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Byvaltsev V.A.

Irkutsk State Medical University, Irkutsk, Russia;
Russian Railways-Medicine Hospital, Irkutsk, Russia;
Irkutsk State Medical Academy of Postgraduate Education, Irkutsk, Russia

Kalinin A.A.

Irkutsk State Medical University, Irkutsk, Russia;
Russian Railways-Medicine Hospital, Irkutsk, Russia

Pestryakov Yu.Ya.

Irkutsk State Medical University, Irkutsk, Russia

Satardinova E.E.

Irkutsk State Medical Academy of Postgraduate Education, Irkutsk, Russia

Noskov S.I.

Irkutsk State University of Railway Engineering, Irkutsk, Russia

Prognostic modeling of long-term outcomes after minimally invasive lumbar fusion based on complex clinical, radiological and neuroimaging analysis in employees of JSC «Russian Railways»

Authors:

Byvaltsev V.A., Kalinin A.A., Pestryakov Yu.Ya., Satardinova E.E., Noskov S.I.

More about the authors

Journal: Burdenko's Journal of Neurosurgery. 2026;90(2): 44‑53

DOI: 10.17116/neiro20269002144

Read: 711 times

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Table of contents

PROGNOSTIC MODELING OF LONG-TERM OUTCOMES AFTER MINIMALLY INVASIVE LUMBAR FUSION BASED ON COMPLEX CLINICAL, RADIOLOGICAL AND NEUROIMAGING ANALYSIS IN EMPLOYEES OF JSC «RUSSIAN RAILWAYS»
PROGNOSTIC MODELING OF LONG-TERM OUTCOMES AFTER MINIMALLY INVASIVE LUMBAR FUSION BASED ON COMPLEX CLINICAL, RADIOLOGICAL AND NEUROIMAGING ANALYSIS IN EMPLOYEES OF JSC «RUSSIAN RAILWAYS»

To cite this article:

Byvaltsev VA, Kalinin AA, Pestryakov YuYa, Satardinova EE, Noskov SI. Prognostic modeling of long-term outcomes after minimally invasive lumbar fusion based on complex clinical, radiological and neuroimaging analysis in employees of JSC «Russian Railways». Burdenko's Journal of Neurosurgery. 2026;90(2):44‑53. (In Russ., In Engl.)
https://doi.org/10.17116/neiro20269002144

Подписка 2025 Журнал «Вопросы нейрохирургии» имени Н.Н. Бурденко (Burdenko's Journal of Neurosurgery)
МСФ на ЯМ
Использование инфографики авторами научных работ
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Abstract:

The incidence of unsatisfactory postoperative outcomes after treatment of degenerative lumbosacral spine diseases depends on surgical method. Their prediction is difficult due to heterogeneity of clinical and instrumental characteristics of patient groups. Development of predictive models of clinical outcomes may be useful for decision making and favorable postoperative outcomes.

OBJECTIVE

To develop and validate the effectiveness of multivariate predictive model for assessing the risks and benefits of minimally invasive lumbar fusion in railway workers with degenerative lumbar spine diseases.

MATERIAL AND METHODS

We retrospectively analyzed prospective database consisting of 457 patients. They underwent minimally invasive lumbar fusion between 2020 and 2023. Comprehensive clinical, radiological and neuroimaging assessments were performed before surgery and 24 months later. Regression analysis was used to create prognostic models of long-term clinical outcomes (y0 — ODI; y1 — SF-36 PCS (physical component score); y2 — SF-36 MCS (mental component score); y3 — Macnab scale).

RESULTS

All clinical parameters (ODI, VAS, SF-36) significantly improved after surgery compared to preoperative values (p<0.01). Within 90 days after surgery, redo surgery rate was 5.7%, and the number of readmissions throughout the entire follow-up period — 8.3%. About 87.3% of railway workers returned to previous work. Clinical deterioration was observed in 51 (11.2%) patients. Preoperative variables predict long-term clinical outcomes. Their role and dominance depend on prognostic model.

CONCLUSION

Predictive models may be valuable to improve long-term outcomes when planning minimally invasive lumbar spine fusion.

Keywords:

lumbar spine
degenerative diseases
railway workers
interbody fusion
minimally invasive interventions
long-term results
predictive modeling

Authors:

Byvaltsev V.A.

Irkutsk State Medical University, Irkutsk, Russia;
Russian Railways-Medicine Hospital, Irkutsk, Russia;
Irkutsk State Medical Academy of Postgraduate Education, Irkutsk, Russia

Kalinin A.A.

Irkutsk State Medical University, Irkutsk, Russia;
Russian Railways-Medicine Hospital, Irkutsk, Russia

Pestryakov Yu.Ya.

Irkutsk State Medical University, Irkutsk, Russia

Satardinova E.E.

Irkutsk State Medical Academy of Postgraduate Education, Irkutsk, Russia

Noskov S.I.

Irkutsk State University of Railway Engineering, Irkutsk, Russia

Received:

20.02.2025

Accepted:

26.11.2025

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References:

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