Pediatric unilateral knee swelling: a case report of a complicated differential diagnosis and often overlooked cause

Lyme disease is the most common vector-borne illness in the United States. However, Lyme arthritis is a diagnosis that is often missed, even in children, who are the population with the highest incidence of Lyme disease. Lyme arthritis, which presents in the later stage of Borrelia burgdorferi infection, needs to be recognized and managed promptly, especially in endemic areas or when exposure to ticks is known. We present a case of a 3-year-old female presenting to the emergency department with a history of limping for 2 weeks. The mother of the child recognized a tick bite. However, the child was not taken to seek care expeditiously, because she had not developed any rashes. Test results demonstrated that the patient was IgG positive and IgM negative for Lyme disease, with Western blot confirming the diagnosis of Lyme arthritis. Most patients presenting with Lyme arthritis do not recall having a tick bite, making it difficult to differentiate it from other pediatric conditions. When this diagnosis is missed, it can result in long-term morbidity, which is generally refractory to intravenous antibiotic therapy, oftentimes requiring synovectomy. Hence, this underscores the importance of the consideration of Lyme arthritis as a differential diagnosis in patients presenting with joint effusion.

Seasonality of Acute Lyme Disease in Children

Due to the life cycle of its vector, Lyme disease has known seasonal variation. However, investigations focused on children have been limited. Our objective was to evaluate the seasonality of pediatric Lyme disease in three endemic regions in the United States. We enrolled children presenting to one of eight Pedi Lyme Net participating emergency departments. Cases were classified based on presenting symptoms: early (single erythema migrans (EM) lesion), early-disseminated (multiple EM lesions, headache, cranial neuropathy, or carditis), or late (arthritis). We defined a case of Lyme disease by the presence of an EM lesion or a positive two-tier Lyme disease serology. To measure seasonal variability, we estimated Fourier regression models to capture cyclical patterns in Lyme disease incidence. While most children with early or early-disseminated Lyme disease presented during the summer months, children with Lyme arthritis presented throughout the year. Clinicians should consider Lyme disease when evaluating children with acute arthritis throughout the year.

623. Exploring ‘Slicer Dicer’, an Extraction Tool in EPIC, for Clinical and Epidemiological Analysis

Background Electronic Health Record (EHR) implementation has created an unprecedented library of patient data. Data extraction tools provide an opportunity to retrieve clinico-epidemiological information on a wide scale. Slicer Dicer is a data exploration tool in the EPIC EHR that allows one to customize searches on large patient populations. This software contains a variety of models that present de-identified information from EPIC’s Caboodle database. We explored the applicability and potential utility of this tool utilizing the diagnosis of Lyme disease as an example. Methods The following steps outline an overview of data extraction utilizing ICD-10 codes around Lyme disease at our health system. Step 1-3: Denominator chosen as ‘All Patients’ over a 3-year period, ‘Slicing’ of the data by ‘Lyme disease, unspecified’ was applied to these results, and the ‘sliced’ data was categorized by year of diagnosis (Slide 1). Step 4: This data was further arranged by month of diagnosis for trend analysis (Slide 2). Step 5: Sub-diagnosis was applied for Lyme arthritis (Slide 3). Step 6: Further ‘slicing’ was/can be done by other variables, such as ‘Hospitalization,’ ‘Encounter Diagnosis,’ and ‘ED Diagnosis’ (Slide 4). Step 7-8: Output was ‘sliced’ by ‘Age’ (Slide 5) and ‘Postal Code’ (Slide 6). Slide 1. EPIC EHR screen capture showing 3-year period data Data shown here represents 'All patients' chosen as the denominator further sliced by 'Lyme disease, unspecified' and categorized by the year of diagnosis. Slide 2. EPIC EHR screen capture showing data further arranged by month of diagnosis Results Macro-level data of period prevalence on Lyme disease over 3 years (Slide 1), seasonal trends (Slide 2), specific sub-diagnosis (Slide 3), output by setting of diagnosis (Slide 4), and demographic information of our patient population (Slides 5, 6) was revealed by application of these parameters. Slide 3. EPIC EHR screen capture showing application of sub-diagnosis for Lyme arthritis Slide 4. EPIC EHR screen capture showing further slicing by multiple variables like hospitalization and diagnosis Slide 5. EPIC EHR screen capture showing slicing of data by demographic information (Age) Conclusion Slicer Dicer can provide a snapshot for preliminary data analysis prior to investing time and commitment to a project. The appeal of this tool is that it mines de-identified data and thus does not require initial IRB approval. This opens an avenue for potential full research projects based on the results obtained and helps generate preliminary hypotheses through analysis of healthcare. Slide 6. EPIC EHR screen capture showing slicing of data by demographic information (Postal Code) Disclosures All Authors: No reported disclosures

241. A Comparison of Staphylococcal and Streptococcal Septic Arthritis with Lyme Arthritis

Background Septic arthritis is considered the most important differential diagnosis in suspected Lyme arthritis. The present study sheds light on the most frequent misdiagnoses in Lyme arthritis cases and clues for differentiation from Staphylococcal and Streptococcal septic arthritis. Methods We studied patients with positive joint fluid cultures with Staphylococcus aureus (SA) and streptococci and Lyme polymerase chain reaction (PCR) positive joint fluid in 9 hospitals in Eastern Pennsylvania and 1 in Warren county, New Jersey over a 3 year period. Results One hundred and thirty four out of 7000 SA and 21 out of 1321 streptococcal isolates were from joint fluid. Twenty nine had Lyme arthritis, ages 5-74 ( 24 males,5 females). Twelve out of 29 were ages 10-18 with 20/29 under age 40. Predominant joint affected was a single knee 27/29. All had pain with or without swelling and little erythema. Two had fever. One reported a tick bite. None had other manifestations of Lyme disease. The diagnosis at the initial visit was sprain or sports injury in 5, osteoarthritis in 5, inflammatory arthritis or gout in 2 each, i septic arthritis, 1 viral syndrome and 1 ruptured Baker's cyst. Joint fluid count range was 3500-77,360 with only 3 over 50,000. White blood cell count (wbc) range was 3200-14,580. SA arthritis involved knee in 66 (49.3%), hip 31(23.9%), elbow 19 (14.2%), shoulder 14 (10.4%) with 2 wrist, 1 ankle and 1 sterno-clavicular joint. Fifty seven had a history of joint surgery. Eighty six were male and 48 female. age range 14-95 with a median age 65. Synovial fluid cell count was 335-470,000 and wbc 5,200-28,410 . Streptococcal septic arthritis ( 13 male 8 female) involved the knee in 17/21 with one each of hip, elbow, shoulder. The ages were 36-86 with 15/21 over age 60. Synovial fluid count was15,242-641,425 . Wbc count 11,140-25,080 .Nine out 21 had prior joint surgery. Conclusion Lyme arthritis patients were younger, mostly involving 1 knee, majority male without other manifestations of Lyme disease. Highest synovial fluid count was 77,360 and highest wbc count 14,580. Most frequent misdiagnoses were sports injury/sprain or osteoarthritis. SA and Streptococcal arthritis were mostly in elderly, with higher joint fluid cell and wbc counts. Only 1/29 Lyme arthritis was initially misdiagnosed septic arthritis. Disclosures All Authors: No reported disclosures

Epidemiological Surveillance of Lyme Borreliosis in Bavaria, Germany, 2013–2020

Lyme borreliosis (LB) is the most common tick-borne disease in Germany. Mandatory notification of acute LB manifestations (erythema migrans (EM), neuroborreliosis (NB), and Lyme arthritis (LA)) was implemented in Bavaria on 1 March 2013. We aimed to describe the epidemiological situation and to identify LB risk areas and populations. Therefore, we analyzed LB cases notified from March 2013 to December 2020 and calculated incidence (cases/100,000 inhabitants) by time, place, and person. Overall, 35,458 cases were reported during the study period (EM: 96.7%; NB: 1.7%; LA: 1.8%). The average incidence was 34.3/100,000, but annual incidence varied substantially (2015: 23.2; 2020: 47.4). Marked regional differences at the district level were observed (annual average incidence range: 4–154/100,000). The Bavarian Forest and parts of Franconia were identified as high-risk regions. Additionally, high risk for LB was found in 5–9-year-old males and in 60–69-year-old females. The first group also had the highest risk of a severe disease course. We were able to identify areas and populations in Bavaria with an increased LB risk, thereby providing a basis for targeted measures to prevent LB. Since LB vaccination is currently not available, such measures should comprise (i) avoiding tick bites, (ii) removing ticks rapidly after a bite, and (iii) treating LB early/adequately.