Evaluation of New Hypertension Guidelines on the Prevalence and Control of Hypertension in a Clinical HIV Cohort: A Community-Based Study.

The prevalence and control of hypertension (HTN) among people with HIV (PWH) have not been widely studied since the release of newer 2017 ACC/AHA guidelines ("new guidelines"). To address this research gap, we evaluated and compared the prevalence and control of HTN using both 2003 JNC 7 ("old guidelines") and new guidelines. We identified 3,206 PWH with HTN from the DC Cohort study in Washington, DC, between January 2018 and June 2019. We defined HTN using International Classification of Diseases (ICD)-9/-10 diagnosis codes for HTN or ≥2 blood pressure (BP) measurements obtained at least 1 month apart (>139/89 mm Hg per old or >129/79 mm Hg per new guidelines). We defined HTN control based on recent BP (≤129/≤79 mm Hg per new guidelines). We identified socio-demographics, cardiovascular risk factors, and co-morbidities associated with HTN control using multivariable logistic regression [adjusted odds ratio (aOR); 95% confidence interval (CI)]. The prevalence of HTN was 50.9% per old versus 62.2% per new guidelines. Of the 3,206 PWH with HTN, 887 (27.7%) had a recent BP ≤129/≤79 mm Hg, 1,196 (37.3%) had a BP 130-139/80-89 mm Hg, and 1,123 (35.0%) had a BP ≥140/≥90 mm Hg. After adjusting for socio-demographics, cardiovascular risk factors, and co-morbidities, factors associated with HTN control included age 60-69 (vs. <40) years (aOR: 1.42; 95% CI: 1.03-1.98), Hispanic (vs. non-Hispanic Black) race/ethnicity (aOR 1.49; 95% CI: 1.04-2.15), receipt of HIV care at a hospital-based (vs. community-based) clinic (aOR 1.21; 95% CI: 1.00-1.47), being unemployed (aOR 1.42; 95% CI: 1.11-1.83), and diabetes (aOR 1.35; 95% CI: 1.13-1.63). In a large urban cohort of PWH, nearly two-thirds had HTN and less than one-third of those met new guideline criteria. Our data suggest that more aggressive HTN control is warranted among PWH, with additional attention to younger patients and non-Hispanic Black patients.

Delayed Hemolytic Transfusion Reaction in a Sickle Cell Disease Patient: A Case Report.

Alloimmunization has been reported in patients with sickle cell disease (SCD). Delayed hemolytic transfusion reaction (DHTR) is one of the complications of alloimmunization. DHTR is of particular clinical significance in this patient population as it may pose a diagnostic and management challenge to most healthcare providers. Symptoms of DHTR are often misinterpreted as pain crisis or worsening of baseline anemia. Furthermore, DHTR may take a turn for the worse in patients with SCD, thereby leading to worsening anemia and hyper-hemolytic crisis. In this report, we discuss the case of a 33-year-old African female, with hemoglobin SS (Hb SS) SCD and a history of multiple blood transfusions in her home country of Nigeria, who presented to the emergency department with generalized body pain, which was typical of her prior vaso-occlusive crisis (VOC). The trigger of her crisis was an acute onset of sepsis secondary to Escherichia coli (E. coli)-associated pyelonephritis. Owing to a worsening of her VOC and a significant drop in her steady-state Hb levels, she required a blood transfusion of one unit of packed red blood cells (PRBC), which was later complicated by a delayed hemolytic reaction and worsening anemia.

Innovative Informatics Approaches for Peripheral Artery Disease: Current State and Provider Survey of Strategies for Improving Guideline-Based Care.

OBJECTIVE: To quantify compliance with guideline recommendations for secondary prevention in peripheral artery disease (PAD) using natural language processing (NLP) tools deployed to an electronic health record (EHR) and investigate provider opinions regarding clinical decision support (CDS) to promote improved implementation of these strategies. PATIENTS AND METHODS: Natural language processing was used for automated identification of moderate to severe PAD cases from narrative clinical notes of an EHR of patients seen in consultation from May 13, 2015, to July 27, 2015. Guideline-recommended strategies assessed within 6 months of PAD diagnosis included therapy with statins, antiplatelet agents, angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, and smoking abstention. Subsequently, a provider survey was used to assess provider knowledge regarding PAD clinical practice guidelines, comfort in recommending secondary prevention strategies, and potential role for CDS. RESULTS: Among 73 moderate to severe PAD cases identified by NLP, only 12 (16%) were on 4 guideline-recommended strategies. A total of 207 of 760 (27%) providers responded to the survey; of these 141 (68%) were generalists and 66 (32%) were specialists. Although 183 providers (88%) managed patients with PAD, 51 (25%) indicated they were uncomfortable doing so; 138 providers (67%) favored the development of a CDS system tailored for their practice and 146 (71%) agreed that an automated EHR-derived mortality risk score calculator for patients with PAD would be helpful. CONCLUSION: Natural language processing tools can identify cases from EHRs to support quality metric studies. Findings of this pilot study demonstrate gaps in application of guideline-recommended strategies for secondary risk prevention for patients with moderate to severe PAD. Providers strongly support the development of CDS systems tailored to assist them in providing evidence-based care to patients with PAD at the point of care.

Natural language processing of clinical notes for identification of critical limb ischemia.

BACKGROUND: Critical limb ischemia (CLI) is a complication of advanced peripheral artery disease (PAD) with diagnosis based on the presence of clinical signs and symptoms. However, automated identification of cases from electronic health records (EHRs) is challenging due to absence of a single definitive International Classification of Diseases (ICD-9 or ICD-10) code for CLI. METHODS AND RESULTS: In this study, we extend a previously validated natural language processing (NLP) algorithm for PAD identification to develop and validate a subphenotyping NLP algorithm (CLI-NLP) for identification of CLI cases from clinical notes. We compared performance of the CLI-NLP algorithm with CLI-related ICD-9 billing codes. The gold standard for validation was human abstraction of clinical notes from EHRs. Compared to billing codes the CLI-NLP algorithm had higher positive predictive value (PPV) (CLI-NLP 96%, billing codes 67%, p < 0.001), specificity (CLI-NLP 98%, billing codes 74%, p < 0.001) and F1-score (CLI-NLP 90%, billing codes 76%, p < 0.001). The sensitivity of these two methods was similar (CLI-NLP 84%; billing codes 88%; p < 0.12). CONCLUSIONS: The CLI-NLP algorithm for identification of CLI from narrative clinical notes in an EHR had excellent PPV and has potential for translation to patient care as it will enable automated identification of CLI cases for quality projects, clinical decision support tools and support a learning healthcare system.

Expect the unexpected: Rectus sheath hematoma comes without a notice.

[Full article available at http://rimed.org/rimedicaljournal-2017-11.asp].