Diagnosis In Primary Care Research Articles

EPH169 Persons Diagnosed with COVID-19 in Linked Clinical Practice Research Datalink (CPRD) – Hospital Episode Statistics (HES) Data: A Cohort Description

Clinical Practice Research Datalink (CPRD) Aurum captures primary care electronic healthcare records for ∼28% of the population in England. From August 2020‒;March 2022, all SARS-CoV-2 polymerase chain reaction (PCR) tests performed were reported back to the patient’s general practitioner (GP), making the CPRD a closed system uniquely positioned to answer COVID research questions. We defined persons with COVID as those recorded in primary care with a positive PCR test from August 1, 2020-March 31, 2021. We required continuous registration with their GP practice for ≥365 days prior to diagnosis to establish comorbid conditions, and eligibility for linkage to Hospital Episode Statistics (HES) Admitted Patient Care data. Hospitalizations for COVID were defined as persons admitted with a primary diagnosis of COVID (ICD-10-CM U07.1) within 12 weeks of the initial primary care diagnosis record. Our cohort included 535,453 persons diagnosed in primary care with COVID, with 2% later hospitalized. The hospitalized group was 57% male, 42% current/former smokers, 35% obese46% with a Charlson Comorbidity Index >1 and 98% had never received any COVID vaccine. Hospitalizations increased with age; <0.1% of patients aged 1-17, 1% aged 18-49, 4% aged 50-64, 9% aged 65-74, 13% aged 74-84, and 11% of COVID cases aged ≥85 were hospitalized. Persons living in socially disadvantaged areas were overrepresented in the hospitalized cohort (25% in the Index of Multiple Deprivation’s most deprived quintile). Consistent with other studies, hospitalized COVID patients were disproportionately those with male sex, smoking history, high body mass index, comorbidity and unvaccinated status. Hospitalizations were more common with age, and for individuals living in socially and economically deprived communities. Understanding the demographic and clinical characteristics of this cohort can help contextualize future work describing healthcare resource utilization and costs, as well as the impact of vaccines, associated with COVID in England.

0483 Stakeholder Engagement Studios to Explore the Journey to Diagnosis of OSA Informed by Primary Care Providers and Patients

Abstract Introduction Barriers to obstructive sleep apnea (OSA) diagnosis include operational misalignments and miscommunications among patients, providers, industry, insurers, and the healthcare system. To explore this, we engaged stakeholders to examine determinants of OSA diagnosis in primary care to optimize trial planning. Methods We conducted two, separate, virtual, 1-hour stakeholder engagement studio sessions with Penn Medicine Primary Care Providers (n=6) and patients referred for OSA diagnostics within prior year (n=3). Facilitation guides were used to elicit barriers/facilitators to reaching diagnosis. Sessions were facilitated by a sleep physician and advanced practice sleep nurse with two note-takers in attendance. Rapid matrix analysis approach identified consistent themes within diagnosis barrier and facilitator categories. Themes were categorized by Safety Engineering Initiative for Patient Safety (SEIPS) work system domains: people (P), environment (E), tools (T), and tasks (T), PETT. Results Fourteen facilitators (2P, 3E, 3T, 6T) and 15 barriers (2P, 4E, 3T, 6T) were identified for “getting to OSA diagnosis.” Provider-level barriers include: hesitancy to provide anticipatory guidance to patients due to ambiguous workflows after referral, excessive referral order options, no access to templated patient instructions or quality education resources, confusing order panels and use of electronic health record (EHR) workarounds, and fragmented communication. Patient-level barriers include: timeliness of communication and care, sleep health unawareness, low technology literacy for EHR messaging, financial considerations, and insufficient follow-up from healthcare team. Provider facilitators include: classic OSA presentation, diagnosis decision aids, patient education resources, easy to find results in EHR, and low threshold to order referral due to knowledge about sleep. Patient facilitators include: trusted primary care relationship, choice of visit type (telehealth vs. in-person) and communication mode (phone call vs. text vs. EHR portal), active outreach/engagement by healthcare team, and access to educational materials. Conclusion Repeated studios, including stakeholders from varied sites, will further refine determinants with more saturation and validity. Engaging with stakeholders is supporting the design of a contextually relevant, end-user valued study to address undiagnosed OSA. Given the estimated high prevalence of undiagnosed OSA and the multiple stakeholders that contribute to the diagnostic process and experience, research-driven solutions will be impactful and better optimized with multi-level partnered research. Support (if any) K12HS026372

Innovative primary care lead community palpitation management and investigation pathway

Abstract Funding Acknowledgements Type of funding sources: None. Background Palpitations are a common reason for General Practitioner (GP) appointment in primary care and a frequent reason for cardiology referral. In the region where this project was performed, this translated to approximately 24,000 primary care and out of hours consultations in 2021 alone. Purpose The purpose of this pilot was to evaluate a pathway for palpitations diagnosis and management in primary care. The proposed pathway was designed to avoid unnecessary referrals to secondary care, to shorten the waiting time to diagnosis for patients and to cut down visits to A&amp;E and out of hours service in primary care. Method The pathway, which was piloted at a federation for 30,000 patients, was based on a community cardiology approach, where a GP with Special interest in cardiology could offer the service for the wider community. The pathway began with an initial clinical evaluation comprising medical history, physical examination, and a standard 12-lead ECG. After ruling out of any red flags and otherwise deemed appropriate to continue to be assessed with the proposed diagnostic method, the patients were provided with a handheld ECG device for intermittent 30 seconds ECG registration at home. During a four-week investigation period the patients would record their ECG when experiencing symptoms. The primary care team remotely monitored the traces which were received on a cloud-based system with AI capabilities, and if pathology was recorded, patient was contacted and informed of management plan. If after four weeks no pathology was found, patients received a discharge consultation for reassurance and final report was generated. Results During the 24-month pilot we screened the total of 191 patients. Out of the patients screened 24 (13%) were diagnosed with atrial fibrillation, 92 (48%) were diagnosed with benign ectopics as the cause of their palpitations. Two rare occurrences of a life threatening broad complex tachycardias were also detected, both of which ended up needing defib implantation. Table 1. further presents the results by diagnosis for rest of the patients. Conclusions The results from the pilot indicated a reduction in GP / out of hours consultations by 50% and over 90% reduction in referral to secondary care for Holter monitoring by implementing an easy-to-use handheld ECG as part of the community led palpitation pathway. The results further implied that a district-wide implementation could lead to at least 120 new AF diagnosis in our project district per year, having a knock-on benefit of stroke reduction and cost economic impact in the society by reducing anxiety, lost employment hours and increasing productivity. Another key outcome seen is the reassurance value of conducting symptomatic palpitation monitoring to reassure patients, majority of whom had either normal sinus rhythm or benign ventricular ectopics and had failed to be satisfied with conventional Holter monitoring in the past.

Using care pathways for cancer diagnosis in primary care: a qualitative study to understand family physicians' mental models.

Care pathways are tools that can help family physicians navigate the complexities of the cancer diagnostic process. Our objective was to examine the mental models associated with using care pathways for cancer diagnosis of a group of family physicians in Alberta. We conducted a qualitative study using cognitive task analysis, with interviews in the primary care setting between February and March 2021. Family physicians whose practices were not heavily oriented toward patients with cancer and who did not work closely with specialized cancer clinics were recruited with the support of the Alberta Medical Association and leveraging our familiarity with Alberta's Primary Care Networks. We conducted simulation exercise interviews with 3 pathway examples over Zoom, and we analyzed data using both macrocognition theory and thematic analysis. Eight family physicians participated. Macrocognitive functions (and subthemes) related to mental models were sense-making and learning (confirmation and validation, guidance and support, and sense-giving to patients), care coordination and diagnostic decision-making (shared understanding). Themes related to the use of the pathways were limited use in diagnosis decisions, use in guiding and supporting referral, only relevant and easy-to-process information, and easily accessible. Our findings suggest the importance of designing pathways intentionally for streamlined integration into family physicians' practices, highlighting the need for co-design approaches. Pathways were identified as a tool that, used in combination with other tools, may help gather information and support cancer diagnosis decisions, with the goals of improving patient outcomes and care experience.

Practitioner characteristics, diagnostic accuracy metrics and discovering-individual with respect to 637 melanomas documented by 27 general practitioners on the Skin Cancer Audit Research Database.

Knowledge of accuracy for melanoma diagnosis and melanoma discovering-individual in primary care is limited. We describe general practitioner (GP) characteristics and analyse defined diagnostic accuracy metrics for GPs in the current study comparing this with a previous study for GPs common to both, and we analyse the individual first discovering each melanoma as a lesion of concern. The characteristics and diagnostic accuracy of 27 Australasian GPs documenting 637 melanomas on the Skin Cancer Audit Research Database (SCARD) in 2013 were described and analysed. The number needed to treat (NNT) and percentage of melanomas that were in situ (percentage in situ) were analysed as surrogates for specificity and sensitivity, respectively. The discovering-individual was analysed according to patient age and sex and lesion Breslow thickness. The average NNT and percentage in situ were 5.73% and 65.07%, respectively. For 21 GPs in both a 2008-2010 study and the current study, the NNT was 10.78 and 5.56, respectively (p = 0.0037). A consistent trend of decreasing NNT and increasing percentage in situ through increasingly subspecialised GP categories did not reach statistical significance. NNT trended high at ages and sites for which melanoma was rare. While the patient or family member was more likely to discover thick melanomas and melanomas in patients under 40 years, GPs discovered 73.9% of the melanomas as lesions of concern. GPs were the discovering-individuals for the majority of melanomas in the current study and their accuracy metrics compared favourably with published figures for dermatologists and GPs.

P023 National care of patients with Polymyalgia Rheumatica: Audit of steroid usage from UK GP data - a cause for concern?

Abstract Background/Aims Polymyalgia rheumatica (PMR) is the most common autoimmune musculoskeletal condition in the developed world. Current BSR guidelines recommend glucocorticoid treatment for one to two years and give suggested taper regimens. The project examines national primary care data to assess the level of adherence to current guidelines, and the proportion of patients at risk from the deleterious effects of prolonged steroid exposure. Methods The ECLIPSE databased covers over 25m patients across 2400 general practices in England and provides insights for enhanced clinical pathway management and to support patient safety in primary care. Routinely recorded diagnoses from primary care data are updated daily, along with administrative prescribing data. Using standardised nationally agreed disease coding frameworks, all diagnoses of PMR were retrieved from the live patient population of 25.4m individuals registered with general practices across England. Primary care diagnosis data for patients with a new diagnosis of PMR recorded in primary care on or after 01/01/2016 were linked with prescribing data from the same time period and followed to 10/10/2022. From the current BSR guidelines the following thresholds were taken to represent above recommended cumulative glucocorticoid exposure: 0-6 months &amp;gt;2100mg, 7 to 12 months &amp;gt;1400mg, 13 to 18 months &amp;gt;910mg and 19 to 24 months &amp;gt;910mg. Finally total numbers of those still prescribed glucocorticoids past 60 months was taken as to represent those who had become steroid-dependent. Results Over the observation period of 6.8 years there were 95,862 people diagnosed with PMR from the UK national data, of whom 22,677 were diagnosed in the East of England and 5,315 from the Norfolk and Waveney Integrated Care System. The prevalence was 0.99%, 1.00% and 1.5% for those aged older than 50 years across the three areas respectively consistent with published disease estimates. There was considerable number of individuals with PMR prescribed glucocorticoids above the recommend levels (see Table 1). Conclusion There is significant departure from the suggested PMR tapering regimens which may be due to frequency of relapse, inadequate treatment response or inadequate guideline implementation. Strategies to reduce glucocorticoid exposure in this older co-morbid population are required urgently. Disclosure P. Saha: None. J. Brown: None. A. MacGregor: None. C. Aldus: None. M. Yates: None.

Socioeconomic, medical and demographic characteristics of early adopters of digital primary care.

In this paper, we investigated which socioeconomic and demographic groups first adopted digital primary care video consultations when they became accessible to the entire population in Sweden. We analysed data on all patients (378,000) who had a consultation with the largest provider of digital healthcare in Sweden - Kry - in the first years of national availability of the service, 2016-2018. We studied their income, education, demographics, and diagnosis backgrounds using matched registry data. Moreover, to compare users and non-users of digital primary care, we used data on all physical primary care users in one Swedish region: Skåne. We found that this digital primary care was first used by young and higher-income adults, but not far from half of adult users had incomes below the national median. Digital care patients were more educated than the general population, reflecting that urban inhabitants were more likely than rural inhabitants to be users. First-generation immigrants were less represented among digital care users than in the population. However, second-generation immigrants with two foreign parents were slightly over-represented. The prevalence of some chronic diseases in pre-digital secondary (specialist and hospital) healthcare data among digital care users was similar to the population adjusted for age. Studying all physical primary care users in Skåne region, young digital care users had more primary care diagnoses and previous in-person primary care appointments than non-users, while the pattern was reversed for older users. When digital primary care became nationally available, younger, urban and more educated patients were the first to adopt the new technology. Regarding medical history, young users of digital care had a higher previous disease burden than young non-users, suggesting that these digital services were first adopted by young people with high primary care needs.

The conceptualization of acute bronchitis in general practice – a fuzzy problem with consequences? A qualitative study in primary care

BackgroundAcute bronchitis is one of the most frequent diagnoses in primary care. Scientifically, it is conceptualized as a viral infection. Still, general practitioners (GPs) often prescribe antibiotics for acute bronchitis. The explanation for this discrepancy may lie in a different conceptualization of acute bronchitis. Therefore, we wanted to know, how GPs conceptualize acute bronchitis, and how they differentiate it from common cold and pneumonia. Furthermore, we tried to find out the GPs’ reasons for prescribing antibiotics in those cases.MethodsTo answer our study questions, we conducted a qualitative study with GPs in Bavaria, Germany, by using semi-structured guided interviews. The analysis of the data was conducted using the documentary method according to Ralf Bohnsack. The transcripts were subdivided into categories. Analyzing each part by reflective interpretation, first manually, secondly with the help of RQDA, we extracted the most representative citations and main messages from the interviews.ResultsThe term acute bronchitis seems to be applied when there is neither certainty of the diagnosis common cold, nor of pneumonia. It seems it bridges the gap of uncertainty between supposedly harmless clinical pictures (common cold/viral), to the more serious ones (pneumonia/bacterial). The conceptual transitions between common cold and acute bronchitis on the one side, and acute bronchitis and pneumonia on the other are fluid. The diagnosis acute bronchitis cannot solve the problem of uncertainty but seems to be a label to overcome it by offering a way to include different factors such as severity of symptoms, presumed signs of bacterial secondary infection, comorbidities, and presumed expectations of patients. It seems to solve the pathophysiologic riddle of bacterial or viral and of decision making in prescribing antibiotics.ConclusionAcute bronchitis as an "intermediate category" proved difficult to define for the GPs. Applying this diagnosis leaves GPs in abeyance of prescribing an antibiotic or not. As a consequence of this uncertainty in pathophysiologic reasoning (viral or bacterial) other clinical and social factors tip the balance towards antibiotic prescribing. Teaching physicians to better think in probabilities of outcomes instead of pathophysiologic reasoning and to deal with uncertainty might help reducing antibiotic overprescribing.

Prevalence and incidence of alcohol dependence: cross-sectional primary care analysis in Liverpool, UK

ObjectivesLiverpool has high prevalence of alcohol use disorders (AUDs) compared with the rest of the UK. Early identification and referral in primary care would improve treatment for people with AUD....

ECHO (Extension for Community Healthcare Outcomes) Autism STAT: A Diagnostic Accuracy Study of Community-Based Primary Care Diagnosis of Autism Spectrum Disorder.

Children can be reliably diagnosed with autism spectrum disorder (ASD) by a highly trained clinician as early as 12 to 24 months of age, but recent estimates indicate that the average age of diagnosis is 4.4 years. We hypothesized that trained primary care physicians and practitioners can reliably and accurately diagnose children 14 to 48 months with unambiguous symptoms of ASD. Through this diagnostic accuracy study, 20 patients diagnosed with ASD by clinicians trained through the ECHO (Extension for Community Healthcare Outcomes) Autism STAT program participated in an independent gold-standard evaluation at a regional autism center. Caregiver perceptions of the diagnostic process were also assessed. Of the 20 patients who received a diagnosis of ASD by a trained clinician and completed the study, 19 diagnoses were confirmed by a gold-standard evaluation. Caregivers indicated that undergoing diagnosis in their local community rather than an autism specialty center was helpful (4.8/5 on a 5-point Likert scale, n = 19). Results of this study demonstrate that primary care clinicians can be trained to reliably diagnose ASD in children 14 to 48 months with unambiguous symptoms. Diagnosis in the primary care setting may lead to earlier diagnosis and quicker connection to evidence-based therapies and interventions. Given the potential impact of increasing access to high-quality diagnostic services, the role of primary care clinicians in the diagnosis of ASD should be further evaluated.

Exploring the potential of artificial intelligence in improving skin lesion diagnosis in primary care

Dermatological conditions are a relevant health problem. Machine learning (ML) models are increasingly being applied to dermatology as a diagnostic decision support tool using image analysis, especially for skin cancer detection and disease classification. The objective of this study was to perform a prospective validation of an image analysis ML model, which is capable of screening 44 skin diseases, comparing its diagnostic accuracy with that of General Practitioners (GPs) and teledermatology (TD) dermatologists in a real-life setting. Prospective, diagnostic accuracy study including 100 consecutive patients with a skin problem who visited a participating GP in central Catalonia, Spain, between June 2021 and October 2021. The skin issue was first assessed by the GPs. Then an anonymised skin disease picture was taken and uploaded to the ML application, which returned a list with the Top-5 possible diagnosis in order of probability. The same image was then sent to a dermatologist via TD for diagnosis, as per clinical practice. The GPs Top-3, ML model’s Top-5 and dermatologist’s Top-3 assessments were compared to calculate the accuracy, sensitivity, specificity and diagnostic accuracy of the ML models. The overall Top-1 accuracy of the ML model (39%) was lower than that of GPs (64%) and dermatologists (72%). When the analysis was limited to the diagnoses on which the algorithm had been explicitly trained (n = 82), the balanced Top-1 accuracy of the ML model increased (48%) and in the Top-3 (75%) was comparable to the GPs Top-3 accuracy (76%). The Top-5 accuracy of the ML model (89%) was comparable to the dermatologist Top-3 accuracy (90%). For the different diseases, the sensitivity of the model (Top-3 87% and Top-5 96%) is higher than that of the clinicians (Top-3 GPs 76% and Top-3 dermatologists 84%) only in the benign tumour pathology group, being on the other hand the most prevalent category (n = 53). About the satisfaction of professionals, 92% of the GPs considered it as a useful diagnostic support tool (DST) for the differential diagnosis and in 60% of the cases as an aid in the final diagnosis of the skin lesion. The overall diagnostic accuracy of the model in this study, under real-life conditions, is lower than that of both GPs and dermatologists. This result aligns with the findings of few existing prospective studies conducted under real-life conditions. The outcomes emphasize the significance of involving clinicians in the training of the model and the capability of ML models to assist GPs, particularly in differential diagnosis. Nevertheless, external testing in real-life conditions is crucial for data validation and regulation of these AI diagnostic models before they can be used in primary care.

Relative energy deficiency in sport: Diagnosis and management in primary care

Relative energy deficiency in sport (RED-S) describes a syndrome that affects multiple bodily systems and functions in both recreational and elite athletes. It is, fundamentally, an imbalance between energy intake and exercise-related energy expenditure, leading to globally impaired physiological function as a result of low energy availability. RED-S developed from the ‘female athlete triad’, describing a relationship between low energy availability (with or without eating disorder), amenorrhea (menstrual dysfunction) and low bone mineral density; it is now recognised to occur across many other bodily systems and also to occur in males. Given its often subtle presentation and consequences early-on, but potentially devastating consequences further down the line, timely recognition and facilitation of management in primary care is crucial to allow safe return to physical activity and to prevent long-term sequelae.

Genetic Validation of Psoriasis Phenotyping in UK Biobank Supports the Utility of Self-Reported Data and Composite Definitions for Large Genetic and Epidemiological Studies

Genetic Validation of Psoriasis Phenotyping in UK Biobank Supports the Utility of Self-Reported Data and Composite Definitions for Large Genetic and Epidemiological Studies

The impact of rapid antigen detection test (RADT) for group A streptococcus on the antibiotic prescription: an observational study from a primary care setting in Lisbon

Introduction: Acute pharyngitis is a common diagnosis in primary care. Although viruses are the most common aetiology, antibiotic therapy is frequently prescribed. The inappropriate antibiotic prescription should be avoided to prevent antibiotic resistance. Many national and international guidelines recommend testing for group A streptococcus (GAS) before antibiotic treatment when clinical presentation suggests GAS infection. Aim: This study aims to describe the feasibility of the implementation of the rapid antigen detection test (RADT) in a primary care setting and its impact on antibiotic prescription. Secondary goals include the evaluation of possible associations between symptoms and RADT results. Methods: From October 2019 to March 2020, patients presenting with acute pharyngitis at USF do Parque were eligible. A questionnaire was applied to divide the individuals into four different groups (clearly viral, probably viral, diagnostic doubt, and probably bacterial), and to assess the previous intention to prescribe antibiotics. We applied 136 questionnaires and performed 133 RADT. Nursing staff classified the specimen collection process and result from interpretation according to its difficulty. The proportion of antibiotics avoided was estimated as the number of times physicians changed their intended antibiotic prescription following a negative RADT result. Results: Among the tests performed, 97.7% were easy to interpret. Without RADT, 45 patients were going to be prescribed an antibiotic. After the test result, 27 antibiotic prescriptions were avoided. Tonsil hypertrophy, palatal petechiae, and fever increased the odds of a positive RADT result. Cough was associated with a negative RADT result. Conclusions: This study showed that RADT is easy to implement and contributed to appropriate antibiotic prescription. Tonsil hypertrophy, palatal petechiae, and fever were significantly associated with a positive RADT result, and cough was associated with a negative RADT result. Primary care centers would benefit from having RADT available when there is strong suspicion or doubt of bacterial pharyngitis.

Patient factors associated with receipt of psychological and pharmacological treatments among individuals with common mental disorders in a Swedish primary care setting.

Psychological and pharmacological therapies are the recommended first-line treatments for common mental disorders (CMDs) but may not be universally accessible or utilised. To determine the extent to which primary care patients with CMDs receive treatment and the impact of sociodemographic, work-related and clinical factors on treatment receipt. National registers were used to identify all Stockholm County residents aged 19-64 years who had received at least one CMD diagnosis (depression, anxiety, stress-related) in primary care between 2014 and 2018. Individuals were followed from the date of their first observed CMD diagnosis until the end of 2019 to determine treatment receipt. Associations between patient factors and treatment group were examined using multinomial logistic regression. Among 223 271 individuals with CMDs, 30.6% received pharmacotherapy only, 16.5% received psychological therapy only, 43.1% received both and 9.8% had no treatment. The odds of receiving any treatment were lower among males (odds ratio (OR) range = 0.76 to 0.92, 95% CI[minimum, maximum] 0.74 to 0.95), individuals born outside of Sweden (OR range = 0.67 to 0.93, 95% CI[minimum, maximum] 0.65 to 0.99) and those with stress-related disorders only (OR range = 0.21 to 0.51, 95% CI[minimum, maximum] 0.20 to 0.53). Among the patient factors examined, CMD diagnostic group, prior treatment in secondary psychiatric care and age made the largest contributions to the model (R2 difference: 16.05%, 1.72% and 1.61%, respectively). Although over 90% of primary care patients with CMDs received pharmacological and/or psychological therapy, specific patient groups were less likely to receive treatment.

Diagnosis and treatment of infectious vaginitis: Proposal for a new algorithm.

Vaginitis is the most common gynecologic diagnosis in primary care, and most women have at least one episode during their lives. The need for standardized strategies to diagnose and treat vaginitis, both in primary care and among gynecologists, is emphasized. The Brazilian Group for Vaginal Infections (GBIV, acronym in Portuguese) aimed to update the practical approach to affected women by reviewing and discussing recent literature, and developing algorithms for diagnosis and treatment of vaginitis. A literature search within biomedical databases PubMed and SCieLo was conducted in January 2022. The available literature was evaluated by three experienced researchers, members of the GBIV, to summarize the main data and develop practical algorithms. Detailed algorithms were developed with the main goal to improve gynecological practice considering different scenarios and access to diagnostic tools, from the simplest to the most complex tests. Different age groups and specific contexts were also considered. The combination of anamnesis, gynecological examination, and complementary tests remains the basis of a proper diagnostic and therapeutic approach. Periodic updates of these algorithms are warranted as new evidence becomes available.

Pediatric Primary Care Diagnoses Among Children with Intrauterine Opioid Exposure.

Characterizing common concerns for children with intrauterine opioid exposure (IOE) can inform tailored primary care. Retrospective analysis of primary care data of children with IOE from birth to age two years within one multi-state pediatric health system. Well child care (WCC) and problem-based visit diagnoses were categorized, and descriptive statistics were tabulated. Three hundred and eighty-five (385) children with IOE had 3,622 primary care visits, of which 51.4% were WCC and 48.6% were problem-based. Most frequent visit diagnoses were upper respiratory complaints (14.8% of visits), feeding difficulties (12.2%), and perinatal viral exposure (9.8%). Although visit type (WCC vs. problem-based) varied across diagnostic category, frequent utilization of both visit types were documented for several diagnoses in infancy (e.g., fussiness/colic, feeding difficulties). Well child care visits for children with IOE are key opportunities for anticipatory guidance with an emphasis on problems that may contribute to acute health care utilization, particularly in early infancy.

Decoding the role of loratadine in optimally managing and in alleviating the burden of allergic rhinitis

Despite an alarmingly rise in prevalence of allergic rhinitis in the last 2 decades, yet till date it remains underdiagnosed, undertreated, or mistreated in India. The distinguishing features of allergic rhinitis are commonly misinterpreted with the common cold and thus early detection of allergic rhinitis is often delayed in primary care. Poorly controlled allergic rhinitis adversely impairs overall long-term productivity at work or school, quality of life (QoL) and can also trigger underlying comorbidities like asthma. Thus, early diagnosis and timely referral is the need of the hour for more effective management which will reduce the overall burden of allergic rhinitis in India. As allergic rhinitis needs long-term management, it is also paramount to prescribe highly efficacious, cost-effective treatment with minimal side effects like drowsiness to prevent disruption of patient’s QoL. However, current therapies including intranasal corticosteroids have adverse long-term complications and antihistamines like cetirizine, levocetirizine, and fexofenadine have varying degrees of sedation.With these concerns, a management algorithm was developed to aid for early diagnosis in primary care which provides cost effective option of right medication for a proper duration of time to optimize overall patient care. After a thorough discussion of key opinion leaders and evidence-based recommendations, it was highlighted that loratadine deserves to be considered as a first-line antihistamine therapy due to its rapid and long-lasting symptom relief, non drowsy, and low complication rate for long-term management of allergic rhinitis.

Development and validation of a diagnostic model for differentiating tuberculous spondylitis from brucellar spondylitis using machine learning: A retrospective cohort study.

Tuberculous spondylitis (TS) and brucellar spondylitis (BS) are commonly observed in spinal infectious diseases, which are initially caused by bacteremia. BS is easily misdiagnosed as TS, especially in underdeveloped regions of northwestern China with less sensitive medical equipment. Nevertheless, a rapid and reliable diagnostic tool remains to be developed and a clinical diagnostic model to differentiate TS and BS using machine learning algorithms is of great significance. A total of 410 patients were included in this study. Independent factors to predict TS were selected by using the least absolute shrinkage and selection operator (LASSO) regression model, permutation feature importance, and multivariate logistic regression analysis. A TS risk prediction model was developed with six different machine learning algorithms. We used several metrics to evaluate the accuracy, calibration capability, and predictability of these models. The performance of the model with the best predictability was further verified with the area under the curve (AUC) of the receiver operating characteristic (ROC) curve and the calibration curve. The clinical performance of the final model was evaluated by decision curve analysis. Six variables were incorporated in the final model, namely, pain severity, CRP, x-ray intervertebral disc height loss, x-ray endplate sclerosis, CT vertebral destruction, and MRI paravertebral abscess. The analysis of appraising six models revealed that the logistic regression model developed in the current study outperformed other methods in terms of sensitivity (0.88 ± 0.07) and accuracy (0.79 ± 0.07). The AUC of the logistic regression model predicting TS was 0.86 (95% CI, 0.81-0.90) in the training set and 0.86 (95% CI, 0.78-0.92) in the validation set. The decision curve analysis indicated that the logistic regression model displayed a higher clinical efficiency in the differential diagnosis. The logistic regression model developed in this study outperformed other methods. The logistic regression model demonstrated by a calculator exerts good discrimination and calibration capability and could be applicable in differentiating TS from BS in primary health care diagnosis.

Completeness and Representativeness of the PHARMO General Practitioner (GP) Data: A Comparison with National Statistics.

When using incomplete or non-representative real-world data (RWD), bias is more likely to occur. The aim of the current study was to assess the completeness and representativeness of the PHARMO GP data for the Dutch population. A cross-sectional study was performed. The PHARMO GP data comprise data from electronic health records registered by GPs. Data on the Dutch population were obtained from Statistics Netherlands (CBS), which offers publicly available data on several themes. The standardized difference (std.diff) was used to compare proportions between the PHARMO GP population and the Dutch population. An absolute std.diff >0.2 was considered a difference. On January 1st, 2018, 3,466,321 persons were included in the PHARMO GP data (mean age: 41.6 years, 49.7% males). The sex and age distribution was similar to the Dutch population. The PHARMO GP data captured less not urbanized areas compared to the Dutch population (not urbanized areas: 9.4% vs 17.1% [std.diff: -0.23]). Regarding medication use, only the pharmacological subgroups "viral vaccines" and "hormonal contraceptives for systemic use" differed (std.diff >0.2); use in the GP data was more complete than in the Statistics Netherlands (CBS) data. No differences were observed regarding diagnoses. The PHARMO GP data are representative of the Dutch population with regard to the demographic characteristics and diagnoses in primary care. Medication data in the PHARMO GP data are more complete than national statistics, and differences are related to reimbursement. Use of the data and interpretation of results based on these sources should be done with experts on the data sources, the Dutch healthcare system and (pharmaco)epidemiology.