PubMed · 15067778
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Peter Kramp. 2004-03-15. [Manuscript guidelines].. https://pubmed.ncbi.nlm.nih.gov/15067778/
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BACKGROUNDIncreasing incidence rates of invasive Streptococcus dysgalactiae subspecies equisimilis (iSDSE) have been detected worldwide.AIMWe aimed to investigate iSDSE infection incidence rates in Denmark during 2014-2024, and characterise the genomic population structure of a subset of iSDSE isolates and their antimicrobial resistance (AMR).METHODSUsing national register data, we estimated overall and sex-/age-stratified iSDSE incidences during 2014-2024, by retrospectively identifying cases of invasive infections with group C and G streptococci or S. dysgalactiae (including specified as subspecies equisimilis). From the voluntary national beta-haemolytic streptococci laboratory surveillance system, whole-genome-sequenced isolates from August 2020-September 2022 were used to investigate the iSDSE genomic population structure. Susceptibility to penicillin, erythromycin and clindamycin was determined and AMR genes identified.RESULTSDuring 2014-2024, iSDSE incidence rates increased significantly (linear trend analysis p < 0.001) with mean annual incidence ranging between 10.3 and 16.4 per 100,000, peaking in 2023. Incidence was higher in males, increasing with older age. Nearly 75% of the 1,223 iSDSE isolates belonged to four of 14 genetic clusters. Sequence types (STs) ST20 and ST17 were most prevalent, while emm-type stG62647, a variant associated internationally with higher virulence, dominated. All isolates were phenotypically susceptible to penicillin but approximately 10% were respectively erythromycin and clindamycin resistant. High erythromycin resistance prevalence (57%; 39/68), coinciding with gene ermA, occurred in one genetic cluster.CONCLUSIONThe findings illustrate the need for national registry-based surveillance to detect epidemiological changes and potential outbreaks. Further, continuous genomic surveillance can monitor the occurrence and expansion of genetic clades and AMR genes.
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BACKGROUND: Evaluation of health care contacts from first events alone often misses large amounts of potentially important data and may produce different results than evaluation of all data including recurrent events. OBJECTIVE: We aim to bring the different methodological approaches for analysing longitudinal health care data to the attention of researchers in primary care. METHODS: We used hospital admission data from the Ebeltoft Health Promotion Project, a randomized trial in primary care examining the effect of preventive health checks. Comparisons included three randomized groups: an intervention group receiving health checks, a group where intervention consisted of a health check followed by a health discussion with the GP and one control group. RESULTS: Both intervention groups had approximately 20% fewer hospital admissions than the control group over a 6 year period. If dependence among recurrent events is excluded, such a reduction amounts to a highly significant effect. Use of the standard Poisson distribution for analysing recurrent events and exclusion of their dependent structure causes data interpretation to be incorrect, because the model does not account for the extra variability between persons; the resulting 95% CIs would therefore be too small. CONCLUSION: Analysis of health care contacts should embrace both first and recurrent events and it should use a model appropriate to these data. An individual rate model that includes a parameter of an unspecified individual event distribution frailty may be a natural choice when analysing longitudinal data of contacts to the health care system in broad terms.