scholarly journals The Incidence and Management of Osgood-Schlatter Disease in General Practice

2021 ◽  
pp. BJGP.2021.0386
Author(s):  
Guido Jan van Leeuwen ◽  
Evelien de Schepper ◽  
Michael Rathleff ◽  
Patrick Bindels ◽  
Sita Bierma-Zeinstra ◽  
...  
Keyword(s):  
General Practice ◽  
Children And Adolescents ◽  
Search Algorithm ◽  
Free Text ◽  
Healthcare Database ◽  
Text Data ◽  
Search Terms ◽  
New Diagnosis ◽  
First Time

Background: Osgood-Schlatter disease (OSD) is a non-traumatic knee problem that primarily observed in sports active children and adolescents between the age of 8 and 15. Aim: The objective of this study was to determine the incidence of OSD and to gain insight into the management of children and adolescents with OSD in general practice. Design and Setting: A retrospective cohort study was conducted using a healthcare database containing full electronic health records of over 200.000 patients in general practice in and around the Dutch city of Rotterdam. Methods: Patients with a new diagnosis of OSD between the years 2012-2018 were extracted using a search algorithm based on International Classification of Primary Health Care (ICPC) coding and search terms in free text. Data on the management of OSD were manually interpreted. Results: The mean incidence over the study period was 3.8 (95% CI 3.5-4.2) per 1000 person years in the age group of 8-19 years. Boys had a higher incidence rate of 4.9 (95% CI 4.3-5.5) compared to girls, at 2.7 (95% CI 2.3-3.2). Peak incidence was at age 12 for boys and at age 11 for girls. Advice was the most commonly applied strategy (55.1%), followed by rest (21.0%) and referral for imaging (19.5%) and physiotherapy (13.4%). Conclusion: For the first time the incidence of OSD is calculated using GP electronic medical files. There is a discrepancy, especially for imaging and referral to a medical specialist, between the current general practice guideline and what GPs actually recommended.

scholarly journals The incidence, prevalence, and management of plantar heel pain in Dutch general practice

2019 ◽  
Vol 69 (suppl 1) ◽  
pp. bjgp19X703217
Author(s):  
Nadine Rasenberg ◽  
Sita MA Bierma-Zeinstra ◽  
Patrick Bindels ◽  
Johan van der Lei ◽  
Marienke Van Middelkoop
Keyword(s):  
Primary Care ◽  
General Practice ◽  
Medical Records ◽  
Search Algorithm ◽  
Heel Pain ◽  
Future Research ◽  
Healthcare Database ◽  
Plantar Heel Pain ◽  
Wait And See ◽  
Multiple Interventions

BackgroundPlantar heel pain (PHP) is a common cause of foot complaints, but information on the occurrence in primary care is scarce.AimThe objective of this study was to determine the incidence and prevalence of PHP and to gain insight in types of treatments provided to patients with PHP in primary care.MethodA cohort study was conducted in a healthcare database containing the electronic general practice medical records of approximately 1.9 million patients throughout the Netherlands. A search algorithm was defined and used to identify cases of PHP in the years 2013–2016. Descriptive statistics were used to obtain the incidence and prevalence of PHP. Data on the management of PHP was extracted in a random sample of 1000 patients.ResultsThe overall incidence of PHP was 3.81 (95% confidence [CI] = 3.75 to 3.87) per 1000 patient years and the overall prevalence of PHP was 0.4374% (95% CI = 0.4369 to 0.4378). Incidence of PHP peaked in the last quarter of every calendar year. The GP applied a wait-and-see policy at the first consultation for PHP in 18.0% of patients. The most commonly applied interventions included prescription for NSAID (19.9%), referral to a paramedical podiatric specialist (19.7%), and advice to wear insoles (16.4%): 34.0% of patients received multiple interventions (range 2–11) and 30.9% had multiple consultations for PHP (range 2–8).ConclusionPHP appears to be common in primary care. Despite a lack of evidence for most treatments, multiple interventions are applied. This urges the need for future research on effectiveness of treatments.

scholarly journals Incorporating natural language processing to improve classification of axial spondyloarthritis using electronic health records

Rheumatology ◽  
2019 ◽  
Vol 59 (5) ◽  
pp. 1059-1065 ◽  
Author(s):  
Sizheng Steven Zhao ◽  
Chuan Hong ◽  
Tianrun Cai ◽  
Chang Xu ◽  
Jie Huang ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Predictive Value ◽  
Area Under The Curve ◽  
Free Text ◽  
Text Data ◽  
Health Records ◽  
Disease Concepts ◽  
Icd Codes ◽  
Electronic Health

Abstract Objectives To develop classification algorithms that accurately identify axial SpA (axSpA) patients in electronic health records, and compare the performance of algorithms incorporating free-text data against approaches using only International Classification of Diseases (ICD) codes. Methods An enriched cohort of 7853 eligible patients was created from electronic health records of two large hospitals using automated searches (⩾1 ICD codes combined with simple text searches). Key disease concepts from free-text data were extracted using NLP and combined with ICD codes to develop algorithms. We created both supervised regression-based algorithms—on a training set of 127 axSpA cases and 423 non-cases—and unsupervised algorithms to identify patients with high probability of having axSpA from the enriched cohort. Their performance was compared against classifications using ICD codes only. Results NLP extracted four disease concepts of high predictive value: ankylosing spondylitis, sacroiliitis, HLA-B27 and spondylitis. The unsupervised algorithm, incorporating both the NLP concept and ICD code for AS, identified the greatest number of patients. By setting the probability threshold to attain 80% positive predictive value, it identified 1509 axSpA patients (mean age 53 years, 71% male). Sensitivity was 0.78, specificity 0.94 and area under the curve 0.93. The two supervised algorithms performed similarly but identified fewer patients. All three outperformed traditional approaches using ICD codes alone (area under the curve 0.80–0.87). Conclusion Algorithms incorporating free-text data can accurately identify axSpA patients in electronic health records. Large cohorts identified using these novel methods offer exciting opportunities for future clinical research.

scholarly journals Describing place through user generated content

First Monday ◽  
2011 ◽  
Author(s):  
Ross Purves ◽  
Alistair Edwardes ◽  
Jo Wood
Keyword(s):  
User Generated Content ◽  
Free Text ◽  
First Time

Geographically referenced user generated content provides us with an opportunity to, for the first time, gather perspectives on place over large areas by exploring how very many people describe information. We present a framework for analysing large collections of user generated content. This involves classification of descriptive terms attached by users to photographs into facets of elements, qualities, and activities. We apply this framework to two contrasting photographic archives — Flickr and Geograph, representing weakly and strongly moderated content respectively. We propose a method for removing user-generated bias from such collections though the user of term profiles that can assess the effect of the most and least prolific contributors to a collection. Analysis and visualization of co–occurrence between terms suggests clear differences in the description of place between the two collections, both in terms of the facets used and their geographical footprints. This is attributed to the role of moderation/editorialising of content; to the role tags and free–text has on descriptive behaviour and on the geographic footprint of content supplied to the two collections.

scholarly journals Basic Study on Automated Extraction of Symptom Related Words from Patient Complaints (Preprint)

2018 ◽  
Author(s):  
Misa Usui ◽  
Eiji Aramaki ◽  
Tomohide Iwao ◽  
Shoko Wakamiya ◽  
Tohru Sakamoto ◽  
...  
Keyword(s):  
Healthcare Workers ◽  
Free Text ◽  
Medication History ◽  
Basic Study ◽  
Text Data ◽  
Medical Institutions ◽  
Classification Of Diseases ◽  
International Statistical Classification ◽  
Target Period

BACKGROUND Although methods of obtaining knowledge from texts written by healthcare professionals such as electronic medical records and discharge summaries have been studied, there are few reports analyzing free-text data on patients’ complaints in Japanese. OBJECTIVE This study aimed to establish a new method for extracting keywords from patients’ free descriptions accumulated in Japanese medical institutions. METHODS We developed a system that automatically annotates free-text data with the codes of the Tenth Revision of the International Statistical Classification of Diseases and Related Health Problems (ICD10) using electronic medication history data (target period: September 1, 2015 to August 31, 2016). The performance of the system was evaluated through comparisons with data manually annotated by healthcare workers. RESULTS The number of ICD10 codes extracted from 5,000 patient statements by healthcare workers was 2,348, while the system extracted 2,236 codes. Of those cases, 1,480 matched. Compared with manual extraction, the performance of the system was 0.66 in terms of precision, 0.63 in recall, and 0.65 for the F-measure. CONCLUSIONS Our results suggested that the system was helpful for extracting and standardizing patient’s words related to symptoms from massive amounts of free-text data instead of manual work. After improving the extraction accuracy, we expect to utilize this system to detect the signals of adverse drug reactions from patients’ statements in the future.

scholarly journals Incidence, prevalence, and management of plantar heel pain: a retrospective cohort study in Dutch primary care

2019 ◽  
Vol 69 (688) ◽  
pp. e801-e808 ◽  
Author(s):  
Nadine Rasenberg ◽  
Sita MA Bierma-Zeinstra ◽  
Patrick J Bindels ◽  
Johan van der Lei ◽  
Marienke van Middelkoop
Keyword(s):  
Primary Care ◽  
General Practice ◽  
Cohort Study ◽  
Search Algorithm ◽  
Treatment Strategies ◽  
Heel Pain ◽  
Healthcare Database ◽  
Plantar Heel Pain ◽  
Conflicting Evidence ◽  
Wait And See

BackgroundPlantar heel pain (PHP) is a common cause of foot complaints in general practice. However, information on the occurrence and practical management is scarce.AimThe aim of this study was to determine the incidence and prevalence of PHP in Dutch primary care and to gain insight into the types of treatments provided to patients with PHP in primary care.Design and settingA cohort study was conducted using a healthcare database containing the electronic general practice medical records of approximately 1.9 million patients throughout the Netherlands.MethodA search algorithm was defined and used to identify cases of PHP from January 2013 to December 2016. Descriptive statistics were used to obtain the incidence and prevalence. Data on the management of PHP were manually validated in a random sample of 1000 patients.ResultsThe overall incidence of PHP was 3.83 cases (95% confidence interval [CI] = 3.77 to 3.89) per 1000 patient-years, the incidence in females was 4.64 (95% CI = 4.55 to 4.72), and 2.98 (95% CI = 2.91 to 3.05) in males. The overall prevalence of PHP was 0.4374% (95% CI = 0.4369 to 0.4378%). Incidence of PHP peaked in September and October of each calendar year. The most commonly applied strategies were a wait-and-see policy (18.0%, n = 168), use of non-steroidal anti-inflammatory drugs (NSAIDs) (19.9%, n = 186), referral to a paramedical podiatric specialist (19.7%, n = 184), and advice to wear insoles (16.4%, n = 153). Treatment strategies varied greatly among GPs.ConclusionThere was large variation in treatment strategies of GPs for patients with PHP. GPs should be aware of conflicting evidence for interventions, such as insoles, and focus more on exercises for which there is evidence for effectiveness.

A Numerically Coded File of Operative Procedures Derived from a Free Text Data Collection System : A Measure of the Accuracy

1976 ◽  
Vol 15 (01) ◽  
pp. 21-28 ◽  
Author(s):  
Carmen A. Scudiero ◽  
Ruth L. Wong
Keyword(s):  
Data Collection ◽  
Pap Smear ◽  
Operative Procedures ◽  
Free Text ◽  
Collection System ◽  
Process Data ◽  
Text Data ◽  
Data Collection System ◽  
History Of ◽  
Correlation System

A free text data collection system has been developed at the University of Illinois utilizing single word, syntax free dictionary lookup to process data for retrieval. The source document for the system is the Surgical Pathology Request and Report form. To date 12,653 documents have been entered into the system.The free text data was used to create an IRS (Information Retrieval System) database. A program to interrogate this database has been developed to numerically coded operative procedures. A total of 16,519 procedures records were generated. One and nine tenths percent of the procedures could not be fitted into any procedures category; 6.1% could not be specifically coded, while 92% were coded into specific categories. A system of PL/1 programs has been developed to facilitate manual editing of these records, which can be performed in a reasonable length of time (1 week). This manual check reveals that these 92% were coded with precision = 0.931 and recall = 0.924. Correction of the readily correctable errors could improve these figures to precision = 0.977 and recall = 0.987. Syntax errors were relatively unimportant in the overall coding process, but did introduce significant error in some categories, such as when right-left-bilateral distinction was attempted.The coded file that has been constructed will be used as an input file to a gynecological disease/PAP smear correlation system. The outputs of this system will include retrospective information on the natural history of selected diseases and a patient log providing information to the clinician on patient follow-up.Thus a free text data collection system can be utilized to produce numerically coded files of reasonable accuracy. Further, these files can be used as a source of useful information both for the clinician and for the medical researcher.

СОЦИАЛЬНАЯ КОНФЛИКТОЛОГИЯ: ТЕОРЕТИКО-ИСТОРИЧЕСКИЙ АСПЕКТ

2020 ◽  
Vol 15 (2) ◽  
pp. 68
Author(s):  
А. Н. Сухов
Keyword(s):  
Theory And Practice ◽  
Important Task ◽  
Social Conflicts ◽  
Psychological Approach ◽  
Structure Dynamics ◽  
History Of ◽  
The Subject ◽  
First Time

This given article reveals the topicality not only of destructive, but also of constructive, as well as hybrid conflicts. Practically it has been done for the first time. It also describes the history of the formation of both foreign and domestic social conflictology. At the same time, the chronology of the development of the latter is restored and presented objectively, in full, taking into account the contribution of those researchers who actually stood at its origins. The article deals with the essence of the socio-psychological approach to understanding conflicts. The subject of social conflictology includes the regularities of their occurrence and manifestation at various levels, spheres and conditions, including normal, complicated and extreme ones. Social conflictology includes the theory and practice of diagnosing, resolving, and resolving social conflicts. It analyzes the difficulties that occur in defining the concept, structure, dynamics, and classification of social conflicts. Therefore, it is no accident that the most important task is to create a full-fledged theory of social conflicts. Without this, it is impossible to talk about effective settlement and resolution of social conflicts. Social conflictology is an integral part of conflictology. There is still a lot of work to be done, both in theory and in application, for its complete design. At present, there is an urgent need to develop conflict-related competence not only of professionals, but also for various groups of the population.

scholarly journals Morphological and Ultrastructural Characterization of Hemocytes in an Insect Model, the Hematophagous Dipetalogaster maxima (Hemiptera: Reduviidae)

Insects ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 640
Author(s):  
Natalia R. Moyetta ◽  
Fabián O. Ramos ◽  
Jimena Leyria ◽  
Lilián E. Canavoso ◽  
Leonardo L. Fruttero
Keyword(s):  
Cell Biology ◽  
Cell Types ◽  
Transmission Electron ◽  
Ultrastructural Characterization ◽  
Current Classification ◽  
Contrast Microscopy ◽  
First Time ◽  
Controversial Aspect

Hemocytes, the cells present in the hemolymph of insects and other invertebrates, perform several physiological functions, including innate immunity. The current classification of hemocyte types is based mostly on morphological features; however, divergences have emerged among specialists in triatomines, the insect vectors of Chagas’ disease (Hemiptera: Reduviidae). Here, we have combined technical approaches in order to characterize the hemocytes from fifth instar nymphs of the triatomine Dipetalogaster maxima. Moreover, in this work we describe, for the first time, the ultrastructural features of D. maxima hemocytes. Using phase contrast microscopy of fresh preparations, five hemocyte populations were identified and further characterized by immunofluorescence, flow cytometry and transmission electron microscopy. The plasmatocytes and the granulocytes were the most abundant cell types, although prohemocytes, adipohemocytes and oenocytes were also found. This work sheds light on a controversial aspect of triatomine cell biology and physiology setting the basis for future in-depth studies directed to address hemocyte classification using non-microscopy-based markers.

scholarly journals Insufficient classification of anaemia in general practice: a Danish register-based observational study

2021 ◽  
pp. 1-9
Author(s):  
Astrid Boennelykke ◽  
Henry Jensen ◽  
Lene Sofie Granfeldt Østgård ◽  
Alina Zalounina Falborg ◽  
Kaj Sparle Christensen ◽  
...  
Keyword(s):  
General Practice ◽  
Observational Study

scholarly journals Predicting adult neuroscience intensive care unit admission from emergency department triage using a retrospective, tabular-free text machine learning approach

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eyal Klang ◽  
Benjamin R. Kummer ◽  
Neha S. Dangayach ◽  
Amy Zhong ◽  
M. Arash Kia ◽  
...  
Keyword(s):  
Machine Learning ◽  
Intensive Care Unit ◽  
Emergency Department ◽  
Intensive Care ◽  
Learning Model ◽  
Free Text ◽  
Combined Model ◽  
Text Data ◽  
Machine Learning Model ◽  
Record Data

AbstractEarly admission to the neurosciences intensive care unit (NSICU) is associated with improved patient outcomes. Natural language processing offers new possibilities for mining free text in electronic health record data. We sought to develop a machine learning model using both tabular and free text data to identify patients requiring NSICU admission shortly after arrival to the emergency department (ED). We conducted a single-center, retrospective cohort study of adult patients at the Mount Sinai Hospital, an academic medical center in New York City. All patients presenting to our institutional ED between January 2014 and December 2018 were included. Structured (tabular) demographic, clinical, bed movement record data, and free text data from triage notes were extracted from our institutional data warehouse. A machine learning model was trained to predict likelihood of NSICU admission at 30 min from arrival to the ED. We identified 412,858 patients presenting to the ED over the study period, of whom 1900 (0.5%) were admitted to the NSICU. The daily median number of ED presentations was 231 (IQR 200–256) and the median time from ED presentation to the decision for NSICU admission was 169 min (IQR 80–324). A model trained only with text data had an area under the receiver-operating curve (AUC) of 0.90 (95% confidence interval (CI) 0.87–0.91). A structured data-only model had an AUC of 0.92 (95% CI 0.91–0.94). A combined model trained on structured and text data had an AUC of 0.93 (95% CI 0.92–0.95). At a false positive rate of 1:100 (99% specificity), the combined model was 58% sensitive for identifying NSICU admission. A machine learning model using structured and free text data can predict NSICU admission soon after ED arrival. This may potentially improve ED and NSICU resource allocation. Further studies should validate our findings.

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