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Introduction: As no standard case definitions for respiratory syncytial virus—associated lower respiratory tract disease (RSV-LRTD) in adults are available, this study analyzed definitions for severe RSV-LRTD from previously published data in hospital and community cohorts of adults with RSV–associated symptoms. Methods: The frequency, sensitivity, and specificity of acute respiratory disease symptoms among hospitalized and community cohorts of adults with RSV were analyzed. RSV-LRTD signs/symptoms assessed included shortness of breath (dyspnea), cough and/or fever, wheezing/rales/rhonchi (abnormal lung sounds by auscultation), sputum production, tachypnea, hypoxemia, and pleuritic chest pain. Results: Dyspnea and tachypnea provided the best differentiation between hospitalized and community RSV-positive cases. The severe RSV-LRTD case definition yielding one of the highest and best-balanced sensitivity and specificity was dyspnea paired with either abnormal lung sounds by auscultation, hypoxemia, tachypnea, cough and/or fever, sputum, or chest pain. Conclusions: Dyspnea alone, and in combination with certain other lower respiratory tract disease signs/symptoms, was a leading symptomatic indicator for severe RSV outcomes. These results contribute to the harmonization of case definitions for RSV disease. [ABSTRACT FROM AUTHOR]

Several websites have offered patients opportunities to find out whether they meet the case definitions for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). The current study describes a new online screener that can be completed by individuals who might like to determine if they meet the current ME/CFS criteria. The website is available for anyone to use, and the feedback is more comprehensive than other site, particularly in providing data on how the participants’ data compares with a large ME/CFS patient population, as well as whether the current ME and ME/CFS case definitions are met.

Several websites have offered patients opportunities to find out whether they meet the case definitions for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). The current study describes a new online screener that can be completed by individuals who might like to determine if they meet the current ME/CFS criteria. The website is available for anyone to use, and the feedback is more comprehensive than other site, particularly in providing data on how the participants' data compares with a large ME/CFS patient population, as well as whether the current ME and ME/CFS case definitions are met. [ABSTRACT FROM AUTHOR]

Little is known about shifts in the fecal microbiome of dairy calves preceding and following the incidence of gastrointestinal disease. The objective of this cohort study was to describe the fecal microbiome of preweaned dairy calves before, during, and after gastrointestinal disease. A total of 111 Holstein dairy calves were enrolled on 2 dairies (D1 and D2) and followed until 5 weeks old. Health assessments were performed weekly and fecal samples were collected every other week. Of the 111 calves, 12 calves from D1 and 12 calves from D2 were retrospectively defined as healthy, and 7 calves from D1 and 11 calves from D2 were defined as diarrheic. Samples from these calves were sequenced targeting the 16S rRNA gene and compared based on health status within age groups and farms: healthy (0-1 week old) vs. pre-diarrheic (0-1 week old), healthy (2-3 weeks old) vs. diarrheic (2-3 weeks old), and healthy (4-5 weeks old) vs. post-diarrheic (4-5 weeks old) calves. Healthy and diarrheic samples clustered together based on age rather than health status on both farms. Based on linear discriminant analysis, a few species were identified to be differently enriched when comparing health status within age groups and farm. Among them, Bifidobacterium sp. was differently enriched in pre-diarrheic calves at D1 (0-1 week old) whereas healthy calves of the same age group and farm showed a higher abundance of Escherichia coli. Bifidobacterium sp. was identified as a biomarker of fecal samples from healthy calves (2-3 weeks old) on D1 when compared with diarrheic calves of the same age group and farm. Feces from diarrheic calves on D2 (2-3 weeks old) were characterized by taxa from Peptostreptococcus and Anaerovibrio genera whereas fecal samples of age-matched healthy calves were characterized by Collinsella aerofaciens and Bifidobacterium longum. After resolution of uncomplicated diarrhea (4-5 weeks old), Collinsella aerofaciens was more abundant in D2 calves whereas Bacteriodes uniformis was more abundant in D1 calves. Taken together, these findings suggest that the age of the preweaned calf is the major driver of changes to fecal microbiome composition and diversity even in the face of uncomplicated gastrointestinal disease. [ABSTRACT FROM AUTHOR]

Introduction: This study compared two previously validated sensitive and specific diabetes case definitions to explore the impact of different classification methods in Ontario ICES administrative data. Methods: This study included patients captured by the Ontario Diabetes Database with type 2 diabetes using either the sensitive cohort definition (≥ 2 physician visits for diabetes within 1 year or ≥ 1 drug claim for diabetes or ≥ 1 hospitalization with diabetes), or the specific cohort definition (≥ 3 physician visits for diabetes within 1 year), between October 1, 2013 to September 30, 2015. Each cohort's demographic and clinical features were described using descriptive analysis. Results: Using sensitive and specific definitions, 1,093,812 and 783,228 patients with type 2 diabetes were identified, respectively. Overall, the demographic and clinical characteristics were similar between cohorts. Patients in the sensitive cohort had mean age of 64.1 years and were 52.4% male, compared to 64.8 years and 53.6% male in the specific cohort. In the sensitive and specific cohorts respectively, 64.4% and 55.7% of patients reported one-year mean HbA1c of < 7% (53 mmol/mol) and 25.3% and 31.5% reported levels between 7.0–8.5% (53–69 mmol/mol). Conclusions: Although sample sizes were different between sensitive and specific cohorts, demographic and clinical characteristics were similar. [ABSTRACT FROM AUTHOR]

BackgroundPublic health newborn screening (NBS) programs continuously evolve, taking advantage of international shared learning. NBS for severe combined immunodeficiency (SCID) has recently been introduced in many countries. However, comparison of screening outcomes has been hampered by use of disparate terminology and imprecise or variable case definitions for non-SCID conditions with T-cell lymphopenia.ObjectivesThis study sought to determine whether standardized screening terminology could overcome a Babylonian confusion and whether improved case definitions would promote international exchange of knowledge.MethodsA systematic literature review highlighted the diverse terminology in SCID NBS programs internationally. While, as expected, individual screening strategies and tests were tailored to each program, we found uniform terminology to be lacking in definitions of disease targets, sensitivity, and specificity required for comparisons across programs.ResultsThe study's recommendations reflect current evidence from literature and existing guidelines coupled with opinion of experts in public health screening and immunology. Terminologies were aligned. The distinction between actionable and nonactionable T-cell lymphopenia among non-SCID cases was clarified, the former being infants with T-cell lymphopenia who could benefit from interventions such as protection from infections, antibiotic prophylaxis, and live-attenuated vaccine avoidance.ConclusionsBy bringing together the previously unconnected public health screening community and clinical immunology community, these SCID NBS deliberations bridged the gaps in language and perspective between these disciplines. This study proposes that international specialists in each disorder for which NBS is performed join forces to hone their definitions and recommend uniform registration of outcomes of NBS. Standardization of terminology will promote international exchange of knowledge and optimize each phase of NBS and follow-up care, advancing health outcomes for children worldwide.

Little is known about shifts in the fecal microbiome of dairy calves preceding and following the incidence of gastrointestinal disease. The objective of this cohort study was to describe the fecal microbiome of preweaned dairy calves before, during, and after gastrointestinal disease. A total of 111 Holstein dairy calves were enrolled on 2 dairies (D1 and D2) and followed until 5 weeks old. Health assessments were performed weekly and fecal samples were collected every other week. Of the 111 calves, 12 calves from D1 and 12 calves from D2 were retrospectively defined as healthy, and 7 calves from D1 and 11 calves from D2 were defined as diarrheic. Samples from these calves were sequenced targeting the 16S rRNA gene and compared based on health status within age groups and farms: healthy (0–1 week old) vs. pre-diarrheic (0–1 week old), healthy (2–3 weeks old) vs. diarrheic (2–3 weeks old), and healthy (4–5 weeks old) vs. post-diarrheic (4–5 weeks old) calves. Healthy and diarrheic samples clustered together based on age rather than health status on both farms. Based on linear discriminant analysis, a few species were identified to be differently enriched when comparing health status within age groups and farm. Among them, Bifidobacterium sp. was differently enriched in pre-diarrheic calves at D1 (0–1 week old) whereas healthy calves of the same age group and farm showed a higher abundance of Escherichia coli. Bifidobacterium sp. was identified as a biomarker of fecal samples from healthy calves (2–3 weeks old) on D1 when compared with diarrheic calves of the same age group and farm. Feces from diarrheic calves on D2 (2–3 weeks old) were characterized by taxa from Peptostreptococcus and Anaerovibrio genera whereas fecal samples of age-matched healthy calves were characterized by Collinsella aerofaciens and Bifidobacterium longum. After resolution of uncomplicated diarrhea (4–5 weeks old), Collinsella aerofaciens was more abundant in D2 calves whereas Bacteriodes uniformis was more abundant in D1 calves. Taken together, these findings suggest that the age of the preweaned calf is the major driver of changes to fecal microbiome composition and diversity even in the face of uncomplicated gastrointestinal disease.

Several criteria exist to diagnose pulmonary aspergillosis with varying degrees of certainty in specific populations, including oncohaematological patients (EORTC/MSG), ICU patients (mAspICU) and COVID-19 patients (ECMM). At the beginning of the pandemic, however, the diagnosis of COVID-19-Associated Pulmonary Aspergillosis (CAPA) could not be performed easily, and the decision to treat (DTT) was empirical. In this cross-sectional retrospective study including patients with SARS-CoV-2 infection and suspicion of CAPA, we studied the concordance between the DTT and the three diagnostic criteria using Cohen's coefficient, and then we identified the factors associated with the DTT and corrected them by treatment to study the influence of the diagnostic criteria on survival. We showed good concordance of the DTT and mAspICU and ECMM criteria, with "compatible signs", "positive culture" and "positive galactomannan" influencing the DTT. Treatment also showed a positive effect on survival once corrected for a putative, possible or probable diagnosis of CAPA using mAspICU and ECMM criteria. We conclude that EORTC/MSGERC are not considered applicable in clinical practice due to the lack of inclusion of signs and symptoms and do not lead to improved survival. mAspICU and ECMM criteria showed a good degree of agreement with the DTT and a positive correlation with patient recovery. [ABSTRACT FROM AUTHOR]

We aimed to identify predictors of confirmed monkeypox (mpox) among people with mpox-like illness and to develop a multivariable model for confirmed mpox. We performed an observational study using national epidemiologic surveillance data in Mexico from May to November 2022. People with mpox-like illness were reported to the Mexican Ministry of Health and real-time polymerase chain reaction was performed in clinical samples to confirm mpox. Sociodemographic and clinical data were collected with a case report form. We performed univariable logistic regressions to estimate the predictive capability of individual characteristics, reported with ORs and 95% CIs. Variables of interest were included in multivariable logistic regression models and Akaike information criterion was used to retain variables for the final model. Discrimination and calibration of the model were estimated in bootstrap resamples. A total of 5078 people were reported with mpox-like illness. Of 5078 people, 3291 (64.8%) had confirmed mpox. The strongest clinical predictors of confirmed mpox in univariable models were proctitis (OR 6.54, 5.93–7.21), inguinal adenopathy (OR 5.91, 5.36–6.52), and anogenital lesions (OR 5.45, 4.94–6.02). The final model included being a man who has sex with men (8.75, 7.37–10.38), HIV diagnosis (3.04, 2.51–3.69), inguinal adenopathy (2.24, 1.81–2.77), anogenital lesions (2.32, 1.97–2.74), and pustules (1.55, 1.32–1.81). Discrimination capability was excellent (c-statistic 0.88, 95% CI 0.87–0.89) and it was well calibrated (calibration slope 1, 95% CI 0.95–1.05). A third of people with mpox-like illness do not have mpox. Factors such as being a man who has sex with men, HIV diagnosis, inguinal adenopathy, pustules, and anogenital lesions are associated with confirmed mpox. [ABSTRACT FROM AUTHOR]

Point-of-care antigen tests are an important tool for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection, yet are less clinically sensitive than real-time reverse-transcription polymerase chain reaction (RT-PCR), affecting their efficacy as screening procedures. Our goal in this analysis was to see whether we could improve this sensitivity by considering antigen test results in combination with other relevant information, namely exposure status and reported symptoms. In November 2020, we collected 3,419 paired upper respiratory specimens tested by RT-PCR and the Abbott BinaxNOW (Abbott Laboratories, Abbott Park, Illinois) antigen test at 2 community testing sites in Pima County, Arizona. We used symptom, exposure, and antigen-testing data to evaluate the sensitivity and specificity of various symptom definitions in predicting RT-PCR positivity. Our analysis yielded 6 novel multisymptom case definitions with and without antigen test results, the best of which overall achieved a Youden's J index of 0.66, as compared with 0.53 for antigen testing alone. Using a random forest as a guide, we show that this definition, along with our others, does not lose the ability to generalize well to new data despite achieving optimal performance in our sample. Our methodology is broadly applicable, and our code is publicly available to aid public health practitioners in developing or fine-tuning their own case definitions. [ABSTRACT FROM AUTHOR]

Several criteria exist to diagnose pulmonary aspergillosis with varying degrees of certainty in specific populations, including oncohaematological patients (EORTC/MSG), ICU patients (mAspICU) and COVID-19 patients (ECMM). At the beginning of the pandemic, however, the diagnosis of COVID-19-Associated Pulmonary Aspergillosis (CAPA) could not be performed easily, and the decision to treat (DTT) was empirical. In this cross-sectional retrospective study including patients with SARS-CoV-2 infection and suspicion of CAPA, we studied the concordance between the DTT and the three diagnostic criteria using Cohen’s coefficient, and then we identified the factors associated with the DTT and corrected them by treatment to study the influence of the diagnostic criteria on survival. We showed good concordance of the DTT and mAspICU and ECMM criteria, with “compatible signs”, “positive culture” and “positive galactomannan” influencing the DTT. Treatment also showed a positive effect on survival once corrected for a putative, possible or probable diagnosis of CAPA using mAspICU and ECMM criteria. We conclude that EORTC/MSGERC are not considered applicable in clinical practice due to the lack of inclusion of signs and symptoms and do not lead to improved survival. mAspICU and ECMM criteria showed a good degree of agreement with the DTT and a positive correlation with patient recovery.

ObjectivesCase Reporting and Surveillance (CRS) are crucial to combat the global spread of the Monkeypox virus (Mpox). To support CRS, the World Health Organization (WHO) has released standardized case definitions for suspected, probable, confirmed, and discarded cases. However, these definitions are often subject to localized adaptations by countries leading to heterogeneity in the collected data. Herein, we compared the differences in Mpox case definitions in 32 countries that collectively reported 96% of the global Mpox caseload.MethodsWe extracted information regarding Mpox case definitions issued by the competent authorities in 32 included countries for suspected, probable, confirmed, and discarded cases. All data were gathered from online public sources.ResultsFor confirmed cases, 18 countries (56%) followed WHO guidelines and tested for Mpox using species specific PCR and/or sequencing. For probable and suspected cases, seven and eight countries, respectively were found to have not released definitions in their national documentations. Furthermore, none of the countries completely matched WHO’s criteria for probable and suspected cases. Overlapping amalgamations of the criteria were frequently noticed. Regarding discarded cases, only 13 countries (41%) reported definitions, with only two countries (6%) having definition consistent with WHO guidelines. For case reporting, 12 countries (38%) were found to report both probable and confirmed cases, in line with WHO requirements.ConclusionThe heterogeneity in case definitions and reporting highlights the pressing need for homogenization in implementation of these guidelines. Homogenization would drastically improve data quality and aid data-scientists, epidemiologists, and clinicians to better understand and model the true disease burden in the society, followed by formulation and implementation of targeted interventions to curb the virus spread.

Abstract Introduction: In May 2020, The Communicable Diseases Network of Australia (CDNA) case definition introduced serological criteria to support the diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). We present findings that support the utility of SARS‐CoV‐2‐specific serology for public health investigations. Methods: From 24 January to 31 July 2020, the following information was collected from individuals with positive SARS‐CoV‐2‐specific immunofluorescence antibody tests: history of contact with COVID‐19 cases; recent travel; symptoms consistent with COVID‐19; and SARS‐CoV‐2 nucleic acid testing (NAT) results. Individuals were classified as confirmed or probable by CDNA criteria or additionally as possible (SARS‐CoV‐2‐specific IgG positive with compatible symptoms or epidemiologic risk) or indeterminate (SARS‐CoV‐2‐specific IgA/IgM positive only) cases. Results: A total of 10,595 individuals were tested in the six‐month period. Of these, 9.8% (1,037) individuals had positive SARS‐CoV‐2‐specific serology of which 566 (53.6%) were NAT‐confirmed COVID‐19 cases and 286 (27.6%) were part of a cruise ship outbreak sero‐survey. The remaining 185 individuals (NAT negative) were individually classified as serologically confirmed (4, 0.4%), probable (72, 6.9%) possible (66, 6.4%) and indeterminate (38, 3.7%) cases. Maternal antibody transfer was inferred in one infant and four were unclassified. Conclusion: SARS‐CoV‐2‐specific serology is a key diagnostic tool for retrospective identification of COVID‐19 infection. Implications for public health: SARS‐CoV‐2 specific serology can enhance the ability to find cases, link missing cases in clusters of infection and identify the epidemiological extent of SARS‐CoV‐2 outbreaks. A combination of epidemiological criteria, clinical criteria and a quantitative serological test can be used as an adjunct to classify SARS‐CoV‐2 cases. Our study confirms the low level of community transmission in NSW during the first year of the COVID‐19 pandemic

Introduction: Case definitions are used to guide clinical practice, surveillance and research protocols. However, how they identify COVID‐19‐hospitalised patients is not fully understood. We analysed the proportion of hospitalised patients with laboratory‐confirmed COVID‐19, in the ISARIC prospective cohort study database, meeting widely used case definitions. Methods: Patients were assessed using the Centers for Disease Control (CDC), European Centre for Disease Prevention and Control (ECDC), World Health Organization (WHO) and UK Health Security Agency (UKHSA) case definitions by age, region and time. Case fatality ratios (CFRs) and symptoms of those who did and who did not meet the case definitions were evaluated. Patients with incomplete data and non‐laboratory‐confirmed test result were excluded. Results: A total of 263,218 of the patients (42%) in the ISARIC database were included. Most patients (90.4%) were from Europe and Central Asia. The proportions of patients meeting the case definitions were 56.8% (WHO), 74.4% (UKHSA), 81.6% (ECDC) and 82.3% (CDC). For each case definition, patients at the extremes of age distribution met the criteria less frequently than those aged 30 to 70 years; geographical and time variations were also observed. Estimated CFRs were similar for the patients who met the case definitions. However, when more patients did not meet the case definition, the CFR increased. Conclusions: The performance of case definitions might be different in different regions and may change over time. Similarly concerning is the fact that older patients often did not meet case definitions, risking delayed medical care. While epidemiologists must balance their analytics with field applicability, ongoing revision of case definitions is necessary to improve patient care through early diagnosis and limit potential nosocomial spread. [ABSTRACT FROM AUTHOR]

Abstract Background Automated Emergency Department syndromic surveillance systems (ED-SyS) are useful tools in routine surveillance activities and during mass gathering events to rapidly detect public health threats. To improve the existing surveillance infrastructure in a lower-resourced rural/remote setting and enhance monitoring during an upcoming mass gathering event, an automated low-cost and low-resources ED-SyS was developed and validated in Yukon, Canada. Methods Syndromes of interest were identified in consultation with the local public health authorities. For each syndrome, case definitions were developed using published resources and expert elicitation. Natural language processing algorithms were then written using Stata LP 15.1 (Texas, USA) to detect syndromic cases from three different fields (e.g., triage notes; chief complaint; discharge diagnosis), comprising of free-text and standardized codes. Validation was conducted using data from 19,082 visits between October 1, 2018 to April 30, 2019. The National Ambulatory Care Reporting System (NACRS) records were used as a reference for the inclusion of International Classification of Disease, 10th edition (ICD-10) diagnosis codes. The automatic identification of cases was then manually validated by two raters and results were used to calculate positive predicted values for each syndrome and identify improvements to the detection algorithms. Results A daily secure file transfer of Yukon’s Meditech ED-Tracker system data and an aberration detection plan was set up. A total of six syndromes were originally identified for the syndromic surveillance system (e.g., Gastrointestinal, Influenza-like-Illness, Mumps, Neurological Infections, Rash, Respiratory), with an additional syndrome added to assist in detecting potential cases of COVID-19. The positive predictive value for the automated detection of each syndrome ranged from 48.8–89.5% to 62.5–94.1% after implementing improvements identified during validation. As expected, no records were flagged for COVID-19 from our validation dataset. Conclusions The development and validation of automated ED-SyS in lower-resourced settings can be achieved without sophisticated platforms, intensive resources, time or costs. Validation is an important step for measuring the accuracy of syndromic surveillance, and ensuring it performs adequately in a local context. The use of three different fields and integration of both free-text and structured fields improved case detection.

Objectives Validation of algorithms to identify health conditions (e.g., diabetes) or service use (e.g., high-cost users) in administrative data is time-consuming and expensive. Many algorithms are only assessed in a single jurisdiction, which may limit generalizability. Our study described the characteristics of multi-jurisdiction algorithms from a Canadian algorithm repository. Approach We summarized algorithms captured in the open-access Algorithms Inventory developed by Health Data Research Network (HDRN) Canada. This inventory contains published algorithms identified through a series of systematic reviews of peer-reviewed research. Algorithms included in the inventory were validated or assessed for feasibility of implementation in two or more provinces/territories; they encompass measures of population health, health service use, and determinants of health. Descriptive statistics were used to characterize the study data on such features as year and discipline of the study journal, algorithm topic area, jurisdictions included in the study, validation source data, and algorithm elements (i.e., diagnosis codes). Results The HDRN Canada Algorithms Inventory currently contains 166 algorithms from 63 published articles. The majority of articles were published in 2010 or later (89%) and more than half (56%) of the articles were found in journals with a clinical focus. Feasibility studies (79%) were conducted more often than validation studies (21%). Most algorithms used data from the provinces of British Columbia, Manitoba, Ontario, and Nova Scotia. The majority of algorithms (72%) measured population health concepts, such as chronic physical health conditions (63%; e.g., hypertension) and mental health conditions (14%; e.g., depression). Algorithms about the determinants of health (17%) mostly focused on measures of socioeconomic status (37%) derived from census data. Multi-jurisdiction algorithms about health service use were least common (11%). Conclusion This synthesis revealed few Canadian multi-jurisdiction validation studies have been conducted and not all provinces/territories are equally represented. New validation studies, particularly about health service use and determinants of health, will increase the consistency and accuracy of Canadian research. Reusing published algorithms from this inventory will facilitate research reproducibility.

Background: Automated Emergency Department syndromic surveillance systems (ED-SyS) are useful tools in routine surveillance activities and during mass gathering events to rapidly detect public health threats. To improve the existing surveillance infrastructure in a lower-resourced rural/remote setting and enhance monitoring during an upcoming mass gathering event, an automated low-cost and low-resources ED-SyS was developed and validated in Yukon, Canada.Methods: Syndromes of interest were identified in consultation with the local public health authorities. For each syndrome, case definitions were developed using published resources and expert elicitation. Natural language processing algorithms were then written using Stata LP 15.1 (Texas, USA) to detect syndromic cases from three different fields (e.g., triage notes; chief complaint; discharge diagnosis), comprising of free-text and standardized codes. Validation was conducted using data from 19,082 visits between October 1, 2018 to April 30, 2019. The National Ambulatory Care Reporting System (NACRS) records were used as a reference for the inclusion of International Classification of Disease, 10th edition (ICD-10) diagnosis codes. The automatic identification of cases was then manually validated by two raters and results were used to calculate positive predicted values for each syndrome and identify improvements to the detection algorithms.Results: A daily secure file transfer of Yukon's Meditech ED-Tracker system data and an aberration detection plan was set up. A total of six syndromes were originally identified for the syndromic surveillance system (e.g., Gastrointestinal, Influenza-like-Illness, Mumps, Neurological Infections, Rash, Respiratory), with an additional syndrome added to assist in detecting potential cases of COVID-19. The positive predictive value for the automated detection of each syndrome ranged from 48.8-89.5% to 62.5-94.1% after implementing improvements identified during validation. As expected, no records were flagged for COVID-19 from our validation dataset.Conclusions: The development and validation of automated ED-SyS in lower-resourced settings can be achieved without sophisticated platforms, intensive resources, time or costs. Validation is an important step for measuring the accuracy of syndromic surveillance, and ensuring it performs adequately in a local context. The use of three different fields and integration of both free-text and structured fields improved case detection. [ABSTRACT FROM AUTHOR]

Objective: To determine the clinical presentations and disease outcomes of suspected and confirmed cases of leptospirosis from 3 high endemic districts of Sri Lanka, during outbreaks reported between 2013 and 2017. Methods: The retrospective multi-center study was carried out during 2013-2017 in 5 selected hospitals representing 3 high endemic districts in Sri Lanka. Clinically suspected leptospirosis patients were recruited according to the Communicable Disease Epidemiology Profile Sri Lanka, WHO. Leptospirosis was confirmed by either single microscopic agglutination test titre 1: 400 or by positive polymerase chain reaction (PCR) test result. Results: Out of 372 clinically suspected cases, 29.00% were confirmed as leptospirosis cases by either microscopic agglutination test (50.00%) or positive polymerase chain reaction (52.77%) and 12.90% were presumptively identified as leptospirosis. Clinical symptoms (headache, vomiting, jaundice and dyspnoea) and variations in haematological parameters (haemoglobin, platelet count) and biochemical parameters (serum creatinine, serum urea, serum bilirubin and C-reactive protein) were associated with confirmed leptospirosis (P

Abstract Background Because the collection of mental health information through interviews is expensive and time consuming, interest in using population-based administrative health data to conduct research on depression has increased. However, there is concern that misclassification of disease diagnosis in the underlying data might bias the results. Our objective was to determine the validity of International Classification of Disease (ICD)-9 and ICD-10 administrative health data case definitions for depression using review of family physician (FP) charts as the reference standard. Methods Trained chart reviewers reviewed 3362 randomly selected charts from years 2001 and 2004 at 64 FP clinics in Alberta (AB) and British Columbia (BC), Canada. Depression was defined as presence of either: 1) documentation of major depressive episode, or 2) documentation of specific antidepressant medication prescription plus recorded depressed mood. The charts were linked to administrative data (hospital discharge abstracts and physician claims data) using personal health numbers. Validity indices were estimated for six administrative data definitions of depression using three years of administrative data. Results Depression prevalence by chart review was 15.9–19.2% depending on year, region, and province. An ICD administrative data definition of ‘2 depression claims with depression ICD codes within a one-year window OR 1 discharge abstract data (DAD) depression diagnosis’ had the highest overall validity, with estimates being 61.4% for sensitivity, 94.3% for specificity, 69.7% for positive predictive value, and 92.0% for negative predictive value. Stratification of the validity parameters for this case definition showed that sensitivity was fairly consistent across groups, however the positive predictive value was significantly higher in 2004 data compared to 2001 data (78.8 and 59.6%, respectively), and in AB data compared to BC data (79.8 and 61.7%, respectively). Conclusions Sensitivity of the case definition is often moderate, and specificity is often high, possibly due to undercoding of depression. Limitations to this study include the use of FP charts data as the reference standard, given the potential for missed or incorrect depression diagnoses. These results suggest that that administrative data can be used as a source of information for both research and surveillance purposes, while remaining aware of these limitations.

We compared symptoms and characteristics of 4961 ambulatory patients with and without laboratory-confirmed severe acute respiratory syndrome coronavirus 2 infection. Findings indicate that clinical symptoms alone would be insufficient to distinguish between coronavirus disease 2019 and other respiratory infections (eg, influenza) and/or to evaluate the effects of preventive interventions (eg, vaccinations). [ABSTRACT FROM AUTHOR]

Abstract Background The correct knowledge of standard case definition is necessary for frontline health workers to diagnose suspected diseases across Africa. However, surveillance evaluations commonly assume this prerequisite. This study assessed the knowledge of case definitions for health workers and their supervisors for disease surveillance activities in rural Kenya. Methods A cross-sectional survey including 131 health workers and their 11 supervisors was undertaken in two counties in Kenya. Descriptive analysis was conducted to classify the correctness of knowledge into four categories for three tracer diseases (dysentery, measles, and dengue). We conducted a univariate and multivariable logistic regression analyses to explore factors influencing knowledge of the case definition for dysentery. Results Among supervisors, 81.8% knew the correct definition for dysentery, 27.3% for measles, and no correct responses were provided for dengue. Correct knowledge was observed for 50.4% of the health workers for dysentery, only 12.2% for measles, and none for dengue. Of 10 examined factors, the following were significantly associated with health workers’ correct knowledge of the case definition for dysentery: health workers’ cadre (aOR 2.71; 95% CI 1.20–6.12; p = 0.017), and display of case definition poster (aOR 2.24; 95% CI 1.01–4.98; p = 0.048). Health workers’ exposure to the surveillance refresher training, supportive supervision and guidelines were not significantly associated with the knowledge. Conclusion The correct knowledge of standard case definitions was sub-optimal among health workers and their supervisors, which is likely to impact the reliability of routine surveillance reports generated from health facilities.

Background: Immunocompromised patients are at increased risk of acquiring healthcare-associated infections (HAIs) and often require specialized models of care. Surveillance of HAIs is essential for effective infection-prevention programmes. However, little is known regarding standardized or specific surveillance methods currently employed for high-risk hospitalized patients.Methods: A systematic review adopting a narrative synthesis approach of published material between 1 January 2000 and 31 March 2018 was conducted. Publications describing the application of traditional and/or electronic surveillance of HAIs in immunocompromised patient settings were identified from the Ovid MEDLINE®, Ovid Embase® and Elsevier Scopus® search engines [PROSPERO international prospective register of systematic reviews (registration ID: CRD42018093651)].Results: In total, 2708 studies were screened, of whom 17 fulfilled inclusion criteria. Inpatients diagnosed with haematological malignancies were the most-represented immunosuppressed population. The majority of studies described manual HAI surveillance utilizing internationally accepted definitions for infection. Chart review of diagnostic and pathology reports was most commonly employed for case ascertainment. Data linkage of disparate datasets was performed in two studies. The most frequently monitored infections were bloodstream infections and invasive fungal disease. No surveillance programmes applied risk adjustment for reporting surveillance outcomes.Conclusions: Targeted, tailored monitoring of HAIs in high-risk immunocompromised settings is infrequently reported in current hospital surveillance programmes. Standardized surveillance frameworks, including risk adjustment and timely data dissemination, are required to adequately support infection-prevention programmes in these populations. [ABSTRACT FROM AUTHOR]

The Iowa Newborn Screening (NBS) Program began screening for very long-chain acyl-CoA dehydrogenase deficiency (VLCAD) in 2003. Untreated VLCAD can lead to liver failure, heart failure, and death. Current confirmatory testing recommendations by the American College of Medical Genetics (ACMG) for VLCAD list molecular and functional analysis (i.e., fibroblast fatty acid oxidation probe) as optional. This can lead to misclassification of VLCAD carriers as false positives. Iowa implemented a comprehensive VLCAD confirmatory testing algorithm at the beginning of 2016 that included both molecular and fibroblast analysis. Here, we compare the historic multi-algorithmic confirmatory testing protocol (2005–2016) to this comprehensive protocol (2016–2017). A metabolic specialist reviewed all medical records and NBS data for each out-of-range VLCAD that fell in each testing period. During the comprehensive testing period, 48,651 specimens were screened. Thirteen individuals with out-of-range C14:1 results were classified as follows after review: ten carriers, zero true positives, zero false positives, zero lost to follow-up, and four unable to assess carrier status. During the variable testing period, a total of 486,566 specimens were screened. Eighty-five individuals with out-of-range C14:1 were classified as follows: 45 carriers, two true positives, four false positives, four lost to follow-up, and 30 unable to assess carrier status. Our findings suggest that many out-of-range VLCAD cases that do not receive molecular confirmatory testing could be carriers mistakenly classified as false positives. We recommend comprehensive molecular and functional testing for all children with out-of-range VLCAD NBS results. [ABSTRACT FROM AUTHOR]

Background Respiratory syncytial virus (RSV) is a leading cause of acute lower respiratory tract infection (ALRTI) in young children, but data on surveillance case definition performance in estimating burdens have been limited. Methods We enrolled children aged <5 years hospitalized for ALRTI (or neonatal sepsis in young infants) through active prospective surveillance at 5 sentinel hospitals in South Africa and collected nasopharyngeal aspirates from them for RSV molecular diagnostic testing between 2009 and 2014. Clinical data were used to characterize RSV disease and retrospectively evaluate the performance of respiratory illness case definitions (including the World Health Organization definition for severe acute respiratory infection [SARI]) in identifying hospitalized children with laboratory-confirmed RSV according to age group (<3, 3–5, 6–11, 12–23, and 24–59 months). Results Of 9969 hospitalized children, 2723 (27%) tested positive for RSV. Signs and symptoms in RSV-positive children varied according to age; fever was less likely to occur in children aged <3 months (57%; odds ratio [OR], 0.8 [95% CI, 0.7–0.9]) but more likely in those aged ≥12 months (82%; OR, 1.7–1.9) than RSV-negative children. The sensitivity (range, 55%–81%) and specificity (range, 27%–54%) of the SARI case definition to identify hospitalized RSV-positive children varied according to age; the lowest sensitivity was for infants aged <6 months. Using SARI as the case definition would have missed 36% of RSV-positive children aged <5 years and 49% of those aged <3 months; removing the fever requirement from the definition recovered most missed cases. Conclusion Including fever in the SARI case definition lowers the sensitivity for RSV case detection among young children hospitalized with an ALRTI and likely underestimates its burden. [ABSTRACT FROM AUTHOR]

Objectives: Case ascertainment algorithms were developed and validated to identify people living with cirrhosis in administrative health data in Manitoba, Canada using primary care electronic medical records (EMR) to define the reference standards., Methods: We linked provincial administrative health data to primary care EMR data. The validation cohort included 116,675 Manitobans aged >18 years with at least one primary care visit between April 1998 and March 2015. Hospital records, physician billing claims, vital statistics, and prescription drug data were used to develop and test 93 case-finding algorithms. A validated case definition for primary care EMR data was the reference standard. We estimated sensitivity, specificity, positive and negative predictive values (PPV, NPV), Youden's index, area under the receiver operative curve, and their 95% confidence intervals (CIs)., Results: A total of 116,675 people were in the validation cohort. The prevalence of cirrhosis was 1.4% ( n = 1593). Algorithm sensitivity estimates ranged from 32.5% (95% CI 32.2-32.8) to 68.3% (95% CI 68.0-68.9) and PPV from 17.4% (95% CI 17.1-17.6) to 23.4% (95% CI 23.1-23.6). Specificity (95.5-98.2) and NPV (approximately 99%) were high for all algorithms. The algorithms had slightly higher sensitivity estimates among men compared with women, and individuals aged ≥45 years compared to those aged 18-44 years., Conclusion: Cirrhosis algorithms applied to administrative health data had moderate validity when a validated case definition for primary care EMRs was the reference standard. This study provides algorithms for identifying diagnosed cirrhosis cases for population-based research and surveillance studies., Competing Interests: The authors have no conflicts of interest to declare., (© Canadian Association for the Study of the Liver, 2024.)

The Institute of Medicine recently proposed a new case definition for chronic fatigue syndrome (CFS), as well as a new name, Systemic Exertion Intolerance Disease (SEID). Contrary to the Fukuda et al.’s CFS case definition, there are few exclusionary illnesses specified for this new SEID case definition. The current study explored this decision regarding exclusionary illnesses using the SEID criteria with four distinct data sets involving patients who had been identified as having CFS, as well as healthy controls, community controls, and other illness groups. The findings indicate that many individuals from major depressive disorder illness groups as well as other medical illnesses were categorized as having SEID. The past CFS Fukuda et al. prevalence rate in a community based sample of 0.42 increased by 2.8 times with the new SEID criteria. The consequences for this broadening of the case definition are discussed.

Background Pertussis is an important cause of hospitalization and death in infants too young to be vaccinated (aged <2 months). Limited data on infant pertussis have been reported from Central America. The aim of this study was to characterize acute respiratory illnesses (ARIs) attributable to Bordetella pertussis among infants enrolled in an ongoing surveillance study in Guatemala. Methods As part of a population-based surveillance study in Guatemala, infants aged <2 months who presented with ARI and required hospitalization were enrolled, and nasopharyngeal and oropharyngeal swab specimens were obtained. For this study, these specimens were tested for B pertussis using real-time polymerase chain reaction (PCR). Results Among 301 infants hospitalized with ARI, we found 11 with pertussis confirmed by PCR (pertussis-positive infants). Compared to pertussis-negative infants, pertussis-positive infants had a higher mean admission white blood cell count (20900 vs 12579 cells/μl, respectively; P =.024), absolute lymphocyte count (11517 vs 5591 cells/μl, respectively; P <.001), rate of admission to the intensive care unit (64% vs 35%, respectively; P =.054), and case fatality rate (18% vs 3%, respectively; P =.014). Ten of the 11 pertussis-positive infants had cough at presentation; the majority (80%) of them had a cough duration of <7 days, and only 1 had a cough duration of >14 days. Fever (temperature ≥ 38°C) was documented in nearly half (45%) of the pertussis-positive infants (range, 38.0–38.4°C). Conclusions In this study of infants <2 months of age hospitalized with ARI in Guatemala, pertussis-positive infants had a high rate of intensive care unit admission and a higher case fatality rate than pertussis-negative infants. [ABSTRACT FROM AUTHOR]

Objectives: Data derived from primary care electronic medical records (EMRs) are being used for research and surveillance. Case definitions are required to identify patients with specific conditions in EMR data with a degree of accuracy. The purpose of this study is to identify and provide a summary of case definitions that have been validated in primary care EMR data.Materials and Methods: We searched MEDLINE and Embase (from inception to June 2016) to identify studies that describe case definitions for clinical conditions in EMR data and report on the performance metrics of these definitions.Results: We identified 40 studies reporting on case definitions for 47 unique clinical conditions. The studies used combinations of International Classification of Disease version 9 (ICD-9) codes, Read codes, laboratory values, and medications in their algorithms. The most common validation metric reported was positive predictive value, with inconsistent reporting of sensitivity and specificity.Discussion: This review describes validated case definitions derived in primary care EMR data, which can be used to understand disease patterns and prevalence among primary care populations. Limitations include incomplete reporting of performance metrics and uncertainty regarding performance of case definitions across different EMR databases and countries.Conclusion: Our review found a significant number of validated case definitions with good performance for use in primary care EMR data. These could be applied to other EMR databases in similar contexts and may enable better disease surveillance when using clinical EMR data. Consistent reporting across validation studies using EMR data would facilitate comparison across studies.Systematic review registration: PROSPERO CRD42016040020 (submitted June 8, 2016, and last revised June 14, 2016). [ABSTRACT FROM AUTHOR]

Renewable energy demands have increased the need for new wind farms. In turn, concerns have been raised about potential adverse health effects on nearby residents. A case definition has been proposed to diagnose "Adverse Health Effects in the Environs of Industrial Wind Turbines" (AHE/IWT); initially in 2011 and then with an update in 2014. The authors invited commentary and in turn, we assessed its scientific merits by quantitatively evaluating its proposed application. We used binomial coefficients to quantitatively assess the potential of obtaining a diagnosis of AHE/IWT. We also reviewed the methodology and process of the development of the case definition by contrasting it with guidelines on case definition criteria of the USA Institute of Medicine. The case definition allows at least 3,264 and up to 400,000 possibilities for meeting second- and third-order criteria, once the limited first-order criteria are met. IOM guidelines for clinical case definitions were not followed. The case definition has virtually no specificity and lacks scientific support from peer-reviewed literature. If applied as proposed, its application will lead to substantial potential for false-positive assessments and missed diagnoses. Virtually any new illness that develops or any prevalent illness that worsens after the installation of wind turbines within 10 km of a residence could be considered AHE/IWT if the patient feels better away from home. The use of this case definition in the absence of a thorough medical evaluation with appropriate diagnostic studies poses risks to patients in that treatable disorders would be overlooked. The case definition has significant potential to mislead patients and its use cannot be recommended for application in any health-care or decision-making setting

Background: The correct knowledge of standard case definition is necessary for frontline health workers to diagnose suspected diseases across Africa. However, surveillance evaluations commonly assume this prerequisite. This study assessed the knowledge of case definitions for health workers and their supervisors for disease surveillance activities in rural Kenya.Methods: A cross-sectional survey including 131 health workers and their 11 supervisors was undertaken in two counties in Kenya. Descriptive analysis was conducted to classify the correctness of knowledge into four categories for three tracer diseases (dysentery, measles, and dengue). We conducted a univariate and multivariable logistic regression analyses to explore factors influencing knowledge of the case definition for dysentery.Results: Among supervisors, 81.8% knew the correct definition for dysentery, 27.3% for measles, and no correct responses were provided for dengue. Correct knowledge was observed for 50.4% of the health workers for dysentery, only 12.2% for measles, and none for dengue. Of 10 examined factors, the following were significantly associated with health workers' correct knowledge of the case definition for dysentery: health workers' cadre (aOR 2.71; 95% CI 1.20-6.12; p = 0.017), and display of case definition poster (aOR 2.24; 95% CI 1.01-4.98; p = 0.048). Health workers' exposure to the surveillance refresher training, supportive supervision and guidelines were not significantly associated with the knowledge.Conclusion: The correct knowledge of standard case definitions was sub-optimal among health workers and their supervisors, which is likely to impact the reliability of routine surveillance reports generated from health facilities. [ABSTRACT FROM AUTHOR]

Newborn screening (NBS) identifies infants with rare conditions to prevent death or the onset of irreversible morbidities. Conditions on the Health and Human Services Secretary’s Recommended Uniform Screening Panel have been adopted by most state NBS programs, providing a consistent approach for identification of affected newborns across the United States. Screen-positive newborns are identified and referred for confirmatory diagnosis and follow-up. The designation of a clinically significant phenotype precursor to a clinical diagnosis may vary between clinical specialists, resulting in diagnostic variation. Determination of disease burden and birth prevalence of the screened conditions by public health tracking is made challenging by these variations. This report describes the development of a core group of new case definitions, along with implications, plans for their use, and links to the definitions that were developed by panels of clinical experts. These definitions have been developed through an iterative process and are piloted in NBS programs. Consensus public health surveillance case definitions for newborn screened disorders will allow for consistent categorization and tracking of short- and long-term follow-up of identified newborns at the local, regional, and national levels.

The burden estimation studies for respiratory syncytial virus (RSV) have been based on varied case definitions, including case–definitions designed for influenza surveillance systems. We used all medical admissions among children aged 0–59 months to study the effect of case definitions on estimation of RSV–associated hospitalizations rates. The hospital–based daily surveillance enrolled children aged 0–59 months admitted with acute medical conditions from July 2009–December 2012, from a well–defined rural population in Ballabgarh in northern India. All study participants were examined and nasal and throat swabs taken for testing by real–time polymerase chain reaction (RT–PCR) for RSV and influenza virus. Clinical data were used to retrospectively evaluate World Health Organization (WHO) case definitions (2011) commonly used for surveillance of respiratory pathogens, ie, acute respiratory illness (WHO–ARI), severe ARI (SARI) and influenza–like illness (ILI), for determination of RSV–associated hospitalization. RSV–associated hospitalization rates adjusted for admissions at non–study hospitals were calculated. Out of 505 children enrolled, 82 (16.2%) tested positive for RSV. Annual incidence rates of RSV–associated hospitalization per 1000 children were highest among infants aged 0–5 months (15.2; 95% confidence interval (CI) 8.3–26.8), followed by ages 6–23 months (5.3, 95% CI 3.2–8.7) and lowest among children 24–59 months (0.5, 95% CI 0.1–1.5). The RSV positive children were more likely to have signs of respiratory distress like wheeze, chest in–drawing, tachypnea, and crepitation compared to RSV–negative based on bivariate comparisons. Other less commonly seen signs of respiratory distress, ie, nasal flaring, grunting, accessory muscle usage were also significantly associated with being RSV positive. Compared to the estimated RSV hospitalization rate based on all medical hospitalizations, the WHO–ARI case definition captured 86% of the total incidence, while case definitions requiring fever like ILI and SARI underestimated the incidence by 50–80%. Our study suggests that RSV is a substantial cause of hospitalization among children aged

Background: Primary care electronic medical record (EMR) data are being used for research, surveillance, and clinical monitoring. To broaden the reach and usability of EMR data, case definitions must be specified to identify and characterize important chronic conditions. The purpose of this study is to identify all case definitions for a set of chronic conditions that have been tested and validated in primary care EMR and EMR-linked data. This work will provide a reference list of case definitions, together with their performance metrics, and will identify gaps where new case definitions are needed. Methods: We will consider a set of 40 chronic conditions, previously identified as potentially important for surveillance in a review of multimorbidity measures. We will perform a systematic search of the published literature to identify studies that describe case definitions for clinical conditions in EMR data and report the performance of these definitions. We will stratify our search by studies that use EMR data alone and those that use EMR-linked data. We will compare the performance of different definitions for the same conditions and explore the influence of data source, jurisdiction, and patient population. Discussion: EMR data from primary care providers can be compiled and used for benefit by the healthcare system. Not only does this work have the potential to further develop disease surveillance and health knowledge, EMR surveillance systems can provide rapid feedback to participating physicians regarding their patients. Existing case definitions will serve as a starting point for the development and validation of new case definitions and will enable better surveillance, research, and practice feedback based on detailed clinical EMR data. [ABSTRACT FROM AUTHOR]

Background: In order to better understand respiratory syncytial virus (RSV) epidemiology and burden in tropical Africa, optimal case definitions for detection of RSV cases need to be identified.Methods: We used data collected between September 2009 - August 2013 from children aged <5 years hospitalized with acute respiratory Illness at Siaya County Referral Hospital. We evaluated the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of individual signs, symptoms and standard respiratory disease case definitions (severe acute respiratory illness [SARI]; hospitalized influenza-like illness [hILI]; integrated management of childhood illness [IMCI] pneumonia) to detect laboratory-confirmed RSV infection. We also evaluated an alternative case definition of cough or difficulty breathing plus hypoxia, in-drawing, or wheeze.Results: Among 4714 children hospitalized with ARI, 3810 (81 %) were tested for RSV; and 470 (12 %) were positive. Among individual signs and symptoms, cough alone had the highest sensitivity to detect laboratory-confirmed RSV [96 %, 95 % CI (95-98)]. Hypoxia, wheezing, stridor, nasal flaring and chest wall in-drawing had sensitivities ranging from 8 to 31 %, but had specificities >75 %. Of the standard respiratory case definitions, SARI had the highest sensitivity [83 %, 95 % CI (79-86)] whereas IMCI severe pneumonia had the highest specificity [91 %, 95 % CI (90-92)]. The alternative case definition (cough or difficulty breathing plus hypoxia, in-drawing, or wheeze) had a sensitivity of [55 %, 95 % CI (50-59)] and a specificity of [60 %, 95 % CI (59-62)]. The PPV for all case definitions and individual signs/symptoms ranged from 11 to 20 % while the negative predictive values were >87 %. When we stratified by age <1 year and 1- < 5 years, difficulty breathing, severe pneumonia and the alternative case definition were more sensitive in children aged <1 year [70 % vs. 54 %, p < 0.01], [19 % vs. 11 %, p = 0.01] and [66 % vs. 43 %, p < 0.01] respectively, while non-severe pneumonia was more sensitive [14 % vs. 26 %, p < 0.01] among children aged 1- < 5 years.Conclusion: The sensitivity and specificity of different commonly used case definitions for detecting laboratory-confirmed RSV cases varied widely, while the positive predictive value was consistently low. Optimal choice of case definition will depend upon study context and research objectives. [ABSTRACT FROM AUTHOR]

Objective: To validate and compare the decision rules to identify rheumatoid arthritis (RA) in administrative databases. Methods: A study was performed using administrative health care data from a population of 1 million people who had access to universal health care. Information was available on hospital discharge abstracts and physician billings. RA cases in health administrative databases were matched 1:4 by age and sex to randomly selected controls without inflammatory arthritis. Seven case definitions were applied to identify RA cases in the health administrative data, and their performance was compared with the diagnosis by a rheumatologist. The validation study was conducted on a sample of individuals with administrative data who received a rheumatologist consultation at the Arthritis Center of Nova Scotia. Results: We identified 535 RA cases and 2,140 non-RA, noninflammatory arthritis controls. Using the rheumatologist's diagnosis as the gold standard, the overall accuracy of the case definitions for RA cases varied between 68.9% and 82.9% with a kappa statistic between 0.26 and 0.53. The sensitivity and specificity varied from 20.7% to 94.8% and 62.5% to 98.5%, respectively. In a reference population of 1 million, the estimated annual number of incident cases of RA was between 176 and 1,610 and the annual number of prevalent cases was between 1,384 and 5,722. Conclusion: The accuracy of case definitions for the identification of RA cases from rheumatology clinics using administrative health care databases is variable when compared to a rheumatologist's assessment. This should be considered when comparing results across studies. This variability may also be used as an advantage in different study designs, depending on the relative importance of sensitivity and specificity for identifying the population of interest to the research question. [ABSTRACT FROM AUTHOR]

Renewable energy demands have increased the need for new wind farms. In turn, concerns have been raised about potential adverse health effects on nearby residents. A case definition has been proposed to diagnose "Adverse Health Effects in the Environs of Industrial Wind Turbines" (AHE/IWT); initially in 2011 and then with an update in 2014. The authors invited commentary and in turn, we assessed its scientific merits by quantitatively evaluating its proposed application. We used binomial coefficients to quantitatively assess the potential of obtaining a diagnosis of AHE/IWT. We also reviewed the methodology and process of the development of the case definition by contrasting it with guidelines on case definition criteria of the USA Institute of Medicine. The case definition allows at least 3,264 and up to 400,000 possibilities for meeting second- and third-order criteria, once the limited fi rst-order criteria are met. IOM guidelines for clinical case definitions were not followed. The case definition has virtually no specificity and lacks scientific support from peer-reviewed literature. If applied as proposed, its application will lead to substantial potential for false-positive assessments and missed diagnoses. Virtually any new illness that develops or any prevalent illness that worsens after the installation of wind turbines within 10 km of a residence could be considered AHE/IWT if the patient feels better away from home. The use of this case definition in the absence of a thorough medical evaluation with appropriate diagnostic studies poses risks to patients in that treatable disorders would be overlooked. The case definition has significant potential to mislead patients and its use cannot be recommended for application in any health-care or decision-making setting. [ABSTRACT FROM AUTHOR]

The Institute of Medicine recently proposed a new case definition for chronic fatigue syndrome (CFS), as well as a new name, Systemic Exertion Intolerance Disease (SEID). Contrary to the Fukuda et al.'s CFS case definition, there are few exclusionary illnesses specified for this new SEID case definition. The current study explored this decision regarding exclusionary illnesses using the SEID criteria with four distinct data sets involving patients who had been identified as having CFS, as well as healthy controls, community controls, and other illness groups. The findings indicate that many individuals from major depressive disorder illness groups as well as other medical illnesses were categorized as having SEID. The past CFS Fukuda et al. prevalence rate in a community based sample of 0.42 increased by 2.8 times with the new SEID criteria. The consequences for this broadening of the case definition are discussed. [ABSTRACT FROM AUTHOR]

Current case definitions of myalgic encephalomyelitis and chronic fatigue syndrome (CFS) have been based on consensus methods, but empirical methods could be used to identify core symptoms and thereby improve the reliability. In the present study, several methods (i.e. continuous scores of symptoms, theoretically and empirically derived cut off scores of symptoms) were used to identify core symptoms best differentiating patients from controls. In addition, data mining with decision trees was conducted. Our study found a small number of core symptoms that have good sensitivity and specificity, and these included fatigue, post-exertional malaise, a neurocognitive symptom, and unrefreshing sleep. Outcomes from these analyses suggest that using empirically selected symptoms can help guide the creation of a more reliable case definition. [ABSTRACT FROM AUTHOR]

Background At the onset of the pandemic H1N1/09 influenza A outbreak in Australia, health authorities devised official clinical case definitions to guide testing and access to antiviral therapy. Objectives To assess the diagnostic accuracy of these case definitions and to attempt to improve on them using a scoring system based on clinical findings at presentation. Patients/Methods This study is a retrospective case-control study across three metropolitan Melbourne hospitals and one associated community-based clinic during the influenza season, 2009. Patients presenting with influenza-like illness who were tested for H1N1/09 influenza A were administered a standard questionnaire of symptomatology, comorbidities, and risk factors. Patients with a positive test were compared to those with a negative test. Logistic regression was performed to examine for correlation of clinical features with disease. A scoring system was devised and compared with case definitions used during the pandemic. The main outcome measures were the positive and negative predictive values of our scoring system, based on real-life data, versus the mandated case definitions'. Results Both the devised scoring system and the case definitions gave similar positive predictive values (38-58% using ascending score groups, against 39-44% using the various case definitions). Negative predictive values were also closely matched (ranging from 94% to 73% in the respective score groups against 83-84% for the case definitions). Conclusions Accurate clinical diagnosis of H1N1/09 influenza A was difficult and not improved significantly by a structured scoring system. Investment in more widespread availability of rapid and sensitive diagnostic tests should be considered in future pandemic planning. [ABSTRACT FROM AUTHOR]