Brian Hutton

Tuesday's rain will briefly mix with flurries, especially north of Pittsburgh.

Tuesday is an Impact Day for accumulating snow in the morning. See when the snow will fall and how much we will get.

A storm will bring accumulating snow to the Pittsburgh region on Tuesday. A winter weather advisory has been issued throughout western Pennsylvania.Tuesday

Pittsburgh is seeing its first accumulating snow of the season. A winter weather advisory is in effect throughout western Pennsylvania on Tuesday.Tuesday is an Impact Day for morning snow showers.

Snow is expected to return late Saturday afternoon and continue into the nighttime hours. A winter weather advisory and a winter storm warning have been issued.

See when the snow will fall and how much we could get.

Impact Day: Rain to Light Snow, Dropping Temps, & Windy for Western PA

A cold front arrives tonight to bring rain showers and usher in windy conditions and colder air to end the year.

Introduction Patient and public involvement (PPI) in research is increasingly recognised for its potential to enhance feasibility, improve relevance and foster collaboration at different stages of a study. Reporting guidelines such as GRIPP2 (Guidance for Reporting Involvement of Patients and the Public) have been developed to help improve completeness and transparency in PPI reporting. This meta-research project aims to assess the impact of the GRIPP2 reporting guidelines through citation and alternative metrics, analysing its uptake or adoption across authors, institutions, journals and countries, as well as its practical application in reporting PPI within diverse research designs.Methods and analysis This protocol for a meta-research project consists of two studies. In Study 1, we will conduct a search across Web of Science, Scopus and Google Scholar to identify all publications citing the GRIPP2 guidelines (planned for July 2026 using forward citation analysis). Retrieved records will undergo standardised processing and structured de-duplication to ensure each citing article is represented once. Following de-duplication, data from unique citations—including title, publication year, journal, subject category, keywords, document type, citations, authors’ names, institutional affiliations, country and funding sources—will be collected. Citation counts, alternative metrics (eg, mentions in policy documents, news media) and knowledge production patterns across authors, institutions, journals and countries will be analysed to assess GRIPP2’s impact and uptake of the guidelines. Descriptive analyses will be conducted (including the number of papers, citations, authors, countries, journals, keywords, funding, field distribution and main collaboration metrics). Network analyses will be carried out to study the structure of collaborations. In Study 2, we will evaluate a random sample of 300 research articles citing GRIPP2, including randomised trials (n=100), systematic reviews with meta-analyses (n=100) and health economic evaluations (n=100). If an insufficient number of citing studies are available within these categories, we will include additional study types identified in Study 1 (eg, study protocols, observational studies, mixed-methods or qualitative research studies and other types of reviews). Reporting and PPI practices in each article will be extracted by at least two researchers using a standardised data extraction form. Information on general, methodological and PPI items will be analysed and reported, stratified by study design (eg, randomised trials vs systematic reviews vs health economic evaluations).Ethics and dissemination Due to the nature of the proposed study, no ethical approval will be required. All data will be deposited in a cross-disciplinary public repository. It is anticipated the study findings could be relevant to a variety of audiences. Study findings will be disseminated at scientific conferences and published in peer-reviewed journals.Trial registration number Open Science Framework:

Systematic reviews with network meta-analysis frequently evaluate complex interventions combining multiple healthcare interventions (known as components). Components may act separately of each other or in conjunction with other components, synergistically or antagonistically. Component effect estimation is crucial to produce relevant and clinically meaningful evidence. However, standard network meta-analysis cannot quantify individual component effects of complex interventions. This article presents methods for modelling complex interventions and highlights the advantages and limitations of component network meta-analysis (CNMA). CNMA enables the estimation of individual component effects, whether additive or interactive. Interaction CNMA can be considered an extension of the additive CNMA model that allows component effects to vary in the presence of each other. This article presents practical guidance on how to carry out these analyses via empirical examples, which showcase both the strengths and limitations of CNMA. Implementing CNMA models is complex and requires the skills of a multidisciplinary team including clinicians, methodologists, and statisticians.Systematic reviews frequently evaluate complex interventions that combine multiple healthcare interventions—called components—to achieve important patient and health system outcomes.12 Clinicians and patients may want to know the safest and most effective individual component and combination of components among many identifiable components and combinations to treat or prevent a given condition. For example, non-drug interventions, such as fall prevention interventions,3 usually share common components that relate to the nature of the intervention (eg, fall prevention devices, social engagement, cognitive behavioural therapy), provider (eg, clinician, nurse, lay person), intensity (eg, daily, weekly), setting (eg, hospital, home, community), and mode of delivery (eg, virtually, in-person). Clinicians and patients need to know what are the most effective components for fall prevention, which can be tailored to their circumstances. Quantitative methods—such as an extension of the standard network meta-analysis (NMA), component NMA (CNMA)—can compare complex interventions and their separate …