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- Govsyeyev, Nicholas, et al.
(författare)
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Etiology and outcomes of amputation in patients with peripheral artery disease in the EUCLID trial
- 2022
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Ingår i: Journal of Vascular Surgery. - : Elsevier. - 0741-5214 .- 1097-6809. ; 75:2, s. 660-670e3
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Tidskriftsartikel (refereegranskat)abstract
- Objective: Amputation remains a frequent and feared outcome in patients with peripheral artery disease (PAD). Although typically characterized as major or minor on the extent of tissue loss, the etiologies and outcomes after amputation by extent are not well-understood. In addition, emerging data suggest that the drivers and outcomes of amputation in patients with PAD may differ in those with and without diabetes mellitus (DM).Methods: The EUCLID trial randomized 13,885 patients with symptomatic PAD, including 5345 with concomitant diabetes, to ticagrelor or clopidogrel and followed them for long-term outcomes. Amputations were prospectively reported by trial investigators. Their primary and contributing drivers were adjudicated using safety data, including infection, ischemia, or multifactorial etiologies. Outcomes following major and minor amputations were analyzed, including recurrent amputation, major adverse limb events, adverse cardiovascular events, and mortality. Multivariable logistic regression models were used to identify independent predictors of minor amputations. Analyses were performed overall and stratified by the presence or absence of DM at baseline.Results: Of the patients randomized, 398 (2.9%) underwent at least one lower extremity nontraumatic amputation, for a total of 511 amputations (255 major and 256 minor) over a median of 30 months. A history of minor amputation was the strongest independent predictor for a subsequent minor amputation (odds ratio, 7.29; 95% confidence interval, 5.17-10.30; P <.001) followed by comorbid DM (odds ratio, 4.60; 95% confidence interval, 3.16-6.69; P <.001). Compared with patients who had a major amputation, those with a minor amputation had similar rates of subsequent major amputation (12.2% vs 13.6%), major adverse limb events (15.1% vs 14.9%), and major adverse cardiovascular events (17.6% vs 16.3%). Ischemia alone was the primary driver of amputation (51%), followed by infection alone (27%), and multifactorial etiologies (22%); however, infection was the most frequent driver in those with DM (58%) but not in those without DM (15%).Conclusions: Outcomes after amputation remain poor regardless of whether they are categorized as major or minor. The pattern of amputation drivers in PAD differs by history of DM, with infection being the dominant etiology in those with DM and ischemia in those without DM. Greater focus is needed on the prognostic importance of minor amputation and of the multifactorial etiologies of amputation in PAD. Nomenclature with anatomical description of amputations and eliminating terms "major" or "minor" would seem appropriate.
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| 2. |
- Schweinsberg, Martin, et al.
(författare)
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Same data, different conclusions : Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis
- 2021
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Ingår i: Organizational Behavior and Human Decision Processes. - : Elsevier BV. - 0749-5978 .- 1095-9920. ; 165, s. 228-249
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Tidskriftsartikel (refereegranskat)abstract
- In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists' gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for orga-nizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed.
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