI 2.139-6.674; p < .001). CONCLUSIONS: BiZact™ tonsillectomy has a low primary PTH rate, with a secondary PTH rate comparable to other 'hot tonsillectomy' techniques. The majority of PTH events were minor and self-reported. There appears to be a learning curve for trainee surgeons.

Ear microbiota and middle ear disease: a longitudinal pilot study of Aboriginal children in a remote south Australian setting.

BACKGROUND: Otitis media (OM) is a major disease burden in Australian Aboriginal children, contributing to serious long-term health outcomes. We report a pilot analysis of OM in children attending an outreach ear and hearing clinic in a remote south Australian community over a two-year period. Our study focuses on longitudinal relationships between ear canal microbiota characteristics with nasopharyngeal microbiota, and clinical and treatment variables. RESULTS: Middle ear health status were assessed in 19 children (aged 3 months to 8 years) presenting in remote western South Australia and medical interventions were recorded. Over the two-year study period, chronic suppurative OM was diagnosed at least once in 7 children (37%), acute OM with perforation in 4 children (21%), OM with effusion in 11 children (58%), while only 1 child had no ear disease. Microbiota analysis of 19 children (51 sets of left and right ear canal swabs and nasopharyngeal swabs) revealed a core group of bacterial taxa that included Corynebacterium, Alloiococcus, Staphylococcus, Haemophilus, Turicella, Streptococcus, and Pseudomonas. Within-subject microbiota similarity (between ears) was significantly greater than inter-subject similarity, regardless of differences in ear disease (p = 0.0006). Longitudinal analysis revealed changes in diagnosis to be associated with more pronounced changes in microbiota characteristics, irrespective of time interval. Ear microbiota characteristics differed significantly according to diagnosis (P (perm) = 0.0001). Diagnoses featuring inflammation with tympanic membrane perforation clustering separately to those in which the tympanic membrane was intact, and characterised by increased Proteobacteria, particularly Haemophilus influenzae, Moraxella catarrhalis, and Oligella. While nasopharyngeal microbiota differed significantly in composition to ear microbiota (P (perm) = 0.0001), inter-site similarity was significantly greater in subjects with perforated tympanic membranes, a relationship that was associated with the relative abundance of H. influenzae in ear samples (rs = - 0.71, p = 0.0003). Longitudinal changes in ear microbiology reflected changes in clinical signs and treatment. CONCLUSIONS: Children attending the ear and hearing clinic in a remote Aboriginal community present with a broad spectrum of OM conditions and severities, consistent with other remote Aboriginal communities. Ear microbiota characteristics align with OM diagnosis and change with disease course. Nasopharyngeal microbiota characteristics are consistent with the contribution of acute upper respiratory infection to OM aetiology.

Tonsillectomy in Australia: an audit of surgical technique and postoperative care.

OBJECTIVE: To assess current tonsillectomy practice among Australian otolaryngologists. STUDY DESIGN: An audit based on an anonymous 19-item postal questionnaire on tonsillectomy technique and perioperative management sent to all Australian otolaryngology specialists. SUBJECTS AND METHODS: Two hundred eighty-four otolaryngologists registered with the Australian Society of Otolaryngology-Head and Neck Surgery database were sent the questionnaire. RESULTS: A 72.5 percent response rate was obtained. Monopolar diathermy was the most common technique for dissection (45%) and hemostasis (54%). Bipolar diathermy was used for hemostasis in 20 percent. Cold-steel dissection was routinely used by 36 percent, ties were used for hemostasis only by 11 percent of surgeons. The use of local anesthetic, dexamethasone, and postoperative antibiotics was 45 percent, 40 percent, and 20 percent, respectively. Seventy-six percent of surgeons always observed tonsil patients overnight. CONCLUSION: Australian surgeons still use monopolar diathermy as their preferred technique for tonsillectomy. Local anesthetic, dexamethasone, and postoperative antibiotics are used infrequently, and fewer than 1:4 surgeons perform day-case tonsillectomy.

The coblation tonsillectomy learning curve.

OBJECTIVE: To establish if there is a learning curve for coblation tonsillectomy. STUDY DESIGN: Regression analysis of data obtained from surgeons identified from the Australian Tonsillectomy Survey. SUBJECTS AND METHODS: Thirty otolaryngologists were invited to contribute audit data. Data were stratified into groups of 10 procedures and analysed with regression analysis. RESULTS: Nineteen (70%) surgeons responded. Complete data were obtained for 1700 cases and return to theatre data on 2062 cases. There was a significant learning curve with respect to both primary (P = 0.050) and secondary (P = 0.028) hemorrhage rates. Mean rates were 0.3% (95% CI 0.1% to 0.7%) and 2.1% (95% CI 1.5% to 2.9%) for primary and secondary bleeds, respectively, with return to theatre in 0.2% (95% CI 0.1% to 0.5%) and 1.3% (95% CI 0.9% to 1.9%), respectively. CONCLUSION: The introduction of coblation tonsillectomy into Australia was associated with a statistically significant learning curve with respect to both primary and secondary hemorrhage rates.