Incidence and Patterns of Extended-Course Antibiotic Therapy in Patients Evaluated for Lyme Disease

Validation of Claims-Based Algorithm for Lyme Disease, Massachusetts, USA

Compared with notifiable disease surveillance, claims-based algorithms estimate higher Lyme disease incidence, but their accuracy is unknown. We applied a previously developed Lyme disease algorithm (diagnosis code plus antimicrobial drug prescription dispensing within 30 days) to an administrative claims database in Massachusetts, USA, to identify a Lyme disease cohort during July 2000-June 2019. Clinicians reviewed and adjudicated medical charts from a cohort subset by using national surveillance case definitions. We calculated positive predictive values (PPVs). We identified 12,229 Lyme disease episodes in the claims database and reviewed and adjudicated 128 medical charts. The algorithm's PPV for confirmed, probable, or suspected cases was 93.8% (95% CI 88.1%-97.3%); the PPV was 66.4% (95% CI 57.5%-74.5%) for confirmed and probable cases only. In a high incidence setting, a claims-based algorithm identified cases with a high PPV, suggesting it can be used to assess Lyme disease burden and supplement traditional surveillance data.

Healthcare claims-based Lyme disease case-finding algorithms in the United States: A systematic literature review

BACKGROUND AND OBJECTIVE

Lyme disease (LD) is the fifth most commonly reported notifiable infectious disease in the United States (US) with approximately 35,000 cases reported in 2019 via public health surveillance. However, healthcare claims-based studies estimate that the number of LD cases is >10 times larger than reported through surveillance. To assess the burden of LD using healthcare claims data and the effectiveness of interventions for LD prevention and treatment, it is important to use validated well-performing LD case-finding algorithms ("LD algorithms"). We conducted a systematic literature review to identify LD algorithms used with US healthcare claims data and their validation status.

METHODS

We searched PubMed and Embase for articles published in English since January 1, 2000 (search date: February 20, 2021), using the following search terms: (1) "Lyme disease"; and (2) "claim*" or "administrative* data"; and (3) "United States" or "the US*". We then reviewed the titles, abstracts, full texts, and bibliographies of the articles to select eligible articles, i.e., those describing LD algorithms used with US healthcare claims data.

RESULTS

We identified 15 eligible articles. Of these, seven studies used LD algorithms with LD diagnosis codes only, four studies used LD diagnosis codes and antibiotic dispensing records, and the remaining four studies used serologic test order codes in combination with LD diagnosis codes and antibiotics records. Only one of the studies that provided data on algorithm performance: sensitivity 50% and positive predictive value 5%, and this was based on Lyme disease diagnosis code only.

CONCLUSIONS

US claims-based LD case-finding algorithms have used diverse strategies. Only one algorithm was validated, and its performance was poor. Further studies are warranted to assess performance for different algorithm designs and inform efforts to better assess the true burden of LD.

The Role of the Infectious Disease Consultation in Lyme Disease

A consultation regarding Lyme disease can be challenging for the infectious disease physician when the referral question centers on the use of prolonged or empirical antibiotic treatment of Lyme disease and associated tick-borne infections. Patients who have been infected with Borrelia burgdorferi, and many who have been misdiagnosed, are confronted with a seemingly endless array of misinformation that is not in keeping with the current understanding of the clinical spectrum of Lyme disease and its response to evidence-based treatment. Preparing for these conversations with a good grasp of the public beliefs regarding Lyme disease and its treatment can be beneficial.

Machine-learning-based predictions of direct-acting antiviral therapy duration for patients with hepatitis C

INTRODUCTION

Hepatitis C, which affects 71 million persons worldwide, is the most common blood-borne pathogen in the United States. Chronic infections can be treated effectively thanks to the availability of modern direct-acting antiviral (DAA) therapies. Real-world data on the duration of DAA therapy, which can be used to optimize and guide the course of therapy, may also be useful in determining quality of life enhancements based upon total required supply of medication and long-term improvements to quality of life. We developed a machine learning model to identify patient characteristics associated with prolonged DAA treatment duration.

METHODS

A nationwide U.S. commercial managed care plan with claims data that covers about 60 million beneficiaries from 2009 to 2019 were used in the retrospective study. We examined differences in age, gender, and multiple comorbidities among patients treated with different durations of DAA treatment. We also examined the performance of machine learning models for predicting a prolonged course of DAA based on the area under the receiver operating characteristic curve (AUC).

RESULTS

We identified 3943 cases with hepatitis C who received sofosbuvir/ledipasvir as the first course of DAA and were eligible for the study. Patients receiving prolonged treatment (n = 240, 6.1%) were more likely to have compensated cirrhosis, decompensated cirrhosis, and other comorbidities (P < 0.001). For distinguishing patients who received prolonged DAA treatment for hepatitis C from patients received standard treatment, the optimal predictive model, constructed with XGBoost, had an AUC of 0.745 ± 0.031 (P < 0.001).

CONCLUSIONS

The risk of antiviral resistance and the cost of DAA are strong motivators to ensure that first-round DAA therapy is effective. For the dominant DAA treatment during the course of this analysis, we present a model that identifies factors already captured in established guidelines and adds to those age, comorbidity burden, and type 2 diabetes status; patient characteristics that are predictive of extended treatment.

Peripherally Inserted Central Catheter-Associated Nocardia nova Endocarditis in a Patient Receiving Intravenous Antibiotics for Chronic Lyme Disease

Long-term antibiotics are not effective for the therapy of patients with persistent symptoms and a history of Lyme disease. However, some clinicians still prescribe these therapies. We present a case of peripherally inserted central catheter-associated Nocardia nova endocarditis in a patient who had been receiving intravenous antibiotics for the management of chronic Lyme disease. This case highlights an important risk associated with the unscientific use of indwelling peripheral catheters and intravenous antibiotics for the management of such patients.

dxpr: an R package for generating analysis-ready data from electronic health records-diagnoses and procedures

BACKGROUND

Enriched electronic health records (EHRs) contain crucial information related to disease progression, and this information can help with decision-making in the health care field. Data analytics in health care is deemed as one of the essential processes that help accelerate the progress of clinical research. However, processing and analyzing EHR data are common bottlenecks in health care data analytics.

METHODS

The dxpr R package provides mechanisms for integration, wrangling, and visualization of clinical data, including diagnosis and procedure records. First, the dxpr package helps users transform International Classification of Diseases (ICD) codes to a uniform format. After code format transformation, the dxpr package supports four strategies for grouping clinical diagnostic data. For clinical procedure data, two grouping methods can be chosen. After EHRs are integrated, users can employ a set of flexible built-in querying functions for dividing data into case and control groups by using specified criteria and splitting the data into before and after an event based on the record date. Subsequently, the structure of integrated long data can be converted into wide, analysis-ready data that are suitable for statistical analysis and visualization.

RESULTS

We conducted comorbidity data processes based on a cohort of newborns from Medical Information Mart for Intensive Care-III (n = 7,833) by using the dxpr package. We first defined patent ductus arteriosus (PDA) cases as patients who had at least one PDA diagnosis (ICD, Ninth Revision, Clinical Modification [ICD-9-CM] 7470*). Controls were defined as patients who never had PDA diagnosis. In total, 381 and 7,452 patients with and without PDA, respectively, were included in our study population. Then, we grouped the diagnoses into defined comorbidities. Finally, we observed a statistically significant difference in 8 of the 16 comorbidities among patients with and without PDA, including fluid and electrolyte disorders, valvular disease, and others.

CONCLUSIONS

This dxpr package helps clinical data analysts address the common bottleneck caused by clinical data characteristics such as heterogeneity and sparseness.

Risk Factors Associated with Outcomes of Recombinant Tissue Plasminogen Activator Therapy in Patients with Acute Ischemic Stroke

Ischemic stroke is the most common type of stroke, and early interventional treatment is associated with favorable outcomes. In the guidelines, thrombolytic therapy using recombinant tissue-type plasminogen activator (rt-PA) is recommended for eligible patients with acute ischemic stroke. However, the risk of hemorrhagic complications limits the use of rt-PA, and the risk factors for poor treatment outcomes need to be identified. To identify the risk factors associated with in-hospital poor outcomes in patients treated with rt-PA, we analyzed the electronic medical records of patients who were diagnosed with acute ischemic stroke and treated for rt-PA at Chang Gung Memorial Hospitals from 2006 to 2016. In-hospital death, intensive care unit (ICU) stay, or prolonged hospitalization were defined as unfavorable treatment outcomes. Medical history variables and laboratory test results were considered variables of interest to determine risk factors. Among 643 eligible patients, 537 (83.5%) and 106 (16.5%) patients had favorable and poor outcomes, respectively. In the multivariable analysis, risk factors associated with poor outcomes were female gender, higher stroke severity index (SSI), higher serum glucose levels, lower mean corpuscular hemoglobin concentration (MCHC), lower platelet counts, and anemia. The risk factors found in this research could help us study the treatment strategy for ischemic stroke.

How safe is doxycycline for young children or for pregnant or breastfeeding women?

Tetracycline antimicrobials entered into clinical usage in the late 1940s. Permanent dental staining from tetracyclines was first appreciated in 1956, eventually leading to avoidance of this class of antibiotics whenever possible in young children and pregnant or breastfeeding women. Doxycycline, introduced in 1967, binds calcium less avidly than prior tetracyclines and is regarded by some authorities as safe to prescribe for pregnant women and young children. Review of the available data, however, suggests that this interpretation may be incorrect or at least premature. In conclusion, until more definitive data are developed, doxycycline should continue to be only selectively prescribed for young children and pregnant or breastfeeding women for whom alternative, safer antibiotics are not available, and courses of treatment should be of as short a duration as possible.

Serious Bacterial Infections Acquired During Treatment of Patients Given a Diagnosis of Chronic Lyme Disease - United States

The term "chronic Lyme disease" is used by some health care providers as a diagnosis for various constitutional, musculoskeletal, and neuropsychiatric symptoms (1,2). Patients with a diagnosis of chronic Lyme disease have been provided a wide range of medications as treatment, including long courses of intravenous (IV) antibiotics (3,4). Studies have not shown that such treatments lead to substantial long-term improvement for patients, and they can be harmful (1,5). This report describes cases of septic shock, osteomyelitis, Clostridium difficile colitis, and paraspinal abscess resulting from treatments for chronic Lyme disease. Patients, clinicians, and public health practitioners should be aware that treatments for chronic Lyme disease can carry serious risks.

Claims-Based Diagnostic Patterns of Patients Evaluated for Lyme Disease and Given Extended Antibiotic Therapy

BACKGROUND

A Lyme disease (LD) diagnosis can be far from straightforward, particularly if erythema migrans does not develop or is not noticed. Extended courses of antibiotics for LD are not recommended, but their use is increasing. We sought to elucidate the patient patterns toward a diagnosis of LD, hypothesizing that a subset of patients ultimately receiving extended courses antibiotics may be symptomatic for an extended period before the first LD diagnosis.

METHODS

Claims submitted to a nationwide U.S. health insurance plan in 14 high-prevalence states were grouped into standardized diagnostic categories. The patterns of diagnostic categories over time were compared between patients evaluated for LD and given standard antibiotic therapy (PLDSA) and patients evaluated for LD and given extended antibiotic therapy (PLDEA) in 2011-2012.

RESULTS

The incidence of PLDSA was 40.45 (N = 3207) and that of PLDEA was 7.57 (N = 600) per 100,000 insured over 2011-2012. 50.3% of PLDEA were diagnosed in the nonsummer months. Seven diagnostic categories were associated with PLDEA. From 180 days before the first LD diagnosis, the risks of having claims associated with back problems (odds ratio [OR], 2.1; confidence interval [95% CI], 1.4-2.9; p < 0.001) and connective tissue disease (OR, 1.6; 95% CI, 1.1-2.3; p < 0.01) complaints were higher among PLDEA. From 90 days before the diagnosis, malaise and fatigue (OR, 1.7; 95% CI, 1.1-2.6; p < 0.05), other nervous system disorders (OR, 2.0; 95% CI, 1.3-3.1; p < 0.01), and nontraumatic joint disorder (OR, 1.4; 95% CI, 1.0-2.0; p < 0.05) were more likely found among PLDEA than PLDSA. From 30 days before the diagnosis, the risk for mental health (OR 1.6; 95% CI, 1.1-2.0; p < 0.01) and headache (OR 1.5; 95% CI, 1.1-2.0; p < 0.05) among PLDEA was elevated.

CONCLUSIONS

Among patients evaluated for LD and ultimately receiving an extended course of antibiotics for LD, 15.8% of them were symptomatic and seeking care for several months before their first LD diagnosis.