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The erythema migrans (EM) rash is an important initial diagnostic sign of early Lyme disease. We tested the hypothesis that patients who noticed EM first differed from those who noticed viral-like symptoms first. “EM First” participants (167/271, 61.6%) had shorter illness duration before treatment (5.0 versus 6.2 days, P = 0.019), were more likely to have seen or removed a tick (P = 0.048) and to be non-Hispanic White (P = 0.025), and were less likely to present with disseminated lesions at the time of diagnosis (P = 0.003) than “Symptoms First” participants (104/271, 38.4%). In multivariate analyses, EM First participants had a 22% decrease in time to treatment (P = 0.012) compared with Symptoms First participants, suggesting that initial presentation affects time to treatment. In a large minority of patients, EM may not be the initial sign or symptom of early Lyme disease. There is a need for rapid diagnostics and improved physician awareness of the varied manifestations of early Lyme disease.

Lyme carditis is a well-established manifestation of early disseminated Lyme infection, yet the relationship between late disseminated Lyme disease and the development of dilated cardiomyopathy (DCM) remains unclear. The present systematic review aims to summarize existing literature on the association between late disseminated Lyme disease and DCM. A systematic review was conducted in PubMed, Embase, CENTRAL, and MEDLINE databases, after which a total of 11 observational studies (n = 771) were ultimately included for final data extraction. Although most studies (7/11) identified evidence associating Borrelia-infection with DCM, further research is required to isolate late disseminated Borrelia infection as a causative agent of DCM.

The erythema migrans (EM) skin lesion is often the first clinical sign of Lyme disease. Significant variability in EM presenting characteristics such as shape, color, pattern, and homogeneity, has been reported. We studied associations between these presenting characteristics, as well as whether they were associated with age, sex, EM duration, body location, and initiation of antibiotics. Two hundred and seventy one adult participants with early Lyme disease who had a physician-diagnosed EM skin lesion of ≥ 5 cm in diameter and ≤ 72 h of antibiotic treatment were enrolled. Participant demographics, clinical characteristics, and characteristics of their primary EM lesion were recorded. After adjusting for potential confounders, EM size increased along with increasing EM duration to a peak of 14 days. Male EM were found to be on average 2.18 cm larger than female EM. The odds of a red (vs blue/red) EM were 65% lower in males compared to females, and were over 3 times as high for EM found on the pelvis, torso, or arm compared to the leg. Age remained a significant predictor of central clearing in adjusted models; for every 10-year increase in age, the odds of central clearing decreased 25%. Given that EM remains a clinical diagnosis, it is essential that both physicians and the general public are aware of its varied manifestations. Our findings suggest possible patterns within this variability, with implications for prompt diagnosis and treatment initiation, as well as an understanding of the clinical spectrum of EM.

Lyme disease (LD) is tick-borne disease whose post-treatment sequelae are not well understood. For this study, we enrolled 152 individuals with symptoms of post-treatment LD (PTLD) to profile their peripheral blood mononuclear cells (PBMCs) with RNA sequencing (RNA-seq). Combined with RNA-seq data from 72 individuals with acute LD and 44 uninfected controls, we investigated differences in differential gene expression. We observe that most individuals with PTLD have an inflammatory signature that is distinguished from the acute LD group. By distilling gene sets from this study with gene sets from other sources, we identify a subset of genes that are highly expressed in the cohorts but are not already established as biomarkers for inflammatory response or other viral or bacterial infections. We further reduce this gene set by feature importance to establish an mRNA biomarker set capable of distinguishing healthy individuals from those with acute LD or PTLD as a candidate for translation into an LD diagnostic.

Purpose: Post-treatment Lyme disease (PTLD) is characterized by patient-reported symptoms after treatment for Borrelia burgdorferi infection. The primary aim of this study was to assess whether participants with a history of Lyme disease (LD) would be more likely to meet criteria for PTLD than those without a history of LD. Methods: We conducted a longitudinal, prospective study among 234 participants with and 49 participants without prior LD. All completed survey metrics for fatigue, pain, sleep, depression, and quality of life. An operationalized PTLD definition was applied to both cohorts, and the distributions of clinical outcomes and symptoms were examined. Results: In total, 13·7% of participants with a history of prior LD met criteria for PTLD compared with 4·1% of those without a history of prior LD. Participants with prior LD were approximately 5·28 times as likely to meet PTLD criteria compared with those without prior LD (p = 0·042) and had 8-15 times as high odds of reporting moderate or severe fatigue and muscle pain (p = 0·002, 0·047, respectively). Risk of meeting PTLD criteria was also independently increased among females and those with higher exposure to previous traumatic life events. Conclusion: Participants ideally diagnosed and treated for prior LD reported more symptoms on standardized surveys and were more likely to meet criteria for PTLD than those without prior LD.

With the incidence of Lyme and other tickborne diseases on the rise in the US and globally, there is a critical need for data-driven tools that communicate the magnitude of this problem and help guide public health responses. We present the Johns Hopkins Lyme and Tickborne Disease Dashboard (https://www.hopkinslymetracker.org/), a new tool that harnesses the power of geography to raise awareness and fuel research and scientific collaboration. The dashboard is unique in applying a geographic lens to tickborne diseases, aiming not only to become a global tracker of tickborne diseases but also to contextualize their complicated geography with a comprehensive set of maps and spatial data sets representing a One Health approach. We share our experience designing and implementing the dashboard, describe the main features, and discuss current limitations and future directions.

Lyme disease (also known as Lyme borreliosis) is the most common vector-borne disease in the United States with an estimated 476,000 cases per year. While historically, the long-term impact of Lyme disease on patients has been controversial, mounting evidence supports the idea that a substantial number of patients experience persistent symptoms following treatment. The research community has largely lacked the necessary funding to properly advance the scientific and clinical understanding of the disease, or to develop and evaluate innovative approaches for prevention, diagnosis, and treatment. Given the many outstanding questions raised into the diagnosis, clinical presentation and treatment of Lyme disease, and the underlying molecular mechanisms that trigger persistent disease, there is an urgent need for more support. This review article summarizes progress over the past 5 years in our understanding of Lyme and tick-borne diseases in the United States and highlights remaining challenges.

Lyme disease, the most common tick-borne illness in the United States, is most frequently caused by infection withBorrelia burgdorferi. Although early antibiotic treatment can prevent development of severe illness and late manifestations, diagnosis is challenging in patients who do not present with a typical erythema migrans rash. To support a diagnosis of Lyme disease in such cases, guidelines recommend 2-tiered serologic testing. However, 2-tiered testing has numerous limitations, including ambiguity in interpretation and lower sensitivity in early disease. We developed a diagnostic approach for Lyme disease based on the T-cell response toB. burgdorferiinfection by immunosequencing T-cell receptor (TCR) repertoires in blood samples from 3 independent cohorts of patients with laboratory-confirmed or clinically diagnosed early Lyme disease, as well as endemic and non-endemic controls. We identified 251 public, Lyme-associated TCRs that were used to train a classifier for detection of early Lyme disease with 99% specificity. In a validation cohort of individuals with early Lyme disease, TCR testing demonstrated a 1.9-fold increase in sensitivity compared to standard 2-tiered testing (STTT; 56% versus 30%), with a 3.1-fold increase ≤4 days from the onset of symptoms (44% versus 14%). TCR positivity predicted subsequent seroconversion in 37% of initially STTT-negative patients, suggesting that the T-cell response is detectable before the humoral response. While positivity for both tests declined after treatment, greater declines in posttreatment sensitivity were observed for STTT compared to TCR testing. Higher TCR scores were associated with clinical measures of disease severity, including abnormal liver function test results, disseminated rash, and number of symptoms. A subset of Lyme-associated TCRs mapped toB. burgdorferiantigens, demonstrating high specificity of a TCR immunosequencing approach. These results support the clinical utility of T-cell‒based testing as a sensitive and specific diagnostic for early Lyme disease, particularly in the initial days of illness.

Purpose Posttreatment Lyme disease (PTLD) is marked by neurologic symptoms, cognitive impairment, and significant symptom burden, including fatigue and ocular complaints. The purpose of this study was to determine whether contrast sensitivity (CS) is altered in patients with PTLD compared with healthy controls and, second, whether CS is associated with cognitive and/or neurologic deficits. Methods CS was measured using a Pelli-Robson chart with forced-choice procedures, and the total number of letters read was recorded for each eye. CS impairment was defined for age

Although widely prevalent, Lyme disease is still under-diagnosed and misunderstood. Here we followed 73 acute Lyme disease patients and uninfected controls over a period of a year. At each visit, RNA-sequencing was applied to profile patients' peripheral blood mononuclear cells in addition to extensive clinical phenotyping. Based on the projection of the RNA-seq data into lower dimensions, we observe that the cases are separated from controls, and almost all cases never return to cluster with the controls over time. Enrichment analysis of the differentially expressed genes between clusters identifies up-regulation of immune response genes. This observation is also supported by deconvolution analysis to identify the changes in cell type composition due to Lyme disease infection. Importantly, we developed several machine learning classifiers that attempt to perform various Lyme disease classifications. We show that Lyme patients can be distinguished from the controls as well as from COVID-19 patients, but classification was not successful in distinguishing those patients with early Lyme disease cases that would advance to develop post-treatment persistent symptoms.

The erythema migrans (EM) skin lesion is often the first clinical sign of Lyme disease. Significant variability in EM presenting characteristics such as shape, color, pattern, and homogeneity, has been reported. We studied associations between these presenting characteristics, as well as whether they were associated with age, sex, EM duration, body location, and initiation of antibiotics.Two hundred and seventy one adult participants with early Lyme disease who had a physician-diagnosed EM skin lesion of ≥ 5 cm in diameter and ≤ 72 h of antibiotic treatment were enrolled. Participant demographics, clinical characteristics, and characteristics of their primary EM lesion were recorded.After adjusting for potential confounders, EM size increased along with increasing EM duration to a peak of 14 days. Male EM were found to be on average 2.18 cm larger than female EM. The odds of a red (vs blue/red) EM were 65% lower in males compared to females, and were over 3 times as high for EM found on the pelvis, torso, or arm compared to the leg. Age remained a significant predictor of central clearing in adjusted models; for every 10-year increase in age, the odds of central clearing decreased 25%.Given that EM remains a clinical diagnosis, it is essential that both physicians and the general public are aware of its varied manifestations. Our findings suggest possible patterns within this variability, with implications for prompt diagnosis and treatment initiation, as well as an understanding of the clinical spectrum of EM.

Most patients with acute Lyme disease are cured with antibiotic intervention, but 10 to 20% endure debilitating symptoms such as fatigue, neurological complications, and myalgias after treatment, a condition known as posttreatment Lyme disease syndrome (PTLDS). The etiology of PTLDS is not understood, and objective diagnostic tools are lacking. PTLDS symptoms overlap several diseases in which patients exhibit alterations in their microbiome. We found that patients with PTLDS have a distinct microbiome signature, allowing for an accurate classification of over 80% of analyzed cases. The signature is characterized by an increase in Blautia, a decrease in Bacteroides, and other changes. Importantly, this signature supports the validity of PTLDS and is the first potential biological diagnostic tool for the disease., Lyme disease is the most common vector-borne disease in the United States, with an estimated incidence of 300,000 infections annually. Antibiotic intervention cures Lyme disease in the majority of cases; however, 10 to 20% of patients develop posttreatment Lyme disease syndrome (PTLDS), a debilitating condition characterized by chronic fatigue, pain, and cognitive difficulties. The underlying mechanism responsible for PTLDS symptoms, as well as a reliable diagnostic tool, has remained elusive. We reasoned that the gut microbiome may play an important role in PTLDS given that the symptoms overlap considerably with conditions in which a dysbiotic microbiome has been observed, including mood, cognition, and autoimmune disorders. Analysis of sequencing data from a rigorously curated cohort of patients with PTLDS revealed a gut microbiome signature distinct from that of healthy control subjects, as well as from that of intensive care unit (ICU) patients. Notably, microbiome sequencing data alone were indicative of PTLDS, which presents a potential, novel diagnostic tool for PTLDS.

Background Post-treatment Lyme disease symptoms/syndrome (PTLDS) occurs in approximately 10% of patients with Lyme disease following antibiotic treatment. Biomarkers or specific clinical symptoms to identify patients with PTLDS do not currently exist and the PTLDS classification is based on the report of persistent, subjective symptoms for ≥6 months following antibiotic treatment for Lyme disease. Methods Untargeted liquid chromatography–mass spectrometry metabolomics was used to determine longitudinal metabolic responses and biosignatures in PTLDS and clinically cured non-PTLDS Lyme patients. Evaluation of biosignatures included (1) defining altered classes of metabolites, (2) elastic net regularization to define metabolites that most strongly defined PTLDS and non-PTLDS patients at different time points, (3) changes in the longitudinal abundance of metabolites, and (4) linear discriminant analysis to evaluate robustness in a second patient cohort. Results This study determined that observable metabolic differences exist between PTLDS and non-PTLDS patients at multiple time points. The metabolites with differential abundance included those from glycerophospholipid, bile acid, and acylcarnitine metabolism. Distinct longitudinal patterns of metabolite abundance indicated a greater metabolic variability in PTLDS versus non-PTLDS patients. Small numbers of metabolites (6 to 40) could be used to define PTLDS versus non-PTLDS patients at defined time points, and the findings were validated in a second cohort of PTLDS and non-PTLDS patients. Conclusions These data provide evidence that an objective metabolite-based measurement can distinguish patients with PTLDS and help understand the underlying biochemistry of PTLDS.

Lyme disease is a tick-borne infection caused by the bacteria Borrelia burgdorferi. Current diagnosis of early Lyme disease relies heavily on clinical criteria, including the presence of an erythema migrans rash. The sensitivity of current gold-standard diagnostic tests relies upon antibody formation, which is typically delayed and thus of limited utility in early infection. We conducted a study of blood and skin biopsy specimens from 57 patients with a clinical diagnosis of erythema migrans. Samples collected at the time of diagnosis were analyzed using an ultrasensitive, PCR-based assay employing an isothermal amplification step and multiple primers. In 75.4% of patients, we directly detected one or more B. burgdorferi genotypes in the skin. Two-tier testing showed that 20 (46.5%) of those found to be PCR positive remained serologically negative at both acute and convalescent time points. Multiple genotypes were found in three (8%) of those where a specific genotype could be identified. The 13 participants who lacked PCR and serologic evidence for exposure to B. burgdorferi could be differentiated as a group from PCR-positive participants by their levels of several immune markers as well as by clinical descriptors such as the number of acute symptoms and the pattern of their erythema migrans rash. These results suggest that within a Mid-Atlantic cohort, patient subgroups can be identified using PCR-based direct detection approaches. This may be particularly useful in future research such as vaccine trials and public health surveillance of tick-borne disease patterns.

This study examines the use of AI methods and deep learning (DL) for prescreening skin lesions and detecting the characteristic erythema migrans rash of acute Lyme disease. Accurate identification of erythema migrans allows for early diagnosis and treatment, which avoids the potential for later neurologic, rheumatologic, and cardiac complications of Lyme disease. We develop and test several deep learning models for detecting erythema migrans versus several other clinically relevant skin conditions, including cellulitis, tinea corporis, herpes zoster, erythema multiforme, lesions due to tick bites and insect bites, as well as non-pathogenic normal skin. We consider a set of clinically-relevant binary and multiclass classification problems of increasing complexity. We train the DL models on a combination of publicly available images and test on public images as well as images obtained in the clinical setting. We report performance metrics that measure agreement with a gold standard, as well as a receiver operating characteristic curve and associated area under the curve. On public images, we find that the DL system has an accuracy ranging from 71.58% (and 95% error margin equal to 3.77%) for an 8-class problem of EM versus 7 other classes including other skin pathologies, insect bites and normal skin, to 94.23% (3.66%) for a binary problem of EM vs. non-pathological skin. On clinical images of affected individuals, the DL system has a sensitivity of 88.55% (2.39%). These results suggest that a DL system can help in prescreening and referring individuals to physicians for earlier diagnosis and treatment, in the presence of clinically relevant confusers, thereby reducing further complications and morbidity.

An African-American man in his 30s presented following seven weeks of symptoms including an initial febrile illness with a rash followed by onset of fatigue, facial weakness, daily headaches, neck pain, leg numbness, hyperacusis, and photosensitivity. Over the seven weeks, he had several evaluations and was treated for cellulitis and facial swelling before ultimately being diagnosed and treated for Lyme disease with seventh nerve palsy and meningitis. His symptoms failed to completely resolve after treatment, and he was diagnosed with post-treatment Lyme disease syndrome (PTLDS) due to ongoing symptoms which lasted for more than six months after treatment. Delayed diagnosis increases the risk of PTLDS and other long-term complications from Lyme disease. Provider awareness of Lyme disease risk factors, common neurologic and other presentations, and racial differences in diagnostic findings such as the skin rash can improve care by achieving earlier, accurate diagnoses and reduce risk of PTLDS.

The epidemiology of Lyme disease has been examined utilizing insurance claims from privately insured individuals; however, it is unknown whether reported patterns vary among the publicly insured. We examined trends in incidence rates of first Lyme disease diagnosis among 384,652 Maryland Medicaid recipients enrolled from July 2004 to June 2011. Age-, sex-, county-, season-, and year-specific incidence rates were calculated, and mixed-effects multiple logistic regression models were used to study the relationship between Lyme disease diagnosis and these variables. The incidence rate in our sample was 97.65 cases per 100,000 person-years (95% confidence interval (CI): 91.53, 104.06), and there was a 13% average annual increase in the odds of a Lyme disease diagnosis (odds ratio = 1.13, 95% CI: 1.09, 1.17; P < 0.001). Incidence rates for males and females were not significantly different, though males were significantly more likely to be diagnosed during high-season months (relative risk (RR) = 1.24, 95% CI: 1.06, 1.44) and less likely to be diagnosed during low-season months (RR = 0.63, 95% CI: 0.46, 0.87) than females. Additionally, adults were significantly more likely than children to be diagnosed during low-season months (RR = 1.59, 95% CI: 1.19, 2.12). While relatively rare in this study sample, Lyme disease diagnoses do occur in a Medicaid population in a Lyme-endemic state.

Lyme disease results from infection of humans with the spirocheteBorrelia burgdorferi. The first and most common clinical manifestation is the circular, inflamed skin lesion referred to as erythema migrans; later manifestations result from infections of other body sites. Laboratory diagnosis of Lyme disease can be challenging in patients with erythema migrans because of the time delay in the development of specific diagnostic antibodies against Borrelia. Reliable blood biomarkers for the early diagnosis of Lyme disease in patients with erythema migrans are needed. Here, we performed selected reaction monitoring, a targeted mass spectrometry-based approach, to measure selected proteins that 1) are known to be predominantly expressed in one organ (i.e., organ-specific blood proteins) and whose blood concentrations may change as a result of Lyme disease, or 2) are involved in acute immune responses. In a longitudinal cohort of 40 Lyme disease patients and 20 healthy controls, we identified 10 proteins with significantly altered serum levels in patients at the time of diagnosis, and we also developed a 10-protein panel identified through multivariate analysis. In an independent cohort of patients with erythema migrans, six of these proteins, APOA4, C9, CRP, CST6, PGLYRP2 and S100A9, were confirmed to show significantly altered serum levels in patients at time of presentation. Nine of the 10 proteins from the multivariate panel were also verified in the second cohort. These proteins, primarily innate immune response proteins or proteins specific to liver, skin or white blood cells, may serve as candidate blood biomarkers requiring further validation to aid in the laboratory diagnosis of early Lyme disease.

Borrelia burgdorferi is the etiological agent of Lyme disease. In the current study, we used direct-detection PCR and electrospray ionization mass spectrometry to monitor and genotype B. burgdorferi isolates from serially collected whole-blood specimens from patients clinically diagnosed with early Lyme disease before and during 21 days of antibiotic therapy.

The pathophysiology of post-treatment Lyme disease syndrome (PTLDS) may be linked to overactive immunity including aberrant activity of the brain’s resident immune cells, microglia. Here we used [11C]DPA-713 and positron emission tomography to quantify the 18 kDa translocator protein, a marker of activated microglia or reactive astrocytes, in the brains of patients with post-treatment Lyme disease symptoms of any duration compared to healthy controls. Genotyping for the TSPO rs6971 polymorphism was completed, and individuals with the rare, low affinity binding genotype were excluded. Data from eight brain regions demonstrated higher [11C]DPA-713 binding in 12 patients relative to 19 controls. [11C]DPA-713 PET is a promising tool to study cerebral glial activation in PTLDS and its link to cognitive symptoms.

ObjectivesTo identify underlying subgroups with distinct symptom profiles, and to characterise and compare these subgroups across a range of demographic, clinical and psychosocial factors, within a heterogeneous group of patients with well-defined post-treatment Lyme disease (PTLD).DesignA clinical case series of patents.SettingParticipants were recruited from a single-site, Lyme disease referral clinic patient population and were evaluated by physical exam, clinical laboratory testing and standardised questionnaires.ParticipantsTwo hundred and twelve participants met study criteria for PTLD, with medical record-confirmed prior Lyme disease as well as current symptoms and functional impact.ResultsExploratory factor analysis classified 30 self-reported symptoms into 6 factors: ‘Fatigue Cognitive’, ‘Ocular Disequilibrium’, ‘Infection-Type’, ‘Mood-Related’, ‘Musculoskeletal Pain’ and ‘Neurologic’. A final latent profile analysis was conducted using ‘Fatigue Cognitive’, ‘Musculoskeletal Pain’ and ‘Mood-Related’ factor-based scores, which produced three emergent symptom profiles, and participants were classified into corresponding subgroups with 59.0%, 18.9% and 22.2% of the sample, respectively. Compared with the other two groups, subgroup 1 had similarly low levels across all factors relative to the sample as a whole, and reported lower rates of disability (1.6% vs 10.0%, 12.8%; q=0.126, 0.035) and higher self-efficacy (median: 7.5 vs 6.0, 5.3; q=0.068,ConclusionsThis analysis identified six symptom factors and three potentially clinically relevant subgroups among patients with well-characterised PTLD. We found that these subgroups were differentiated not only by symptom phenotype, but also by a range of other factors. This may serve as an initial step towards engaging with the symptom heterogeneity that has long been observed among patients with this condition.

Approximately 10% to 20% of patients optimally treated for early Lyme disease develop persistent symptoms of unknown pathophysiology termed posttreatment Lyme disease syndrome (PTLDS). The objective of this study was to investigate associations between PTLDS and immune mediator levels during acute illness and at several time points following treatment. Seventy-six participants with physician-documented erythema migrans and 26 healthy controls with no history of Lyme disease were enrolled. Sixty-four cytokines, chemokines, and inflammatory markers were measured at each visit for a total of 6 visits over 1 year. An operationalized definition of PTLDS incorporating symptoms and functional impact was applied at 6 months and 1 year following treatment completion, and clinical outcome groups were defined as the return-to-health, symptoms-only, and PTLDS groups. Significance analysis of microarrays identified 7 of the 64 immune mediators to be differentially regulated by group. Generalized logit regressions controlling for potential confounders identified posttreatment levels of the T-cell chemokine CCL19 to be independently associated with clinical outcome group. Receiver operating characteristic analysis identified a CCL19 cutoff of >111.67 pg/ml at 1 month following treatment completion to be 82% sensitive and 83% specific for later PTLDS. We speculate that persistently elevated CCL19 levels among participants with PTLDS may reflect ongoing, immune-driven reactions at sites distal to secondary lymphoid tissue. Our findings suggest the relevance of CCL19 both during acute infection and as an immunologic risk factor for PTLDS during the posttreatment phase. Identification of a potential biomarker predictor for PTLDS provides the opportunity to better understand its pathophysiology and to develop early interventions in the context of appropriate and specific clinical information.

Persistent, subjective symptoms of unknown etiology following treatment for Lyme disease have been termed post- treatment Lyme disease syndrome or chronic Lyme disease (PTLDS/CLD). The objective of this study was to give primacy to the patient experience of this medically contested condition by eliciting patient illness narratives and identifying emergent issues through semistructured interviews conducted among 29 participants. We used thematic narrative analysis to identify three predominant themes: (a) Physical and social limitations lead to a “new normal” characterized by fundamental shifts of ways of being in the world, (b) disease-specific factors contribute to symptom and illness invisibility that affects social support in nuanced ways, and (c) pervasive medical uncertainty regarding PTLDS/CLD promotes an increased sense of personal responsibility for care. Similar to other contested or medically unexplained syndromes, our findings suggest that the social sequelae of PTLDS/CLD can be equally protracted as the physical effects of this illness.

Lyme disease can lead to neurological, cardiac, and rheumatologic complications when untreated. Timely recognition of the erythema migrans rash of acute Lyme disease by patients and clinicians is crucial to early diagnosis and treatment. Our objective in this study was to develop deep learning approaches using deep convolutional neural networks for detecting acute Lyme disease from erythema migrans images of varying quality and acquisition conditions. This study used a cross-sectional dataset of images to train a model employing a deep convolutional neural network to perform classification of erythema migrans versus other skin conditions including tinea corporis and herpes zoster, and normal, non-pathogenic skin. Evaluation of the machine's ability to classify skin types was also performed on a validation set of images. Machine performance for detecting erythema migrans was further tested against a panel of non-medical humans. Online, publicly available images of both erythema migrans and non-Lyme confounding skin lesions were mined, and combined with erythema migrans images from an ongoing, longitudinal study of participants with acute Lyme disease enrolled in 2016 and 2017 who were recruited from primary and urgent care centers. The final dataset had 1834 images, including 1718 expert clinician-curated online images from unknown individuals with erythema migrans, tinea corporis, herpes zoster, and normal skin. It also included 116 images taken of 63 research participants from the Mid-Atlantic region. Two clinicians carefully annotated all lesion images. A convenience sample of 7 non-medically-trained humans were used as a panel to compare against machine performance. We calculated several performance metrics, including accuracy and Kappa (characterizing agreement with gold standard), as well as a receiver operating characteristic curve and associated area under the curve. For detecting erythema migrans, the machine had an accuracy (95% confidence interval error margin) of 86.53% (2.70), ROCAUC of 0.9510 (0.0171) and Kappa of 0.7143. Our results suggested substantial agreement between machine and clinician criterion standard. Comparison of machine with non-medical expert human performance indicated that the machine almost always exceeded acceptable specificity, and could operate with higher sensitivity. This could have benefits for prescreening prior to physician referral, earlier treatment, and reductions in morbidity.

Lyme disease (Borrelia burgdorferi infection) is increasingly recognized as a significant source of morbidity worldwide. Here, we show that blood plasmablasts and CD27− memory B cells are elevated in untreated Lyme disease, with higher plasmablast levels associated with more rapid resolution of clinical symptoms. Stronger serum reactivity to surface proteins and peptides from B. burgdorferi was also associated with faster resolution of clinical symptoms. Through molecular identifier-enabled antibody heavy-chain sequencing of bulk B cells and single-cell paired-chain antibody sequencing of blood plasmablasts, we characterized immunoglobulin gene usage patterns specific to B. burgdorferi infection. Recombinantly expressed antibodies from expanded lineages bound B. burgdorferi antigens, confirming that these clones are driven by the infection. Furthermore, recombinant sequence-derived antibodies were functional, inhibiting growth of B. burgdorferi in vitro. Elevations and clonal expansion of blood plasmablasts were associated with rapid return to health, while poor plasmablast responses were associated with a longer duration of symptoms following treatment. Plasmablasts induced by B. burgdorferi infection showed preferential antibody gene segment usage, while bulk sequencing of total B cells revealed convergent CDR3 motifs specific to B. burgdorferi-infected patients. Our results show that robust plasmablast responses encoding Bb-static antibodies are associated with more rapid resolution of Lyme disease, and these antibodies could provide the basis for next-generation therapeutics for Lyme disease.

Objective For many individuals with Lyme disease, prompt treatment leads to rapid resolution of infection. However, severe complications can occur if treatment is delayed. Our objective was to identify themes around belated diagnosis or treatment of Lyme disease using the General Model of Total Patient Delay (GMTPD). Design We conducted a qualitative interview study using indepth telephone interviews. Setting Participants were patients from a large, integrated health system in the state of Pennsylvania, USA. Participants There were 26 participants. Participants had to have a diagnosis of Lyme disease between 2014 and 2017 and a positive IgG western blot. We used a stratified purposeful sampling design to identify patients with and without late Lyme disease manifestations. To ensure variation in care experiences, we oversampled patients diagnosed outside of primary care. Outcome measures We asked participants about their experience from first Lyme disease symptoms to treatment. We applied an iterative coding process to identify key themes and then synthesised codes into higher order codes representing the GMTPD stages: appraisal delay (symptom to recognition of illness); illness delay (inferring illness to deciding to seek help); behavioural delay (deciding to seek help to the act of seeking help); scheduling delay (seeking help to attending an appointment); and treatment delay (attending appointment to treatment). Results Appraisal delay themes included symptom misattribution, intermittent symptoms and misperceptions about the necessity of a bull’s-eye rash. Health insurance status was a driver of illness and behavioural delays. Scheduling delay was not noted by participants, in part, because 10 of the 26 patients went to urgent care or emergency department settings. Misdiagnoses were more common in these settings, contributing to treatment delay. Conclusion Our study identified potentially modifiable risk factors for belated treatment. Targeting these risk factors may minimise time to treatment and reduce the occurrence of preventable complications.

Study objectives Lyme disease (LD) is the most common vector-borne disease in the United States. Approximately 5-15 per cent of patients develop postantibiotic treatment symptoms termed post-treatment Lyme disease syndrome (PTLDS). The primary objective of this study is to examine and quantify sleep quality among patients with early LD during the acute and convalescent periods, including among the subset who met criteria for PTLDS. Methods This paper draws from a clinical cohort study of participants with early LD (n = 122) and a subcohort of individuals who later met criteria for PTLDS (n = 6). Participants were followed for 1 year after antibiotic treatment. The Pittsburgh Sleep Quality Index and standardized measures of pain, fatigue, depressive symptoms, and functional impact were administered at all visits for participants and controls (n = 26). Participants meeting criteria for PTLDS at 1 year post-treatment were compared with a subset of PSQI-defined poor sleeping controls (n = 10). Results At the pretreatment visit, participants with early LD reported poorer sleep than controls. By 6 months post-treatment, participant sleep scores as a group returned to control levels. Participants with PTLDS reported significantly worse global sleep and sleep disturbance scores and worse fatigue, functional impact, and more cognitive-affective depressive symptoms compared with poor sleeping controls. Conclusions Participants with early LD experienced poor sleep quality, which is associated with typical LD symptoms of pain and fatigue. In the subset of patients who developed PTLDS, sleep quality remains affected for up to 1 year post-treatment and is commonly associated with pain. Sleep quality should be considered in the clinical picture for LD and PTLDS.

Background The increased incidence and geographic expansion of Lyme disease has made it the most common vector-borne infection in North America. Posttreatment Lyme disease syndrome (PTLDS) represents a subset of patients who remain ill following standard antibiotic therapy for Lyme disease. The spectrum of symptoms and their impact on quality of life remain largely unexplored among patients with well-documented PTLDS. Objective To characterize a case series of patients with well-documented PTLDS compared to a sample of healthy controls. Methods Sixty-one participants met the proposed case definition for PTLDS. Twenty-six healthy controls had neither a clinical history of Lyme disease nor current antibodies to Borrelia burgdorferi. Participants with PTLDS and controls were evaluated by physical exam, clinical laboratory testing, standardized questionnaires, and a 36-item current symptom list. Results Compared to controls, participants with PTLDS reported significantly greater fatigue, pain, sleep disturbance, and depression (Fatigue Severity Scale: 50.0 ± 10.6 vs. 19.8 ± 8.6; Short-Form McGill Pain Questionnaire: 13.7 ± 8.3 vs. 0.8 ± 1.9; Pittsburgh Sleep Quality Index: 10.1 ± 4.7 vs. 4.1 ± 2.1; Beck Depression Inventory-II: 15.1 ± 7.7 vs. 2.2 ± 3.2; p

Objective Patient-reported cognitive complaints are common in those with post-treatment Lyme disease syndrome (PTLDS). Objective evidence of cognitive impairment in this population is variable in part due to methodological variability in existing studies. In this study, we sought to use a systematic approach to characterizing PTLDS based on the most current consensus diagnosis. We further examined PTLDS-related cognitive decline, operationalized as a significant decline in cognitive test performance relative to premorbid cognitive ability. Method We enrolled a case series of 124 patients with confirmed PTLDS defined by Infectious Diseases Society of America-proposed case definition. Cognitive functioning was evaluated using standardized neuropsychological measures. Results The majority (92%) of participants endorsed some level of cognitive difficulty, yet 50% of the sample showed no statistically or clinically significant cognitive decline, 26% of the sample evidenced significant cognitive decline on measures of memory and variably on measures of processing speed, and 24% of the sample were excluded from analyses due to suboptimal test engagement. Conclusions The current findings are consistent with the literature showing that the most robust neurocognitive deficit associated with PTLDS is in verbal memory and with variable decline in processing speed. Compared to population normative comparison standards, PTLDS-related cognitive decline remains mild. Thus, further research is needed to better understand factors related to the magnitude of subjective cognitive complaints as well as objective evidence of mild cognitive decline.

Objective Understanding the Lyme disease (LD) literature is challenging given the lack of consistent methodology and standardized measurement of symptoms and the impact on functioning. This prospective study incorporates well-validated measures to capture the symptom picture of individuals with early LD from time of diagnosis through 6-months post-treatment. Method One hundred seven patients with confirmed early LD and 26 healthy controls were evaluated using standardized instruments for pain, fatigue, depressive symptoms, functional impact, and cognitive functioning. Results Prior to antibiotic treatment, patients experience notable symptoms of fatigue and pain statistically higher than controls. After treatment, there are no group differences, suggesting that symptoms resolve and that there are no residual cognitive impairments at the level of group analysis. However, using subgroup analyses, some individuals experience persistent symptoms that lead to functional decline and these individuals can be identified immediately post-completion of standard antibiotic treatment using well-validated symptom measures. Conclusions Overall, the findings suggest that ideally-treated early LD patients recover well and experience symptom resolution over time, though a small subgroup continue to suffer with symptoms that lead to functional decline. The authors discuss use of standardized instruments for identification of individuals who warrant further clinical follow-up.