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Abstract Statistical regression models are used for predicting outcomes based on the values of some predictor variables or for describing the association of an outcome with predictors. With a data set at hand, a regression model can be easily fit with standard software packages. This bears the risk that data analysts may rush to perform sophisticated analyses without sufficient knowledge of basic properties, associations in and errors of their data, leading to wrong interpretation and presentation of the modeling results that lacks clarity. Ignorance about special features of the data such as redundancies or particular distributions may even invalidate the chosen analysis strategy. Initial data analysis (IDA) is prerequisite to regression analyses as it provides knowledge about the data needed to confirm the appropriateness of or to refine a chosen model building strategy, to interpret the modeling results correctly, and to guide the presentation of modeling results. In order to facilitate reproducibility, IDA needs to be preplanned, an IDA plan should be included in the general statistical analysis plan of a research project, and results should be well documented. Biased statistical inference of the final regression model can be minimized if IDA abstains from evaluating associations of outcome and predictors, a key principle of IDA. We give advice on which aspects to consider in an IDA plan for data screening in the context of regression modeling to supplement the statistical analysis plan. We illustrate this IDA plan for data screening in an example of a typical diagnostic modeling project and give recommendations for data visualizations.

Abstract Background Glenoid version is an important factor in the evaluation of shoulder stability and shoulder pathologies. However, there are neither established reference values nor known factors that influence the glenoid version, even though valid reference values are needed for diagnostic and orthopaedic surgery like corrective osteotomy and total or reverse shoulder arthroplasty (TSA/RSA). The aim of our population-based study was to identify factors influencing the glenoid version and to establish reference values from a large-scale population cohort. Results Our study explored the glenoid versions in a large sample representing the general adult population. We investigated 3004 participants in the population-based Study of Health in Pomerania (SHIP). Glenoid version was measured for both shoulders via magnetic resonance imaging (MRI). Associations with the glenoid version were calculated for sex, age, body height, body weight and BMI. The reference values for glenoid version in the central European population range between −9° and 7.5°, while multiple factors are associated with the glenoid version. Conclusion To achieve a reliable interpretation prior to orthopaedic surgery, sex- and age-adjusted reference values are proposed.

Abstract The German initiative “National Research Data Infrastructure for Personal Health Data” (NFDI4Health) focuses on research data management in health research. It aims to foster and develop harmonized informatics standards for public health, epidemiological studies, and clinical trials, facilitating access to relevant data and metadata standards. This publication lists syntactic and semantic data standards of potential use for NFDI4Health and beyond, based on interdisciplinary meetings and workshops, mappings of study questionnaires and the NFDI4Health metadata schema, and literature search. Included are 7 syntactic, 32 semantic and 9 combined syntactic and semantic standards. In addition, 101 ISO Standards from ISO/TC 215 Health Informatics and ISO/TC 276 Biotechnology could be identified as being potentially relevant. The work emphasizes the utilization of standards for epidemiological and health research data ensuring interoperability as well as the compatibility to NFDI4Health, its use cases, and to (inter-)national efforts within these sectors. The goal is to foster collaborative and inter-sectoral work in health research and initiate a debate around the potential of using common standards.

Objective To assess the presence of mental health disorders in persons with rheumatoid arthritis (RA), ankylosing spondylitis (AS), psoriatic arthritis (PsA), systemic lupus erythematosus (SLE) and Sjögren’s disease (SjD) (all: inflammatory rheumatic disease, iRMD) in a population-based cohort.Methods Baseline data from 101 601 participants of the German National Cohort (NAKO) were analysed. Self-reported physician’s diagnoses of depression and anxiety, the depression scale of the Patient Health Questionnaire (PHQ-9), the Generalised Anxiety Disorder Symptoms Scale (GAD-7), the depression section of the Mini-International Neuropsychiatric Interview (MINI) and cognitive tests on memory and executive functions were analysed. Results of participants with iRMD were compared with participants with osteoarthritis (OA), stratified by age and sex. Cognitive function was described for iRMD and OA using a linear regression model, adjusted for sex and education.Results n=3257 participants (3.2%) had an iRMD (2.3% RA, 0.6% AS, 0.5% PsA, 0.2% SLE, 0.1% SjD) and n=24 030 (24%) had OA. Physicians’ diagnoses of depression (26% vs 21%), anxiety (15% vs 11%), current depressive (PHQ-9 ≥10: 13% vs 9.0%) and anxiety symptoms (GAD-7 ≥10: 8.6% vs 5.8%) were more frequent in iRMDs compared with OA. In all age groups, women were more often affected than men. Linear regression models showed no differences in neuropsychological test results between iRMD and OA.Conclusion Individuals with iRMD frequently experience mental disorders. The study provides an assessment of both self-report and test-based occurrences in this group. Depression and anxiety are more frequent in iRMD compared with OA, whereas levels of cognitive dysfunction were comparable.

Sex differences in the size of specific brain structures have been extensively studied, but careful and reproducible statistical hypothesis testing to identify them produced overall small effect sizes and differences in brains of males and females. On the other hand, multivariate statistical or machine learning methods that analyze MR images of the whole brain have reported respectable accuracies for the task of distinguishing brains of males from brains of females. However, most existing studies lacked a careful control for brain volume differences between sexes and, if done, their accuracy often declined to 70% or below. This raises questions about the relevance of accuracies achieved without careful control of overall volume.We examined how accurately sex can be classified from gray matter properties of the human brain when matching on overall brain volume. We tested, how robust machine learning classifiers are when predicting cross-cohort, i.e. when they are used on a different cohort than they were trained on. Furthermore, we studied how their accuracy depends on the size of the training set and attempted to identify brain regions relevant for successful classification. MRI data was used from two population-based data sets of 3298 mostly older adults from the Study of Health in Pomerania (SHIP) and 399 mostly younger adults from the Human Connectome Project (HCP), respectively. We benchmarked two multivariate methods, logistic regression and a 3D convolutional neural network.We show that male and female brains of the same intracranial volume can be distinguished with >92% accuracy with logistic regression on a dataset of 1166 matched individuals. The same model also reached 85% accuracy on a different cohort without retraining. The accuracy for both methods increased with the training cohort size up to and beyond 3000 individuals, suggesting that classifiers trained on smaller cohorts likely have an accuracy disadvantage. We found no single outstanding brain region necessary for successful classification, but important features appear rather distributed across the brain.

Abstract Background Although chronic kidney disease (CKD) is highly prevalent in the general population, little research has been conducted on CKD management in ambulatory care. Objective was to assess management and quality of care by evaluating CKD coding in ambulatory care, patient diagnosis awareness, frequency of monitoring and whether appropriate patients are referred to nephrology. Methods Clinical data from the population-based cohort Study of Health in Pomerania (SHIP-START) were matched with claims data of the Association of Statutory Health Insurance Physicians. Quality of care was evaluated according international and German recommendations. Results Data from 1778 participants (56% female, mean age 59 years) were analysed. 10% had eGFR

Abstract Background Periodontitis is among the most common chronic diseases worldwide, and it is one of the main reasons for tooth loss. Comprehensive profiling of the metabolite content of the saliva can enable the identification of novel pathways associated with periodontitis and highlight non-invasive markers to facilitate time and cost-effective screening efforts for the presence of periodontitis and the prediction of tooth loss. Methods We first investigated cross-sectional associations of 13 oral health variables with saliva levels of 562 metabolites, measured by untargeted mass spectrometry among a sub-sample (n = 938) of the Study of Health in Pomerania (SHIP-2) using linear regression models adjusting for common confounders. We took forward any candidate metabolite associated with at least two oral variables, to test for an association with a 5-year tooth loss over and above baseline oral health status using negative binomial regression models. Results We identified 84 saliva metabolites that were associated with at least one oral variable cross-sectionally, for a subset of which we observed robust replication in an independent study. Out of 34 metabolites associated with more than two oral variables, baseline saliva levels of nine metabolites were positively associated with a 5-year tooth loss. Across all analyses, the metabolites 2-pyrrolidineacetic acid and butyrylputrescine were the most consistent candidate metabolites, likely reflecting oral dysbiosis. Other candidate metabolites likely reflected tissue destruction and cell proliferation. Conclusions Untargeted metabolic profiling of saliva replicated metabolic signatures of periodontal status and revealed novel metabolites associated with periodontitis and future tooth loss.

Abstract Background The variety of medical documentation often leads to incompatible data elements that impede data integration between institutions. A common approach to standardize and distribute metadata definitions are ISO/IEC 11179 norm-compliant metadata repositories with top-down standardization. To the best of our knowledge, however, it is not yet common practice to reuse the content of publicly accessible metadata repositories for creation of case report forms or routine documentation. We suggest an alternative concept called pragmatic metadata repository, which enables a community-driven bottom-up approach for agreeing on data collection models. A pragmatic metadata repository collects real-world documentation and considers frequent metadata definitions as high quality with potential for reuse. Methods We implemented a pragmatic metadata repository proof of concept application and filled it with medical forms from the Portal of Medical Data Models. We applied this prototype in two use cases to demonstrate its capabilities for reusing metadata: first, integration into a study editor for the suggestion of data elements and, second, metadata synchronization between two institutions. Moreover, we evaluated the emergence of bottom-up standards in the prototype and two medical data managers assessed their quality for 24 medical concepts. Results The resulting prototype contained 466,569 unique metadata definitions. Integration into the study editor led to a reuse of 1836 items and item groups. During the metadata synchronization, semantic codes of 4608 data elements were transferred. Our evaluation revealed that for less complex medical concepts weak bottom-up standards could be established. However, more diverse disease-related concepts showed no convergence of data elements due to an enormous heterogeneity of metadata. The survey showed fair agreement (Kalpha = 0.50, 95% CI 0.43–0.56) for good item quality of bottom-up standards. Conclusions We demonstrated the feasibility of the pragmatic metadata repository concept for medical documentation. Applications of the prototype in two use cases suggest that it facilitates the reuse of data elements. Our evaluation showed that bottom-up standardization based on a large collection of real-world metadata can yield useful results. The proposed concept shall not replace existing top-down approaches, rather it complements them by showing what is commonly used in the community to guide other researchers.

Abstract Background The Patient Health Questionnaire-9 (PHQ-9) has been proposed as a reliable and valid screening instrument for depressive symptoms with one latent factor. However, studies explicitly testing alternative model structures found support for a two-dimensional structure reflecting a somatic and a cognitive-affective dimension. We investigated the bidimensional structure of the PHQ-9, with a somatic (sleeping problems, fatigability, appetitive problems, and psychomotor retardation) and a cognitive-affective dimension (lack of interest, depressed mood, negative feelings about self, concentration problems, and suicidal ideation), and tested for sex- and regional-differences. Methods We have included data from the GEnder-Sensitive Analyses of mental health trajectories and implications for prevention: A multi-cohort consortium (GESA). Privacy-preserving analyses to provide information on the overall population and cohort-specific information and analyses of variance to compare depressive, somatic and cognitive-affective symptoms between sexes and cohorts were executed in DataSHIELD. In order to determine the dimensionality and measurement invariance of the PHQ-9 we tested three models (1 factor, 2 correlated factors, and bifactor) via confirmatory analyses and performed multi-group confirmatory factor analysis. Results Differences between sex and cohorts exist for PHQ-9 and for both of its dimensions. Women reported depressive symptoms in general as well as somatic and cognitive-affective symptoms more frequently. For all tested models an acceptable to excellent fit was found, consistently indicating a better model fit for the two-factor and bifactor model. Scalar measurement invariance was established between women and men, the three cohorts, and their interaction. Conclusions The two facets of depression should be taken into account when using PHQ-9, while data also render support to a general factor. Somatic and cognitive-affective symptoms assessed by the PHQ-9 can be considered equivalent across women and men and between different German populations from different regions.

Abstract Background No standards exist for the handling and reporting of data quality in health research. This work introduces a data quality framework for observational health research data collections with supporting software implementations to facilitate harmonized data quality assessments. Methods Developments were guided by the evaluation of an existing data quality framework and literature reviews. Functions for the computation of data quality indicators were written in R. The concept and implementations are illustrated based on data from the population-based Study of Health in Pomerania (SHIP). Results The data quality framework comprises 34 data quality indicators. These target four aspects of data quality: compliance with pre-specified structural and technical requirements (integrity); presence of data values (completeness); inadmissible or uncertain data values and contradictions (consistency); unexpected distributions and associations (accuracy). R functions calculate data quality metrics based on the provided study data and metadata and R Markdown reports are generated. Guidance on the concept and tools is available through a dedicated website. Conclusions The presented data quality framework is the first of its kind for observational health research data collections that links a formal concept to implementations in R. The framework and tools facilitate harmonized data quality assessments in pursue of transparent and reproducible research. Application scenarios comprise data quality monitoring while a study is carried out as well as performing an initial data analysis before starting substantive scientific analyses but the developments are also of relevance beyond research.

Abstract Background In the data pipeline from the data collection process to the planned statistical analyses, initial data analysis (IDA) typically takes place between the end of the data collection and do not touch the research questions. A systematic process for IDA and clear reporting of the findings would help to understand the potential shortcomings of a dataset, such as missing values, or subgroups with small sample sizes, or shortcomings in the collection process, and to evaluate the impact of these shortcomings on the research results. A clear reporting of findings is also relevant when making datasets available to other researchers. Initial data analyses can provide valuable insights into the suitability of a data set for a future research study. Our aim was to describe the practice of reporting of initial data analyses in observational studies in five highly ranked medical journals with focus on data cleaning, screening, and reporting of findings which led to a potential change in the analysis plan. Methods This review was carried out using systematic search strategies with eligibility criteria for articles to be reviewed. A total of 25 papers about observational studies were selected from five medical journals published in 2018. Each paper was reviewed by two reviewers and IDA statements were further discussed by all authors. The consensus was reported. Results IDA statements were reported in the methods, results, discussion, and supplement of papers. Ten out of 25 papers (40%) included a statement about data cleaning. Data screening statements were included in all articles, and 18 (72%) indicated the methods used to describe them. Item missingness was reported in 11 papers (44%), unit missingness in 15 papers (60%). Eleven papers (44%) mentioned some changes in the analysis plan. Reported changes referred to missing data treatment, unexpected values, population heterogeneity and aspects related to variable distributions or data properties. Conclusion Reporting of initial data analyses were sparse, and statements on IDA were located throughout the research articles. There is a lack of systematic reporting of IDA. We conclude the article with recommendations on how to overcome shortcomings in the practice of IDA reporting in observational studies.

Objective Whole-body MRI (wb-MRI) is increasingly used in research and screening but little is known about the effects of incidental findings (IFs) on health service utilisation and costs. Such effects are particularly critical in an observational study. Our principal research question was therefore how participation in a wb-MRI examination with its resemblance to a population-based health screening is associated with outpatient service costs.Design Prospective cohort study.Setting General population Mecklenburg-Vorpommern, Germany.Participants Analyses included 5019 participants of the Study of Health in Pomerania with statutory health insurance data. 2969 took part in a wb-MRI examination in addition to a clinical examination programme that was administered to all participants. MRI non-participants served as a quasi-experimental control group with propensity score weighting to account for baseline differences.Primary and secondary outcome measures Outpatient costs (total healthcare usage, primary care, specialist care, laboratory tests, imaging) during 24 months after the examination were retrieved from claims data. Two-part models were used to compute treatment effects.Results In total, 1366 potentially relevant IFs were disclosed to 948 MRI participants (32% of all participants); most concerned masses and lesions (769 participants, 81%). Costs for outpatient care during the 2-year observation period amounted to an average of €2547 (95% CI 2424 to 2671) for MRI non-participants and to €2839 (95% CI 2741 to 2936) for MRI participants, indicating an increase of €295 (95% CI 134 to 456) per participant which corresponds to 11.6% (95% CI 5.2% to 17.9%). The cost increase was sustained rather than being a short-term spike. Imaging and specialist care related costs were the main contributors to the increase in costs.Conclusions Communicated findings from population-based wb-MRI substantially impacted health service utilisation and costs. This introduced bias into the natural course of healthcare utilisation and should be taken care for in any longitudinal analyses.

Various data sharing platforms are being developed to enhance the sharing of cohort data by addressing the fragmented state of data storage and access systems. However, policy challenges in several domains remain unresolved. The euCanSHare workshop was organized to identify and discuss these challenges and to set the future research agenda. Concerns over the multiplicity and long-term sustainability of platforms, lack of resources, access of commercial parties to medical data, credit and recognition mechanisms in academia and the organization of data access committees are outlined. Within these areas, solutions need to be devised to ensure an optimal functioning of platforms.

Abstract Background Ambulatory geriatric rehabilitation (AGR) is a multidisciplinary outpatient prevention program designed to decrease hospitalisation and dependence on nursing care in multimorbid patients ≥70 years of age. We evaluated the effectiveness of AGR compared to usual care on progression of nursing care levels, nursing home admissions, hospital admissions, incident fractures, mortality rate and total cost of care during a one-year follow-up period. Methods Analyses were based on claims data from the health insurance company AOK Nordost. Propensity Score matching was used to match 4 controls to each person receiving the AGR intervention. Results A total of 632 AGR participants and 2528 matched controls were included. The standardized mean difference of matching variables between cases and controls was small (mean: + 1.4%; range: − 4.4/3.9%). In AGR patients, the progression of nursing care levels (+ 2.2%, 95%CI: − 0.9 /5.3), nursing home admissions (+ 1.7%, 95%CI: − 0.1/3.5), hospital admissions (+ 1.1%, 95%CI: − 3.2/5.4), incident fractures (+ 11.1%, 95%CI: 7.3/15) and mortality rate (+ 1.2%, p = 0.20) showed a less favourable course compared to controls. The average total cost per AGR participant was lower than in the control group (− 353€, 95%CI: − 989€/282€), not including costs for AGR. Conclusions Analysis based on claims data showed no clinical benefit from AGR intervention regarding the investigated outcomes. The slightly worse outcomes may reflect limitations in matching based on claims data, which may have insufficiently reflected morbidity and psychosocial factors. It is possible that the intervention group had poorer health status at baseline compared to the control group. Trial registration German Clinical Trials Register DRKS00008926, registered 29.07.2015.

Various data sharing platforms are being developed to enhance the sharing of cohort data by addressing the fragmented state of data storage and access systems. However, policy challenges in several domains remain unresolved. The euCanSHare workshop was organized to identify and discuss these challenges and to set the future research agenda. Concerns over the multiplicity and long-term sustainability of platforms, lack of resources, access of commercial parties to medical data, credit and recognition mechanisms in academia and the organization of data access committees are outlined. Within these areas, solutions need to be devised to ensure an optimal functioning of platforms.

doch erfüllen Studienprotokolle, eingesetzte Erhebungsinstrumente und erhobene Daten die Anforderungen der FAIR-Prinzipien nicht in ausreichendem Maße. NFDI4Health wird daher eine Struktur schaffen, die eine zentrale Suche nach existierenden, dezentral verwalteten Datenkörpern und zugehörigen Dokumenten sowie einen FAIRen Zugang zu diesen erleichtert. Dazu werden die Auffindbarkeit und der Zugang zu strukturierten Gesundheitsdaten aus Registern, administrativen Gesundheitsdatenbanken, klinischen und epidemiologischen sowie Public Health-Studien verbessert und die Qualität und Harmonisierung der zugrundeliegenden Daten optimiert. Eine weitere Herausforderung entsteht durch die Verwendung personenbezogener Gesundheitsdaten. Diese sind hoch sensibel, so dass ihre Nutzung restriktive Datenschutzbestimmungen und informierte Einwilligungserklärungen der Studienteilnehmenden erfordert, was jedoch ihre Wiederverwendbarkeit einschränkt. NFDI4Health zielt daher darauf ab, den Austausch und die Verknüpfung von personenbezogenen Gesundheitsdaten sowie verteilte Datenanalysen unter Einhaltung datenschutzrechtlicher und ethischer Bestimmungen zu erleichtern. Um dies möglichst effizient zu erreichen, wird NFDI4Health die Entwicklung neuer, maschinenprozessierbarer Zustimmungsmöglichkeiten sowie innovativer Datenzugriffsservices auf Grundlage der FAIR-Prinzipien vorantreiben und die Interoperabilität von IT-Lösungen für Metadatenrepositorien stärken. Komplementiert wird dies durch die Entwicklung entsprechender Angebote für Training und Ausbildung, um der Herausforderung der Umsetzung der Lösungen in den Universitäten und Forschungseinrichtungen zu begegnen. Schließlich wird durch die gemeinsame Arbeit in der NFDI4Health die Kooperation zwischen klinischer und epidemiologischer/Public Health-Forschung gestärkt.

Summary: Psychological and social factors are known to influence blood pressure (BP) and risk of hypertension and associated cardiovascular diseases. To identify novel BP loci, we carried out genome-wide association meta-analyses of systolic, diastolic, pulse, and mean arterial BP, taking into account the interaction effects of genetic variants with three psychosocial factors: depressive symptoms, anxiety symptoms, and social support. Analyses were performed using a two-stage design in a sample of up to 128,894 adults from five ancestry groups. In the combined meta-analyses of stages 1 and 2, we identified 59 loci (p value < 5e−8), including nine novel BP loci. The novel associations were observed mostly with pulse pressure, with fewer observed with mean arterial pressure. Five novel loci were identified in African ancestry, and all but one showed patterns of interaction with at least one psychosocial factor. Functional annotation of the novel loci supports a major role for genes implicated in the immune response (PLCL2), synaptic function and neurotransmission (LIN7A and PFIA2), as well as genes previously implicated in neuropsychiatric or stress-related disorders (FSTL5 and CHODL). These findings underscore the importance of considering psychological and social factors in gene discovery for BP, especially in non-European populations.

BACKGROUND:Benign osseous lesions of the spine are common but precise population prevalence estimates are lacking. Our study aimed to provide the first population-based prevalence estimates and examine association with back and neck pain. MATERIALS AND METHODS:We used data from the population-based Study of Health in Pomerania (SHIP). Whole-body MRI examinations (1.5 Tesla: T1, T2, and TIRM weightings) were available from 3,259 participants. Readings of the spinal MRI images were conducted according to a standardized protocol by a single reader (JS). The intra-rater reliability was greater than Kappa values of 0.98. Pain measures included the seven-day prevalence of spine pain and neck pain, and average spine pain intensity due to spine pain during the past three months. RESULTS:We found 1,200 (36.8%) participants with at least one osseous lesion (2,080 lesions in total). Osseous lesions were less common in men than in women (35.5% vs 38.9%; P = .06). The prevalence of osseous lesions was highest at L2 in both sexes. The prevalence of osseous lesions increased with age. Up to eight osseous lesions were observed in a single subject. Hemangioma (28%), and lipoma (13%) occurred most often. Sclerosis (1.7%), aneurysmal bone cysts (0.7%), and blastoma (0.3%) were rare. Different osseous lesions occurred more often in combination with each other. The association with back or neck pain was mostly negligible. CONCLUSION:Osseous lesions are common in the general population but of no clinical relevance for spinal pain. The prevalence of osseous lesions varied strongly across different regions of the spine and was also associated with age and gender. Our population-based data offer new insights and assist in judging the relevance of osseous lesions observed on MRIs of patients.

PURPOSE:To provide population-based reference values for cervical spinal canal parameters and vertebral body (VB) width and to study their associations with sex, age, body height, body weight and body mass index (BMI) using MRI. METHODS:Cross-sectional analyses included data from 2,453 participants, aged 21-89 years, of the population-based Study of Health in Pomerania (SHIP) who underwent whole-body MRI at 1.5 Tesla between July 2008 and March 2011. A standardised reading was performed for the C2-C7 cervical spine levels at sagittal T2 TSE weighted sequences. RESULTS:Reference intervals for spinal canal parameters were similar in males and females, while VB width was on average 2.1-2.2 mm larger in males. Age effects were only substantial regarding VB width with a 0.5 mm per ten-year age increase. Body height effects were only substantial regarding the osseous spinal canal and VB width. Body weight and BMI effects are mostly not substantial. CONCLUSIONS:Our study provides MRI-based reference values for the cervical spinal canal parameters in an adult Caucasian population. Except for VB width, associations with sex, age and somatometric measures are mostly small and thus have only limited clinical implications. Some available cut-off values may need a revision because they likely overestimate risks.

Objectives. To improve understanding of periodontitis pathology, we need more profound knowledge of relative abundances of single prokaryotic species and colonization dynamics between habitats. Thus, we quantified oral microbes from two oral habitats to gain insights into colonization variability and correlation to the clinical periodontal status. Methods. We analyzed tongue scrapings and subgingival pocket samples from 237 subjects (35–54 years) with at least 10 teeth and no recent periodontal treatment from the 11-year follow-up of the Study of Health in Pomerania. Relative abundances of Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans, Fusobacterium nucleatum, Streptococcus sanguinis, total bacteria, and Archaea were correlated to clinically assessed pocket depths (PD) and clinical attachment levels (CAL). Results. Increased relative abundances of P. gingivalis, A. actinomycetemcomitans, and F. nucleatum were linked to increased levels of PD and CAL (i) on the subject level (mean PD, mean CAL) and (ii) in subgingival pockets. Relative abundances of Archaea from tongue samples correlated negatively with mean PD or mean CAL. Detection and quantity of bacterial species correlated weakly to moderately between the tongue and subgingival pocket, except for Archaea. Conclusions. Relative abundances of specific oral species correlated weakly to moderately between habitats. Single species, total bacteria, and Archaea were linked to clinically assessed severity of periodontitis in a habitat-dependent manner.

Spinal manual therapy (SMT) is a popular treatment option for low back pain (LBP). The aim of our analysis was to evaluate the effects of manual therapy delivered by general practitioners and ambulatory orthopedic surgeons in routine care on follow up consultations, sick leave, health service utilization and costs for acute LBP compared to matched patients not receiving manual therapy. This is a propensity score matched cohort study based on health claims data. We identified a total of 113.652 adult patients with acute LBP and no coded red flags of whom 21.021 (18%) received SMT by physicians. In the final analysis 17.965 patients in each group could be matched. Balance on patients' coded characteristics, comorbidity and prior health service utilization was achieved. The provision of SMT for acute LBP had no relevant impact on follow up visits and days of sick leave for LBP in the index billing period and the following year. SMT was associated with a higher proportion of imaging studies for LBP (30.6% vs. 23%, SMD: 0.164 [95% CI 0.143-0.185]). SMT did not lead to meaningful savings by replacing other health services for LBP. SMT for acute non-specific LBP in routine care was not clinically meaningful effective to reduce sick leave and reconsultation rates compared to no SMT and did not lead to meaningful savings by replacing other health services from the perspective of health insurance. This does not imply that SMT is ineffective but might reflect a problem with selection of suitable patients and the quality and quantity of SMT in routine care. National Manual Medicine societies should state clearly that imaging is not routinely needed prior to SMT in patients with low suspicion of presence of red flags and monitor the quality of provided services.