Supplementary material - Cambridge University Press



Epidemiology and InfectionSeasonality of urinary tract infections in the United Kingdom in different age groups: longitudinal analysis of The Health Improvement Network (THIN) A. ROSELLO*1,2, K. B. POUWELS1,3, M. DOMENECH DE CELL?S4, E. VAN KLEEF5,6, A. C. HAYWARD2,7, S. HOPKINS8,9, J. V. ROBOTHAM1, T. SMIESZEK1,3, L. OPATOWSKI4 and S. R. DEENY10.Supplementary materialAppendix 1- Tables and FiguresTablesTable S1. Studies that analysed the seasonality of UTIAuthorYearCountryCommunity/ hospitalOrganismSexAgeSeasonalityMethodsStansfeldADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "ISSN" : "0007-1447", "PMID" : "5908707", "author" : [ { "dropping-particle" : "", "family" : "Stansfeld", "given" : "J M", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "British medical journal", "id" : "ITEM-1", "issue" : "5488", "issued" : { "date-parts" : [ [ "1966", "3" ] ] }, "page" : "631-5", "title" : "Clinical observations relating to incidence and aetiology of urinary-tract infections in children.", "type" : "article-journal", "volume" : "1" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[1]", "plainTextFormattedCitation" : "[1]", "previouslyFormattedCitation" : "[1]" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }[1]1966EnglandHospitalAllAll0-12In cases >1 year age, 96 in winter and 58 in summer (significant at 1% level)UnknownAndersonADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "abstract" : "SUMMARY Bacterial infections of the female urinary tract (UTI) are a frequent clinical problem. A chance observation, supported by a one year survey reported from another country, suggested that UTI presented to the general practitioner more frequently in the summer. A retrospective survey, covering three consecutive years, was carried out to test this observation. The records of all women reported as attending this practice with a UTI showed that 213 culture positive episodes occurred in the third calendar quarter of each year. Edward's test for cyclic variation showed a significant peaking in August. These results indicate a definite seasonal fluctuation in the frequency with which symptomatic UTIs present to general practitioners in this practice. The clinical and epidemiological significance of this phenomenon remains to be determined. Bacterial infections of the urinary tract (UTI) are a common problem in women. General practitioners have reported encounter rates of from eight to 17 per thousand registered patients.1\"3 Surveys for asymptomatic UTI have estimated prevalence rates of 5-10% in populations of sexually active women.4 Despite the common nature of the problem, there remain gaps in our knowledge about it. From the epidemiological standpoint, the abrupt rise in frequency during late adolesence and early adulthood has been ascribed to sexual activity.5 Both Asscher and Rocha have concluded that race has no significant effect on prevalence rates,6 7 although Bailey has noted a high rate in Maori women.4 Increasing age seems associated with increased risk, independent of sexual activity and parity.6 Kunin has stated that neither the use of oral contraceptives nor different modes of menstrual hygiene \"appear to affect the frequency of bacteriuria.\"8 A chance observation in the practice at the Hotel Dieu Family Medicine Centre of Queen's University raised the possibility of a seasonal fluctuation in the frequency of UTI, with a peaking in the summer. This possibility was strengthened by similar findings in a one year study in Denmark.9 In contrast, peak rates in children have been reported to occur in the winter in both England'\u00b0 and Finland.1\"", "author" : [ { "dropping-particle" : "", "family" : "Anderson", "given" : "John E", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Journal of Epidemiology and Community Health", "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "1983" ] ] }, "page" : "286-290", "title" : "Seasonality of symptomatic bacterial urinary infections in women", "type" : "article-journal", "volume" : "37" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[2]", "plainTextFormattedCitation" : "[2]", "previouslyFormattedCitation" : "[2]" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }[2]1983CanadaCommunityAllFemales15 or olderAugust peakEdward's test for cyclic variationPead et al.ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "ISSN" : "0267-0623", "PMID" : "3931834", "abstract" : "Over six years (1978-83, inclusive) weekly laboratory records of organisms causing urinary tract infection in women aged 15-25 not attending hospital were kept prospectively and analysed. The incidence of infection with Staphylococcus saprophyticus defined by age and sex was confirmed. This organism caused an increasing proportion of infections in young women over the six years studied, and these infections showed noticeable seasonality. All but four isolates of S saprophyticus were sensitive to all the commonly used antimicrobial agents that were tested. This might be because the organism is not often present in the body as a commensal and therefore not subject to the selection pressures exerted by such agents. As infection with S saprophyticus has different clinical connotations from infection with other coagulase negative staphylococci it should be differentiated from them in routine laboratory practice.", "author" : [ { "dropping-particle" : "", "family" : "Pead", "given" : "L", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Maskell", "given" : "R", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Morris", "given" : "J", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "British medical journal (Clinical research ed.)", "id" : "ITEM-1", "issue" : "6503", "issued" : { "date-parts" : [ [ "1985", "10", "26" ] ] }, "page" : "1157-9", "title" : "Staphylococcus saprophyticus as a urinary pathogen: a six year prospective survey.", "type" : "article-journal", "volume" : "291" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[3]", "plainTextFormattedCitation" : "[3]", "previouslyFormattedCitation" : "[3]" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }[3]1985EnglandCommunityAllFemales15-25S. saprophyticus UTI peak in mid-September. Coliform (all Gram-negative bacilli other than Proteus spp. and Pseudomonas spp.) UTI peak in mid-MarchChi-squared testVorland et al.ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "ISSN" : "0066-4804", "PMID" : "3885842", "abstract" : "Escherichia coli strains from outpatient urinary tract infections in northern Norway over a period of 1 year were examined for resistance to nine commonly used antibiotics. Strains collected during 4.5 months were examined for R plasmid content by using conjugation and in vitro transformation. Of the E. coli strains, 42% were resistant to one or more antibiotics. Resistance was highest to sulfonamide (20.8% of all strains), nitrofurantoin (14.5%), and tetracycline (10.1%), whereas less than 6% of the strains were resistant to ampicillin, carbenicillin, cephalothin, nalidixic acid, or trimethoprim-sulfamethoxazole. No strain was resistant to gentamicin. Tetracycline resistance was more common in men than in women. Resistance to cephalothin, nalidixic acid, and sulfonamide was higher in strains from older people. Resistance to sulfonamide was more frequent in the urban community. These was no seasonal variation in antibiotic resistance, although the incidence of urinary tract infection varied with seasons. Plasmid-determined resistance to ampicillin, streptomycin, sulfonamide, and tetracycline was found. About 18% of the resistant strains from the urban municipality carried R plasmids, most of which were small plasmids mediating resistance to sulfonamide and streptomycin. The overall frequency of resistance in strains collected from rural areas was similar to the urban frequency, but in the rural strains, R plasmids were found in only 5% of the resistant strains.", "author" : [ { "dropping-particle" : "", "family" : "Vorland", "given" : "L H", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Carlson", "given" : "K", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Aalen", "given" : "O", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Antimicrobial agents and chemotherapy", "id" : "ITEM-1", "issue" : "1", "issued" : { "date-parts" : [ [ "1985", "1" ] ] }, "page" : "107-13", "title" : "Antibiotic resistance and small R plasmids among Escherichia coli isolates from outpatient urinary tract infections in northern Norway.", "type" : "article-journal", "volume" : "27" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[4]", "plainTextFormattedCitation" : "[4]", "previouslyFormattedCitation" : "[4]" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }[4]1985NorwayCommunityE. coliAllAllHigher incidence from September to December (10.2 per 1,000 inhabitants) than from January to April (8.6 per 1000 inhabitants) or May to August (6.2 per 1,000 inhabitants), but non-significant.Chi-squared testFerry et al.ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "ISSN" : "0281-3432", "PMID" : "3616271", "abstract" : "During a 12-month study at the primary health care (PHC) centre in V\u00e4nn\u00e4s (population 8,000) 632 encounters by 265 individuals because of suspected urinary tract infection (UTI) or control after treatment resulted in 279 episodes of bacteriuria in 185 patients. Nine per cent of the episodes concerned patients with indwelling catheter or incontinence requiring other aids. Symptoms of lower and higher UTI were recorded in 56 and 12%, respectively, whereas one third of the episodes were associated with vague or no symptoms and discovered mainly at planned treatment controls. The annual incidence of bacteriuria recorded increased from 0.5% in the first decade of life to more than 10% in the age group 90-100 years. Male UTI comprised 13% of the episodes, increased after middle age and contributed 40% at greater than or equal to 80 years of age. The risk of recurrence (on average 50% during the year studied) was relatively independent of sex and age. No seasonal variation of UTI was observed except for a peak in late summer due to Staphylococcus saprophyticus confined to females aged 15-64 years and causing 28% of the episodes in August. Although UTI in PHC appears to be similar globally it represents a far more complex patient group than indicated by the UTI drug trials frequently published.", "author" : [ { "dropping-particle" : "", "family" : "Ferry", "given" : "S", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Burman", "given" : "L G", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Mattsson", "given" : "B", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Scandinavian journal of primary health care", "id" : "ITEM-1", "issue" : "2", "issued" : { "date-parts" : [ [ "1987", "5" ] ] }, "page" : "123-8", "title" : "Urinary tract infection in primary health care in northern Sweden. I. Epidemiology.", "type" : "article-journal", "volume" : "5" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[5]", "plainTextFormattedCitation" : "[5]", "previouslyFormattedCitation" : "[5]" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }[5]1987SwedenCommunityAllAllAllNo seasonality in E. coli UTI but August peak in S. saprophyticus UTIsComparing incidenceStamm et al.ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "ISSN" : "0162-0886", "PMID" : "2017637", "abstract" : "To evaluate the natural history of uncomplicated urinary tract infections in women, we observed 51 infection-prone women in a standardized fashion for a median of 9 years. During intervals when patients were not receiving antimicrobial prophylaxis, infections occurred at an average rate of 2.6 per patient-year, but the rate varied widely from patient to patient (range 0.3-7.6 episodes per year). Seventy-three percent of the observed episodes were symptomatic, with an 18:1 ratio of cystitis to pyelonephritis episodes. Infectious episodes were strikingly clustered, and rates of infection decreased in the winter months. Antimicrobial prophylaxis was highly effective in preventing acute cystitis, asymptomatic bacteriuria, and acute pyelonephritis, even when used for as long as 5 years. The proportions of infecting strains resistant in vitro to ampicillin (19%-32%) and nitrofurantoin (5%-18%) were unchanged over the 15-year observation period, while resistance to trimethoprim-sulfamethoxazole increased in the last 5 years of the study.", "author" : [ { "dropping-particle" : "", "family" : "Stamm", "given" : "W E", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "McKevitt", "given" : "M", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Roberts", "given" : "P L", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "White", "given" : "N J", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Reviews of infectious diseases", "id" : "ITEM-1", "issue" : "1", "issued" : { "date-parts" : [ [ "1991" ] ] }, "page" : "77-84", "title" : "Natural history of recurrent urinary tract infections in women.", "type" : "article-journal", "volume" : "13" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[6]", "plainTextFormattedCitation" : "[6]", "previouslyFormattedCitation" : "[6]" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }[6]1991USAOutpatient recurrence clinicAllFemalesAllDecrease in incidence November to FebruaryWilcoxon's signed-rank testKwok et al.ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1186/1471-2431-6-10", "ISSN" : "1471-2431", "PMID" : "16584577", "abstract" : "BACKGROUND We aimed to investigate incidence rates of urinary tract infections in Dutch general practice and their association with gender, season and urbanisation level, and to analyse prescription and referral in case of urinary tract infections. METHOD During one calendar year, 195 general practitioners in 104 practices in the Netherlands registered all their patient contacts. This study was performed by the Netherlands Institute for Health Services Research (NIVEL) in 2001. Of 82,053 children aged 0 to 18 years, the following variables were collected: number of episodes per patient, number of contacts per episode, month of the year in which the diagnosis of urinary tract infection was made, age, gender, urbanisation level, drug prescription and referral. RESULTS The overall incidence rate was 19 episodes per 1000 person years. The incidence rate in girls was 8 times as high as in boys. The incidence rate in smaller cities and rural areas was 2 times as high as in the three largest cities. Throughout the year, incidence rates varied with a decrease in summertime for children at the age of 0 to 12 years. Of the prescriptions, 66% were in accordance with current guidelines, but only 18% of the children who had an indication were actually referred. CONCLUSION This study shows that incidence rates of urinary tract infections are not only related to gender and season, but also to urbanisation. General practitioners in the Netherlands frequently do not follow the clinical guidelines for urinary tract infections, especially with respect to referral.", "author" : [ { "dropping-particle" : "", "family" : "Kwok", "given" : "Wing-Yee", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Kwaadsteniet", "given" : "Marjolein C E", "non-dropping-particle" : "de", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Harmsen", "given" : "Mirjam", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Suijlekom-Smit", "given" : "Lisette W A", "non-dropping-particle" : "van", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Schellevis", "given" : "Fran\u00e7ois G", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Wouden", "given" : "Johannes C", "non-dropping-particle" : "van der", "parse-names" : false, "suffix" : "" } ], "container-title" : "BMC pediatrics", "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2006" ] ] }, "page" : "10", "title" : "Incidence rates and management of urinary tract infections among children in Dutch general practice: results from a nation-wide registration study.", "type" : "article-journal", "volume" : "6" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[7]", "plainTextFormattedCitation" : "[7]", "previouslyFormattedCitation" : "[7]" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }[7]2006NetherlandsCommunityAllAll0-18Decrease in the summer months mainly in children 0-12Comparing incidence ratesFalagas et al.ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1007/s10096-008-0679-z", "ISSN" : "1435-4373", "PMID" : "19104854", "abstract" : "Several types of infections involving the respiratory tract have a seasonal variation. We further examined whether lower urinary tract infections (UTIs) are associated with meteorological parameters. We retrospectively evaluated the correlation of the weekly percentage of house call visits for lower UTIs (relatively to all house call visits, excluding those for respiratory tract infections), performed by \"SOS Doctors\" specialized physicians in Attica, Greece (1/11/2000-18/1/2005), with the average weekly temperature and humidity, recorded at the same area, 3 days earlier. Three thousand two hundred and twenty-one visits for lower UTIs were recorded in patients of 62.9 +/- 21.0 years of age. House call visits for lower UTIs, as defined above, correlated with the average weekly temperature (Spearman's rho+0.468) and humidity (Spearman's rho -0.394); similarly, if respiratory tract infections were not excluded from the calculations (Spearman's rho +0.491 and -0.406, respectively); or if a 2-day lag between measurements was used (Spearman's rho +0.468 and -0.386, respectively). All the above findings were significant (p<0.001). In conclusion, in a population that consisted mainly of patients of advanced age, higher temperature and decreased humidity are associated with an increase in house call visits for lower UTIs. The awareness of this association may facilitate preventive public health strategies. [corrected]", "author" : [ { "dropping-particle" : "", "family" : "Falagas", "given" : "M E", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Peppas", "given" : "G", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Matthaiou", "given" : "D K", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Karageorgopoulos", "given" : "D E", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Karalis", "given" : "N", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Theocharis", "given" : "G", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology", "id" : "ITEM-1", "issue" : "6", "issued" : { "date-parts" : [ [ "2009", "6" ] ] }, "page" : "709-12", "title" : "Effect of meteorological variables on the incidence of lower urinary tract infections.", "type" : "article-journal", "volume" : "28" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[8]", "plainTextFormattedCitation" : "[8]", "previouslyFormattedCitation" : "[8]" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }[8]2009GreeceCommunity (house call visits)AllAllAllUTIs correlate with higher temperatures and decreased relative humiditySpearman's rank correlationEriksson et al.ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1111/j.1600-0463.2012.02937.x", "ISSN" : "09034641", "author" : [ { "dropping-particle" : "", "family" : "Eriksson", "given" : "Andreas", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Giske", "given" : "Christian G.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Ternhag", "given" : "Anders", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "APMIS", "id" : "ITEM-1", "issue" : "1", "issued" : { "date-parts" : [ [ "2013", "1" ] ] }, "page" : "72-78", "title" : "The relative importance of <i>Staphylococcus saprophyticus</i> as a urinary tract pathogen: distribution of bacteria among urinary samples analysed during 1\u00a0year at a major Swedish laboratory", "type" : "article-journal", "volume" : "121" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[9]", "plainTextFormattedCitation" : "[9]", "previouslyFormattedCitation" : "[9]" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }[9]2013SwedenCommunity and hospitalE. coli, K. pneumoniae and P. mirabilis aggregated and S. saprophyticus Females15-29In GP samples, both peak in September, in hospital samples, both peak in August. Stronger seasonality in S. saprophyticus.Chi-squared testRossignol et al.ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1371/journal.pone.0076020", "ISSN" : "1932-6203", "PMID" : "24204587", "abstract" : "BACKGROUND: Despite the fact that urinary tract infection (UTI) is a very frequent disease, little is known about its seasonality in the community.\n\nMETHODS AND FINDINGS: To estimate seasonality of UTI using multiple time series constructed with available proxies of UTI. Eight time series based on two databases were used: sales of urinary antibacterial medications reported by a panel of pharmacy stores in France between 2000 and 2012, and search trends on the Google search engine for UTI-related terms between 2004 and 2012 in France, Germany, Italy, the USA, China, Australia and Brazil. Differences between summers and winters were statistically assessed with the Mann-Whitney test. We evaluated seasonality by applying the Harmonics Product Spectrum on Fast Fourier Transform. Seven time series out of eight displayed a significant increase in medication sales or web searches in the summer compared to the winter, ranging from 8% to 20%. The eight time series displayed a periodicity of one year. Annual increases were seen in the summer for UTI drug sales in France and Google searches in France, the USA, Germany, Italy, and China. Increases occurred in the austral summer for Google searches in Brazil and Australia.\n\nCONCLUSIONS: An annual seasonality of UTIs was evidenced in seven different countries, with peaks during the summer.", "author" : [ { "dropping-particle" : "", "family" : "Rossignol", "given" : "Louise", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Pelat", "given" : "Camille", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Lambert", "given" : "Bruno", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Flahault", "given" : "Antoine", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Chartier-Kastler", "given" : "Emmanuel", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Hanslik", "given" : "Thomas", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "PloS one", "id" : "ITEM-1", "issue" : "10", "issued" : { "date-parts" : [ [ "2013", "1", "25" ] ] }, "page" : "e76020", "publisher" : "Public Library of Science", "title" : "A method to assess seasonality of urinary tract infections based on medication sales and google trends.", "type" : "article-journal", "volume" : "8" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[10]", "plainTextFormattedCitation" : "[10]", "previouslyFormattedCitation" : "[10]" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }[10]2013France, Germany, USA, China Italy, Brazil and AustraliaCommunity (online)AllAllAllIncreases of 8-19% in search trends for UTI-related terms in summer in France, Germany, USA, China and Italy, and peaks in the southern hemisphere austral summer in Brazil and AustraliaGoogle trends analysis, Mann-Whitney testYolbas et al.ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "ISSN" : "1128-3602", "PMID" : "23640446", "abstract" : "AIM Urinary tract infections (UTIs) are common infections affecting children. The aim of our study is to determine microorganisms that cause community-acquired urinary tract infections and their antibiotic susceptibility in children. MATERIALS AND METHODS Our investigation includes 150 cases which has positive urine culture. The cases are detected at Pediatric Polyclinics of Dicle University between June 2010 and June 2011. RESULTS The study included 118 (78.7%) female and 32 (21.3%) male children. Urinary tract infections were seen in autumn 10.7% (n = 16), summer 35.3% (n = 53), winter 30.7% (n = 46) and spring 23.3% (n = 35). The culture results indicated 75.3% (n = 113) Escherichia coli; 20.7% (n = 31) Klebsiella; 2.7% (n = 4) Proteus and % 1.3 (n = 2) Pseudomonas. The antibiotic resistance against Escherichia coli was found out is amikacin (3%), ertapenem (7%), imipenem (0%), meropenem (0%), nitrofurantoin (9%), trimethoprim/sulfamethoxazole (58%), piperacillin (83%), amoxicillin/clavulanate (50%), ampicillin/sulbactam (65%), cefazolin (54%), cefotaxime (51%), cefuroxime sodium (51% ) and tetracycline (68%). The resistance ratios of Klebsiella are amikacin (0%), imipenem (0%), levofloxacin (0%), meropenem (0%), amoxicillin/clavulanate (57%), ampicillin/sulbactam (79%), ceftriaxone (68%), cefuroxime sodium (74%) and trimethoprim/sulfamethoxazole (61%). CONCLUSIONS The results represent the increasing antibiotic resistance against microorganisms among the community-acquired UTI patients in a developing country such as Turkey. So, the physicians should consider resistance status of the infectious agent and choose effective antibiotics which are nitrofurantoin and cefoxitin for their empirical antibiotic treatment. Furthermore, they should be trained about selection of more effective antibiotics and check the regional studies regularly.", "author" : [ { "dropping-particle" : "", "family" : "Yolba\u015f", "given" : "I", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Tekin", "given" : "R", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Kelekci", "given" : "S", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Tekin", "given" : "A", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Okur", "given" : "M H", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Ece", "given" : "A", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Gunes", "given" : "A", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Sen", "given" : "V", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "European review for medical and pharmacological sciences", "id" : "ITEM-1", "issue" : "7", "issued" : { "date-parts" : [ [ "2013", "4" ] ] }, "page" : "971-6", "title" : "Community-acquired urinary tract infections in children: pathogens, antibiotic susceptibility and seasonal changes.", "type" : "article-journal", "volume" : "17" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[11]", "plainTextFormattedCitation" : "[11]", "previouslyFormattedCitation" : "[11]" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }[11]2013TurkeyCommunityAllAll1 month- 15 yearsMore UTIs in summer (53/150) than overall in winter (46/150), spring (35/150) or autumn (16/150) but difference in seasonality by sexComparing incidenceMelamed et al.ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1186/1471-2105-15-S6-S3", "ISSN" : "1471-2105", "PMID" : "25078762", "abstract" : "BACKGROUND: Patterns of disease incidence can identify new risk factors for the disease or provide insight into the etiology. For example, allergies and infectious diseases have been shown to follow periodic temporal patterns due to seasonal changes in environmental or infectious agents. Previous work searching for seasonal or other temporal patterns in disease diagnosis rates has been limited both in the scope of the diseases examined and in the ability to distinguish unexpected seasonal patterns. Electronic Health Records (EHR) compile extensive longitudinal clinical information, constituting a unique source for discovery of trends in occurrence of disease. However, the data suffer from inherent biases that preclude an identification of temporal trends.\n\nMETHODS: Motivated by observation of the biases in this data source, we developed a method (Lomb-Scargle periodograms in detrended data, LSP-detrend) to find periodic patterns by adjusting the temporal information for broad trends in incidence, as well as seasonal changes in total hospitalizations. LSP-detrend can sensitively uncover periodic temporal patterns in the corrected data and identify the significance of the trend. We apply LSP-detrend to a compilation of records from 1.5 million patients encoded by ICD-9-CM (International Classification of Diseases, Ninth Revision, Clinical Modification), including 2,805 disorders with more than 500 occurrences across a 12 year period, recorded from 1.5 million patients.\n\nRESULTS AND CONCLUSIONS: Although EHR data, and ICD-9 coded records in particular, were not created with the intention of aggregated use for research, these data can in fact be mined for periodic patterns in incidence of disease, if confounders are properly removed. Of all diagnoses, around 10% are identified as seasonal by LSP-detrend, including many known phenomena. We robustly reproduce previous findings, even for relatively rare diseases. For instance, Kawasaki disease, a rare childhood disease that has been associated with weather patterns, is detected as strongly linked with winter months. Among the novel results, we find a bi-annual increase in exacerbations of myasthenia gravis, a potentially life threatening complication of an autoimmune disease. We dissect the causes of this seasonal incidence and propose that factors predisposing patients to this event vary through the year.", "author" : [ { "dropping-particle" : "", "family" : "Melamed", "given" : "Rachel D", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Khiabanian", "given" : "Hossein", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Rabadan", "given" : "Raul", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "BMC bioinformatics", "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2014", "1" ] ] }, "page" : "S3", "title" : "Data-driven discovery of seasonally linked diseases from an Electronic Health Records system.", "type" : "article-journal", "volume" : "15 Suppl 6" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[12]", "plainTextFormattedCitation" : "[12]", "previouslyFormattedCitation" : "[12]" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }[12]2014USAHospitalAllAllAllSummer peakLomb-Scargle periodograms in de-trended dataTable S2. Akaike information criteria (AIC) for the models of UTI consultations in the UK including a seasonal component with no trend term, a linear trend term and a quadratic trend term, by sex and age group. *In order to calculate the AIC, the dispersion parameter (theta) was fixed at the estimate derived for the most complex model (the seasonal model with a quadratic trend term). The trend term was given by t+t2 and the seasonality term by cos2Πt12+sin2Πt12, where t was the month of the study (1 to 96).SexAge groupAIC of the regression model with no trend term*AIC of the regression model with a linear trend term (t)*AIC of the regression model with a quadratic trend term (t+t2)All UTIs14-171131.302936.8906925.5975All UTIs18-241375.331119.6631083.569All UTIs25-451330.7031249.7251234.055All UTIs46-691281.1981244.5961231.499All UTIs70-841193.3731181.4681168.383All UTIs85+1298.5371054.3431036.552Female UTIs14-171170.251930.8574917.3008Female UTIs18-241360.8371117.9741078.937Female UTIs25-451327.8621237.1771221.477Female UTIs46-691262.2411218.7611205.818Female UTIs70-841143.9591134.7961123.924Female UTIs85+1241.1391015.2061001.247Male UTIs14-17582.4998568.1808570.5024Male UTIs18-24678.9267624.9811627.5591Male UTIs25-45918.8692802.7613797.7937Male UTIs46-69930.2015922.5998920.3444Male UTIs70-84929.6153931.4508920.3366Male UTIs85+861.6667830.0555819.1208Table S3. Coefficients and 95% confidence intervals (CI) of the models of UTI consultations in the UK by sex and age group. The trend term was given by t+t2 and the seasonality term by cos2Πt12+sin2Πt12, where t was the month of the study (1 to 96). The confidence intervals were calculated using the confint function in R. Sexagesintercept (95% CI)t (95% CI)t2 (95% CI)cos2Πt12 (95% CI)sin2Πt12 (95% CI)All UTIs14-17-6.08 (-6.15, -0.00268)0.000415 (-6.15, -0.00268)-6.2e-05 (-6.15, -0.00268)0.0994 (-6.15, -0.00268)-0.154 (-6.15, -0.00268)All UTIs18-24-5.46 (-5.49, 0.00013)0.00193 (-5.49, 0.00013)-5.85e-05 (-5.49, 0.00013)0.0241 (-5.49, 0.00013)-0.1 (-5.49, 0.00013)All UTIs25-45-5.93 (-5.97, 4.64e-05)0.00173 (-5.97, 4.64e-05)-3.83e-05 (-5.97, 4.64e-05)0.0205 (-5.97, 4.64e-05)-0.0818 (-5.97, 4.64e-05)All UTIs46-69-5.76 (-5.79, 0.000349)0.00172 (-5.79, 0.000349)-2.9e-05 (-5.79, 0.000349)0.0102 (-5.79, 0.000349)-0.0763 (-5.79, 0.000349)All UTIs70-84-5.1 (-5.13, 0.000806)0.00222 (-5.13, 0.000806)-2.98e-05 (-5.13, 0.000806)-0.00302 (-5.13, 0.000806)-0.0524 (-5.13, 0.000806)All UTIs85+-5.1 (-5.13, 0.000806)0.00222 (-5.13, 0.000806)-2.98e-05 (-5.13, 0.000806)-0.00302 (-5.13, 0.000806)-0.0524 (-5.13, 0.000806)Female UTIs14-17-5.4 (-5.47, -0.0029)0.000229 (-5.47, -0.0029)-6.72e-05 (-5.47, -0.0029)0.101 (-5.47, -0.0029)-0.167 (-5.47, -0.0029)Female UTIs18-24-4.84 (-4.87, 0.000431)0.00225 (-4.87, 0.000431)-6.12e-05 (-4.87, 0.000431)0.0236 (-4.87, 0.000431)-0.101 (-4.87, 0.000431)Female UTIs25-45-5.36 (-5.4, -6.22e-05)0.00164 (-5.4, -6.22e-05)-3.87e-05 (-5.4, -6.22e-05)0.0201 (-5.4, -6.22e-05)-0.0852 (-5.4, -6.22e-05)Female UTIs46-69-5.27 (-5.3, 0.000253)0.00168 (-5.3, 0.000253)-2.98e-05 (-5.3, 0.000253)0.0114 (-5.3, 0.000253)-0.0812 (-5.3, 0.000253)Female UTIs70-84-4.81 (-4.84, 0.000701)0.00216 (-4.84, 0.000701)-2.85e-05 (-4.84, 0.000701)-0.00206 (-4.84, 0.000701)-0.0564 (-4.84, 0.000701)Female UTIs85+-4.81 (-4.84, 0.000701)0.00216 (-4.84, 0.000701)-2.85e-05 (-4.84, 0.000701)-0.00206 (-4.84, 0.000701)-0.0564 (-4.84, 0.000701)Male UTIs14-17-8.43 (-8.61, -0.00787)0.00113 (-8.61, -0.00787)-6.03e-05 (-8.61, -0.00787)0.0924 (-8.61, -0.00787)0.0412 (-8.61, -0.00787)Male UTIs18-24-8.08 (-8.19, -0.00684)-0.00185 (-8.19, -0.00684)-3.08e-05 (-8.19, -0.00684)0.0383 (-8.19, -0.00684)-0.0673 (-8.19, -0.00684)Male UTIs25-45-7.8 (-7.85, -0.00216)0.000213 (-7.85, -0.00216)-3.67e-05 (-7.85, -0.00216)0.028 (-7.85, -0.00216)-0.0499 (-7.85, -0.00216)Male UTIs46-69-6.97 (-7.01, -0.000274)0.0015 (-7.01, -0.000274)-2.24e-05 (-7.01, -0.000274)0.00462 (-7.01, -0.000274)-0.0508 (-7.01, -0.000274)Male UTIs70-84-5.84 (-5.88, 0.00151)0.00323 (-5.88, 0.00151)-3.39e-05 (-5.88, 0.00151)-0.0071 (-5.88, 0.00151)-0.036 (-5.88, 0.00151)Male UTIs85+-5.84 (-5.88, 0.00151)0.00323 (-5.88, 0.00151)-3.39e-05 (-5.88, 0.00151)-0.0071 (-5.88, 0.00151)-0.036 (-5.88, 0.00151)Table S4. Month of the year with the highest number of UTI consultations or trimethoprim and nitrofurantoin prescriptions by age group. In brackets, the rate of UTI consultations or trimethoprim and nitrofurantoin prescriptions per 100,000 person years for that month.DateTrimethoprim and nitrofurantoin prescriptions in the UK <85Trimethoprim and nitrofurantoin prescriptions in the UK 85+UTI consultations in the UK <85UTI consultations in the UK 85+UTI consultations in England <85UTI consultations in England 85+2008Oct (515.08)Jan (1886.24)Sep (352.52)Jan (922.37)Sep (355.56)Jan (826.19)2009Sep (535.13)Oct (1622.4)Sep (350.65)Jan (881.78)Sep (352.6)Jan (817.95)2010Sep (554.32)Mar (1612.09)Sep (344.01)Jul (838.79)Sep (339.61)Jul (764.2)2011Nov (587.15)Mar (1653.98)Sep (342.48)Aug (814)Sep (345.05)Nov (742.15)2012Oct (621.67)Jan (1799.42)Oct (349.52)Jan (817.35)Oct (345.29)Jan (740.61)2013Oct (622.2)Jan (1768.77)Oct (349.18)Jan (809.73)Oct (340.93)Oct (741.06)2014Oct (597.12)Jan (1687.91)Jan (325.01)Jan (756.34)Oct (317.27)Jan (645.86)2015Sep (556.59)Jan (1517.94)Sep (293.28)Jan (692.45)Sep (282.98)Jan (611.35)Table S5. Akaike information criteria (AIC) for models of the scaled UTI consultations in the UK which included a seasonal component and models that did not by age group. *In order to calculate the AIC for the non-seasonal model, the dispersion parameter (theta) was fixed at the estimate derived for the seasonal model.Age groupAIC seasonal modelAIC non-seasonal model*% deviance explained by the seasonal model% deviance explained by the non-seasonal model14-17960.781041.5872.2146.8418-241096.011196.4577.9253.525-451242.651293.5554.0626.8546-691254.361309.2148.8816.5570-841196.561217.8628.748.5185+1108.251103.9244.4343.47FiguresFigure S SEQ Figure \* ARABIC 1. Percentage of monthly UTI consultation coded with any antibiotic prescription on the same day for which that antibiotic was trimethoprim or nitrofurantoin, by age group. Figure S SEQ Figure \* ARABIC 2. Percentage of monthly trimethoprim and nitrofurantoin prescriptions that had a UTI consultation coded on the same day for those aged under 85 and 85 or over. Nitrofurantoin and trimethoprim are almost exclusively prescribed for UTI, therefore this can be interpreted as a proxy for coding of UTI consultation. Figure S3. Monthly UTI consultations coded by GPs per 100,000 person years in the UK by age group and sex. The central red lines represent the fitted trend predictions from the seasonal regression model. This was a negative binomial polynomial regression model of degree two with the number of patients registered at each of the GP practices on the 1st of July (mid-year) each year of the study as offset. The UTI consultations were de-duplicated to one per 30-day period. The y axes differ between panels.Figure S4. Monthly UTI consultations coded by GPs per 100,000 person years in England and in the UK by age group. The central red lines represent the fitted predictions of the negative binomial polynomial regression model of degree two with the number of patients registered at each of the GP practices on the 1st of July (mid-year) each year of the study as offset. The central blue lines represent the fitted predictions of the same model but with a seasonal component included. The shaded areas represent the 95% confidence intervals for their respective models. These were calculated using the standard errors from the predict function, which calculates the confidence intervals around the mean. The UTI consultations were de-duplicated to one per 30-day period. The y axes differ between panels.Figure S5. Scaled monthly UTI consultations coded per 100,000 person years in the UK by age group. The UTI consultations were de-duplicated to one per 30-day period. The red lines represent the fitted predictions of the negative binomial polynomial regression model of degree two with the number of patients registered at each of the GP practices on the 1st of July (mid-year) each year of the study as offset. The blue lines represent the fitted predictions of the same model but with a seasonal component included. No confidence intervals are presented as these were scaled predictions. The monthly UTI consultations were scaled for each age group by dividing by a scaling factor. This scaling factor was the percentage of UTIs coded in each month (the percentage of monthly trimethoprim and nitrofurantoin prescriptions that had a UTI consultation coded on the same day) divided by the maximum percentage coded over the study period for that age group. The right panels show the correlograms for the residuals of the regression models without seasonality at lags of 0-12 months for each age group. The y axes differ between panels.Figure S6. Monthly nitrofurantoin and trimethoprim prescriptions administered by GPs per 100,000 person years in the UK by age group. The nitrofurantoin and trimethoprim prescriptions were de-duplicated to one per 30-day period. The central red lines represent the fitted predictions of the negative binomial polynomial regression model of degree two with the number of patients registered at each of the GP practices on the 1st of July (mid-year) each year of the study as offset. The central blue lines represent the fitted predictions of the same model but with a seasonal component included. The shaded areas represent the 95% confidence intervals for their respective models. These were calculated using the standard errors from the predict function, which calculates the confidence intervals around the mean. The right panels show the correlograms for the residuals of the regression models without seasonality at lags of 0-12 months for each age group. The y axes differ between panels.Figure S7. Monthly UTI consultations coded per 100,000 person years in England by age group. The UTI consultations were de-duplicated to one per 30-day period. The central red lines represent the fitted predictions of the negative binomial polynomial regression model of degree two with the number of patients registered at each of the GP practices on the 1st of July (mid-year) each year of the study as offset. The central blue lines represent the fitted predictions of the same model but with a seasonal component included. The shaded areas represent the 95% confidence intervals for their respective models. These were calculated using the standard errors from the predict function, which calculates the confidence intervals around the mean. The right panels show the correlograms for the residuals of the regression models without seasonality at lags of 0-12 months for each age group. The y axes differ between panels.Figure S8. Monthly nitrofurantoin and trimethoprim prescriptions administered by GPs to males per 100,000 person years in the UK by age group. The nitrofurantoin and trimethoprim prescriptions were de-duplicated to one per 30-day period. The central red lines represent the fitted predictions of the negative binomial polynomial regression model of degree two with the number of patients registered at each of the GP practices on the 1st of July (mid-year) each year of the study as offset. The central blue lines represent the fitted predictions of the same model but with a seasonal component included. The shaded areas represent the 95% confidence intervals for their respective models. These were calculated using the standard errors from the predict function, which calculates the confidence intervals around the mean. The right panels show the correlograms for the residuals of the regression models without seasonality at lags of 0-12 months for each age group. The AIC of the model in those aged under 85 decreases (from 1262.5 to 1237.4) by including seasonality in the elderly, but remains similar in those aged 85+ (928.0 in the model without seasonality and 932.9 in the model with seasonality). The y axes differ between panels.Appendix 2DatasetTHIN is a validated database of primary care consultation data covering over 3.7 million active patients which are demographically representative of the UK.ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "ISSN" : "1476-0320", "PMID" : "22828580", "abstract" : "INTRODUCTION The degree of generalisability of patient databases to the general population is important for interpreting database research. This report describes the representativeness of The Health Improvement Network (THIN), a UK primary care database, of the UK population. METHODS Demographics, deprivation (Townsend), Quality and Outcomes Framework (QOF) condition prevalence and deaths from THIN were compared with national statistical and QOF 2006/2007 data. RESULTS Demographics were similar although THIN contained fewer people aged under 25 years. Condition prevalence was comparable, e.g. 3.5% diabetes prevalence in THIN, 3.7% nationally. More THIN patients lived in the most affluent areas (23.5% in THIN, 20% nationally). Between 1990 and 2009, standardised mortality ratio ranged from 0.81 (95% CI: 0.39-1.49; 1990) to 0.93 (95% CI: 0.48-1.64; 1995). Adjusting for demographics/deprivation, the 2006 THIN death rate was 9.08/1000 population close to the national death rate of 9.4/1000 population. CONCLUSION THIN is generalisable to the UK for demographics, major condition prevalence and death rates adjusted for demographics and deprivation.", "author" : [ { "dropping-particle" : "", "family" : "Blak", "given" : "Betina T", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Thompson", "given" : "Mary", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Dattani", "given" : "Hassy", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Bourke", "given" : "Alison", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Informatics in primary care", "id" : "ITEM-1", "issue" : "4", "issued" : { "date-parts" : [ [ "2011" ] ] }, "page" : "251-5", "title" : "Generalisability of The Health Improvement Network (THIN) database: demographics, chronic disease prevalence and mortality rates.", "type" : "article-journal", "volume" : "19" }, "uris" : [ "" ] }, { "id" : "ITEM-2", "itemData" : { "URL" : "", "accessed" : { "date-parts" : [ [ "2017", "4", "21" ] ] }, "id" : "ITEM-2", "issued" : { "date-parts" : [ [ "0" ] ] }, "title" : "IMS Health", "type" : "webpage" }, "uris" : [ "" ] }, { "id" : "ITEM-3", "itemData" : { "ISSN" : "1476-0320", "PMID" : "15606990", "abstract" : "OBJECTIVES To build and test a model for the collection of computerised retrospective primary care data from the UK, and to assess its quality for use in medical and pharmaceutical research. DESIGN Collection and evaluation of sampled retrospective general practice data recording. SETTING General practices, using the Vision practice management software in the UK. MAIN OUTCOME MEASURES Quality indicators of completeness of data recording. RESULTS Initial audit of 236 practices indicated good recording of prescribing in all practices and a high level of completeness of recording of clinical information in many of the practices. CONCLUSIONS In the group of practices studied, levels of recording were generally assessed to be of sufficient quality to enable a database of quality-evaluated, anonymised primary care records to be created.", "author" : [ { "dropping-particle" : "", "family" : "Bourke", "given" : "Alison", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Dattani", "given" : "Hassy", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Robinson", "given" : "Michael", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Informatics in primary care", "id" : "ITEM-3", "issue" : "3", "issued" : { "date-parts" : [ [ "2004" ] ] }, "page" : "171-7", "title" : "Feasibility study and methodology to create a quality-evaluated database of primary care data.", "type" : "article-journal", "volume" : "12" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[13\u201315]", "plainTextFormattedCitation" : "[13\u201315]", "previouslyFormattedCitation" : "^13\u201315" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }[13–15] The dataset contains individual pseudonomysed patient ID, prescription details, consultation date and time, reason for consultation (recorded through diagnostic code), patient registration details and patient clinical and demographic information.In order to obtain the monthly rate of de-duplicated UTI consultations, nitrofurantoin prescriptions and trimethoprim prescriptions by age and sex, for 2008-2015, we extracted UTI diagnostic codes (listed in Appendix 3), Patient ID, trimethoprim and nitrofurantoin prescriptions (derived from the prescribing information in THIN), country, date of UTI consultation/prescription, date of registration at GP, date of de-registration at GP, patient age, patient sex, and patients registered on the 1st of July (mid-year) each year for 2008-2015 at each of the GP practices present in THIN during the whole duration of the study (for this, practice ID was required). UTI consultations and nitrofurantoin and trimethoprim prescriptions from UK practices meeting acceptable standard for research (as suggested by the THIN Data Guide for Researchers) were de-duplicated to one per patient per 30-day period in order to approximate episodes of infection (one nitrofurantoin or trimethoprim prescription during the 30-day period) and subsequently aggregated by age group, sex and moth of the study. The denominator population was the number of patients (of the corresponding age group and sex) registered at each of the GP practices on the 1st of July (mid-year) each year of the study. Reasoning for analysing both GP consultations and antibiotic prescriptionsConsultation codes in THIN are known to be poorly recordedADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.4104/pcrj.2013.00061", "ISSN" : "1471-4418", "author" : [ { "dropping-particle" : "", "family" : "James", "given" : "Gareth Dean Russell", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Petersen", "given" : "Irene", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Nazareth", "given" : "Irwin", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Wedzicha", "given" : "Jadwiga A", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Donaldson", "given" : "Gavin C", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Wedzicha", "given" : "JA", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Primary Care Respiratory Journal", "id" : "ITEM-1", "issue" : "3", "issued" : { "date-parts" : [ [ "2013", "7", "9" ] ] }, "page" : "271-277", "publisher" : "Nature Publishing Group", "title" : "Use of long-term antibiotic treatment in COPD patients in the UK: a retrospective cohort study", "type" : "article-journal", "volume" : "22" }, "uris" : [ "" ] }, { "id" : "ITEM-2", "itemData" : { "DOI" : "10.1093/jac/dkq307", "ISSN" : "0305-7453", "author" : [ { "dropping-particle" : "", "family" : "Petersen", "given" : "I.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Gilbert", "given" : "R.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Evans", "given" : "S.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Ridolfi", "given" : "A.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Nazareth", "given" : "I.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Journal of Antimicrobial Chemotherapy", "id" : "ITEM-2", "issue" : "10", "issued" : { "date-parts" : [ [ "2010", "10", "1" ] ] }, "page" : "2238-2246", "publisher" : "Oxford University Press", "title" : "Oral antibiotic prescribing during pregnancy in primary care: UK population-based study", "type" : "article-journal", "volume" : "65" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[16,17]", "plainTextFormattedCitation" : "[16,17]", "previouslyFormattedCitation" : "^16,17" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }[16,17]. However, all prescriptions made by GP practices reporting to THIN are automatically included in the database and do not suffer from this reporting bias. Hence, the analysis of UTI consultations was repeated for trimethoprim and nitrofurantoin prescriptions. Both trimethoprim and nitrofurantoin are almost exclusively prescribed for UTIs and account for the majority of antibiotics used for UTIs in primary care. Only the rate of UTI consultations (and not antibiotic prescriptions) were used to assess the trend in UTIs over time, because nitrofurantoin and trimethoprim prescriptions for UTI as a proportion of all antibiotic prescriptions increased over the study period. (Figure S1, Appendix 1). Although coding for UTI consultations by GPs was poor, it remained stable over the study period (the percentage of trimethoprim and nitrofurantoin prescriptions that had a UTI consultation coded on the same day fluctuated between 35-41% during the study period), enabling the study of trend over time (Figure S2, Appendix 1).Appendix 3Read codes for UTI'K190300', 'K190400', '1AG..00', 'K190311', 'K190.11', '14D7.00', 'L166z11', 'L166800', 'K190.00', 'K190500', 'K190z00', 'K190000', 'K190100', 'K190200', 'K190600', 'K190X00', 'Q40y100', '1J4..00', '46U3.00', '4617.00', 'K190011', 'L166600','K15..00', 'K150.00', 'K15z.00', 'K152000', 'K154.00', 'K154000', 'K154300', 'K154400', 'K154600', 'K154800', 'K154z00', 'K15y.00', 'K15y200', 'K15y300', 'K15yz00', 'A32y300', 'K153.11', 'K151.00', 'K152y00', 'K152.00', 'K152z00', 'K155.00', '14D4.00','L166.11', 'L166500', 'K101.00', 'K101000', 'K101100', 'K101200', 'K101300', 'K101400', 'K101500', 'K101z00', 'K106.00', 'K100.00', 'K100000', 'K100100', 'K100200', 'K100300', 'K100400', 'K100500', 'K100600', 'K100z00', 'K10y000', 'A160200', 'K104.00', 'K10..00', 'K102.00', 'K102000', 'K102100', 'K102200', 'K102z00', 'K103.00', 'K105.00', 'K10y.00', 'K10y000', 'K10y100', 'K10y200', 'K10y300', 'K10y400', 'K10yz00','K10z.00', 'K10..11'.Appendix 4The following negative binomial model was fit to the rates of consultations and prescriptions: logλt=a+trendt+seasonalityt+log?(populationt)Where, t was the month of the study; λt was the number of consultations and prescriptions at month t; a was the intercept; trendt was a quadratic term defined as trendt=a+bt+ct2, used to account for the decreasing trend observed in the rates; seasonalityt was a seasonality term defined as seasonalityt=cos2Πt12+sin2Πt12; and log?(populationt) was an offset used to model the rates of consultations and prescriptions instead of the counts.Negative binomial models were best suited to model the rates of consultations and prescriptions due to the overdispersion in the data.ReferencesADDIN Mendeley Bibliography CSL_BIBLIOGRAPHY 1.Stansfeld JM. Clinical observations relating to incidence and aetiology of urinary-tract infections in children. British medical journal 1966; 1: 631–5. 2.Anderson JE. Seasonality of symptomatic bacterial urinary infections in women. Journal of Epidemiology and Community Health 1983; 37: 286–290. 3.Pead L, Maskell R, Morris J. Staphylococcus saprophyticus as a urinary pathogen: a six year prospective survey. British medical journal (Clinical research ed.) 1985; 291: 1157–9. 4.Vorland LH, Carlson K, Aalen O. Antibiotic resistance and small R plasmids among Escherichia coli isolates from outpatient urinary tract infections in northern Norway. Antimicrobial agents and chemotherapy 1985; 27: 107–13. 5.Ferry S, Burman LG, Mattsson B. Urinary tract infection in primary health care in northern Sweden. I. Epidemiology. Scandinavian journal of primary health care 1987; 5: 123–8. 6.Stamm WE, et al. Natural history of recurrent urinary tract infections in women. Reviews of infectious diseases 1991; 13: 77–84. 7.Kwok W-Y, et al. Incidence rates and management of urinary tract infections among children in Dutch general practice: results from a nation-wide registration study. BMC pediatrics 2006; 6: 10. 8.Falagas ME, et al. Effect of meteorological variables on the incidence of lower urinary tract infections. European journal of clinical microbiology & infectious diseases?: official publication of the European Society of Clinical Microbiology 2009; 28: 709–12. 9.Eriksson A, Giske CG, Ternhag A. The relative importance of Staphylococcus saprophyticus as a urinary tract pathogen: distribution of bacteria among urinary samples analysed during 1?year at a major Swedish laboratory. APMIS 2013; 121: 72–78. 10.Rossignol L, et al. A method to assess seasonality of urinary tract infections based on medication sales and google trends. PloS one Public Library of Science, 2013; 8: e76020. 11.Yolba? I, et al. Community-acquired urinary tract infections in children: pathogens, antibiotic susceptibility and seasonal changes. European review for medical and pharmacological sciences 2013; 17: 971–6. 12.Melamed RD, Khiabanian H, Rabadan R. Data-driven discovery of seasonally linked diseases from an Electronic Health Records system. BMC bioinformatics 2014; 15 Suppl 6: S3. 13.Blak BT, et al. Generalisability of The Health Improvement Network (THIN) database: demographics, chronic disease prevalence and mortality rates. Informatics in primary care 2011; 19: 251–5. 14.IMS Health. (). Accessed 21 April 2017. 15.Bourke A, Dattani H, Robinson M. Feasibility study and methodology to create a quality-evaluated database of primary care data. Informatics in primary care 2004; 12: 171–7. 16.James GDR, et al. Use of long-term antibiotic treatment in COPD patients in the UK: a retrospective cohort study. Primary Care Respiratory Journal Nature Publishing Group, 2013; 22: 271–277. 17.Petersen I, et al. Oral antibiotic prescribing during pregnancy in primary care: UK population-based study. Journal of Antimicrobial Chemotherapy Oxford University Press, 2010; 65: 2238–2246. ................
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