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Record W4254535891 · doi:10.21203/rs.3.rs-15464/v1

Effect of Bisphosphonates or Teriparatide on Mechanical Complications after Posterior Instrumented Fusion for Osteoporotic Vertebral Fracture: A Multi-center Retrospective Study

2020· preprint· en· W4254535891 on OpenAlexaff
Atsuyuki Kawabata, Toshitaka Yoshii, Takashi Hirai, Shuta Ushio, Takashi Kaito, Tomoya Yamashita, Hiroyasu Fujiwara, Yukitaka Nagamoto, Yuji Matsuoka, Hidekazu Suzuki, Hirosuke Nishimura, Hidetomi Terai, Koji Tamai, Atsushi Tagami, Syuta Yamada, Shinji Adachi, Kei Watanabe, Keiichi Katsumi, Masayuki Ohashi, Yohei Shibuya, Katsumi Harimaya, Kenichi Kawaguchi, Nobuhiko Yokoyama, Hidekazu Oishi, Toshiro Doi, Atsushi Kimura, Hirokazu Inoue, Gen Inoue, Masayuki Miyagi, Wataru Saito, Atsushi Nakano, Daisuke Sakai, Tadashi Nukaga, Shota Ikegami, Masayuki Shimizu, Toshimasa Futatsugi, Seiji Ohtori, Takeo Furuya, Sumihisa Orita, Shiro Imagama, Kei Ando, Kazuyoshi Kobayashi, Katsuhito Kiyasu, Hideki Murakami, Katsuhito Yoshioka, Shoji Seki, Michio Hongo, Kenichiro Kakutani, Takashi Yurube, Yasuchika Aoki, Masashi Oshima, Masahiko Takahata, Akira Iwata, Hirooki Endo, Tetsuya Abe, Toshinori Tsukanishi, Kazuyoshi Nakanishi, Kota Watanabe, Tomohiro Hikata, Satoshi Suzuki, Norihiro Isogai, Eijiro Okada, Haruki Funao, Seiji Ueda, Yuta Shiono, Kenya Nojiri, Naobumi Hosogane, Ken J. Ishii

Bibliographic record

VenueResearch Square · 2020
Typepreprint
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsNational Defence Medical Centre
Fundersnot available
KeywordsMedicineTeriparatideOsteoporosisRetrospective cohort studyComplicationSurgeryImplantPseudarthrosisLumbarSpinal fusionInternal medicineBone mineral

Abstract

fetched live from OpenAlex

Abstract Background: The optimal treatment of osteoporosis after reconstruction surgery for osteoporotic vertebral fractures (OVF) remains unclear. In this multicentre retrospective study, we investigated the effects of typically used agents for osteoporosis, namely, bisphosphonates (BP) and teriparatide (TP), on surgical results in patients with osteoporotic vertebral fractures. Methods: Retrospectively registered data were collected from 27 universities and affiliated hospitals in Japan. We compared the effects of BP vs TP on postoperative mechanical complication rates, implant-related reoperation rates, and clinical outcomes in patients who underwent posterior instrumented fusion for OVF and had been followed up at least for 2 years. Data were analysed according to whether the osteoporosis was primary or glucocorticoid-induced. Results: A total of 165 patients who underwent posterior instrumented fusion for OVF were included. The overall mechanical complication rate was significantly lower in the TP group than in the BP group (BP vs TP: 73.0% vs. 55.7%, p = 0.018). The screw backout rate was significantly lower and the rates of new vertebral fractures and pseudoarthrosis tended to be lower in the TP group than in the BP group. However, there were no significant differences in lumbar functional scores and visual analogue scale pain scores or in implant-related reoperation rates between the two groups. The incidence of pseudoarthrosis was significantly higher in patients with glucocorticoid-induced osteoporosis (GIOP) than in those with primary osteoporosis; however, the pseudoarthrosis rate was reduced by using TP. The use of TP also tended to reduce the overall mechanical complication rate in both primary osteoporosis and GIOP. Conclusions: The overall mechanical complication rate was lower in patients who received TP than in those who received a BP postoperatively, regardless of type of osteoporosis. The incidence of pseudoarthrosis was significantly higher in patients with GIOP, but the use of TP reduced the rate of pseudoarthrosis in GIOP patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.072
GPT teacher head0.449
Teacher spread0.377 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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