Assessment of Tree-Based Statistical Learning to Estimate Optimal Personalized Treatment Decision Rules for Traumatic Finger Amputations Article Swipe
Kelly Speth
,
Alfred P. Yoon
,
Lu Wang
,
Kevin C. Chung
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1001/jamanetworkopen.2019.21626
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1001/jamanetworkopen.2019.21626
IMPORTANCE: Optimal treatment for traumatic finger amputation is unknown to date. OBJECTIVE: To use statistical learning methods to estimate evidence-based treatment assignment rules to enhance long-term functional and patient-reported outcomes in patients after traumatic amputation of fingers distal to the metacarpophalangeal joint. DESIGN, SETTING, AND PARTICIPANTS: This decision analytical model used data from a retrospective cohort study of 338 consenting adult patients who underwent revision amputation or replantation at 19 centers in the United States and Asia from August 1, 2016, to April 12, 2018. Of those, data on 185 patients were included in the primary analysis. EXPOSURES: Treatment with revision amputation or replantation. MAIN OUTCOMES AND MEASURES: Outcome measures were hand strength, dexterity, hand-related quality of life, and pain. A tree-based statistical learning method was used to derive clinical decision rules for treatment of traumatic finger amputation. RESULTS: Among 185 study participants (mean [SD] age, 45 [16] years; 156 [84%] male), the median number of fingers amputated per patient was 1 (range, 1-5); 115 amputations (62%) were distal to the proximal interphalangeal joint, and 110 (60%) affected the nondominant hand. On the basis of the tree-based statistical learning estimates, to maximize hand dexterity or to minimize patient-reported pain, replantation was found to be the best strategy. To maximize hand strength, revision amputation was the best strategy for patients with a single-finger amputation but replantation was preferred for all other injury patterns. To maximize patient-reported quality of life, revision amputation was the best approach for patients with dominant hand injuries, and replantation was the best strategy for patients with nondominant hand injuries. CONCLUSIONS AND RELEVANCE: The findings suggest that the approach to treating traumatic finger amputations varies based on the patient’s injury characteristics and functional needs.
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Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1001/jamanetworkopen.2019.21626
- https://jamanetwork.com/journals/jamanetworkopen/articlepdf/2761548/speth_2020_oi_190812.pdf
- OA Status
- gold
- Cited By
- 9
- References
- 42
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3007360914Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1001/jamanetworkopen.2019.21626Digital Object Identifier
- Title
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Assessment of Tree-Based Statistical Learning to Estimate Optimal Personalized Treatment Decision Rules for Traumatic Finger AmputationsWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-02-21Full publication date if available
- Authors
-
Kelly Speth, Alfred P. Yoon, Lu Wang, Kevin C. ChungList of authors in order
- Landing page
-
https://doi.org/10.1001/jamanetworkopen.2019.21626Publisher landing page
- PDF URL
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https://jamanetwork.com/journals/jamanetworkopen/articlepdf/2761548/speth_2020_oi_190812.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://jamanetwork.com/journals/jamanetworkopen/articlepdf/2761548/speth_2020_oi_190812.pdfDirect OA link when available
- Concepts
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Amputation, Replantation, Medicine, Quality of life (healthcare), Surgery, Metacarpophalangeal joint, Interphalangeal Joint, Range of motion, Physical therapy, Thumb, NursingTop concepts (fields/topics) attached by OpenAlex
- Cited by
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9Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 1, 2023: 1, 2022: 1, 2021: 3Per-year citation counts (last 5 years)
- References (count)
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42Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W1992463313, https://openalex.org/W4250730523, https://openalex.org/W2590404929, https://openalex.org/W2789257385, https://openalex.org/W4254399638, https://openalex.org/W1964171796, https://openalex.org/W2087087121, https://openalex.org/W2416491336, https://openalex.org/W2021196901, https://openalex.org/W2939255606, https://openalex.org/W2073654584, https://openalex.org/W2028332018, https://openalex.org/W2188278300, https://openalex.org/W2053261213, https://openalex.org/W2070705145, https://openalex.org/W1988764089, https://openalex.org/W2892114828, https://openalex.org/W2036193982, https://openalex.org/W2139149106, https://openalex.org/W4244201324, https://openalex.org/W2021645358, https://openalex.org/W2112800880, https://openalex.org/W6734147592, https://openalex.org/W2888812268, https://openalex.org/W4253573792, https://openalex.org/W2130732995, https://openalex.org/W2089281600, https://openalex.org/W2065921149, https://openalex.org/W2600229727, https://openalex.org/W2024764362, https://openalex.org/W2061107261, https://openalex.org/W2934399013, https://openalex.org/W2177870565, https://openalex.org/W2314301696, https://openalex.org/W1989097401, https://openalex.org/W2020505357, https://openalex.org/W2589214206, https://openalex.org/W1999233430, https://openalex.org/W2970567995, https://openalex.org/W1985624390, https://openalex.org/W1974884549, https://openalex.org/W1492815834 |
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| abstract_inverted_index.1 | 161 |
| abstract_inverted_index.A | 120 |
| abstract_inverted_index.a | 53, 220 |
| abstract_inverted_index.1, | 79 |
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| abstract_inverted_index.110 | 175 |
| abstract_inverted_index.115 | 164 |
| abstract_inverted_index.12, | 83 |
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| abstract_inverted_index.185 | 89, 140 |
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| abstract_inverted_index.[16] | 147 |
| abstract_inverted_index.[SD] | 144 |
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