Evidence map›Paper›PMID 35265345›Full record

ArticleSovremennye tekhnologii v meditsine2021

Assessment of Clinical Decision Support System Efficiency in Spinal Neurosurgery for Personalized Minimally Invasive Technologies Used on Lumbar Spine.

V А Byvaltsev, А А Kalinin

Open access · diamondAbstract read
In one paragraph

Article in Sovremennye tekhnologii v meditsine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 45% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

V А ByvaltsevProfessor, Head of the Department of Neurosurgery and Innovative Medicine Irkutsk State Medical University, 1 Krasnogo Vosstaniya St., Irkutsk, 664003, Russia;; Chief of Neurosurgery Center Road Clinical Hospital, 10 Botkin St., Irkutsk, 664005, Russia;; Professor, Department of Traumatology, Orthopedics and Neurosurgery Irkutsk State Medical Academy for Postgraduate Education, 100 Yubileyny Microdistrict, Irkutsk, 664049, Russia.
А А KalininAssociate Professor, Department of Neurosurgery and Innovative Medicine Irkutsk State Medical University, 1 Krasnogo Vosstaniya St., Irkutsk, 664003, Russia;; Neurosurgeon, Neurosurgery Center Road Clinical Hospital, 10 Botkin St., Irkutsk, 664005, Russia.
Irkutsk State Medical University · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Materials and Methods: The prospective study involved 59 patients operated on using CDSS based on a personalized surgical algorithm considering patient-specific parameters of lumbar segments. Among them, 11 patients underwent total disk replacement (TDR), 25 and 23 patients had minimally invasive (MI-TLIF) and open (O-TLIF) dorsal rigid stabilization, respectively, according to an original technology. The comparative analysis was carried out using retrospective findings of 196 patients operated on involving TDR (n=42), MI-TLIF (n=79), and O-TLIF (n=75). The efficiency of CDSS medical algorithms was assessed by pain syndrome in the lumbar spine and lower limbs, as well as by patients' functional status on discharge according to ODI, 3 and 6 months after the operation. Results: The comparison by gender characteristics and anthropometric data revealed no significant intergroup differences among the groups under study (p>0.05). Intergroup analysis of functional status by ODI, pain intensity in lower limbs and lumbar spine showed better clinical outcomes in patients operated using CDSS compared to a retrospective group (p<0.05): 6 months after TDR and O-TLIF, and 3 months after MI-TLIF. Conclusion: The study findings demonstrated high efficiency of CDSS developed for personalized surgical treatment of patients with degenerative lumbar spine diseases taking into consideration individual biometric parameters of lumbar segments.

Indexed as

Decision Support Systems, ClinicalNeurosurgerySpinal FusionHumansLumbar VertebraeMinimally Invasive Surgical ProceduresProspective StudiesRetrospective StudiesTechnologyTreatment Outcomeartificial intelligenceclinical decision support systemsdegenerative lumbar diseasesmachine learningminimally invasive spinal neurosurgery

Identifiers

PMID35265345
PMCPMC8858415
OpenAlexW3211293718

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.