Annals of Internal Medicine最新文献

Background: Firearm acquisitions in the United States surged after the onset of the pandemic. The increase, sustained through at least early 2021, resulted from a modest increase in the proportion of long-standing gun owners who purchased firearms (most were White and men) and an unprecedented increase in the proportion of adults who became new gun owners (half were women; half were Hispanic and/or people of color). Little is known about firearm acquisitions beyond 2021.

Objective: To estimate the number of adults who acquired firearms since 1 January 2021, how many were new owners, and how many other people they newly exposed to household firearms.

Design: Probability-based national survey conducted 18 December to 25 December 2024.

Setting: United States.

Participants: 4059 firearm owners.

Measurements: The number and characteristics of respondents who acquired firearms from 2021 to 2024, distinguishing those who already owned firearms from those who did not; among the latter, the number of household members newly exposed to firearms.

Results: An estimated 29.8 million adults (95% CI, 28.2 to 31.5 million) acquired firearms from 2021 to 2024; 11.2 million adults (CI, 10.2 to 12.4 million) became new gun owners (4.2% of U.S. adults). The annual number of new owners declined monotonically, from 3.6 million in 2021 to 1.9 million by 2024. Women made up 46.3% (CI, 41.4% to 51.6%) of new owners; 46.1% (CI, 41.0% to 51.4%) were Hispanic and/or people of color; and 7.8 million lived in a household without firearms at the time of their earliest purchase, newly exposing 9.0 million other adults (CI, 7.5 to 10.6 million) and 6.6 million children (CI, 5.2 to 8.0 million) to household firearms.

Limitation: Retrospective assessment of when respondents purchased firearms.

Conclusion: These findings underscore the need for periodic survey-based assessments of firearm exposure and suggest that the risk for violent death has likely increased substantially for millions of Americans who became new gun owners and for millions of other adults and children who were newly exposed to the risks of living in households with guns.

Primary funding source: Joyce Foundation, Fund for a Safer Future, and Robert Wood Johnson Foundation.

Evidence-based decision making in health often requires comparison of multiple options for a given condition. The GRADE (Grading of Recommendations Assessment, Development and Evaluation) evidence-to-decision (EtD) framework provides a structured approach for moving from evidence to decisions but was originally designed for pairwise comparisons. Hence, there is a need to accommodate decision making based on multiple comparisons, especially with the increasing use of systematic reviews and network meta-analyses in guideline development. Furthermore, since the original EtD framework was developed, further relevant GRADE guidance has been developed.

The aim of this work was to develop a new EtD framework to accommodate multiple comparisons and reflect current GRADE guidance. The new EtD framework was revised and developed through iterative discussion, feedback, and refinement by the GRADE EtD Project Group and the GRADE Working Group. Experiences and examples from guideline developers, methodological experts, and other stakeholders informed improvements in its structure and usability for multiple comparisons and were subsequently approved by the GRADE Working Group.

This article describes the new EtD framework, which now includes 2 corresponding parts for reviews of pairwise and multiple comparisons. The authors describe application to a review with multiple comparisons for the different parts of the EtD framework: the question definition, which now includes the presentation of values of health outcomes and decision thresholds; the assessment section, where the new "net effect" criterion has been included; and the conclusion section, which includes an adaptation for multiple comparisons. The article provides examples and suggestions for presentation of findings. The framework does have limitations, in that its usability has not been tested across a broad spectrum of guideline development contexts.

Background: Systematic reviews can inform research, funding, and guideline decisions. However, it can be challenging to know whether a systematic review has answered a research question conclusively, and it is unclear which methods exist for such assessments.

Purpose: To map methods related to determining the conclusiveness of systematic reviews.

Data sources: Medline (Ovid), Embase (Ovid), and Web of Science until 26 September 2025.

Study selection: Any documents describing methods for determining the conclusiveness of systematic reviews.

Data extraction: Two reviewers independently extracted data from the primary references of the included methods. Forward citation searches of the primary references were then conducted to identify examples of application of the methods.

Data synthesis: Sixty-two methods related to assessing the conclusiveness of systematic review results were identified; 45 of these had at least 1 example of their application. The 62 methods were categorized into 3 approaches comprising 23 groups. Mathematical approaches for meta-analyses included 29 methods categorized into 9 groups, such as the fail-safe number, Barrowman's n, and the fragility index. Mathematical approaches for cumulative meta-analyses comprised 15 methods categorized into 7 groups, including trial sequential analyses, sequential meta-analyses, and the law of the iterated logarithm methods. Nonmathematical approaches included 18 methods across 7 groups, such as GRADE (Grading of Recommendations Assessment, Development and Evaluation) frameworks, Ottawa methods, and the RAND method.

Limitations: There was no assessment of which methods perform better. Not all methods strictly aimed to determine conclusiveness.

Conclusion: This review identified various methods related to assessing the conclusiveness of systematic reviews to enhance their ability to guide research, funding, and clinical decisions.

Primary funding source: Western Norway University of Applied Sciences. (Protocol registered in the Open Science Framework [https://osf.io/dthps]).