Effect of repetitive transcranial magnetic stimulation on trigeminal-mediated headshaking in 17 horses.

BACKGROUND: Trigeminal-mediated headshaking is a neuropathic facial pain condition in horses. No treatment has been entirely successful. Repetitive transcranial magnetic stimulation (rTMS) is used in human medicine as a treatment for various neuropathic pain conditions, and good results have been achieved in cases of trigeminal neuralgia. OBJECTIVES: Apply rTMS to horses with trigeminal-mediated headshaking (TMHS) and to evaluate tolerability, application of the setting, and success rate. ANIMALS: Seventeen horses with nonseasonal signs of TMHS. METHODS: Other underlying causes of headshaking were ruled out. The rTMS was performed under standing sedation on 5 consecutive days applying 3 sets of 500 stimulations each, with a stimulation strength of 5 Hz. Horses were evaluated on Day 1 (t0) and Day 5 (t1) of the treatment and 2 (t2) and 4 weeks (t3) afterwards using a special scoring system. RESULTS: The rTMS was well tolerated. Headshaking signs during exercise were decreased by 70% (Day 5; t1). Four weeks after rTMS, signs were still decreased (mean reduction of 50%) during exercise. Improvement of mean resting and exercise scores was significant (P < .05) and effect sizes between pretreatment and all time points after treatment (t1, t2, t3) were large (>±0.8). CONCLUSIONS AND CLINICAL IMPORTANCE: Repetitive transcranial magnetic stimulation may be a promising treatment for neuropathic pain and headshaking in affected horses. Pain-free periods after treatment differ individually, and repeated treatment may be necessary. More studies should be performed to determine ideal settings for horses.

Evaluation of substance P as a biomarker for pain in equine colic.

Equine colic is an important condition associated with acute abdominal pain and one of the leading causes of death in horses. As such, objectively evaluating pain is of interest for attending veterinarians. Pain scales for assessment are present, but no single pain-specific biomarker has been reported. The aim of this study was to determine if substance P (SP) could be a reliable biomarker to reflect pain and serve as a parameter to predict outcome in equine colic. The hypothesis was that horses displaying severe colic signs present with higher values of SP in contrast to those with mild colic signs. Thirty warmblood horses, aged between 3 and 20 years were recruited; evenly distributed (10 horses each) in three colic groups (mild, moderate, severe). To classify the colic signs, the horses were graded by the Equine Acute Abdominal Pain Scale (EAAPS). Clinical examination and EAAPS were performed at arrival in the hospital. Blood samples were collected four times in hourly intervals commencing from arrival. For comparison, already established parameters for prognosticating equine colic (heart rate, serum cortisol, and blood lactate concentration) were also measured. The assumption of increasing SP concentrations along with pain could not be confirmed. SP did not show any association with heart rate, cortisol, lactate, or EAAPS. Whereas the established parameters increased according to the EAAPS, SP remained stable in individual horses regardless of clinical signs, treatment, and disease progression. Consequently, SP was not a reliable parameter to reflect painful conditions or to predict outcome in equine colic.

Individuals at risk for severe COVID-19 in whom ritonavir-containing therapies are contraindicated or may lead to interactions with concomitant medications: a retrospective analysis of German health insurance claims data.

Background: Nirmatrelvir/ritonavir is authorized for the treatment of COVID-19 but has several contraindications and potential drug-drug interactions (pDDIs) due to ritonavir-induced irreversible inhibition of cytochrome P450 3A4. We aimed to assess the prevalence of individuals with one or more risk factors for severe COVID-19 along with contraindications and pDDIs due to ritonavir-containing COVID-19 therapy. Methods: Retrospective observational study of individuals with one or more risk factors according to Robert Koch Institute criteria for severe COVID-19 according to German statutory health insurance (SHI) claims data from the pre-pandemic years 2018-2019 based on the German Analysis Database for Evaluation and Health Services Research. Prevalence was extrapolated to the entire SHI population using age-adjusted and sex-adjusted multiplication factors. Results: Nearly 2.5 million fully insured adults, representing 61 million people in the German SHI population, were included in the analysis. In 2019, prevalence of individuals that would have been at risk of severe COVID-19 was 56.4%. Amongst them, the prevalence of contraindications for treatment with ritonavir-containing COVID-19 therapy was approximately 2% according to presence of somatic comorbidities (severe liver or kidney disease). Prevalence of intake of medicines contraindicated for their potential interactions with ritonavir-containing COVID-19 therapy was 16.5% according to Summary of Product Characteristics and 31.8% according to previously published data. The prevalence of individuals at risk of pDDIs during ritonavir-containing COVID-19 therapy without adjustment of their concomitant therapy was 56.0% and 44.3%, respectively. Prevalence data for 2018 were similar. Conclusion: Administering ritonavir-containing COVID-19 therapy can be challenging as thorough medical record review and close monitoring are required. In some cases, ritonavir-containing treatment may not be appropriate due to contraindications, risk of pDDIs, or both. For those individuals, an alternative ritonavir-free treatment should be considered.

Use of algorithms for identifying patients in a German claims database: learnings from a lung cancer case.

BACKGROUND: The analysis of statutory health insurance (SHI) data is a little-used approach for understanding treatment and care as well as resource use of lung cancer (LC) patients in Germany. The aims of this observational, retrospective, longitudinal analysis of structured data were to analyze the healthcare situation of LC patients in Germany based on routine data from SHI funds, to develop an algorithm that sheds light on LC types (non-small cell / NSCLC vs. small cell / SCLC), and to gain new knowledge to improve needs-based care. METHODS: Anonymized billing data of approximately four million people with SHI were analyzed regarding ICD-10 (German modification), documented medical interventions based on the outpatient SHI Uniform Assessment Standard Tariff (EBM) or the inpatient Operations and Procedure Code (OPS), and the dispensing of prescription drugs to outpatients (ATC classification). The study included patients who were members of 64 SHI funds between Jan-1st, 2015 and Dec-31st, 2016 and who received the initial diagnosis of LC in 2015 and 2016. RESULTS: The analysis shows that neither the cancer type nor the cancer stage can be unambiguously described by the ICD-10 coding. Furthermore, an assignment based on the prescribed medication provides only limited information: many of the drugs are either approved for both LC types or are used off-label, making it difficult to assign them to a specific LC type. Overall, 25% of the LC patients were unambiguously identifiable as NSCLC vs SCLC based on the ICD-10 code, the drug therapy, and the billing data. CONCLUSIONS: The current coding system appears to be of limited suitability for drawing conclusions about LC and therefore the SHI patient population. This makes it difficult to analyze the healthcare data with the aim of gathering new knowledge to improve needs-based care. The approach chosen for this study did not allow for development of a LC differentiation algorithm based on the available healthcare data. However, a better overview of patient specific needs could make it possible to modify the range of services provided by the SHI funds. From this perspective, it makes sense, in a first step, to refine the ICD-10 system to facilitate NSCLC vs. SCLC classification.