Purpose: The objective was to investigate the consistency in cumulative revision rates (CRRs) for a selection of total hip arthroplasty cups and stems across national/regional hip arthroplasty registries worldwide. • Methods: Ten cups and ten stems from total hip systems were randomly selected. Two frequently used implants across registries were added, totalling 11 cups and 11 stems. CRRs and 95% CIs were extracted from the latest annual registry reports using these implants. CRRs were pooled for each cup or stem, and differences between cup-stem combinations and between registries were investigated. • Results: CRRs were available for ten cups and eight stems from eight registries, totalling 552,148 cups and 727,447 stems. Follow-up was 1–20 years. The 5-year CRR pooled for all cups was 2.9% (95% CI: 2.3–3.6) and for all stems, 3.0% (95% CI: 2.4–3.8). Homogeneous (consistent) CRRs with respect to both associated implant and country were observed for two cups and three stems. Significant differences in CRR were identified in one cup by associated implant only, in one cup by registry only, and in two cups and four stems for both. Sparse data prevented evaluation of four cups and one stem. • Conclusion: Registries’ annual reports provide a large amount of publicly available information on CRRs of specific implants. These CRRs can be synthesised to improve the assessment of implant performance over time. Our CRR analysis represents a promising approach to detect implants with a consistent low- or high-risk pattern across registries.

Background and purpose — The safety and performance of hip and knee prostheses can be assessed by ana-lyzing peer-reviewed literature, registry reports, and safety notices published by national competent authorities/regula-tory agencies, or manufacturers. The percentage of hip and knee prostheses with a safety signal published through any of these data sources is unknown. We aimed to assess the frequency of signals identified for a random sample of 10 hip stems, 10 hip cups, and 10 knee implants. Methods — 3 literature libraries were searched to find safety signals defined as information on patterns/occurrences that may alter the device’s benefit–risk profile, reported in peer-reviewed publications for the randomly selected implants. Annual registry reports from 5 national registries were examined to check whether any of the selected implants had outlier performance. The CORE-MD post-market surveillance (PMS) tool was used to collect all related safety notices from 13 competent authority/regulatory agency websites. Manufacturers’ websites were screened for any reported safety information. Results — Safety signals were identified for 21 of the 30 randomly selected implants: 18 identified by registries, 7 by the CORE-MD PMS tool, and 8 based on literature, with 10 implants identified by multiple sources. There was no systematic pattern in timing of publication with a particular source publishing safety signals earlier than other sources. Conclusion — 70% of the randomly selected hip and knee prostheses had ≥ 1 safety signals published, with registries as the source for the majority. No single source identified all 21 implants with signals, which highlights the need for a comprehensive surveillance strategy to aggregate safety signals from multiple sources.

In the European Union (EU) the delivery of health services is a national responsibility but there are concerted actions between member states to protect public health. Approval of pharmaceutical products is the responsibility of the European Medicines Agency, whereas authorizing the placing on the market of medical devices is decentralized to independent 'conformity assessment' organizations called notified bodies. The first legal basis for an EU system of evaluating medical devices and approving their market access was the medical device directives, from the 1990s. Uncertainties about clinical evidence requirements, among other reasons, led to the EU Medical Device Regulation (2017/745) that has applied since May 2021. It provides general principles for clinical investigations but few methodological details-which challenges responsible authorities to set appropriate balances between regulation and innovation, pre- and post-market studies, and clinical trials and real-world evidence. Scientific experts should advise on methods and standards for assessing and approving new high-risk devices, and safety, efficacy, and transparency of evidence should be paramount. The European Commission recently awarded a Horizon 2020 grant to a consortium led by the European Society of Cardiology and the European Federation of National Associations of Orthopaedics and Traumatology, that will review methodologies of clinical investigations, advise on study designs, and develop recommendations for aggregating clinical data from registries and other real-world sources. The CORE-MD project (Coordinating Research and Evidence for Medical Devices) will run until March 2024; here we describe how it may contribute to the development of regulatory science in Europe.

Interactions between spatial and temporal variability of rainfall and catchment characteristics strongly influence hydrological response. In urban areas, where runoff generation is fast due to high imperviousness degree, it is especially relevant to capture the high spatiotemporal rainfall variability. Significant progress has been made in the development of spatially distributed rainfall measurements and of distributed hydrological models, to represent the variability of catchment's characteristics. Interactions between rainfall and basin scales on hydrological response sensitivity, however, needs deeper investigation. A previous study investigated the hydrological response in the small urbanized catchment of Cranbrook (8 km ² , London, UK) and proposed three dimensionless “scale factors” to identify if the available rainfall resolution is sufficient to properly predict hydrological response. We aim to verify the applicability of these scale factors to larger scales, with a distinct physiographic setting, in Little Sugar Creek (111 km ² , Charlotte, USA), to identify the required rainfall resolution and to predict model performance. Twenty-eight events were selected from a weather radar data set from the National Weather Radar Network, with a resolution of 1 km ² and 15 min. Rainfall data were aggregated to coarser resolutions and used as input for a distributed hydrological model. Results show that scale factors and associated thresholds are generally applicable for characterization of urban flood response to rainfall across spatiotemporal scales. Additionally, application of scale factors in observation-based analysis supports identification of event characteristics that are poorly captured and critical improvements that need to be made before the model can benefit from high-resolution rainfall.

The impact of spatial and temporal variability of rainfall on hydrological response remains poorly understood, in particular in urban catchments due to their strong variability in land use, a high degree of imperviousness and the presence of stormwater infrastructure. In this study, we analyze the effect of storm scale, position and movement in relation to basin scale and flow-path network structure on urban hydrological response. A catalog of 279 peak events was extracted from a high-quality observational dataset covering 15 years of flow observations and radar rainfall data for five (semi)urbanized basins ranging from 7.0 to 111.1km2 in size. Results showed that the largest peak flows in the event catalog were associated with storm core scales exceeding basin scale, for all except the largest basin. Spatial scale of flood-producing storm events in the smaller basins fell into two groups: Storms of large spatial scales exceeding basin size or small, concentrated events, with storm core much smaller than basin size. For the majority of events, spatial rainfall variability was strongly smoothed by the flow-path network, increasingly so for larger basin size. Correlation analysis showed that position of the storm in relation to the flow-path network was significantly correlated with peak flow in the smallest and in the two more urbanized basins. Analysis of storm movement relative to the flow-path network showed that direction of storm movement, upstream or downstream relative to the flow-path network, had little influence on hydrological response. Slow-moving storms tend to be associated with higher peak flows and longer lag times. Unexpectedly, position of the storm relative to impervious cover within the basins had little effect on flow peaks. These findings show the importance of observation-based analysis in validating and improving our understanding of interactions between the spatial distribution of rainfall and catchment variability.

We examine urban flood response through data-driven analyses for a diverse sample of “small” watersheds (basin scale ranging from 7.0 to 111.1 km²) in the Charlotte Metropolitan region. These watersheds have experienced extensive urbanization and suburban development since the 1960s. The objective of this study is to develop a broad characterization of land surface and hydrometeorological controls of urban flood hydrology. Our analyses are based on peaks-over-threshold flood data developed from USGS streamflow observations and are motivated by problems of flood hazard characterization for urban regions. We examine flood-producing rainfall using high-resolution (1 km² spatial resolution and 15 min time resolution), bias-corrected radar rainfall fields that are developed through the Hydro-NEXRAD system. The analyses focus on the 2001–2015 period. The results highlight the complexities of urban flood response. There are striking spatial heterogeneities in flood peak magnitudes, response times, and runoff ratios across the study region. These spatial heterogeneities are mainly linked to watershed scale, the distribution of impervious cover, and storm water management. Contrasting land surface properties also determine the mixture of flood-generating mechanisms for a particular watershed. Warm-season thunderstorm systems and tropical cyclones are main flood agents in Charlotte, with winter/spring storms playing a role in less-urbanized watersheds. The mixture of flood agents exerts a strong impact on the upper tail of flood frequency distributions. Antecedent watershed wetness plays a minor role in urban flood response, compared with less-urbanized watersheds. Implications for flood hazard characterization in urban watersheds and for advances in flood science are discussed.

The microphysical aspects of the relationship between radar reflectivity Z and rainfall rate R are examined. Various concepts discussed in the literature are integrated into a coherent analytical framework and discussed with a focus on the interpretability of Z-R relations from a microphysical point of view. The forward problem of analytically characterizing the Z-R relationship based on exponential, gamma, and monodisperse raindrop size distributions is highlighted as well as the inverse problem of a microphysical interpretation of empirically obtained Z-R relation coefficients. Three special modes that a Z-R relationship may attain are revealed, depending on whether the variability of the raindrop size distribution is governed by variations of drop number density, drop size, or a coordinated combination thereof with constant ratio of mean drop size and number density. A rain parameter diagram is presented that assists in diagnosing these microphysical modes. The number-controlled case results in linear Z-R relations that have been observed for steady and statistically homogeneous or equilibrium rainfall conditions. Most rainfall situations. however, exhibit a variability of drop spectra that is facilitated by a mix of variations of drop size and number density, which results in the well-known power-law Z-R relationships. Significant uncertainties are found to be associated with the retrieval of microphysical information from the Z-R relation coefficients, but even more so with shortcomings of the measurement of rainfall information and the subsequent processing of that data to obtain a Z-R relation. Given a proper consideration of the uncertainties, however, valuable microphysical information may be obtained, particularly as a result of long-term monitoring of rainfall for fixed observational settings but also through comparisons among different climatic rainfall regimes.

The intrastorm variability of raindrop size distributions as a source of uncertainty in single-parameter and dual-parameter radar rainfall estimates is studied using time series analyses of disdrometer observations. Two rain-rate (R) estimators are considered: the traditional single-parameter estimator using only the radar reflectivity factor (Z) and a dual-polarization estimator using a combination of radar reflectivity at horizontal polarization (Z_n) and differential reflectivity (Z_DR). A case study for a squall-line system passing over the Goodwin Creek experimental watershed in northern Mississippi is presented. Microphysically, the leading convective line is characterized by large raindrop concentrations (> 500 drops per cubic meter), large mean raindrop sizes ( > 1 mm), and wide raindrop size distributions (standard deviations >0.5 mm), as compared to the transition region and the trailing stratiform rain. The transition and stratiform phases have similar raindrop concentrations and mean raindrop sizes. Their main difference is that the distributions are wider in the latter. A scaling-law analysis reveals that the shapes of the sealed spectra are bent downward for small raindrop sizes in the leading convective line, slightly bent upward in the transition zone, and strongly bent upward in the trailing stratiform rain. The exponents of the resulting Z-R relationships are roughly the same for the leading convective line and the trailing stratiform rain ( ≈ 1.4) and slightly larger for the transition region ( ≈ 1.5), with prefactors increasing in this order: transition ( ≈ 200), convective ( ≈ 300), stratiform ( ≈ 450). In terms of rainfall estimation bias, the best-fit mean R(Z_H, Z_DR) relationship outperforms the best-fit mean R(Z) relationship, both for each storm phase separately and for the event as a whole.

The controls on the variability of raindrop size distributions in extreme rainfall and the associated radar reflectivity-rain rate relationships are studied using a scaling-law formalism for the description of raindrop size distributions and their properties. This scaling-law formalism enables a separation of the effects of changes in the scale of the raindrop size distribution from those in its shape. Parameters controlling the scale and shape of the scaled raindrop size distribution may be related to the microphysical processes generating extreme rainfall. A global scaling analysis of raindrop size distribution, corresponding to rain rates exceeding 100 mm h^-1, collected during the 1950s with the Illinois State Water Survey raindrop camera in Miami, Florida, reveals that extreme rain rates tend to be associated with conditions in which the variability of the raindrop size distribution is strongly number controlled (i.e., characteristic drop sizes are roughly constant). This means that changes in properties of raindrop size distributions in extreme rainfall are largely produced by varying raindrop concentrations. As a result, rainfall integral variables (such as radar reflectivity and rain rate) are roughly proportional to each other, which is consistent with the concept of the so-called equilibrium raindrop size distribution and has profound implications for radar measurement of extreme rainfall. A time series analysis for two contrasting extreme rainfall events supports the hypothesis that the variability of raindrop size distributions for extreme rain rates is strongly number controlled. However, this analysis also reveals that the actual shapes of the (measured and scaled) spectra may differ significantly from storm to storm. This implies that the exponents of power-law radar reflectivity-rain rate relationships may be similar and close to unity, for different extreme rainfall events, but their prefactors may differ substantially. Consequently, there is no unique radar reflectivity-rain rate relationship for extreme rain rates, but the variability is essentially reduced to one free parameter (i.e., the prefactor). It is suggested that this free parameter may be estimated on the basis of differential reflectivity measurements in extreme rainfall.