Comparing and combining stable isotope datasets from different laboratories and different years is essential for many research areas, such as isotope hydrology, greenhouse gas observations, food studies, isotope forensics, palaeo-reconstructions, etc. Data compatibility (i.e. the ability to combine data) is related to the data quality. The prerequisite for data comparability is data normalization to a common stable isotope scale (often referred to as calibration) based on reliable reference materials (RMs) with accurately assigned values and uncertainties. Still, that does not guarantee the data compatibility (mutual agreement). Albeit metrological concepts related to data compatibility and measurement uncertainty have been developed and applied to analytical chemistry in general, these concepts have not yet been fully applied to stable isotope research. This can affect daily calibrations, analytical data and, therefore, data compatibility. In addition, IRMS users often prepare different laboratory standards themselves. Thereafter, users should then understand the contemporary concepts used for assigning RM value and uncertainty, as well as the limitations and potential problems associated with RMs. The history of RMs, preparation reports and also some problems in the past provide lessons to be learned. These include the δ13C drift of LSVEC (the second anchor on the δ13C scale before 2017), revisions to the value assignment principles, the introduction of replacements for LSVEC, related disputes and the potential underestimation of uncertainties for secondary RMs. The review describes metrological concepts related to isotopic scales, RMs and calibration hierarchies and data compatibility. The main RMs and their uncertainties are reviewed through the lens of metrology concepts. Additional focus is given to the VPDB scale for δ13C and issues of scale discontinuity, which can significantly reduce data compatibility in δ13C. The given examples of value and uncertainty assignment for RMs should be viewed as an example of value and uncertainty calculation in daily practice.

The appropriate use of predictive equations in estimating body composition through bioelectrical impedance analysis (BIA) depends on the device used and the subject\'s age, geographical ancestry, healthy status, physical activity level and sex. However, the presence of many isolated predictive equations in the literature makes the correct choice challenging, since the user may not distinguish its appropriateness. Therefore, the present systematic review aimed to classify each predictive equation in accordance with the independent parameters used. Sixty-four studies published between 1988 and 2023 were identified through a systematic search of international electronic databases. We included studies providing predictive equations derived from criterion methods, such as multi-compartment models for fat, fat-free and lean soft mass, dilution techniques for total-body water and extracellular water, total-body potassium for body cell mass, and magnetic resonance imaging or computerized tomography for skeletal muscle mass. The studies were excluded if non-criterion methods were employed or if the developed predictive equations involved mixed populations without specific codes or variables in the regression model. A total of 106 predictive equations were retrieved; 86 predictive equations were based on foot-to-hand and 20 on segmental technology, with no equations used the hand-to-hand and leg-to-leg. Classifying the subject\'s characteristics, 19 were for underaged, 26 for adults, 19 for athletes, 26 for elderly and 16 for individuals with diseases, encompassing both sexes. Practitioners now have an updated list of predictive equations for assessing body composition using BIA. Researchers are encouraged to generate novel predictive equations for scenarios not covered by the current literature.Registration code in PROSPERO: CRD42023467894.

The accuracy of artificial intelligence-aided (AI) caries diagnosis can vary considerably depending on numerous factors. This review aimed to assess the diagnostic accuracy of AI models for caries detection and classification on bitewing radiographs. Publications after 2010 were screened in five databases. A customized risk of bias (RoB) assessment tool was developed and applied to the 14 articles that met the inclusion criteria out of 935 references. Dataset sizes ranged from 112 to 3686 radiographs. While 86 % of the studies reported a model with an accuracy of ≥80 %, most exhibited unclear or high risk of bias. Three studies compared the model\'s diagnostic performance to dentists, in which the models consistently showed higher average sensitivity. Five studies were included in a bivariate diagnostic random-effects meta-analysis for overall caries detection. The diagnostic odds ratio was 55.8 (95 % CI= 28.8 - 108.3), and the summary sensitivity and specificity were 0.87 (0.76 - 0.94) and 0.89 (0.75 - 0.960), respectively. Independent meta-analyses for dentin and enamel caries detection were conducted and showed sensitivities of 0.84 (0.80 - 0.87) and 0.71 (0.66 - 0.75), respectively. Despite the promising diagnostic performance of AI models, the lack of high-quality, adequately reported, and externally validated studies highlight current challenges and future research needs.

BACKGROUND: Medication review (MR) is the systematic assessment of a patient\'s medications for safety and effectiveness by a healthcare professional. The language used to describe MR activity, such as stopped medicine and increased dose, should be consistent across studies to assist researchers compare how different services operate and identify their mechanism of impact.
OBJECTIVE: To develop an international taxonomy of standardized terms and activity definitions related to medication reviews.
METHODS: This was a three-stage Delphi-based consensus study with international medication review experts. A systematic review provided MR activity terms for the survey. Experts rated their consensus on each activity term and its definition on a Likert scale and provided written feedback. The consensus was 75% panel agreement. At each stage, consensus elements were retained, and feedback was used to revise definitions.
RESULTS: Seven experts were recruited for the study (response rate 15.2%) from four countries: the United Kingdom (n = 4), New Zealand (n = 1), Australia (n = 1), and Malaysia (n = 1). The following terms achieved consensus: the term Medication as a descriptor for MR terms; discontinue medication, start medication, dose increase, dose decrease, dosage form change, and medication safety and efficacy monitor to describe MR activity; Educate to describe the delivery of healthcare professionals and patients/carers education.
CONCLUSIONS: Standardized medication review activity terms and definitions have been selected for universal adoption in all future MR research to facilitate a meaningful comparison of process evaluations within different settings.

In the current neurosurgical field, there is a constant emphasis on providing the best care with the most value. Such work requires the constant optimization of not only surgical but also perioperative services. Recent work has demonstrated the power of standardized techniques in limiting complication while promoting optimal outcomes. In this review article, protocols addressing operative and perioperative care for common pediatric neurosurgical procedures are discussed. These articles address how various institutions have optimized procedures through standardization. Our objective is to improve patient outcomes through the optimization of protocols.

OBJECTIVE: This systematic review aims to elucidate the methodological practices and reporting standards associated with sequence analysis (SA) for the identification of clinical pathways in real-world scenarios, using routinely collected data.
METHODS: We conducted a methodological systematic review, searching five medical and health databases: MEDLINE, PsycINFO, CINAHL, EMBASE and Web of Science. The search encompassed articles from the inception of these databases up to February 28, 2023. The search strategy comprised two distinctive sets of search terms, specifically focused on sequence analysis and clinical pathways.
RESULTS: 19 studies met the eligibility criteria for this systematic review. Nearly 60% of the included studies were published in or after 2021, with a significant proportion originating from Canada (n = 7) and France (n = 5). 90% of the studies adhered to the fundamental SA steps. The optimal matching (OM) method emerged as the most frequently employed dissimilarity measure (63%), while agglomerative hierarchical clustering using Ward\'s linkage was the preferred clustering algorithm (53%). However, it is imperative to underline that a majority of the studies inadequately reported key methodological decisions pertaining to SA.
CONCLUSIONS: This review underscores the necessity for enhanced transparency in reporting both data management procedures and key methodological choices within SA processes. The development of reporting guidelines and a robust appraisal tool tailored to assess the quality of SA would be invaluable for researchers in this field.

OBJECTIVE: Endovascular technology innovation requires rigorous evaluation in high quality randomised controlled trials (RCTs). However, due to numerous methodological challenges, RCTs evaluating endovascular interventions are complex and potentially difficult to design, conduct, and report. This systematic review aimed to assess the quality of reporting of RCTs for endovascular interventions for lower limb peripheral arterial disease (PAD).
METHODS: A systematic review of Medline, Embase, and the Cochrane Library databases from inception to December 2021 was performed to identify RCTs including participants with PAD undergoing any infrainguinal lower limb endovascular intervention. Study data were extracted and assessed against the Consolidating Standards of Reporting Trials extension for Non-Pharmacological Treatments (CONSORT-NPT) and the Template for Intervention Description and Replication (TIDieR) checklists. Descriptive statistics were used to summarise general study details and reporting standards of the trials.
RESULTS: After screening 6 567 abstracts and 526 full text articles, 112 eligible studies were identified, reporting on 228 different endovascular devices and techniques. Details judged sufficient to replicate the investigated intervention were provided for 47 (21%) interventions. It was unclear whether the description was reported with sufficient details in a further 56 (24%), and the description was judged inadequate in 125 (55%). Any intervention descriptions were provided for 184 (81%), with variable levels of detail (some in 134 [59%] and precise in 50 [22%]). Standardisation of intervention or some aspect of this was reported in 25 (22%) trials, but only one specified that adherence to the study protocol would be monitored.
CONCLUSIONS: The quality of the reporting standards of RCTs investigating lower limb endovascular treatments is severely limited because the interventions are poorly described, standardised, and reported. PROSPERO registration number: CRD42022288214.

Investigators are increasingly measuring skeletal muscle (SM) and adipose tissue (AT) change during cancer treatment to understand impact on patient outcomes. Recent meta-analyses have reported high heterogeneity in this literature, representing uncertainty in the resulting estimates. Using the setting of palliative-intent chemotherapy as an exemplar, we aimed to systematically summarize the sources of variability among studies evaluating SM and AT change during cancer treatment and propose standards for future studies to enable reliable meta-analysis. Studies that measured computed tomography-defined SM and/or AT change in adult patients during palliative-intent chemotherapy for solid tumours were included, with no date or geographical limiters. Of 2496 publications screened by abstract/title, 83 were reviewed in full text and 38 included for extraction, representing 34 unique cohorts across 8 tumour sites. The timing of baseline measurement was frequently defined as prior to treatment, while endpoint timing ranged from 6 weeks after treatment start to time of progression. Fewer than 50% specified the actual time interval between measurements. Measurement error was infrequently discussed (8/34). A single metric (cm2 /m2 , cm2 or %) was used to describe SM change in 18/34 cohorts, while multiple metrics were presented for 10/34 and no descriptive metrics for 6/34. AT change metrics and sex-specific reporting were available for 10/34 cohorts. Associations between SM loss and overall survival were evaluated in 24 publications, with classification of SM loss ranging from any loss to >14% loss over variable time intervals. Age and sex were the most common covariates, with disease response in 50% of models. Despite a wealth of data and effort, heterogeneity in study design, reporting and statistical analysis hinders evidence synthesis regarding the severity and outcomes of SM and AT change during cancer treatment. Proposed standards for study design include selection of homogenous cohorts, clear definition of baseline/endpoint timing and attention to measurement error. Standard reporting should include baseline SM and AT by sex, actual scan interval, SM and AT change using multiple metrics and visualization of the range of change observed. Reporting by sex would advance understanding of sexual dimorphism in SM and AT change. Evaluating the impact of tissue change on outcomes requires adjustment for relevant covariates and concurrent disease response. Adoption of these standards by researchers and publishers would alter the current paradigm to enable meta-analysis of future studies and move the field towards meaningful application of SM and AT change to clinical care.

OBJECTIVE: To provide an overview of various sepsis International Classification of Diseases (ICD) coding methods and their diagnostic accuracy.
METHODS: We undertook a systematic scoping review between 1991 and 2020 (search terms: sepsis, coding, and epidemiology) to include studies reporting the accuracy of a sepsis ICD coding method. Studies were grouped by ICD coding method, number of diagnostic accuracy parameters, ICD version, reference standard, design, country, setting, type of dataset and sepsis definition. ICD coding methods were categorised as explicit or implicit, with the explicit methods further divided into wide and narrow groups. Descriptive statistics were used to present data.
RESULTS: We analysed 17 studies, of which 16 (94.1%) used retrospective medical chart review as the reference standard for clinical sepsis, and eight (47.1%) used hospital administrative data to identify sepsis. There were 53 assessments of various ICD coding methods, with 32 (60.4%) of them being explicit and 21 (39.6%) implicit methods. The coding methods had a median sensitivity of <75% but a median specificity of >85%. However, a wide variation was noted in the diagnostic accuracy parameters of all ICD coding methods. Most of the studies showed high methodological quality.
CONCLUSIONS: None of the current ICD coding methods is optimal for identifying sepsis.

Most diagnostic studies exclude missing values and inconclusive results from the analysis or apply simple methods resulting in biased accuracy estimates. This may be due to the lack of availability or awareness of appropriate methods. This scoping review aimed to provide an overview of strategies to handle missing values and inconclusive results in the reference standard or index test in diagnostic accuracy studies. Conducting a systematic literature search in MEDLINE, Cochrane Library, and Web of Science, we could identify many articles proposing methods for addressing missing values in the reference standard. There are also several articles describing methods regarding missing values or inconclusive results in the index test. The latter encompass imputation, frequentist and Bayesian likelihood, model-based, and latent class methods. While methods for missing values in the reference standard are regularly applied in practice, this is not true for methods addressing missing values and inconclusive results in the index test. Our comprehensive overview and description of available methods may raise further awareness of these methods and will enhance their application. Future research is needed to compare the performance of these methods under different conditions to give valid and robust recommendations for their usage in various diagnostic accuracy research scenarios.