Sick of Feeling Sick: Management of Opioid Treatment-Induced Refractory Nausea Resulting in Suicidal Ideations With a Plan and Intent.

In this case report, we present the case of a 60-year-old Caucasian male with a history of depression, anxiety, opioid dependence, and idiopathic polyneuropathy, admitted to an inpatient psychiatric unit for suicidal ideation. The patient's symptoms were characterized by months of intractable nausea, severe anxiety, suicidal ideation (SI), and significant unintentional weight loss in the context of methadone-assisted treatment. Over nine days in the hospital, a treatment strategy was developed and refined, which eventually achieved sustained relief from nausea and significant improvement in anxiety. The most effective pharmacological interventions included mirtazapine, scopolamine, and gabapentin.

Microscaled proteogenomic methods for precision oncology.

Cancer proteogenomics promises new insights into cancer biology and treatment efficacy by integrating genomics, transcriptomics and protein profiling including modifications by mass spectrometry (MS). A critical limitation is sample input requirements that exceed many sources of clinically important material. Here we report a proteogenomics approach for core biopsies using tissue-sparing specimen processing and microscaled proteomics. As a demonstration, we analyze core needle biopsies from ERBB2 positive breast cancers before and 48-72 h after initiating neoadjuvant trastuzumab-based chemotherapy. We show greater suppression of ERBB2 protein and both ERBB2 and mTOR target phosphosite levels in cases associated with pathological complete response, and identify potential causes of treatment resistance including the absence of ERBB2 amplification, insufficient ERBB2 activity for therapeutic sensitivity despite ERBB2 amplification, and candidate resistance mechanisms including androgen receptor signaling, mucin overexpression and an inactive immune microenvironment. The clinical utility and discovery potential of proteogenomics at biopsy-scale warrants further investigation.

Validation of a Clinical Decision Rule to Identify Risk Factors Associated With Multidrug-Resistant Urinary Pathogens in the Emergency Department.

BACKGROUND: Antimicrobial resistance remains a significant obstacle for clinicians when treating patients presenting to the emergency department (ED) with urinary tract infections. OBJECTIVE: The goal of the proposed study was to validate a previously developed clinical decision rule identifying risk factors for multidrug-resistant (MDR) urinary pathogens. METHODS: We conducted a validation study of a previously published clinical decision rule to identify patients with MDR urinary pathogens using a cohort from an urban academic center ED with annual census over 80 000. Using our previously identified clinical risk factors, we determined the sensitivity, specificity, positive likelihood ratio (+LR), and negative LR (-LR) to estimate measures of precision of our clinical decision rule in the validation cohort. RESULTS: Factors associated with MDR urinary pathogen included sex, recent hospitalization, nursing home residency, and catheter placement. Using our previously defined threshold of greater than 1 risk factor, the adjusted model in the validation cohort identified that only nursing home residency was associated with positive MDR pathogen (adjusted odds ratio = 4.13; 95% CI = 1.95-8.77). The clinical decision rule in the validation cohort yielded a sensitivity of 56.4%, specificity of 66.3%, +LR of 1.7, and -LR of 0.7. Conclusion and Relevance: Our clinical decision rule to identify patients at risk for MDR urinary pathogens was unable to be validated in the setting of different antimicrobial resistance patterns. Future studies should evaluate an improved clinical decision rule identifying risk factors associated with MDR pathogens that performs well in varying patient populations.