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1.
JACC CardioOncol ; 6(2): 200-213, 2024 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-38774008

RESUMO

Background: Older patients with Hodgkin lymphoma (HL) often have comorbid cardiovascular disease; however, the impact of pre-existing heart failure (HF) on the management and outcomes of HL is unknown. Objectives: The aim of this study was to assess the prevalence of pre-existing HF in older patients with HL and its impact on treatment and outcomes. Methods: Linked Surveillance, Epidemiology, and End Results (SEER) and Medicare data from 1999 to 2016 were used to identify patients 65 years and older with newly diagnosed HL. Pre-existing HF, comorbidities, and cancer treatment were ascertained from billing codes and cause-specific mortality from SEER. The associations between pre-existing HF and cancer treatment were estimated using multivariable logistic regression. Cause-specific Cox proportional hazards models adjusted for comorbidities and cancer treatment were used to estimate the association between pre-existing HF and cause-specific mortality. Results: Among 3,348 patients (mean age 76 ± 7 years, 48.6% women) with newly diagnosed HL, pre-existing HF was present in 437 (13.1%). Pre-existing HF was associated with a lower likelihood of using anthracycline-based chemotherapy regimens (OR: 0.42; 95% CI: 0.29-0.60) and a higher likelihood of lymphoma mortality (HR: 1.25; 95% CI: 1.06-1.46) and cardiovascular mortality (HR: 2.57; 95% CI: 1.96-3.36) in models adjusted for comorbidities. One-year lymphoma mortality cumulative incidence was 37.4% (95% CI: 35.5%-39.5%) with pre-existing HF and 26.3% (95% CI: 25.0%-27.6%) without pre-existing HF. The cardioprotective medications dexrazoxane and liposomal doxorubicin were used in only 4.2% of patients. Conclusions: Pre-existing HF in older patients with newly diagnosed HL is common and associated with higher 1-year mortality. Strategies are needed to improve lymphoma and cardiovascular outcomes in this high-risk population.

2.
Am J Health Syst Pharm ; 76(13): 970-979, 2019 Jun 18.
Artigo em Inglês | MEDLINE | ID: mdl-31361884

RESUMO

PURPOSE: To examine the extent to which outpatient clinicians currently document drug indications in prescription instructions. METHODS: Free-text sigs were extracted from all outpatient prescriptions generated by the computerized prescriber order entry system of a major academic institution during a 5-year period. Natural language processing was used to identify drug indications. The data set was analyzed to determine the rates at which prescribers included indications. It was stratified by provider specialty, drug class, and specific medications, to determine how often these indications were in prescriptions for as-needed (PRN) versus non-PRN medications. RESULTS: During the study period, 4,356,086 prescriptions were ordered. Indications were included in 322,961 orders (7.41%). From these orders, 249,262 indications (77.18%) were written for PRN orders. Although internal medicine prescribers generated the highest number of medication orders, they included indications in only 6.26% of their prescriptions, whereas orthopedic surgery providers had the highest rate of documenting indications (33.41%). Pain was the most common indication, accounting for 30.35% of all documented indications. The drug class with the highest number of sigs-containing indications was narcotic analgesics. Non-PRN chronic medication prescriptions rarely included the indication. CONCLUSION: Prescribers rarely included drug indications in electronic free-text prescription instructions, and, when they did, it was mostly for PRN uses such as pain.


Assuntos
Assistência Ambulatorial/estatística & dados numéricos , Prescrições de Medicamentos/estatística & dados numéricos , Sistemas de Registro de Ordens Médicas/estatística & dados numéricos , Assistência Ambulatorial/normas , Conjuntos de Dados como Assunto , Prescrições de Medicamentos/normas , Humanos , Sistemas de Registro de Ordens Médicas/normas , Erros de Medicação/prevenção & controle , Processamento de Linguagem Natural
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