Improving thyroid function monitoring in head and neck cancer patients: A quality improvement study

Electrocardiographic biomarker based on machine learning for detecting overt hyperthyroidism

Aims

Although overt hyperthyroidism adversely affects a patient's prognosis, thyroid function tests (TFTs) are not routinely conducted. Furthermore, vague symptoms of hyperthyroidism often lead to hyperthyroidism being overlooked. An electrocardiogram (ECG) is a commonly used screening test, and the association between thyroid function and ECG is well known. However, it is difficult for clinicians to detect hyperthyroidism through subtle ECG changes. For early detection of hyperthyroidism, we aimed to develop and validate an electrocardiographic biomarker based on a deep learning model (DLM) for detecting hyperthyroidism.

Methods and results

This multicentre retrospective cohort study included patients who underwent ECG and TFTs within 24 h. For model development and internal validation, we obtained 174 331 ECGs from 113 194 patients. We extracted 48 648 ECGs from 33 478 patients from another hospital for external validation. Using 500 Hz raw ECG, we developed a DLM with 12-lead, 6-lead (limb leads, precordial leads), and single-lead (lead I) ECGs to detect overt hyperthyroidism. We calculated the model's performance on the internal and external validation sets using the area under the receiver operating characteristic curve (AUC). The AUC of the DLM using a 12-lead ECG was 0.926 (0.913-0.94) for internal validation and 0.883(0.855-0.911) for external validation. The AUC of DLMs using six and a single-lead were in the range of 0.889-0.906 for internal validation and 0.847-0.882 for external validation.

Conclusion

We developed a DLM using ECG for non-invasive screening of overt hyperthyroidism. We expect this model to contribute to the early diagnosis of diseases and improve patient prognosis.

Reducing opioid use in post-operative otolaryngology patients: A quality improvement project

PURPOSE

In opioid-naive patients, many low-risk surgical procedures are associated with an increased risk of chronic opioid use. The goal of this quality improvement project was to reduce the amount of opioid prescriptions after commonly performed surgeries in otolaryngology.

MATERIALS AND METHODS

Pre-intervention opioid prescribing state was measured using anonymous provider and patient surveys, as well as pharmacy provider prescription data. Next, this information was used to develop an opioid prescription protocol that both standardized opioid prescribing practices and encouraged multimodal analgesia following routine surgery. Finally, post-intervention data were gathered and compared to pre-intervention data to assess changes in prescribing patterns.

RESULTS

By patient survey, the worst pain and average pain after surgery (scale of 1-10) were unchanged after the intervention (5.1 to 4.8, p = 0.52; 4.1 to 3.6, p = 0.35, respectively). Post-intervention, 41% of patients reported receiving no opiates, whereas pre-intervention 100% of patients surveyed received opiates. The amount of ibuprofen and acetaminophen prescribed post-intervention increased 113% and 71%, respectively. By survey, the average number of opioid doses decreased from 24.0 ± 7.0 to 18.4 ± 6.6 (p = 0.018).

CONCLUSIONS

The implementation of a standardized physician opioid prescription protocol did not affect patient pain perceptions, resulted in an increase in multimodal analgesia prescription, and increased provider awareness of opioid over prescription.

Implementation of a stereotactic body radiotherapy program for unresectable pancreatic cancer in an integrated community academic radiation oncology satellite network

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PDSA methodology was used to implement a pancreas SBRT in an academic satellite network.

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Oncologic outcomes were favorable with no serious adverse events.

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This technical note provides groundwork for safe establishment of SBRT pancreas programs.

With increasing interest in stereotactic body radiotherapy (SBRT) for unresectable pancreatic cancer, quality improvement (QI) initiatives to develop integrated clinical workflows are crucial to ensure quality assurance (QA) when introducing this challenging technique into radiation practices.

Materials/Methods: In 2017, we used the Plan, Do, Study, Act (PDSA) QI methodology to implement a new pancreas SBRT program in an integrated community radiation oncology satellite. A unified integrated information technology infrastructure was used to virtually integrate the planned workflow into the community radiation oncology satellite network (P – Plan/D – Do). This workflow included multiple prospective quality assurance (QA) measures including multidisciplinary evaluation, prospective scrutiny of radiation target delineation, prospective radiation plan evaluation, and monitoring of patient outcomes. Institutional review board approval was obtained to retrospectively study and report outcomes of patients treated in this program (S – Study).

Results:

There were 12 consecutive patients identified who were treated in this program from 2017 to 2020 with a median follow-up of 27 months. The median survival was 13 months, median local failure free survival was 12 months and median progression free survival was 6 months from SBRT. There were no acute or late Common Terminology Criteria for Adverse Effects (CTCAE) version 5 toxicities ≥ Grade 3.

Conclusion:

We report the successful implementation of a community pancreas SBRT program involving multiple prospective QA measures, providing the groundwork to safely expand access to pancreas SBRT in our community satellite network (A – Act).

Impact of provider type and number of providers on surveillance testing among survivors of head and neck cancers

BACKGROUND

Guidelines for follow-up after head and neck cancer (HNC) treatment recommend frequent clinical examinations and surveillance testing. Here, the authors describe real-world follow-up care for HNC survivors and variations in surveillance testing.

METHODS

Using Surveillance, Epidemiology, and End Results (SEER)-Medicare data, this study examined a population-based cohort of HNC survivors between 2001 and 2011 Usage of cross-sectional head and neck imaging (CHNI), chest imaging (CI), positron emission tomography (PET), fiberoptic nasopharyngolaryngoscopy (FNPL), and, in irradiated patients, thyroid function testing (TFT) was captured over 2 consecutive surveillance years. Multivariate modeling with logistic regression analyses was used to assess variations by clinical factors, nonclinical factors, number and types of providers seen and their evolution over time.

RESULTS

Among 13,836 HNC survivors, the majority saw a medical, radiation, or surgical oncologist and a primary care provider (PCP; 81.7%) in their first year of surveillance. However, only 58.1% underwent either PET or CHNI, 47.8% underwent CHNI, 64.1% underwent CI, 32.5% underwent PET scans, 55.0% underwent FNPL, and 55.9% underwent TFT. In multivariate analyses, patients who followed up with more providers and those who followed up with both a PCP and an oncologist were more likely to undergo surveillance testing (P < .007). However, adjusting for providers seen did not explain the variations in surveillance testing rates based on age, race, education, income level, and place of residence. Over time, there was a gradual increase in the use of PET scans and TFT during surveillance years.

CONCLUSIONS

In this large SEER-Medicare data study, only half of HNC survivors received the recommended testing, and greater compliance was seen in those who followed up with both an oncologist and a PCP. More attention is needed to minimize variations in surveillance testing across sociodemographic groups.