Evidence map›Paper›PMID 33393052›Full record

ArticleAnnals of surgical oncology2021

Readmission-Free Survival Analysis in Metastatic Spine Tumour Surgical Patients: A Novel Concept.

Naresh Kumar, Andrew Cherian Thomas, Miguel Rafael David Ramos, Joel Yong Hao Tan, Liang Shen, Sirisha Madhu, Keith Gerard Lopez, Andre Villanueva, Jiong Hao Tan, Balamurugan A Vellayappan

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Article in Annals of surgical oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.7field-weighted citation impact, top 10% 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

9 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Implant and construct decision-making in metastatic spine tumour surgery: a review of current concepts with a decision-making algorithm.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2024
    Review
  7. Article
  8. Predicting 30-day mortality after surgery for metastatic disease of the spine: the HEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2023
    Article
  9. Review
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

10 authors at 2 institutions in 1 country.

Naresh KumarDepartment of Orthopaedic Surgery, National University Health System, Singapore, Singapore. dosksn@nus.edu.sg.
Andrew Cherian ThomasDepartment of Orthopaedic Surgery, National University Health System, Singapore, Singapore.
Miguel Rafael David RamosDepartment of Orthopaedic Surgery, National University Health System, Singapore, Singapore.
Joel Yong Hao TanDepartment of Orthopaedic Surgery, National University Health System, Singapore, Singapore.
Liang ShenBiostatistics Unit, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Sirisha MadhuDepartment of Orthopaedic Surgery, National University Health System, Singapore, Singapore.
Keith Gerard LopezDepartment of Orthopaedic Surgery, National University Health System, Singapore, Singapore.
Andre VillanuevaDepartment of Orthopaedic Surgery, National University Health System, Singapore, Singapore.
Jiong Hao TanDepartment of Orthopaedic Surgery, National University Health System, Singapore, Singapore.
Balamurugan A VellayappanDepartment of Radiation Oncology, National University Health System, Singapore, Singapore.
National University Health System · SGNational University of Singapore · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOutcomes commonly used to ascertain success of metastatic spine tumour surgery (MSTS) are 30-day complications/mortality and overall/disease-free survival. We believe a new, effective outcome indicator after MSTS would be the absence of unplanned hospital readmission (UHR) after index discharge. We introduce the concept of readmission-free survival (ReAFS), defined as 'the time duration between hospital discharge after index operation and first UHR or death'. The aim of this study is to identify factors influencing ReAFS in MSTS patients. PATIENTS AND

methodsWe retrospectively analysed 266 consecutive patients who underwent MSTS between 2005 and 2016. Demographics, oncological characteristics, procedural, preoperative and postoperative details were collected. ReAFS of patients within 2 years or until death was reviewed. Perioperative factors predictive of reduced ReAFS were evaluated using multivariate regression analysis.

resultsOf 266 patients, 230 met criteria for analysis. A total of 201 had UHR, whilst 1 in 8 (29/230) had no UHR. Multivariate analysis revealed that haemoglobin ≥ 12 g/dL, ECOG score of ≤ 2, primary prostate, breast and haematological cancers, comorbidities ≤ 3, absence of preoperative radiotherapy and shorter postoperative length of stay significantly prolonged the time to first UHR.

conclusionsReadmission-free survival is a novel concept in MSTS, which relies on patients' general condition, appropriateness of interventional procedures and underlying disease burden. Additionally, it may indicate the successful combination of a multi-disciplinary treatment approach. This information will allow oncologists and surgeons to identify patients who may benefit from increased surveillance following discharge to increase ReAFS. We envisage that ReAFS is a concept that can be extended to other surgical oncological fields.

Indexed as

NeoplasmsPostoperative ComplicationsHumansLength of StayMalePatient ReadmissionRetrospective StudiesRisk FactorsSpineSurvival Analysis

Identifiers

PMID33393052
OpenAlexW3119441894

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Registered trials

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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.