Data on utilization patterns and safety of non-steroidal anti-inflammatory drugs (NSAIDs) in children are scarce. The purpose of this study was to investigate the utilization of NSAIDs among children in four European countries as part of the Safety Of non-Steroidal anti-inflammatory drugs (SOS) project.We used longitudinal patient data from seven databases  to calculate prevalence rates of NSAID use among children (0–18 years of age) from Germany, Italy, Netherlands, and United Kingdom. All databases contained a representative population sample and recorded demographics, diagnoses, and drug prescriptions. Prevalence rates of NSAID use were stratified by age, sex, and calendar time. The person-time of NSAID exposure was calculated by using the duration of the prescription supply. We calculated incidence rates for serious adverse events of interest. For these adverse events of interest, sample size calculations were conducted  to determine the amount of NSAID exposure time that would be required for safety studies in children.The source population comprised 7.7 million children with a total of 29.6 million person-years of observation. Of those, 1.3 million children were exposed to at least one of 45 NSAIDs during observation time. Overall prevalence rates of NSAID use in children differed across countries, ranging from 4.4  to 197 (Germany) per 1000 person-years in 2007. For Germany, United Kingdom, and Italian pediatricians, we observed high rates of NSAID use among children aged one to four years. For all four countries, NSAID use increased with older age categories for children older than 11. In this analysis, only for ibuprofen (the most frequently used NSAID), enough exposure was available to detect a weak association (relative risk of 2) between exposure and asthma exacerbation (the most common serious adverse event of interest).Patterns of NSAID use in children were heterogeneous across four European countries. The SOS project platform captures data on more than 1.3 million children who were exposed to NSAIDs. Even larger data platforms and the use of advanced versions of case-only study designs may be needed to conclusively assess the safety of these drugs in children. Non-steroidal anti-inflammatory drugs (NSAIDs) are frequently used for their analgesic, antipyretic, and anti-inflammatory effects, even in children. NSAIDs were the tenth most frequently prescribed drug in the age group 2–11 years (33 users/1000 person years) and the sixth most frequently prescribed drug in age group 12–18 years (57 users/1000 person years) in a combined primary care database study conducted in Italy, the Netherlands and the United Kingdom [The Safety of Non-steroidal Anti-inflammatory Drugs (SOS) project is a research and development project funded by the Health Area of the European Commission under the Seventh Framework Programme, with the aim to assess the cardiovascular and gastrointestinal safety of NSAIDs, in particular with respect to children . In the In this study, as part of the SOS project, we aimed to investigate NSAID utilization patterns among children in four European countries and assess statistical power to study NSAID safety for ten adverse events of interest.Data for this study were obtained from seven longitudinal observational databases from four European countries involving medical data from more than 32 million people. Three primary care databases and four hospital discharge or administrative databases provided data from Germany (DE), Italy (IT), the Netherlands (NL) and the United Kingdom (UK) Table . All datGePaRD is a claims database and consists of claims data from four German statutory health insurance (SHI) providers. It covers about 14 million persons throughout Germany who have at any time between 2004 and 2008 been enrolled in one of the four SHIs. The database population represents approximately 17% of the German population. Available data contain demographic information and information on hospital discharges, outpatient physician visits, and outpatient dispensing of prescribed medications in the pharmacies. Hospital diagnoses are coded according to the German Modification of the International Classification of Diseases, 10th Revision (ICD-10 GM) with at least 4 digits , prescriTHIN is a longitudinal database of primary care medical records from more than 10 million people in the UK. Some electronic records date back to 1985. Currently, the database has 3.6 million active patients registered. Data recorded in THIN include demographics, diagnoses, symptoms, prescriptions, life style information such as smoking or alcohol consumption, test results, height, weight, referrals to hospitals and specialists, and, on request, specialist letters and hospital discharge summaries. Diagnoses and symptoms are recorded using READ codes. Information on drug prescriptions is coded with MULTILEX product dictionary, mapped to ATC codes, and contains dose and duration. Approval for this study has been obtained from the Scientific Review Committee for the THIN database.The IPCI database is a dynamic longitudinal primary care research database from NL initiated in 1992. Currently, it covers about one million people from 150 active general practices. Symptoms and diagnoses are recorded using the International Classification for Primary Care (ICPC ) and freThe PHARMO medical record linkage system is a population-based patient-centric data tracking system of 3.2 million community-dwelling inhabitants from NL. Data have been collected since October 1994. The drug dispensing data originate from out-patient-pharmacies. Via the Dutch National Medical Register (LMR) hospital admissions are collected with ICD-9-clinically modified (CM). Information on drug prescriptions is coded according to the ATC classification.In the Italian National Health Service (NHS), the Local Health Authority is responsible for the health of the citizens in a given geographical area, usually a province. In 2006, eight authorities have established a network named OSSIFF, accounting for a population of about 3.8 million people. Hospital diagnoses are coded according to ICD-9-CM. Prescriptions are coded according to the ATC coding system, and additionally prescription date, number of prescribed units, drug strength and the defined daily dose (DDDs) of the active entity are available.In the Italian SISR database, data are obtained from the electronic healthcare databases of the Lombardy region. Lombardy is the largest Italian region with about nine million inhabitants, about 16% of the population of Italy. This population is entirely covered by a system of electronically linkable databases containing information on health services reimbursable by the NHS. The SISR database has complete population coverage and data is available from 2002. Via the ICD-9-CM dictionary and ATC classification, the database captures information on diagnoses from hospitalizations and drugs. Because OSSIFF covers a subset of patients covered by SISR, this database excluded the common subset of patients to avoid overlap.The Italian Pedianet database is a primary care pediatric database comprising the clinical data of about 160 family pediatricians (FPs) distributed throughout Italy. In Italy all children until the age of 14 years are registered with an FP. Pedianet has been built up since 1999. By December 2010, Pedianet database contained data on 370,000 children. Information on all drugs , symptoms and diagnoses are available in free text or coded by the ICD-9 system.In accordance with European data protection standards, neither personal identifiers nor other patient-level data were shared across countries. Data were extracted and processed locally by Jerboa© software, a software developed and validated at Erasmus University Medical Center in Rotterdam . The JerThree input files were extracted from each database locally according to a pre-specified common format containing information on: (i) patient characteristics such as date of birth, sex, and registration date; (ii) NSAID prescriptions or dispensing (ATC code M01A) including duration of supply, and (iii) diagnoses and their corresponding date through ICD-10, READ, ICD-9, ICPC codes or free text. The observation time for each patient started 365 days after registration with a practice or health insurance system. For children who were born into the database, observation started at date of birth. The observation period ended at the earliest of the following dates: turning 14 (Pedianet) or 18 years of age, transfer out of the practice or insurance system, death, or last data collection. The study period varied between databases according to data availability , a biomedical terminology integration system handling more than 150 medical dictionaries . This prFor each database, the prevalence rate of NSAID use was calculated by dividing the number of prevalent NSAID users by the person-time of observation, stratified by age, sex, calendar year, and calendar month. The reference calendar year was 2007. The person-time of NSAID exposure was calculated by using the duration of the prescription supply. Relative prevalence rates (in percentages) were calculated by dividing the absolute prevalence rate by the mean prevalence rate within each database for each calendar month and one-year age category.We calculated incidence rates (IRs) per 100,000 person-years for each of the events of interest for each database and performed direct standardization using the WHO World Standard Population as reference to account for age differences when comparing the overall diagnosis rates  . We onlyTo determine the usability of the SOS database platform for the study of NSAID safety with respect to adverse events of interest in children, we calculated the person-years of exposure required to detect a drug-event association over varying magnitudes of relative risks (RR), using RRs of 2 (weak association), 4 (moderate association), and 6 (strong association), a one-sided significance level (α) of 0.05, and a power (1-β) of 80%. To estimate the required exposure for specific strengths of association we used a previously published sample size formula . The reqThe pediatric population of the SOS platform network comprised 7.7 million children and adolescents 0 to 18 years) contributing 29.6 million person-years (PYs) of observation between 1999 and 2011  used one of the 45 NSAIDs for at least one day during observation time , THIN , and Pedianet  , followed by ketoprofen and naproxen. Together with ibuprofen and ketoprofen, morniflumate was common in Pedianet. In the Netherlands (IPCI and PHARMO), diclofenac, naproxen and ibuprofen were most common. Nimesulide, morniflumate and niflumic acid were only available in Italy, while lonazolac and parecoxib were only available in the GePaRD database (Germany), and etodolac, fenbufen, and fenoprofen were only prescribed in THIN (UK). In IPCI and PHARMO (both from NL) a fixed combination of diclofenac and misoprostol  was frequently prescribed to adolescents, whereas this was not common in other databases (data not shown). In all databases except OSSIFF and SISR (both from IT), the three most frequently used NSAIDs accounted for more than 80% of the total person-years of NSAID exposure. Proprionic acid derivates  were by far most common in all databases except OSSIFF and SIRS. OSSIFF and SIRS showed highest prescription rates for cyclooxygenase-2-selective NSAIDs .Table In the SOS project, the combined source population of children and adolescents (0 to 18 years of age) from seven databases from four European countries involved 7.7 million children and adolescents and generated 29.6 million person-years of observation between 1999 and 2011. Of these, 1.3 million children received NSAID prescriptions during the studied periods in the respective databases. Overall, 56 children/adolescents out of 1000 received an NSAID prescription per year. This varied largely between 4 per 1000 in OSSIFF to 197 per 1000 in GePaRD in the pediatric population. In general, one could conclude that the annual prevalence of prescribed NSAIDs is lowest in Italy, followed by the Netherlands, the United Kingdom and highest for Germany. Also, in all databases except the Italian ones, females received more NSAID prescriptions than males, mainly related to diverging prevalence rates in adolescence  dispensations of NSAIDs, the prevalence of NSAID exposure was slightly higher for PHARMO than for IPCI, especially in adolescents. Three Italian databases participated in the SOS platform and the prevalence rates for different ages of NSAID use were very similar for OSSIFF and SISR, but not for Pedianet Figure . This coAlthough the SOS platform appears to provide a unique opportunity to study the safety of NSAIDs in a large number of children and adolescents, we showed that the data are still too limited to study the safety of specific NSAID substances or the safety of NSAIDs in general for rare adverse drug reactions. Only for ibuprofen enough exposure time was available in the platform to investigate the risk of asthma exacerbation (the most common event) for a ‘weak association’ with a RR of 2. Data accumulation in platforms like SOS and others is of utmost importance for the safety evaluation of drugs in adults and children. The coming decade is likely to bring enormous expansion of available health care records, and advancement of data mining and harmonisation methods. Both the U.S. Food and Drug Administration and the European Medicines Agency invest in infrastructure and knowledge expansion in this field. However, our study shows how difficult it is to study safety in children, when compared to adults. Because of lower drug consumption – fortunately – use of these platforms for adequate drug safety surveillance is more challenging, as are many aspects of drug research in children. This should emphasize the responsibility as researchers, clinicians, and policy makers to facilitate high quality research in this vulnerable patient group through funding, scholarship, education and collaboration.Some limitations should be considered. First, in this analysis, we primarily used alpha = 0.05 as a testing threshold. To propose a tentative signal for NSAID safety in the pediatric population, a less stringent testing threshold may be indicated. For an expected RR of 6, a ‘strong association’ , we performed additional power calculations with a less stringent alpha value of 0.1 Table . This seFor the SOS studies, to estimate outcome risks with NSAID use in children and adolescents, we will consider case-only designs such as self-controlled case series or case-crossover . One advNSAID use is common in children and utilization patterns varied between Germany, Italy, United Kingdom, and The Netherlands. There is a clear need to study NSAID safety in children . AlthougATC: Anatomical therapeutic chemical classification system; BNF: British national formulary; CV: Cardiovascular; DDD: Defined daily dose; DW: Data warehouse; EMA: European medicines agency; EU: European union; FDA: U.S. Food and drug administration; FP: Family pediatrician/Office-based pediatrician; GE: Germany; GePaRD: German pharmacoepidemiological research database; GP: General practitioner/family physician; ICH: International conference of harmonization; IPCI: Integrated primary care information project; IT: Italy; NL: The Netherlands; NSAID: Non-steroidal anti-inflammatory drug; OSSIFF: Osservatorio Interaziendale per la Farmacoepidemiologia e la Farmacoeconomia; PY: Person-years ; SAE: Serious adverse event; SISR: Sistema informativo sanitario regionale ; THIN: The health improvement network; UK: United Kingdom; WHO: World health organization of the united nations (UN).Vera Valkhoff, as employee of Erasmus MC, has conducted research for AstraZeneca.René Schade has no conflicts of interest to disclose.Geert ’t Jong has no conflicts of interest to disclose.Geert ‘t Jong had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.Silvana Romio has no conflicts of interest to disclose.Martijn J. Schuemie has no conflicts of interest to disclose.Andrea Arfe has no conflicts of interest to disclose.Edeltraut Garbe runs a department that occasionally performs studies for pharmaceutical industries with the full freedom to publish. The companies include Mundipharma, Bayer, Stada, Sanofi-Aventis, Sanofi-Pasteur, Novartis, Celgene, and GSK. She has been consultant to Bayer-Schering, Nycomed, Teva, and Novartis in the past. The present work is unrelated to the above grants and relationships.Ron Herings has no conflicts of interest to disclose.Silvia Lucchi has no conflicts of interest to disclose.Gino Picelli has conducted studies for Merck and Pfizer.Tania Schink has no conflicts of interest to disclose.Huub Straatman has no conflicts of interest to disclose.Marco Villa has no conflicts of interest to disclose.Ernst J Kuipers has no conflicts of interest to disclose.Miriam Sturkenboom is head of a unit that conducts some research for pharmaceutical companies: Pfizer, Lilly and Altana.VEV, RS, SR, and MCJMS participated in the conception and design of the study. VEV, RS, AA, EG, RH, SL, GP, TS, HS, MV, and MCJMS participated in the acquisition of data. VEV, RS, GW’tJ, SR, MJS, SL, EJK, and MCJMS participated in the analysis and interpretation of data. VEV, RS, and GW’tJ drafted the manuscript. All authors revised the manuscript for important intellectual content and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2431/13/192/prepub


To investigate the association between frailty index (FI) of deficit accumulation and risk of falls, fractures, death and overnight hospitalizations in women aged 55 years and older.The data were from the Global Longitudinal Study of Osteoporosis in Women (GLOW) Hamilton Cohort. In this 3-year longitudinal, observational cohort study, women  aged ≥55 years were enrolled between May 2008 and March 2009 in Hamilton, Canada. A FI including co-morbidities, activities of daily living, symptoms and signs, and healthcare utilization was constructed using 34 health deficits at baseline. Relationship between the FI and falls, fractures, death and overnight hospitalizations was examined.The FI was significantly associated with age, with a mean rate of deficit accumulation across baseline age of 0.004 or 0.021  per year. During the third year of follow-up, 1,068 (31.89%) women reported at least one fall. Each increment of 0.01 on the FI was associated with a significantly increased risk of falls during the third year of follow-up . The area under the curve (AUC) of the predictive model was 0.69 (95% CI: 0.67-0.71). Results of subgroup and sensitivity analyses indicated the relationship between the FI and risk of falls was robust, while bootstrap analysis judged its internal validation. The FI was significantly related to fractures , death  during the 3-year follow-up period and overnight hospitalizations  for an increase of 0.01 on the FI during the third year of follow-up. Measured by per standard deviation (SD) increment of the FI, the ORs were 1.21 and 1.40 for falls and death respectively, while the HR was 1.17 for fractures and the IRR was 1.18 for overnight hospitalizations respectively.The FI of deficit accumulation increased with chronological age significantly. The FI was associated with and predicted increased risk of falls, fractures, death and overnight hospitalizations significantly. Frailty is a state of vulnerability and is highly associated with age ,2. FrailIdeally, frailty models should have both discriminative and evaluative properties, and should reliably reflect the natural history of aging . The pheFalls are a very important public health issue for the elderly and will increase in frequency as the proportion of elderly grows larger . One thiIn this study, using the Global Longitudinal Study of Osteoporosis in Women (GLOW) 3-year Hamilton cohort, our primary objective was to examine the association between frailty and the risk of falls in women aged 55 years and older, by constructing a feasible and pragmatic FI. The secondary objective was to investigate the relationship between frailty and risk of fractures, death and overnight hospitalizations. We hypothesized that a higher FI was associated with increased risk of falls, fractures, death and overnight hospitalizations significantly.The Global Longitudinal Study of Osteoporosis in Women (GLOW) is an observational study designed to explore risk factors for and health consequences of fragility fractures in 60,393 women aged 55 years and older who had consulted their physician in the past 24 months, involving 723 physician practices at 17 sites in 10 countries . Each site obtained local ethics committee approval to participate in the study. This has been described in detail previously . BrieflyParticipants were surveyed annually with mailed questionnaires. Telephone interviews were performed if the participant needed assistance with finishing the survey or did not return mailed questionnaires. Surveys used in the GLOW study were designed to be self-administered by participants and covered the domains as follows: participant characteristics and risk factors, perception about fracture risk and osteoporosis, medication use, co-morbidities, health care use and access, physical activity, physical function and quality of life . This stWe constructed our FI based on the standard procedure and framework suggested by Searle and Rockwood ,19. In cThe FI was calculated by adding up the values of deficits and dividing by the total number of items (n = 34), with the FI ranging from 0 to 1. For instance, if an individual had three deficits with each score of 1 point, two deficits with each score of 0.5 point and the other 29 deficits with each score of 0, her cumulative values of deficits would therefore be 4 divided by 34 giving a FI = 0.12.The outcomes included falls, fractures, death and overnight hospitalizations. All the outcomes were self-reported and information from medical records was not available.The primary outcome in this study, falls, were measured at baseline and each year of follow-up. Participants reported number of incident falls  in the prior 12 months on the annually mailed questionnaires.Women were identified as having baseline self-reported fractures that included fractures of the clavicle, upper arm, wrist, spine, rib, hip, pelvis, ankle, upper leg or lower leg since the age of 45 years. Incident fractures and the dates of the fractures were reported on the 1-, 2- and 3- year follow-up surveys. At baseline, participants categorized their number of overnight hospitalizations according to the options on the questionnaire . At each follow-up year, they were asked to record the total number of hospitalizations and total number of nights spent in hospital. Death was ascertained through contact with participants’ spouses, friends or family members and through electronic searches of obituaries. Some spouses and family members notified us of the participant’s death when they received mailings from our office, or when we called the homes of those participants who did not mail back their annual questionnaire. If we were unable to contact the household of the non-responders, we searched electronic databases of obituaries for entries which matched the participant’s full names and dates of birth.The continuous FI was reported as mean and standard deviation (SD). Comparison of the categorized falls status  at baseline was examined using Chi-square tests for categorical variables and analysis of variance (ANOVA) for continuous variables. The rate of deficit accumulation per year at baseline was calculated on the basis of the mean FI with age. To make the results comparable with other studies ,19,20, tThe relationship between each individual variable included in the FI and risk of falls during the third year of follow-up was also examined, after adjusted for baseline age. Binary logistic regression  was performed to assess the association between baseline FI and risk of falls if the proportional odds assumption for ordinal logistic regression  was not met, taking women with no falls as the reference category.Because the dates for falls were not available, unless otherwise emphasized, analyses of the relationship between baseline FI and risk of falls was conducted only using the data on the falls during the third year of follow-up. Baseline age-adjusted binary logistic regression models and fully-adjusted multivariable logistic regression models were performed and compared, where fully-adjusted models were adjusted for age, body mass index (BMI), smoking, drinking, education and baseline falls, to analyze the association between baseline FI and risk of falls. Receiver operating characteristic curves (ROC) were used to calculate the areas under the curve (AUC), which could judge the discriminability of the FI. A bootstrap analysis resampling 1,000 times with replacement from the original sample was conducted to assess the internal validation of the relationship between the FI and falls . MoreoveSecondary outcomes were fractures, death and overnight hospitalization. Similarly, age-adjusted models and fully-adjusted models were carried out and compared. Because the dates for death and overnight hospitalization were unavailable, logistic regression was applied to death during the follow-up, while Poisson regression was used to analyze the relationship between the FI and overnight hospitalizations during the third year of follow-up given the number of overall nights spent in the hospital as count data. Cox proportional hazards regression based on time-to-event was used to assess the associations between the FI and fractures after adjusting for age, BMI, smoking, drinking, education, baseline fractures and family history of fractures, where both a statistical test of proportional hazards assumption and a graphical examination using Schoenfeld residuals were performed .To compare the results with other studies’ findings ,19,24, aGiven that the findings on participants aged <65 years were scanty , subgrou2. Approximately 11% of the women were smokers and 49% drank alcohol. Most participants did not have a family history of fractures (76%), overnight hospitalizations (89%) in the past year, or fractures since 45 years old (78%).Characteristics of the GLOW Hamilton cohort are presented in Table There were 62% n = 2,471), 22% (n = 853), 16% (n = 630) of the women who reported no falls, one fall and no less than two falls at baseline, respectively. With the increased number of falls, participants tended to be more educated (P < 0.001) and with higher BMI (P = 0.002). More family history of fractures, overnight hospitalizations and prior fractures were reported as the number of baseline falls increased (P < 0.001). However, no differences in age, ethnicity, smoking and drinking status were found between the three groups  reported at least one fall in the past year , indicating the relationship between the FI and falls was internally validated.During the 3-year follow-up, 6.36% (n = 238) reported incident fractures (Table One hundred and seven women (2.69%) died during the follow-up Table . The FI The results of age-adjusted models and subgroup analyses stratified by age-stratum were similar to those based on the fully-adjusted models for fractures, death and overnight hospitalizations Table .With the use of the GLOW Hamilton cohort, we constructed a FI of deficit accumulation and investigated its relationship to risk of falls, fractures, death and overnight hospitalizations. The FI was associated significantly with increased risk of falls. Results of subgroup and sensitivity analyses indicated the relationship between the FI and risk of falls was robust, while bootstrap analysis judged its internal validation. Positive associations were also identified between the FI and risk of fractures, death and overnight hospitalizations.The underlying premise of the theory of deficit accumulation is that individuals with more deficits are more likely to be frail, which could be quantifiable using a FI . AlthougThe FI was significantly correlated with chronological age. The estimated FI increased across ages per year with a similar rate to other studies  ,19,20. WThe incremental FI significantly predicted increased risk of falls, fractures, death and overnight hospitalizations. This implies that the FI would be helpful to plan and assess future interventions aiming at improving the health outcomes of the elderly. Of note, the risk of death increased with the incremental FI significantly, with the OR of 1.05 measured by per change of 0.01 on the FI Table . This suSome types of fractures were likely due to trauma, thus being irrelevant to frailty . HoweverCompared with the phenotypic model -17,38-41Our results agreed with the findings from a Chinese study which used the FI with 33 health deficits to examine risk of health adverse outcomes in community-dwellers aged 55 years and older , especiaHowever, unlike other studies, we did not choose cutpoints to trichotomize participants into three groups  ,21,42,43Using a FI to quantify the change in the health status of the elderly would be a major concern to geriatricians and to population planners . Our stuHowever, our data must be interpreted with caution. The data was collected by patient self-report and could not be validated by medical records. Nevertheless, self-reported data have been shown to be reasonably credible for health adverse outcomes in different populations and settings -54. TherTo conclude, in this study the FI of deficit accumulation increased with chronological age significantly. The FI was related to and predicted increased risk of falls, fractures, death and overnight hospitalizations significantly. A validated and pragmatic FI would be considerably helpful for decision-making at a clinical research and health care policy level.FI: Frailty index; GLOW: Global Longitudinal Study of Osteoporosis in Women; ADL: Activities of daily living; SD: Standard deviation; ANOVA: Analysis of variance; BMI: Body mass index; ROC: Receiver operating characteristic; AUC: Area under the curve; CI: Confidence interval; OR: Odds ratio; HR: Hazard ratio; IRR: Incidence rate ratio.The authors declare that they have no competing interests.GL was responsible for the study conception and design, data analyses and the draft of manuscript. JDA enrolled participants, conceived the plan, and provided comments on the manuscript and data. GI, LP, CK, AP and LT made critical revisions to the manuscript, and provided professional and statistical support. All authors approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2474/15/185/prepub


Endometriosis is ectopic development of endometrial glands and stroma in extra-uterine sites and if the lesions occur as a well-defined mass is referred to as endometrioma. In the literature, endometrioma has been reported in only women and there are no reports of endometrioma in animals, including non-human primates.A rare case of endometrioma is reported in an 11-year-old female German Shepherd with clinical signs of dehydration, anemia and prostration. Necropsy revealed ascites, generalized pallor, and a well-demarcated reddish mass adjacent to the left ovary and uterus and adherent to the retroperitoneum. The mass measured 25.0 × 20.0 cm with intermingled soft and firm areas. Upon incision, the mass was found to be solid with variable sized cystic cavities filled with coagulated blood. Microscopically, the mass was composed of cuboidal or prismatic epithelial cells arranged in tubules or acini. The epithelium of the mass had similar characteristics to the normal endometrium with PAS-positive secretions. The stroma was prominent and formed by loose connective tissue and smooth muscle fibers as confirmed by Masson trichrome. Extensive multifocal areas of hemorrhage were also observed in the stroma of the mass and in the interior of some epithelium-lined, cystic structures. Most of the epithelial cells had strong and diffuse cytokeratin expression, and some had vimentin expression. Epithelial and stromal cells also showed ERβ, AR, VEGF and COX2 expression. The stroma showed areas with strong and diffuse vimentin expression. Factor VIII expression was observed only in the endothelium of blood vessels in the stroma.The macroscopic, microscopic and immunohistochemical findings are consistent with an endometrioma. Endometriosis is ectopic development of endometrial glands and stroma in extra-uterine sites , 2. EndoEndometriosis is a common gynecological disease in women, affecting approximately 10 % of the female population in the reproductive age. In rare cases, endometriosis has been diagnosed in men , 5. In aTwo theories have been proposed to explain the development of endometriosis in women and non-human primates. The retrograde menstruation theory suggests that viable endometrial cells, which are shed during menstruation, are fixed outside of the uterus . The coeThe occurrence of endometriosis in animal species with an estrous cycle is rare. In addition to the lack of shedding of the endometrium, which prevents the development of endometriosis by implantation, these species have minimum levels of estradiol, with only one peak along the estrous cycle . TherefoThe objective of this study is to report the macroscopic, microscopic and immunohistochemical features of an endometrioma in a bitch.An 11-years-old female German Shepherd was admitted to the Veterinary Teaching Hospital of the Universidade Federal de Minas Gerais, Brazil with a history of prostration one month ago. According to the owner, the animal had multiple normal deliveries, never exposed to contraceptives and experienced estrus regularly twice a year. Clinical examination showed mild dehydration, prostration and intensely pale mucosa. However, no other changes were observed as the dog suddenly died during the clinical examination, before laboratory testing was possible.Necropsy revealed intensely pale mucous membranes, generalized atrophy of the skeletal muscles and absence of subcutaneous and visceral adipose tissue. In the abdominal cavity, there were approximately 600 ml of reddish and translucent fluid. Adjacent to the left ovary and uterus and adherent to the retroperitoneum, there was a well-demarcated reddish mass, measuring 25.0 × 20.0 cm Fig.  with a mThe entire genital tract and specimens of the mass and other abdominal and thoracic organs were fixed in 10 % neutral phosphate-buffered formalin, sectioned, processed, embedded in paraffin, and stained with hematoxylin-eosin for histopathological examination. To better characterize the mass, staining with Masson trichrome, Periodic Acid Schiff (PAS) and immunohistochemistry were performed. Antibodies used for immunohistochemistry and their dilutions were as follows: anti-Factor VIII (1:300) , anti-vimentin (1:200) , anti-cytokeratin (1:200) , anti-VEGF (1:100) , anti-COX2 (1:40) , anti-estrogen receptor (ER) β (1:25) , and anti-androgen receptor (AR) (1:500) . The streptavidin-biotin-peroxidase technique was used and antigen retrieval was performed in a water bath at 98 °C using Retrieval solution for anti-Factor VIII, anti-cytokeratin and anti-vimentin antibodies. For anti-ERβ and anti-androgen receptor (AR), antigen retrieval was achieved by microwave. The slides were incubated overnight in a humid chamber with the primary antibody and for 30 min for each of the following steps: blocking endogenous peroxidase, blocking serum  and streptavidin peroxidase . Incubation with the secondary antibody  was performed for 45 min. The chromogen used was diaminobenzidine . Sections were counterstained with Harris hematoxylin. As a positive control for each antibody, the ovary of the animal was used because it expresses all the markers assessed. A negative control was performed by replacing the primary antibodies by IgG.Microscopically, the mass was composed of cuboidal or prismatic epithelial cells arranged in tubules, acini or cystic structures, which were sometimes filled with erythrocytes. The epithelium had a round basal nucleus with loose chromatin and the apex of the cell had a finely particulate PAS-positive material Fig. and b. ThEpithelial cells, especially prismatic cells, formed structures such as endometrial glands and demonstrated strong and diffuse cytokeratin expression Fig.  althoughModerate cystic endometrial hyperplasia with the presence of endometrial glands in the myometrium was observed in the uterus (adenomyosis). The right and left ovaries showed corpus luteum in regression and some follicles at different stages of development. The other organs showed no significant microscopic changes.Clinical and macroscopic findings of anemia may have been derived from extensive bleeding in the endometrial tissue. Cases of ascites associated with endometriosis have also been reported. It is suggested that the occurrence of ascites may be due to the rupture of cysts in the endometrial tissue with extravasation of fluid and red blood cells into the abdominal cavity. Moreover, when the formation of large masses occurs, as in this dog, lymphatic drainage may be impaired with extravasation of fluid from the endometrial tissue or from adjacent organs and tissue , 21–23. Despite the endometrioma, the dog had showed no disturbance of the estrous cycle or fertility as it had delivered normal viable full-term offspring previously. Unlike endometrioma, deep endometriosis is the main presentation that causes pelvic pain and infertility in women , 26. In The occurrence of endometriosis caused by cell implantation is unlikely in dogs because dogs lack the endometrial desquamation observed in women during menses and in non-human primates in the diestrus phase. In dogs, endometrial shedding does not occur and the bleeding during estrus comes from red cell diapedesis from blood vessels. In addition, female dogs have 3–10 months of anestrus characterized by the permanence of serum sex hormones at basal levels. Therefore, we suggest that these differences might favor, at least in part, the occurrence of endometriosis in women . HoweverStudies have demonstrated that estradiol plays an important role in the appearance, perpetuation and proliferative potential of the endometrial tissue , 14, 16.rete ovarii because such tumors have cysts averaged 8.7 cm, a flat, cuboidal, or columnar, usually nonciliated-lining epithelium and can sometimes present a fibromuscular wall [Despite the macroscopic characteristics of the mass described in some cases of endometrioma in women , 32, baslar wall , 34. Howlar wall , 34. Thelar wall , 36. Thelar wall . Howeverlar wall . Moreovelar wall –42.The endometrial tissue found in this bitch was restricted to a mass located adjacent to the uterus and ovary and fixed to the retroperitoneum. The association of the epithelium with a richly vascularized fibrous stroma observed in the present dog has also been described in endometrioma in women , 7, 43. The immunohistochemical characteristics of endometriosis have been widely studied. Similar to what was observed herein, ectopic endometrial cells are positive for cytokeratin  and may Immunohistochemical expression of COX2 and VEGF by endometrial epithelium and stromal cells was also observed in cases of endometriosis in women , 50. It Based on the macroscopic, microscopic and immunohistochemical findings, the diagnosis of endometrioma was confirmed. The occurrence of endometrioma in animal species with an estrous cycle is rare, and this is the first case described in dogs.


Bunyaviridae, genus Orthobunyavirus. These viruses are associated with fever and encephalitis, although INKV infections are not usually reported and the incidence is largely unknown. The aim of the study was to determine the prevalence of anti-INKV antibodies and associated risk factors in humans living in northern Sweden. Seroprevalence was investigated using the World Health Organization Monitoring of Trends and Determinants in Cardiovascular Disease study, where a randomly selected population aged between 25 and 74 years  was invited to participate. The presence of anti-INKV IgG antibodies was determined by immunofluorescence assay. Seropositivity for anti-INKV was significantly higher in men (46.9%) than in women . In women, but not in men, the prevalence increased somewhat with age (P = 0.06). The peak in seropositivity was 45–54 years for men and 55–64 years for women. Living in rural areas was associated with a higher seroprevalence. In conclusion, the prevalence of anti-INKV antibodies was high in northern Sweden and was associated with male sex, older age, and rural living. The age distribution indicates exposure to INKV at a relatively early age. These findings will be important for future epidemiological and clinical investigations of this relatively unknown mosquito-borne virus.The mosquito-borne Inkoo virus (INKV) is a member of the California serogroup in the family  Togaviridae, Flaviviridae, and Bunyaviridae. The genus Orthobunyavirus in the Bunyaviridae family has a growing number of strains. Among them, the viruses in the California serogroup are commonly found in the northern hemisphere, particularly in North America, although some―such as Inkoo virus (INKV), Tahyna virus (TAHV), and Snowshoe hare virus (SSHV) or the closely related Chatanga virus―are also present in Europe.Mosquito-borne viruses cause a variety of clinical syndromes in humans, and they include members of the Ochlerotatus communis mosquitoes in Finland, Sweden, and Russia, and from Ochlerotatus hexodontus and Ochlerotatus punctor in Russia.17INKV is known to circulate in northern Europe and Russia.The degree of exposure of the human population to INKV infection in Sweden is not known, so we wanted to investigate the prevalence of anti-INKV IgG antibodies. In this large randomized, stratified, and population-based survey in northern Sweden, we also investigated possible associated risk factors.In this study, we used data from the northern Sweden component of the World Health Organization Monitoring of Trends and Determinants in Cardiovascular Disease (WHO MONICA) study.18Of the 2,500 subjects invited, a total of 1,729 participated (69.2%) in the MONICA study in northern Sweden, which was used in the screening for anti-INKV IgG antibodies. Data on individuals who declined participation have been published.18Serological samples from 7.4% of subjects were missing. Thus, valid data were available for 1,607 subjects: 50.7% men and 49.3% women.The measurement procedures included blood pressure measured twice in a sitting position with an interval of 5 minutes. Subjects were weighed on an electronic scale. The highest level of education attained was classified as 1) primary school or secondary school (0–12 years of school) or 2) university studies. Regular smokers smoked at least one cigarette a day; all other subjects were considered to be nonsmokers. Subjects who answered yes to the question, “Do you have diabetes mellitus?” or the question, “Have you been treated for high blood pressure in the past two weeks” in the questionnaire were reported as having “known diabetes” and “hypertension.” Subjects who owned a farm were reported as being “farmers.”The study was approved by the Regional Ethical Review Board, Umeå, and all subjects gave informed consent.Serum samples obtained from the participants were stored at −80°C before analysis. Anti-INKV IgG antibodies were detected using a previously validated anti-INKV IgG immunofluorescence assay (IFA).N = 90) with negative, weakly positive, or strongly positive INKV IgG results from the IFA were verified with a neutralization assay to determine whether the IgG antibodies were specific to INKV, TAHV, or SSHV.3A subset of sera N = 0 with net test or χ2 test, and means and proportions were reported. When accounting for differences in sex and age between groups, general linear models were used. All P values < 0.05 were considered significant.Differences between groups were tested with P < 0.001). The proportion of men who were seropositive varied between the different age groups  but there was no linear relationship with increasing age . In women, the prevalence increased somewhat with age   than in women  (P < 0.03). No other background factors or prevalent disease showed any relationship with previous INKV infection. In an analysis taking gender into account, we found no differences in seropositivity for variables such as level of education, living on a farm, diabetes, and myalgia or arthralgia in either sex with the exception of men living on a small farm . However, the 95% confidence interval for this 18.2% difference in prevalence was 1.2–32%.Living in smaller communities or rural areas was associated with a higher prevalence of seropositivity (< 0.001)  . This pSeropositive subjects generally had higher body mass index, waist circumference, systolic and diastolic blood pressure, and serum creatinine (data not shown). After adjusting for the differences in sex and age, no differences between groups remained significant.Supplemental Table 1). As expected, there was some cross-reactivity with TAHV and SSHV. However, anti-INKV titers were approximately 4-fold higher than the antibody titers to the other viruses tested , with geometrical mean titers of 77 for anti-INKV, 28 for anti-SSHV, and 24 for anti-TAHV). One IFA-positive sample that did not neutralize any of the three viruses was observed, and interestingly, one of the weak IFA-positive samples had a high neutralization titer to TAHV only . Of the anti-INKV positive samples that neutralized INKV, 11 were further verified by PRNT, and they were all confirmed to be positive (data not shown).Because of the large number of anti-INKV antibody positives, a subset of serum samples (64 positive and 26 negative) was selected for verification of the anti-INKV IgG IFA results by a neutralization assay. The assay involved neutralization of three viruses from the California serogroup: INKV, TAHV, and SSHV. Altogether, 62 of 64 (97%) of the anti-INKV IgG IFA–positive samples, either strongly or weakly positive, specifically neutralized INKV and all anti-INKV IFA–negative serum samples were confirmed to be negative (There are numerous kinds of mosquito-borne viruses that may be a threat to public health. Members of the California serogroup are less well known, and there have been very few studies of the epidemiological and clinical properties of the European orthobunyavirus INKV. In this study, we found a high prevalence of anti-INKV antibodies in a population-based cohort from northern Sweden, and more so in men than in women. A similarly high seroprevalence has been shown in a previous study in Finland.9The strength of this study was the use of a large randomized and stratified population-based sample. The only background variable that was significantly associated with seropositivity was living in small communities or rural areas, which suggests more exposure to mosquitoes. All other associations noted could be explained by age and sex differences.We used a previously validated9We cannot completely rule out cross-reactivity to other members of the California serogroup, but positive samples had higher neutralization titers to INKV than to TAHV and SSHV, indicating the presence of anti-INKV antibodies. It is possible that some individuals had undergone infections by other orthobunyaviruses of the California serogroup, either through travel or locally. Interestingly, a SSHV-like Chatanga virus has been identified in the neighboring country Finland.3Intriguingly, the high prevalence of anti-INKV antibodies is not reflected by recognized cases of human infections. The high proportion of seropositive individuals already in the younger age group, 25–35 years, suggests that there is relatively early exposure to this mosquito-borne virus. Interestingly, for the mosquito-borne Sindbis virus, which is also present in northern Sweden, we found that virus antibodies were uncommon in young people, with no age-dependent increase, suggesting a recent introduction of Sindbis virus and increase in this region.21Ochlerotatus communis and Ochlerotatus punctor are very commonOur results indicate that INKV is widespread and highly endemic in northern Sweden, which may be explained in part by the fact that two of the suggested mosquito vectors, In conclusion, the high prevalence of anti-INKV antibodies indicates that this mosquito-borne viral pathogen has been very common in northern Sweden. The seroprevalence was found to be higher in men and in rural areas. These findings draw attention to the possible impact of this infection, which is still relatively unknown to the medical community. However, the clinical importance of INKV requires further studies of febrile cases during the mosquito season in endemic areas. More arbovirus studies are also needed to determine the factors that are important for its circulation and human infection.Supplemental Table.


In apple cultivation, simulation models may be used to monitor fruit size during the growth and development process to predict production levels and to optimize fruit quality. Here, Fuji apples cultivated in spindle-type systems were used as the model crop. Apple size was measured during the growing period at an interval of about 20 days after full bloom, with three weather stations being used to collect orchard temperature and solar radiation data at different sites. Furthermore, a 2-year dataset (2011 and 2012) of apple fruit size measurements were integrated according to the weather station deployment sites, in addition to the top two most important environment factors, thermal and sunshine hours, into the model. The apple fruit diameter and length were simulated using physiological development time (PDT), an indicator that combines important environment factors, such as temperature and photoperiod, as the driving variable. Compared to the model of calendar-based development time (CDT), an indicator counting the days that elapse after full bloom, we confirmed that the PDT model improved the estimation accuracy to within 0.2 cm for fruit diameter and 0.1 cm for fruit length in independent years using a similar data collection method in 2013. The PDT model was implemented to realize a web-based management information system for a digital orchard, and the digital system had been applied in Shandong Province, China since 2013. This system may be used to compute the dynamic curve of apple fruit size based on data obtained from a nearby weather station. This system may provide an important decision support for farmers using the website and short message service to optimize crop production and, hence, economic benefit. Apples are one of the four most popular fruits worldwide because of their high fruit quality, which is important for human health . Apple tThe fruit shape index (FSI) is the ratio between fruit length and diameter, and represents one of the most important traits of apple fruit external quality. In East Asia, cultivars with large FSI have greater economic potential in the fresh-product market . Many moPhysiological development time (PDT) was proposed in 1997 , which dThus, this study developed a simulation model of apple fruit size using PDT as the driving variable. We compared the results against the CDT model, and validated the model from field data. Finally, the model was implemented in a digital orchard management system conducted on web sites and cell phones.Malus domestica Borkh.) trees were selected on seedling rootstock tea crabapple (M. hupehensis [Pamp.] Rehd.) trees of uniform canopy size (3.5 × 3 m) with a thinned spindle-type training system, so that the crop loads of all trees were similar: 235 ± 20 fruits per tree in 2011, 206 ± 16 fruits per tree in 2012, and 220 ± 15 fruits per tree in 2013. This area of China is frequently subjected to periods of high summer and warm autumn temperatures, with a moderate amount of rainfall (680 mm/year) in the last 30 years (from 1981 to 2010). The annual mean temperature was 15.6 ºC, 16.1 ºC, and 16.5 ºC in 2011, 2012, and 2013, respectively, at the site, with a rising trend being documented over the last 30 years . These records support the global warming trend [This study was conducted from 2011 to 2013 in a private fruit orchard  at Chaoquan Town, Feicheng County, Tai’an, Shandong Province, China, with permission being provided by the host, Mr. Chengjun Yin. 12-year-old Fuji apple  at one-hour intervals. The three devices were placed between two apple trees in each row. The data were sent to a server in the office of the authors using general packet radio service (GPRS), and analyzed remotely.Two apple trees located close to each environment monitoring device were chosen, and randomly marked 10 apples in the mid-upper part of shoots positioned at four compass directions, East, South, West, and North, in each tree. At an interval of about 20 (from 10 to 40) days after full bloom, fruit length and size were taken using a Vernier caliper until the fruit had ripened and, afterward it harvested. The mean values for apple fruit sizes on the trees near to each device on each sampling date were computed, with this information being used as a reference for the simulation model. The apple fruits were measured eight times in 2011 and five times in 2012 and 2013, so the datasets consisted of the means of 20 fruits per monitoring location at five to eight dates during each season. Twenty-four, fifteen and fifteen samples were collected in 2011, 2012, and 2013, respectively. The data in 2011 and 2012 were used to establish the models, while the data in 2013 were used to validate the models.Fruit development was computed after full bloom, and the driving variable was changed from time t to PDT. PDT is the sum of the relative physiological development effectiveness (RPDE), which is the combination of the relative thermal effectiveness (RTE) and relative sunshine-hour effectiveness (RSE).RTE(T) and temperature maybe described by the following RTE(T) is the relative thermal effectiveness at daily temperature T, which is computed using mean hourly temperature; Tb is the lower temperature limit for apple development; Tm is the upper temperature limit for apple development; Tob and Tou are the lower and upper optimal temperature limits for apple development. These parameters were determined from the published literatures [The relationship between relative thermal effectiveness eratures –33.RSE(T) and daily sunshine hours is described by the following RPE(DL) is the relative photoperiodic effectiveness at the daily length of sunshine (DL); DL is defined as the number of daily sunshine hours (the time when solar radiation intensity ≥120 W/m2); DLc is the lower photoperiod limit for apple development; DLo is the optimum photoperiod for apple development [PDT is the sum of the RPDE each day after full bloom (DAFB) for apples.CDT is the sum of the DAFB of apples, which is calculated as an unit of days.The relationship between relative sunshine-hour effectiveness elopment .RPDE=RTThe relationship of PDT and CDT with fruit size was fitted following the logistic pattern using the nonlinear regression procedure (NLIN) with the Gauss–Newton method of the SAS program .The PDT model was expressed as:In addition, we used the CDT model for reference and comparison purposes:RMSE, Willmott agreement index (W), mean absolute error (MAE), and mean bias error (MBE) [Pi is the estimated values, Mi is the measured values, P′i is the deviations from mean estimated values, M′i is the deviations from mean measured values, and N is the sample size.The estimated and measured diameters of apple fruits were compared using random point figures. The graphical procedures in SAS were used to evaluate the model estimations facing actual measurements. Scatter plots of the model-estimated values were compared to the measured values were presented for each year. The REG Procedure of SAS was used to evaluate the linear relationship for the simulation versus the measurements for each year . Statistor (MBE) ; in whicThe model was implemented by Visual Studio 2005 (Microsoft Corporation) to generate a web service for the management information system of a digital orchard (MISDO). The system had several practical functions, such as Viewing orchard information, Querying fruit tree information, Diagram of production record, and Statistical analysis. Using the data from a nearby weather database in the orchard, the mean diameter and length of apples could be estimated by the PDT model . Using tR2 = 0.8881 to 0.9807 and W = 0.9263 to 0.9870. The estimation errors from 2011 and 2012 were less than 0.5 cm (MAE = 0.2494 to 0.4527). Thus, the two models could estimate fruit diameter to within 0.5 cm. The fruit size class at market is mostly expressed in millimeters, with the change from one class size to another generally being set at 5 mm or 0.5 cm intervals [The measurement and simulation results using the PDT and CDT models in 2011 Figs  and 3A antervals . TherefoMAE, MBE, and RMSE of the PDT model were 0.1908, -0.1514, and 0.2791, respectively, in 2013 (MAE), whereas that of the CDT model increased (to 0.3634 for MAE)  .R2 = 0.9108 to 0.9645 and W = 0.9744 to 0.9816. The estimation errors in 2011 and 2012 were less than 0.5 cm (MAE = 0.1960 to 0.2761). Thus, the PDT model could provide length estimation with the error being within 0.3 cm, which was similar to the diameter estimation results.The PDT and CDT models appeared to fit the fruit length measurement in 2011 Figs  and 3C aMAE, MBE, and RMSE of the PDT model were 0.1488, -0.1194, and 0.2127, respectively, in 2013. These parameters were 10.1%, 2.1%, and 7.2% lower than the CDT model , validated the PDT model, showing that it performed better than the CDT model. The reason for this difference may be climatic differences during the production years, with the calendar-based estimation requiring accumulated data from many years, leading to inevitable errors. Similar results have been reported in previous research , with apHere, the MISDO was developed to link with sensors, models, and systems, facilitating the provision of short message services to farmers. The system overcame the barrier of data input for decision making ,43, and PDT is the sum of the RPDE, and integrates thermal and sunshine hours, which are the top two most important environmental factors that influence apple fruit size. Unlike CDT, PDT is able to take into account variation in thermal and sunshine hours among years, facilitating greater flexibility in predictions. Using the measurements of fruit in an apple orchard during 2011 and 2012, four logistic models of fruit size (including diameter and length development) were computed using the PDT and CDT as the driving variables. Both models had similar performance based on the data used for model-establishment; however, the PDT model estimated the mean diameter and length of apple fruits with an error of within 0.2 cm in an independent year (2013), confirming that it was more robust than the CDT model. Furthermore, the PDT model provided the basis for predicting fruit weight, production, and external quality. The PDT model was also implemented into a digital orchard management information system to help farmers optimize fruit size by using fertigation, training, and microclimate control during the key stages of apple development.S1 Table(XLS)Click here for additional data file.


Health-service evaluation studies are fundamental for proposing interventions and ensuring improvements in healthcare quality. The present study assesses the performance of health services for indigenous and non-indigenous populations with regard to tuberculosis (TB) control.Primary Care Assessment Tool adapted for TB care in Brazil.Interviews with TB patients who underwent treatment between 2009 and 2011 were conducted using the Primary healthcare (PHC) was the first treatment for most patients at symptom onset, and the diagnoses were typically performed by specialized services. Many patients experienced delayed TB diagnoses that required more than three medical appointments . Indigenous people received social support, such as basic-needs grocery packages  and home visits from health professionals, with an emphasis on the performance of directly observed treatment strategies .Regardless of the differences between indigenous and non-indigenous populations, the time needed to receive a TB diagnosis was unsatisfactory for both groups. Furthermore, DOT must be performed with better coverage among non-indigenous patients. Mycobacterium tuberculosis. Brazil is among the 22 countries with the highest incidence of TB, with a rate of 43 cases per 100,000 inhabitants in 2010 [Tuberculosis (TB) is a worldwide health problem. One-third of the world’s population may be infected with  in 2010 .Since 1998, TB control has been the responsibility of Brazil’s primary healthcare . In receOperational studies are important because they provide information that may help services focus their practice more precisely and efficiently . AlthougDourados was a priority city for disease control determined by the National TB Control Program and includes the largest indigenous population of the State of Mato Grosso do Sul with a high incidence of TB. The incidence of TB in the urban population of Dourados is 44 cases per 100,000 inhabitants, and the incidence among the indigenous people of this municipality is even higher, at 230 per 100,000 inhabitants .Before 2000, TB treatment for indigenous patients was hospitalization for several months, and the default rate was 20% ,22. CrodTo clarify these initial findings, a cross-sectional study was proposed to evaluate the performance of two different TB control programs (indigenous and non-indigenous) in Dourados using a standardized tool to evaluate the performance of health services.This cross-sectional study was conducted in Dourados, Mato Grosso do Sul (MS). This city has 196,035 inhabitants, including 12,602 indigenous people (Guarani-Kaiowá ethnicity) who reside in the indigenous reserves of Bororó and Jaguapiru, the second largest indigenous population of the country.Dourados serves as a reference for 34 cities in the South region of the state in terms of healthcare, agriculture, and trading  is responsible for the management of a health and tuberculosis control program that manages the diagnosis and treatment of TB and notifies the Information System for Notifiable Diseases (SINAN) about TB infections in this population.The diagnosis of TB is accomplished by smear, culture, and X-rays . The BHUThe sample size required for the T-test was 49 patients, calculated using Statistica software ; mu1 = 2; mu = 3; sigma = 1.5; probability of type I error = 0.05; and power 0.9.The inclusion criteria were diagnosis with TB by the Notifiable Diseases Information System  and residence in Dourados during treatment between June 1, 2009 and July 31, 2011. Prisoners and patients with diagnosis changes were excluded from this study. Study attrition was due to patients who chose not to participate and those who died or abandoned treatment prior to the interview.Medical students received specific training, including a detailed description of the study and examples of interviewing techniques. They collected data during two periods: in the first month for the collection of sociodemographic and economic data and in the sixth month for the evaluation of health services data. Both data sets were collected at the patients’ homes after obtaining informed consent and explaining the purpose of the study.Indigenous health workers were present at all of the interviews conducted in the indigenous communities. These employees helped search for households, introduced the study staff, and translated when necessary.The instrument includes questions to elicit sociodemographic, clinical, and epidemiologic information, the location and type of treatment, and specific questions for each PHC component. The Primary Care Assessment Tool (PCAT)  was adapI. “Access”, which is divided into the categories “access to diagnosis” and “access to treatment”, includes the locations of the basic health units (BHUs), the hours/days that they are open, their degree of tolerance for unscheduled consultations, and the extent to which the population perceives that the access is convenient .II. “Bond” measures the existence of a regular source of care and use over time .III. “List of services” assesses arrangements for the patient to receive any type of required healthcare service .The respondent  answered each question on the form using a five-point Likert scale.The variables were entered twice into the Epi-Data program database, Version 3.0 and were analyzed using the Statistical Analysis Software Version 9.1 . The double entry of the questionnaire identified mistakes in typing.Frequency and mean distributions were used to describe the patients’ sociodemographic and clinical profiles. Means and standard deviations of the variables described using the Likert scale were analyzed and compared using the nonparametric Kruskal-Wallis test. These averages were evaluated on an intensity scale from one to five: (1) never, (2) almost never, (3) sometimes, (4) almost always, and (5) always. This order was reversed if necessary according to the observed variable. To evaluate the item “home visit”, the average number of times that health professionals delivered the drug was used, and the following scale values were assigned: (1) self-administered, (2) every 15 to 30 days, (3) 1 to 2 times a week, (4) 3 to 4 times a week, and (5) every day. All inquiries were made to all individuals. The no-answer condition was assigned a value of zero, “do not know”, which was not counted in the analysis of each question.Despite the use of the Kruskal-Wallis test when comparing the differences between the Likert scales, the results were deliberately presented in means and standard deviations to facilitate the visualization of the data. Dichotomous and categorical data were analyzed using the chi-square or Fisher’s exact tests.The PCAT’s reliability was assessed using its internal consistency and verified by Cronbach’s alpha. Values between 0.70 and 0.90 were considered acceptable .The Ethics Committee of the Federal University of Grande Dourados (nº 002/2009) and the National Committee for Research Ethics/National Health Committee  approved the present study.versus 81.5%, mortality rate 9.3% versus 6.7% and default rate of 0% versus 5.2% for indigenous and urban populations, respectively. Thus, 109 patients constituted the sample evaluation of health services  were excluded for not having a confirmed diagnosis or being in a seclusion regimen. Among the remaining 140 patients, 13 had follow-up losses due to our inability to locate, 11 died before the end of treatment, and six patients refused to participate in the study. Four non-indigenous patients presented treatment default. The cure rate was 90.6% 4.7% wereRegarding losses, no significant differences were found between the two groups. A total of 12 children required legal representatives to answer the PCAT, including 2/52 (3.8%) in the non-indigenous population and 10/57 (17.5%) in the indigenous population. There was no difference between those who self-responded and those who did not. The internal consistency coefficient  ranged from 0.71 to 0.80 for the Likert scale variables.Among the 109 patients with TB who were interviewed, men constituted the majority (60%). The indigenous patients had a lower mean age, less education, lower social class, and lower income per capita as well as more individuals per room compared with non-indigenous patients. Compared with the indigenous patients, the non-indigenous patients had higher rates of alcoholism, drug abuse, and human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) (Table Patients with TB in Dourados most often sought PHC at symptom onset (75% of indigenous patients and 65% of non-indigenous patients), and their diagnoses were primarily performed at specialized services . A delayed diagnosis of TB, which required more than three medical appointments (46% for indigenous patients and 44% for non-indigenous patients) and over five weeks (51% for indigenous patients and 47% for non-indigenous patients), was found with regard to both PHC and specialized services. For indigenous people, home visits by health professionals were offered more frequently, highlighting the performance of the strategies of directly observed treatment (DOT) Table .Regarding compliance/bond, the indigenous patients with TB felt that they were not as well understood as non-indigenous patients when asking questions Table .Fewer indigenous patients had access to HIV/AIDS testing compared with non-indigenous patients. Furthermore, the indigenous patients were less likely to spend money to reach the BHUs, and they were treated at the BHU closest to their homes. Moreover, the indigenous patients were more likely to receive social support, such as basic-needs grocery packages and home visits from health professionals, when the performance of DOTS was emphasized compared with non-indigenous patients Table .Despite the differences between the indigenous and non-indigenous groups, the time to diagnosis was shown to be unsatisfactory in both groups. Previous studies have also found delayed TB diagnoses -32. As aIndigenous families are large and have more people per room than non-indigenous families . The size and number of rooms in the home together with aglomeration are factors that influence the risk of TB transmission  and can In this study, home visits for the treatment of tuberculosis occurred less frequently in the non-indigenous population . A study conducted by Croda et al.  observed. This perspective emphasizes the need to expand the diagnosis of tuberculosis and to offering more X-rays and smears in primary healthcare. This approach would provide the opportunity for earlier diagnosis by decreasing the time to diagnosis and the number of late diagnoses in emergency and secondary or tertiary services.The WHO highlights the importance of the organizational and performance dimensions of healthcare services (HS), stating that the problem does not lie in detecting or treating TB, but in how healthcare services are organized to detect and treat cases of TB . This peAlthough the majority of patients sought medical care at the PHC, the current study showed that most TB diagnoses were performed in emergency departments and hospitals. The healthcare model found in the municipality explains this trend because the Mission Hospital specializes in TB diagnosis among the indigenous population, whereas University Hospital primarily serves the non-indigenous population. These findings are similar to several studies conducted in Brazil ,13.Supplying HIV/AIDS exams did not result in satisfactory performance, particularly among the indigenous population. In Brazil, it is recommended that the investigation of HIV should be supplied to 100% of TB patients -39.The indigenous patients felt that they were not as well understood as the non-indigenous patients when they asked health questions. Indigenous people consider diseases to be individual, a sign of social or world disorder, which contradicts the understanding of occidental biomedicine . SensitiThis study has limitations related to possible sample selection bias because of participant attrition related to death and treatment default, which led to the non-completion of the questionnaire and the exclusion of data from the analyses. Communication difficulties with the indigenous community were not reduced even in the presence of an indigenous health worker. This difficulty was due to both the low level of education and the language barriers, which resulted in a lack of understanding of certain terms and phrases as well as difficulty in responding according to the Likert scale. The instrument is extensive and requires response measures. The application of the PCAT for the indigenous population may not be the best alternative, although it is the only validated instrument in Brazil for the evaluation of health services in primary tuberculosis.Despite these limitations, this study showed that after operating the decentralization process, there were improvements in TB control among the indigenous population, with home visits providing a reduction in the incidence rate. In the non-indigenous population, despite decentralization, there is a lack of access to diagnosis and a need for greater coverage and commitment of health professionals in providing the DOT.Despite the differences between the indigenous and non-indigenous groups, the time to diagnosis was shown to be unsatisfactory in both groups. In particular, the rapid HIV-AIDS test should be offered through primary healthcare, especially in indigenous communities. For non-indigenous people, improvements in access to diagnosis and treatment are necessary, especially with regard to greater coverage of DOT. Incentives for the strengthening of primary healthcare with the co-responsibility of other services may contribute to effective improvements in TB treatment.PHC: Primary healthcare; DOTS: Directly Observed Treatment Strategy; UH: University Hospital; PCAT: Primary care assessment tool; SESAI: Special Indigenous Health Agency (Secretaria de Saúde Indígena); SINAN: Notifiable diseases information system (Sistema de Informação de Agravos e Notificação); TB: Tuberculosis; BHU: Basic health unit; HS: Healthcare services.The authors declare that they have no competing interests.EFL coordinated and drafted the manuscript, designed the study, and participated in the data analysis and discussion. JC coordinated the research project, designed the study, analyzed the data, and contributed to the discussion. AMSA, GCO, MPR, and NDGM collected the data, analyzed the data, and contributed to the discussion. All authors interpreted the results and read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1472-6963/14/237/prepub


Although the effects of socioeconomic status (SES) on mortality are well established, these effects may vary based on contextual factors such as race and place. Using 25-year follow-up data of a nationally representative sample of adults in the U.S., this study had two aims: (1) to explore separate, additive, and multiplicative effects of race and place (urbanity) on mortality and (2) to test the effects of education and income on all-cause mortality based on race and place.The Americans’ Changing Lives (ACL) Study followed Whites and Blacks 25 years and older from 1986 until 2011. The focal predictors were baseline SES (education and income) collected in 1986. The main outcome was time until death due to all causes from 1986 until 2011. Age, gender, behaviors (smoking and exercise), and health  at baseline were potential confounders. A series of survey Cox proportional hazard models were used to test protective effects of education and income on mortality based on race and urbanity.Race and place had separate but not additive or multiplicative effects on mortality. Higher education and income were protective against all-cause mortality in the pooled sample. Race and urbanity significantly interacted with baseline education but not income on all-cause mortality, suggesting that the protective effect of education but not income depend on race and place. While the protective effect of education were fully explained by baseline health status, the effect of income remained significant beyond health.In the U.S., the health return associated with education depends on race and place. This finding suggests that populations differently benefit from SES resources, particularly education. Differential effect of education on employment and health care may explain the different protective effect of education based on race and place. Findings support the “diminishing returns” hypothesis for Blacks. The protective effects of socioeconomic status  on health are consistently shown . MirowskIn the U.S., the education system and job market are both segregated by race, place, and social class , 13. As Our knowledge of the effect of place on health is mostly limited only to the direct effect , 26. ResThis study investigated separate, additive, and multiplicative effects of race, place, and SES (education and income) on mortality. We were particularly interested in the moderating effects of race and place on the protective effects of baseline education and income (in 1986) on all-cause mortality during a 25-year follow-up in the U.S. We had three specific hypotheses: first, race and place would have separate, additive, and multiplicative effects on mortality. Second, the effects of education and income on mortality would be weaker for Blacks compared to Whites. Third, we expect urbanity to modify the effect of education and income on all-cause mortality. To provide generalizable results to the U.S., we used a nationally representative sample of American adults.The ACL is a 25-year cohort study conducted from 1986 to 2011. The ACL study is the oldest ongoing longitudinal study with a nationally representative sample. The aim of the study is to investigate the role of a broad range of social, environmental, psychological, and behavioral factors  in health changes with age over the life course. The study began in 1986 with a national face-to-face survey of 3,617 adults ages 25 and up in the continental U.S. –41.n = 3,617) aged 25 and older in 1986 . Both individuals over 60 years of age and Blacks were oversampled , race , and age in years (a continuous variable).Participant’s race was defined based on self-reported race and ethnicity, collected at baseline in 1986 with several survey items. Respondents gave an open-ended response to the question, “In addition to being American, what do you think of as your ethnic background or origins?” Respondents were then asked a multiple-choice question, “Are you white, black, American Indian, Asian, or another race?” and allowed to answer with multiple categories. Those who responded with more than one non-white group were asked to identify which “best described” their race. The survey also assessed the state or foreign country in which the respondent, respondent’s mother, and respondent’s father were born, and the respondent’s father’s last name. Finally, participants were asked “Are you of Spanish or Hispanic descent, that is, Mexican, Mexican–American, Chicano, Puerto Rican, Cuban, or Other Spanish?” Responses from the above questions were used to construct race categories of “Non-Hispanic White,” “Non-Hispanic Black,” “Non-Hispanic Native American,” “Non-Hispanic Asian,” and “Hispanic.” This study’s analysis only included Non-Hispanic White and Non-Hispanic Black respondents –41.We collected information on urbanity at an individual level. We defined urbanity as a three-level categorical variable. Multiple items were used to define urbanity in this study. Categories included (1) inner cities (urban areas), defined as the centers  of cities, which are classified as metropolitan statistical areas greater than or equal to 50,000 people; (2) suburban areas, defined as suburbs to large or small central cities, and (3) rural areas, defined as other adjacent and outlying areas. Our urbanity measure is comparable with the Rural-Urban Continuum Codes, developed by the USDA Economic Research Service . This syEducation, measured in 1986 as years of completed education, was the first SES predictor of interest. Due to low frequency of tertiary education among Blacks in 1986, we operationalized education in two ways: a continuous measure, reflecting years of education, and a three-level categorical variable . Other studies have operationalized education similarly –47.We measured baseline income  in 1986 as our second SES predictor of interest.Number of chronic medical conditions (CMC) was measured using self-report data at baseline (1986). All participants were asked whether a health-care provider had ever told them they had any of the following seven focal conditions: hypertension, diabetes, chronic lung disease, heart disease, stroke, cancer, and arthritis. A sum score was calculated, ranging from 0 to 7. A detailed description on the measurement of CMC is provided elsewhere in House and colleagues .Respondents were asked to rate their self-rated health (SRH) as excellent, very good, good, fair, or poor. The literature has treated the SRH in three distinct ways, namely as a dichotomous variable, a nominal variable, and a continuous score –51. We tDepressive symptoms were measured with an 11-item version of the Center for Epidemiological Studies-Depression scale (CES-D) . CES-D iA physical activity index was derived from answers to survey questions regarding engagement in exercise, active sports, gardening/yard work, household chores, and walking. Higher scores on this index were indicative of more exercise frequency , 56.Information was collected on self-reported history of smoking. We used a dichotomous variable .The main outcome variables were mortality from all causes, internal causes, and external causes. Information on all deaths from mid-1986 through 2011 was obtained through the National Death Index (NDI), death certificates, and also from informants. In most cases, time and cause of death were verified with death certificates. The handful of cases where death could not be verified with death certificates were reviewed carefully, and actual death was certain in all cases. Only in these cases, lacking death certificates was the date of death ascertained from the informants or the NDI report , 57, 58.Due to the complex sample design used in the ACL, Stata 13.0  was used for data analysis. Application of baseline weights provides rates and results that are generalizable to the US population in 1986. Taylor series linearization was used for estimation of SEs.p < 0.01 as the level of statistical significance. For comparability, all main effects and interaction terms were left in models if they were not significant.We estimated seven Cox proportional hazard models to determine the effects of education and income on mortality. Baseline SES (education and income) collected in 1986 was the focal predictor, time to death through 2011 from all causes was the main outcome, and age, gender, and health  were confounders. Hazard ratios (HRs) with 95% confidence intervals are reported. A HR of <1 indicates a protective effect of the independent variable on the outcome. Because we consider multiple outcomes, we set Model 1 estimated age- and gender-adjusted effect of race. Model 2 tested age- and gender-adjusted effects of place. Model 3 estimated additive (combined) effects of race and place. Model 4 also controlled for SES, to test if education and income explain the effect of race and place on mortality. Model 5 also controls for health, in addition to SES. Models 3–5 also included interactions between race and place to test multiplicative effects of race and place. Model 6 and Model 7 included interaction terms between race and place with education and income. While Model 6 did not include health status, Model 7 controlled for baseline health.p > 0.05 for both comparisons), average education  and income  were lower for Blacks than Whites. Mortality was higher among Blacks (39.41%) compared to Whites (35.66%) (p < 0.05).Table Model 1 reports the age- and gender-adjusted effect of race. Based on this model, race had a significant age- and gender-adjusted effect on mortality . Model 2 reports age- and gender-adjusted effects of place. Based on Model 2, place also had a separate effect on mortality risk. Based on this model, compared to residing in the inner city, living in suburban areas  was marginally associated with lower mortality risk, while residence in rural areas  was significantly associated with lower mortality risk. Model 3 reports the additive effects of race and place. Based on this model, the effect of place on mortality did not remain above and beyond race . Model 4 also controls for SES and shows that education and income explain the effect of race on mortality. In this model, education  and income  were protective against mortality. Model 5 also controls for health, as well as SES. Based on this model, the effect of education on mortality is explained by health (p > 0.05). However, the effect of income on mortality stays in the model . Based on Models 3–5, race and place did not have multiplicative effects, as interaction terms between race and urbanity were non-significant .Table Model 6 and Model 7) that included interaction terms between race, place, education, and income. While Model 6 did not include health status, Model 7 also controlled for baseline health. Based on Model 6, race moderated the effect of education but not income on mortality. In this model, we found a significant interaction term between race and education . This model also showed a marginally significant interaction between place and education . In Model 7, which also controlled for health, the interaction term between race and education stayed significant , but the interaction between place and education was explained by baseline health status (p > 0.05).Table diminishing returns hypothesis for Blacks. Based on this hypothesis, as education levels increase, Blacks do not gain as much improvement in health as Whites . The lower health gain of educational attainment for Blacks compared to Whites is possibly due to structural racism, which even blocks gains associated with education for Blacks. Future research should explore mechanisms by which race and place alter the effects of health return associated with education in the U.S.All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation  with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was obtained from all participants included in the study. The study protocol received approval by the Institutional Review Board of the University of Michigan.No animal studies were carried out by the authors for this article.SA designed the study, analyzed the data, and contributed to the revision. ML drafted the manuscript and revised the paper.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


This study focused on low-income rural and nomadic minority people residing in China's far west and investigated their relationship between inflammatory markers  and MS and ethnic differences. And it found that improving behavioral lifestyle by education or using drugs to control inflammation may prevent MS. These observations may benefit low-income populations. Metabolic syndrome (MS) comprises a cluster of clinical metabolic diseases that include hypertension, insulin resistance (IR), obesity, and dyslipidemia –3. MS isChina is a multiethnic country, with more than 10 ethnic groups in Xinjiang. In this region, Kazakh and Uyghur populations constitute large minority groups, with most individuals residing in low-income rural communities . For exaMS is a chronic, low-grade, systemic inflammatory state , and theHowever, these findings were primarily obtained in high-income and urban settings, whereas little information has been gathered in low-income rural settings. Specifically, data concerning inflammatory marker levels and their relationship with MS in Uyghur and Kazakh people and data concerning differences between these two local minority groups are lacking. In this study, we analyzed the relationships between inflammation and MS and the possible differences between these ethnic groups residing in far western China to examine the reasons underlying the incidence of MS in Xinjiang.The Institutional Ethics Review Board (IERB) at the First Affiliated Hospital of the Shihezi University School of Medicine approved the study (IERB no. SHZ2010LL01). Standard university hospital guidelines, including informed consent, voluntary participation, confidentiality, and anonymity, were followed. All of the participants provided written informed consent before the study began.This study was conducted from 2009 to 2012 among Uyghurs residing along the Bazi Xiang River region of Jiashi and Kazakhs residing in Nalati township of Yili in Xinjiang. For the basic survey, we divided subjects from the two ethic groups into MS and non-MS groups according to the 2005 IDF criteria. Using a random number table in SPSS 19.0, we then randomly selected 218 and 156 cases from the MS groups and 201 and 180 cases from the non-MS groups of the Uyghur and Kazakh populations, respectively, for laboratory testing.(1) MS was defined by central obesity according to the IDF (modified guidelines of the WHO for the Asia Pacific region) , a waistμIU] per mL) × fasting glucose (in mM)/22.5 . All of the rates were compared using the Chi-square test. Differences of P < 0.05 were considered to be statistically significant.All of the analyses were performed using the SPSS statistical package for Windows (version 19.0). Continuously and normally distributed variables were analyzed using P > 0.05 for each comparison). Among Uyghurs and Kazakhs, BMI, WC, SBP, DBP, TG, HDL-C, FPG, LDL-C, and TC levels were higher in the MS group than in the non-MS group (P < 0.05 for each comparison). However, there were no differences between the two ethnicities, regardless of whether they were classified in the MS or non-MS group (P > 0.05 for each comparison) (Average age and gender were not significantly different between the MS and non-MS groups in the Uyghur and Kazakh populations or between the two ethnicities (parison) .P < 0.01 for each comparison). Conversely, adiponectin levels displayed the opposite trends (P < 0.01 for each comparison)  .1 group to the Q4 group, the rates of detection for MS and its components in Uyghurs and Kazakhs tended to increase as the levels of IL-6, hsCRP, and FFA increased. Comparing the Q4 and Q1 groups, all OR values were >1, indicating that the Q4 group's risk was higher than that of the Q1 group. However, the adiponectin levels exhibited opposite results (Tables From the Qs Tables –6.P < 0.01 for each comparison); however, this trend was more obvious for Kazakh individuals, as shown in the top curve. In contrast, adiponectin levels showed the opposite trend  . In factThe current study analyzed the relationship between MS and inflammation in adults of rural Kazakh and Uyghur populations in northwest China. We determined that, for both populations, IL-6, hsCRP, and FFA levels were higher in the MS group than in the non-MS group and that adiponectin is an adipose tissue factor that could improve IR. This trend is similar to those reported in domestic and foreign research, though the levels in our study are higher –28. Nish1 group to the Q4 group. The results demonstrated increasing trends for the levels of IL-6, hsCRP, and FFA. Moreover, the OR values were >1 for the Q4 and Q1 groups, predicting that the incidence risk of MS and its components is higher in the Q4 group. However, the opposite trends were observed with increased adiponectin levels.Nishida et al. reported that individuals with an increased number of MS components have higher CRP levels . In anotUyghurs and Kazakhs are the two main ethnic groups in Xinjiang, and their unique geographical environment and living habits are very different from those of the rest of the country. For instance, their economy is primitive, their environment is harsh, their education and medical knowledge are deficient, and their self-awareness of prevention and treatment is poor. Additionally, the staple of their diet is Nang, which contains a large amount of salt, and they do not eat many fruits or vegetables. Indeed, Kazakhs consume Nang three times a day and are accustomed to drinking tea with plenty of salt and milk. They also frequently consume cured meat, which may lead to higher prevalence of MS and its components in Kazakhs compared to Uyghurs. The reported prevalence of MS in Kazakhs is 26.6% , whereasWe could not establish causal relationships in our study due to its cross-sectional design, and we did not collect data on the socioeconomic or environmental variables that could have an impact on MS. We also recruited subjects during a local investigation in northwest China and not from hospitals or other medical institutions. Subjects from hospitals or other medical institutions could be more representative, and the use of such a sample could have allowed us to explore the relationship between MS and inflammation over a range of demographic groups. Nonetheless, these findings provide important demographic insight into the growing problem of MS in rural Kazakh and Uyghur populations.In conclusion, this study explored the relationship between MS and inflammation among Uyghur and Kazakh people. Despite the higher prevalence of MS in these groups compared with the rest of China, to date, few studies have investigated the underlying reasons for this higher prevalence. We observed that the abnormal expression of inflammatory cytokines might contribute to the high prevalence of MS, which could be associated with the characteristics of the different ethnicities and areas . To prevent MS, these groups could improve their lifestyle behaviors through education or medication to control IL-6, hsCRP, FFA, and adiponectin levels. Therefore, our observations and recommendations should be used to establish appropriate public health policies to benefit low-income populations.