Outcome Validation of a Simulation Based Patient Specific TKA Planning Tool Article Swipe
Joshua Twiggs
,
Justin Roe
,
Brett Fritsch
,
David Parker
,
Brad Miles
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.29007/3mvp
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.29007/3mvp
Dynamic knee computer simulations are a promising surgical planning option in TKA, allowing the impact of plan alterations on joint dynamics to be analysed prior to surgery. Previously, the dynamic results of our simulation have been shown to correlate with outcome; here we show validation of its use in pre-operative planning. A database of TKA Patients undergoing surgery from 1-Jan-2014 operated on by 9 surgeons, who received a pre-operative and post-operative CT were assessed. A musculoskeletal computational model with similar boundary conditions to the Oxford Knee Rig was used to simulate post-TKA knee dynamics using Adams MSC software (Newport, CA). In addition, a set of pre-operative simulations were generated covering positional variations. The Dynamic Knee Score (DKS), a predictive algorithm machine learned from KOOS scored postoperative cases to predict outcome in preoperative planning was applied to all simulations. Patients were split into groups depending on whether the ‘post-operative achieved position’ was the ‘best’ of the preoperative modelled options in terms of simulated DKS score or not. These results were compared with 12 month postoperative KOOS scores. Cases where the best plan was followed had better outcome results. A relationship was shown with the KOOS Pain subscore, with the portion of patients below a KOOS Pain score of 70 dropping to 11% from 16% (p=0.030) when the best plan was followed. This study shows significant relationships between selection of patient specific kinematically optimal surgical plan and outcome. Such tools will play an important role in future patient specific decision making.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.29007/3mvp
- https://easychair.org/publications/open/RqMC
- OA Status
- bronze
- References
- 12
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3092627009
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3092627009Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.29007/3mvpDigital Object Identifier
- Title
-
Outcome Validation of a Simulation Based Patient Specific TKA Planning ToolWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-09-26Full publication date if available
- Authors
-
Joshua Twiggs, Justin Roe, Brett Fritsch, David Parker, Brad MilesList of authors in order
- Landing page
-
https://doi.org/10.29007/3mvpPublisher landing page
- PDF URL
-
https://easychair.org/publications/open/RqMCDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
-
https://easychair.org/publications/open/RqMCDirect OA link when available
- Concepts
-
Outcome (game theory), Plan (archaeology), Physical therapy, Medicine, Surgical planning, Set (abstract data type), Computer science, Surgery, Physical medicine and rehabilitation, Mathematics, Archaeology, Programming language, History, Mathematical economicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
12Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W3092627009 |
|---|---|
| doi | https://doi.org/10.29007/3mvp |
| ids.doi | https://doi.org/10.29007/3mvp |
| ids.mag | 3092627009 |
| ids.openalex | https://openalex.org/W3092627009 |
| fwci | 0.0 |
| type | article |
| title | Outcome Validation of a Simulation Based Patient Specific TKA Planning Tool |
| biblio.issue | |
| biblio.volume | 4 |
| biblio.last_page | 253 |
| biblio.first_page | 259 |
| topics[0].id | https://openalex.org/T10562 |
| topics[0].field.id | https://openalex.org/fields/27 |
| topics[0].field.display_name | Medicine |
| topics[0].score | 1.0 |
| topics[0].domain.id | https://openalex.org/domains/4 |
| topics[0].domain.display_name | Health Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2746 |
| topics[0].subfield.display_name | Surgery |
| topics[0].display_name | Total Knee Arthroplasty Outcomes |
| topics[1].id | https://openalex.org/T10512 |
| topics[1].field.id | https://openalex.org/fields/27 |
| topics[1].field.display_name | Medicine |
| topics[1].score | 0.9986000061035156 |
| topics[1].domain.id | https://openalex.org/domains/4 |
| topics[1].domain.display_name | Health Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2746 |
| topics[1].subfield.display_name | Surgery |
| topics[1].display_name | Orthopaedic implants and arthroplasty |
| topics[2].id | https://openalex.org/T10280 |
| topics[2].field.id | https://openalex.org/fields/27 |
| topics[2].field.display_name | Medicine |
| topics[2].score | 0.987500011920929 |
| topics[2].domain.id | https://openalex.org/domains/4 |
| topics[2].domain.display_name | Health Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2746 |
| topics[2].subfield.display_name | Surgery |
| topics[2].display_name | Shoulder Injury and Treatment |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C148220186 |
| concepts[0].level | 2 |
| concepts[0].score | 0.7769303321838379 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q7111912 |
| concepts[0].display_name | Outcome (game theory) |
| concepts[1].id | https://openalex.org/C2776505523 |
| concepts[1].level | 2 |
| concepts[1].score | 0.5521482825279236 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q4785468 |
| concepts[1].display_name | Plan (archaeology) |
| concepts[2].id | https://openalex.org/C1862650 |
| concepts[2].level | 1 |
| concepts[2].score | 0.48152026534080505 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q186005 |
| concepts[2].display_name | Physical therapy |
| concepts[3].id | https://openalex.org/C71924100 |
| concepts[3].level | 0 |
| concepts[3].score | 0.474211722612381 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q11190 |
| concepts[3].display_name | Medicine |
| concepts[4].id | https://openalex.org/C2779370443 |
| concepts[4].level | 2 |
| concepts[4].score | 0.4318659007549286 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q1776627 |
| concepts[4].display_name | Surgical planning |
| concepts[5].id | https://openalex.org/C177264268 |
| concepts[5].level | 2 |
| concepts[5].score | 0.4135042130947113 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q1514741 |
| concepts[5].display_name | Set (abstract data type) |
| concepts[6].id | https://openalex.org/C41008148 |
| concepts[6].level | 0 |
| concepts[6].score | 0.3515106439590454 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[6].display_name | Computer science |
| concepts[7].id | https://openalex.org/C141071460 |
| concepts[7].level | 1 |
| concepts[7].score | 0.35062676668167114 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q40821 |
| concepts[7].display_name | Surgery |
| concepts[8].id | https://openalex.org/C99508421 |
| concepts[8].level | 1 |
| concepts[8].score | 0.32452091574668884 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q2678675 |
| concepts[8].display_name | Physical medicine and rehabilitation |
| concepts[9].id | https://openalex.org/C33923547 |
| concepts[9].level | 0 |
| concepts[9].score | 0.1643815040588379 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[9].display_name | Mathematics |
| concepts[10].id | https://openalex.org/C166957645 |
| concepts[10].level | 1 |
| concepts[10].score | 0.0 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q23498 |
| concepts[10].display_name | Archaeology |
| concepts[11].id | https://openalex.org/C199360897 |
| concepts[11].level | 1 |
| concepts[11].score | 0.0 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q9143 |
| concepts[11].display_name | Programming language |
| concepts[12].id | https://openalex.org/C95457728 |
| concepts[12].level | 0 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q309 |
| concepts[12].display_name | History |
| concepts[13].id | https://openalex.org/C144237770 |
| concepts[13].level | 1 |
| concepts[13].score | 0.0 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q747534 |
| concepts[13].display_name | Mathematical economics |
| keywords[0].id | https://openalex.org/keywords/outcome |
| keywords[0].score | 0.7769303321838379 |
| keywords[0].display_name | Outcome (game theory) |
| keywords[1].id | https://openalex.org/keywords/plan |
| keywords[1].score | 0.5521482825279236 |
| keywords[1].display_name | Plan (archaeology) |
| keywords[2].id | https://openalex.org/keywords/physical-therapy |
| keywords[2].score | 0.48152026534080505 |
| keywords[2].display_name | Physical therapy |
| keywords[3].id | https://openalex.org/keywords/medicine |
| keywords[3].score | 0.474211722612381 |
| keywords[3].display_name | Medicine |
| keywords[4].id | https://openalex.org/keywords/surgical-planning |
| keywords[4].score | 0.4318659007549286 |
| keywords[4].display_name | Surgical planning |
| keywords[5].id | https://openalex.org/keywords/set |
| keywords[5].score | 0.4135042130947113 |
| keywords[5].display_name | Set (abstract data type) |
| keywords[6].id | https://openalex.org/keywords/computer-science |
| keywords[6].score | 0.3515106439590454 |
| keywords[6].display_name | Computer science |
| keywords[7].id | https://openalex.org/keywords/surgery |
| keywords[7].score | 0.35062676668167114 |
| keywords[7].display_name | Surgery |
| keywords[8].id | https://openalex.org/keywords/physical-medicine-and-rehabilitation |
| keywords[8].score | 0.32452091574668884 |
| keywords[8].display_name | Physical medicine and rehabilitation |
| keywords[9].id | https://openalex.org/keywords/mathematics |
| keywords[9].score | 0.1643815040588379 |
| keywords[9].display_name | Mathematics |
| language | en |
| locations[0].id | doi:10.29007/3mvp |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4386872386 |
| locations[0].source.issn | 2398-5305 |
| locations[0].source.type | conference |
| locations[0].source.is_oa | False |
| locations[0].source.issn_l | 2398-5305 |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | EPiC series in health sciences |
| locations[0].source.host_organization | |
| locations[0].source.host_organization_name | |
| locations[0].license | |
| locations[0].pdf_url | https://easychair.org/publications/open/RqMC |
| locations[0].version | publishedVersion |
| locations[0].raw_type | proceedings-article |
| locations[0].license_id | |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | EPiC Series in Health Sciences |
| locations[0].landing_page_url | https://doi.org/10.29007/3mvp |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5074213660 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-0063-0435 |
| authorships[0].author.display_name | Joshua Twiggs |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Joshua Twiggs |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5054247370 |
| authorships[1].author.orcid | https://orcid.org/0009-0000-8909-2682 |
| authorships[1].author.display_name | Justin Roe |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Justin Roe |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5045615142 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-2268-2298 |
| authorships[2].author.display_name | Brett Fritsch |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Brett Fritsch |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5007829352 |
| authorships[3].author.orcid | https://orcid.org/0000-0001-6930-8490 |
| authorships[3].author.display_name | David Parker |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | David Parker |
| authorships[3].is_corresponding | False |
| authorships[4].author.id | https://openalex.org/A5071532975 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-3016-8168 |
| authorships[4].author.display_name | Brad Miles |
| authorships[4].author_position | last |
| authorships[4].raw_author_name | Brad Miles |
| authorships[4].is_corresponding | False |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://easychair.org/publications/open/RqMC |
| open_access.oa_status | bronze |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Outcome Validation of a Simulation Based Patient Specific TKA Planning Tool |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10562 |
| primary_topic.field.id | https://openalex.org/fields/27 |
| primary_topic.field.display_name | Medicine |
| primary_topic.score | 1.0 |
| primary_topic.domain.id | https://openalex.org/domains/4 |
| primary_topic.domain.display_name | Health Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2746 |
| primary_topic.subfield.display_name | Surgery |
| primary_topic.display_name | Total Knee Arthroplasty Outcomes |
| related_works | https://openalex.org/W2978999882, https://openalex.org/W2153369162, https://openalex.org/W2181392282, https://openalex.org/W2119369480, https://openalex.org/W3141031773, https://openalex.org/W1595686156, https://openalex.org/W148937441, https://openalex.org/W1027719266, https://openalex.org/W2039552377, https://openalex.org/W2150763126 |
| cited_by_count | 0 |
| locations_count | 1 |
| best_oa_location.id | doi:10.29007/3mvp |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4386872386 |
| best_oa_location.source.issn | 2398-5305 |
| best_oa_location.source.type | conference |
| best_oa_location.source.is_oa | False |
| best_oa_location.source.issn_l | 2398-5305 |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | EPiC series in health sciences |
| best_oa_location.source.host_organization | |
| best_oa_location.source.host_organization_name | |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://easychair.org/publications/open/RqMC |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | proceedings-article |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | EPiC Series in Health Sciences |
| best_oa_location.landing_page_url | https://doi.org/10.29007/3mvp |
| primary_location.id | doi:10.29007/3mvp |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4386872386 |
| primary_location.source.issn | 2398-5305 |
| primary_location.source.type | conference |
| primary_location.source.is_oa | False |
| primary_location.source.issn_l | 2398-5305 |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | EPiC series in health sciences |
| primary_location.source.host_organization | |
| primary_location.source.host_organization_name | |
| primary_location.license | |
| primary_location.pdf_url | https://easychair.org/publications/open/RqMC |
| primary_location.version | publishedVersion |
| primary_location.raw_type | proceedings-article |
| primary_location.license_id | |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | EPiC Series in Health Sciences |
| primary_location.landing_page_url | https://doi.org/10.29007/3mvp |
| publication_date | 2020-09-26 |
| publication_year | 2020 |
| referenced_works | https://openalex.org/W2109571834, https://openalex.org/W2802731756, https://openalex.org/W2617607625, https://openalex.org/W2085655293, https://openalex.org/W2560932184, https://openalex.org/W2164971193, https://openalex.org/W1976556192, https://openalex.org/W2950175465, https://openalex.org/W2090324495, https://openalex.org/W2076241594, https://openalex.org/W2020685161, https://openalex.org/W1171259770 |
| referenced_works_count | 12 |
| abstract_inverted_index.9 | 63 |
| abstract_inverted_index.A | 51, 74, 187 |
| abstract_inverted_index.a | 5, 67, 102, 117, 202 |
| abstract_inverted_index.12 | 171 |
| abstract_inverted_index.70 | 207 |
| abstract_inverted_index.CT | 71 |
| abstract_inverted_index.In | 100 |
| abstract_inverted_index.an | 240 |
| abstract_inverted_index.be | 22 |
| abstract_inverted_index.by | 62 |
| abstract_inverted_index.in | 10, 48, 130, 158, 243 |
| abstract_inverted_index.of | 15, 31, 45, 53, 104, 153, 160, 199, 206, 227 |
| abstract_inverted_index.on | 18, 61, 144 |
| abstract_inverted_index.or | 164 |
| abstract_inverted_index.to | 21, 25, 37, 82, 89, 127, 135, 209 |
| abstract_inverted_index.we | 42 |
| abstract_inverted_index.11% | 210 |
| abstract_inverted_index.16% | 212 |
| abstract_inverted_index.DKS | 162 |
| abstract_inverted_index.MSC | 96 |
| abstract_inverted_index.Rig | 86 |
| abstract_inverted_index.TKA | 54 |
| abstract_inverted_index.The | 112 |
| abstract_inverted_index.all | 136 |
| abstract_inverted_index.and | 69, 234 |
| abstract_inverted_index.are | 4 |
| abstract_inverted_index.had | 183 |
| abstract_inverted_index.its | 46 |
| abstract_inverted_index.our | 32 |
| abstract_inverted_index.set | 103 |
| abstract_inverted_index.the | 13, 28, 83, 146, 151, 154, 178, 192, 197, 215 |
| abstract_inverted_index.use | 47 |
| abstract_inverted_index.was | 87, 133, 150, 181, 189, 218 |
| abstract_inverted_index.who | 65 |
| abstract_inverted_index.CA). | 99 |
| abstract_inverted_index.KOOS | 123, 174, 193, 203 |
| abstract_inverted_index.Knee | 85, 114 |
| abstract_inverted_index.Pain | 194, 204 |
| abstract_inverted_index.Such | 236 |
| abstract_inverted_index.TKA, | 11 |
| abstract_inverted_index.This | 220 |
| abstract_inverted_index.been | 35 |
| abstract_inverted_index.best | 179, 216 |
| abstract_inverted_index.from | 58, 122, 211 |
| abstract_inverted_index.have | 34 |
| abstract_inverted_index.here | 41 |
| abstract_inverted_index.into | 141 |
| abstract_inverted_index.knee | 1, 92 |
| abstract_inverted_index.not. | 165 |
| abstract_inverted_index.plan | 16, 180, 217, 233 |
| abstract_inverted_index.play | 239 |
| abstract_inverted_index.role | 242 |
| abstract_inverted_index.show | 43 |
| abstract_inverted_index.used | 88 |
| abstract_inverted_index.were | 72, 107, 139, 168 |
| abstract_inverted_index.when | 214 |
| abstract_inverted_index.will | 238 |
| abstract_inverted_index.with | 39, 78, 170, 191, 196 |
| abstract_inverted_index.Adams | 95 |
| abstract_inverted_index.Cases | 176 |
| abstract_inverted_index.Score | 115 |
| abstract_inverted_index.These | 166 |
| abstract_inverted_index.below | 201 |
| abstract_inverted_index.cases | 126 |
| abstract_inverted_index.joint | 19 |
| abstract_inverted_index.model | 77 |
| abstract_inverted_index.month | 172 |
| abstract_inverted_index.prior | 24 |
| abstract_inverted_index.score | 163, 205 |
| abstract_inverted_index.shown | 36, 190 |
| abstract_inverted_index.shows | 222 |
| abstract_inverted_index.split | 140 |
| abstract_inverted_index.study | 221 |
| abstract_inverted_index.terms | 159 |
| abstract_inverted_index.tools | 237 |
| abstract_inverted_index.using | 94 |
| abstract_inverted_index.where | 177 |
| abstract_inverted_index.(DKS), | 116 |
| abstract_inverted_index.Oxford | 84 |
| abstract_inverted_index.better | 184 |
| abstract_inverted_index.future | 244 |
| abstract_inverted_index.groups | 142 |
| abstract_inverted_index.impact | 14 |
| abstract_inverted_index.option | 9 |
| abstract_inverted_index.scored | 124 |
| abstract_inverted_index.Dynamic | 0, 113 |
| abstract_inverted_index.applied | 134 |
| abstract_inverted_index.between | 225 |
| abstract_inverted_index.dynamic | 29 |
| abstract_inverted_index.learned | 121 |
| abstract_inverted_index.machine | 120 |
| abstract_inverted_index.making. | 248 |
| abstract_inverted_index.optimal | 231 |
| abstract_inverted_index.options | 157 |
| abstract_inverted_index.outcome | 129, 185 |
| abstract_inverted_index.patient | 228, 245 |
| abstract_inverted_index.portion | 198 |
| abstract_inverted_index.predict | 128 |
| abstract_inverted_index.results | 30, 167 |
| abstract_inverted_index.scores. | 175 |
| abstract_inverted_index.similar | 79 |
| abstract_inverted_index.surgery | 57 |
| abstract_inverted_index.whether | 145 |
| abstract_inverted_index.Patients | 55, 138 |
| abstract_inverted_index.achieved | 148 |
| abstract_inverted_index.allowing | 12 |
| abstract_inverted_index.analysed | 23 |
| abstract_inverted_index.boundary | 80 |
| abstract_inverted_index.compared | 169 |
| abstract_inverted_index.computer | 2 |
| abstract_inverted_index.covering | 109 |
| abstract_inverted_index.database | 52 |
| abstract_inverted_index.decision | 247 |
| abstract_inverted_index.dropping | 208 |
| abstract_inverted_index.dynamics | 20, 93 |
| abstract_inverted_index.followed | 182 |
| abstract_inverted_index.modelled | 156 |
| abstract_inverted_index.operated | 60 |
| abstract_inverted_index.outcome. | 235 |
| abstract_inverted_index.outcome; | 40 |
| abstract_inverted_index.patients | 200 |
| abstract_inverted_index.planning | 8, 132 |
| abstract_inverted_index.post-TKA | 91 |
| abstract_inverted_index.received | 66 |
| abstract_inverted_index.results. | 186 |
| abstract_inverted_index.simulate | 90 |
| abstract_inverted_index.software | 97 |
| abstract_inverted_index.specific | 229, 246 |
| abstract_inverted_index.surgery. | 26 |
| abstract_inverted_index.surgical | 7, 232 |
| abstract_inverted_index.(Newport, | 98 |
| abstract_inverted_index.(p=0.030) | 213 |
| abstract_inverted_index.addition, | 101 |
| abstract_inverted_index.algorithm | 119 |
| abstract_inverted_index.assessed. | 73 |
| abstract_inverted_index.correlate | 38 |
| abstract_inverted_index.depending | 143 |
| abstract_inverted_index.followed. | 219 |
| abstract_inverted_index.generated | 108 |
| abstract_inverted_index.important | 241 |
| abstract_inverted_index.planning. | 50 |
| abstract_inverted_index.promising | 6 |
| abstract_inverted_index.selection | 226 |
| abstract_inverted_index.simulated | 161 |
| abstract_inverted_index.subscore, | 195 |
| abstract_inverted_index.surgeons, | 64 |
| abstract_inverted_index.1-Jan-2014 | 59 |
| abstract_inverted_index.conditions | 81 |
| abstract_inverted_index.positional | 110 |
| abstract_inverted_index.predictive | 118 |
| abstract_inverted_index.simulation | 33 |
| abstract_inverted_index.undergoing | 56 |
| abstract_inverted_index.validation | 44 |
| abstract_inverted_index.‘best’ | 152 |
| abstract_inverted_index.Previously, | 27 |
| abstract_inverted_index.alterations | 17 |
| abstract_inverted_index.position’ | 149 |
| abstract_inverted_index.significant | 223 |
| abstract_inverted_index.simulations | 3, 106 |
| abstract_inverted_index.variations. | 111 |
| abstract_inverted_index.preoperative | 131, 155 |
| abstract_inverted_index.relationship | 188 |
| abstract_inverted_index.simulations. | 137 |
| abstract_inverted_index.computational | 76 |
| abstract_inverted_index.kinematically | 230 |
| abstract_inverted_index.postoperative | 125, 173 |
| abstract_inverted_index.pre-operative | 49, 68, 105 |
| abstract_inverted_index.relationships | 224 |
| abstract_inverted_index.post-operative | 70 |
| abstract_inverted_index.musculoskeletal | 75 |
| abstract_inverted_index.‘post-operative | 147 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/16 |
| sustainable_development_goals[0].score | 0.5799999833106995 |
| sustainable_development_goals[0].display_name | Peace, Justice and strong institutions |
| citation_normalized_percentile.value | 0.40084388 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |