Thomas Anderson, MD, PhD

Moderate-to-severe acute pain is prevalent in many healthcare settings and associated with adverse outcomes. Peripheral nerve blockade using traditional needle-based and local anesthetic-based techniques improves pain outcomes for some patient populations but has shortcomings limiting use. These limitations include its invasiveness, potential for local anesthetic systemic toxicity, risk of infection with an indwelling catheter, and relatively short duration of blockade compared with the period of pain after major injuries. Focused ultrasound is capable of inhibiting the peripheral nervous system and has potential as a pain management tool. However, investigations of its effect on peripheral nerve nociceptive fibers in animal models of acute pain are lacking. In an in vivo acute pain model, we investigated focused ultrasound's effects on behavior and peripheral nerve structure.Focused ultrasound was applied directly to the sciatic nerve of rats just prior to a hindpaw incision; three control groups (focused ultrasound sham only, hindpaw incision only, focused ultrasound sham+hindpaw incision) were also included. For all four groups (intervention and controls), behavioral testing (thermal and mechanical hyperalgesia, hindpaw extension and flexion) took place for 4 weeks. Structural changes to peripheral nerves of non-focused ultrasound controls and after focused ultrasound application were assessed on days 0 and 14 using light microscopy and transmission electron microscopy.Compared with controls, after focused ultrasound application, animals had (1) increased mechanical nociceptive thresholds for 2 weeks; (2) sustained increase in thermal nociceptive thresholds for ≥4 weeks; (3) a decrease in hindpaw motor response for 0.5 weeks; and (4) a decrease in hindpaw plantar sensation for 2 weeks. At 14 days after focused ultrasound application, alterations to myelin sheaths and nerve fiber ultrastructure were observed both by light and electron microscopy.Focused ultrasound, using a distinct parameter set, reversibly inhibits A-delta peripheral nerve nociceptive, motor, and non-nociceptive sensory fiber-mediated behaviors, has a prolonged effect on C nociceptive fiber-mediated behavior, and alters nerve structure. Focused ultrasound may have potential as a peripheral nerve blockade technique for acute pain management. However, further investigation is required to determine C fiber inhibition duration and the significance of nerve structural changes.

View details for DOI 10.1136/rapm-2022-104060

View details for PubMedID 36822815

Chronic pain (CP) is a major public health issue. While new onset CP is known to occur frequently after some pediatric surgeries, its incidence after the most common pediatric surgeries is unknown. This retrospective cohort study used insurance claims data from 2002 to 2017 for patients 0-21 years of age. The primary outcome was CP 90-365 days after each of the 20 most frequent surgeries in five age categories (identified using CP ICD codes). Multivariable logistic regression identified surgeries and risk factors associated with CP after surgery. A total of 424,590 surgical patients aged 0-21 were included, 22,361 of whom developed CP in the 90-365 days after surgery. The incidences of CP after surgery were: 1.1% in age group 0-1 years; 3.0% in 2-5 years; 5.6% in 6-11 years; 10.1% in 12-18 years; 9.9% in 19-21 years. Some surgeries and patient variables were associated with CP. Approximately one in ten adolescents who underwent the most common surgeries developed CP, as did a striking percentage of children in other age groups. Given the long-term consequences of CP, resources should be allocated toward identification of high-risk pediatric patients and strategies to prevent CP after surgery.

View details for DOI 10.1016/j.jpain.2022.09.015

View details for PubMedID 36216129

View details for Web of Science ID 000840283001013

View details for Web of Science ID 000840283001012

View details for Web of Science ID 000840283000146

BACKGROUND: Anesthesiologists integrate numerous variables to determine an opioid dose that manages patient nociception and pain while minimizing adverse effects. Clinical dashboards that enable physicians to compare themselves to their peers can reduce unnecessary variation in patient care and improve outcomes. However, due to the complexity of anesthetic dosing decisions, comparative visualizations of opioid-use patterns are complicated by case-mix differences between providers.OBJECTIVES: This single-institution case study describes the development of a pediatric anesthesia dashboard and demonstrates how advanced computational techniques can facilitate nuanced normalization techniques, enabling meaningful comparisons of complex clinical data.METHODS: We engaged perioperative-care stakeholders at a tertiary care pediatric hospital to determine patient and surgical variables relevant to anesthesia decision-making and to identify end-user requirements for an opioid-use visualization tool. Case data were extracted, aggregated, and standardized. We performed multivariable machine learning to identify and understand key variables. We integrated interview findings and computational algorithms into an interactive dashboard with normalized comparisons, followed by an iterative process of improvement and implementation.RESULTS: The dashboard design process identified two mechanisms-interactive data filtration and machine-learning-based normalization-that enable rigorous monitoring of opioid utilization with meaningful case-mix adjustment. When deployed with real data encompassing 24,332 surgical cases, our dashboard identified both high and low opioid-use outliers with associated clinical outcomes data.CONCLUSION: A tool that gives anesthesiologists timely data on their practice patterns while adjusting for case-mix differences empowers physicians to track changes and variation in opioid administration over time. Such a tool can successfully trigger conversation amongst stakeholders in support of continuous improvement efforts. Clinical analytics dashboards can enable physicians to better understand their practice and provide motivation to change behavior, ultimately addressing unnecessary variation in high impact medication use and minimizing adverse effects.

View details for DOI 10.1055/s-0042-1744387

View details for PubMedID 35322398

BACKGROUND: In animal models, focused ultrasound can reversibly or permanently inhibit nerve conduction, suggesting a potential role in managing pain. We hypothesized focused ultrasound's effects on action potential parameters may be similar to those of local anesthetics.METHODS: In an ex vivo rat sciatic nerve model, action potential amplitude, area under the curve, latency to 10% peak, latency to 100% peak, rate of rise, and half peak width changes were assessed after separately applying increasing focused ultrasound pressures or concentrations of bupivacaine and ropivacaine. Focused ultrasound's effects on nerve structure were examined histologically.RESULTS: Increasing focused ultrasound pressures decreased action potential amplitude, area under the curve, and rate of rise, increased latency to 10% peak, and did not change latency to 100% peak or half peak width. Increasing local anesthetic concentrations decreased action potential amplitude, area under the curve, and rate of rise and increased latency to 10% peak, latency to 100% peak, and half peak width. At the highest focused ultrasound pressures, nerve architecture was altered compared with controls.DISCUSSION: While some action potential parameters were altered comparably by focused ultrasound and local anesthetics, there were small but notable differences. It is not evident if these differences may lead to differences in clinical pain effects when focused ultrasound is applied in vivo or if focused ultrasound pressures that result in clinically relevant changes damage nerve structures. Given the potential advantages of a non-invasive technique for managing pain conditions, further investigation may be warranted in an in vivo pain model.

View details for DOI 10.1136/rapm-2021-103115

View details for PubMedID 35115412

View details for DOI 10.1213/ANE.0000000000005710

View details for PubMedID 34908540

BACKGROUND: Long-term opioid use has negative health care consequences. Patients who undergo surgery are at risk for prolonged opioid use after surgery (POUS). While risk factors have been previously identified, no methods currently exist to determine higher-risk patients. We assessed the ability of a variety of machine-learning algorithms to predict adolescents at risk of POUS and to identify factors associated with this risk.METHODS: A retrospective cohort study was conducted using a national insurance claims database of adolescents aged 12-21 years who underwent 1 of 1297 surgeries, with general anesthesia, from January 1, 2011 to December 30, 2017. Logistic regression with an L2 penalty and with a logistic regression with an L1 lasso (Lasso) penalty, random forests, gradient boosting machines, and extreme gradient boosted models were trained using patient and provider characteristics to predict POUS (≥1 opioid prescription fill within 90-180 days after surgery) risk. Predictive capabilities were assessed using the area under the receiver-operating characteristic curve (AUC)/C-statistic, mean average precision (MAP); individual decision thresholds were compared using sensitivity, specificity, Youden Index, F1 score, and number needed to evaluate. The variables most strongly associated with POUS risk were identified using permutation importance.RESULTS: Of 186,493 eligible patient surgical visits, 8410 (4.51%) had POUS. The top-performing algorithm achieved an overall AUC of 0.711 (95% confidence interval [CI], 0.699-0.723) and significantly higher AUCs for certain surgeries (eg, 0.823 for spinal fusion surgery and 0.812 for dental surgery). The variables with the strongest association with POUS were the days' supply of opioids and oral morphine milligram equivalents of opioids in the year before surgery.CONCLUSIONS: Machine-learning models to predict POUS risk among adolescents show modest to strong results for different surgeries and reveal variables associated with higher risk. These results may inform health care system-specific identification of patients at higher risk for POUS and drive development of preventative measures.

View details for DOI 10.1213/ANE.0000000000005527

View details for PubMedID 33939656

View details for DOI 10.1213/ANE.0000000000005470

View details for PubMedID 33857985