Prediction models in degenerative spine surgery: a systematic review

D Lubelski, A Hersh, TD Azad… - Global spine …, 2021 - journals.sagepub.com
Study Design: Systematic review. Objectives: To review the existing literature of prediction
models in degenerative spinal surgery. Methods: Review of PubMed/Medline and Embase …

Development of supervised machine learning algorithms for prediction of satisfaction at 2 years following total shoulder arthroplasty

EM Polce, KN Kunze, MC Fu, GE Garrigues… - Journal of shoulder and …, 2021 - Elsevier
Background Patient satisfaction after primary anatomic and reverse total shoulder
arthroplasty (TSA) represents an important metric for gauging patients' perception of their …

Limitations in evaluating machine learning models for imbalanced binary outcome classification in spine surgery: a systematic review

M Ghanem, AK Ghaith, VG El-Hajj, A Bhandarkar… - Brain Sciences, 2023 - mdpi.com
Clinical prediction models for spine surgery applications are on the rise, with an increasing
reliance on machine learning (ML) and deep learning (DL). Many of the predicted outcomes …

Assessment of probable opioid use disorder using electronic health record documentation

SA Palumbo, KM Adamson, S Krishnamurthy… - JAMA network …, 2020 - jamanetwork.com
Importance Electronic health records are a potentially valuable source of information for
identifying patients with opioid use disorder (OUD). Objective To evaluate whether proxy …

A machine learning algorithm for predicting prolonged postoperative opioid prescription after lumbar disc herniation surgery. An external validation study using 1,316 …

HK Yen, PT Ogink, CC Huang, OQ Groot, CC Su… - The Spine Journal, 2022 - Elsevier
ABSTRACT BACKGROUND CONTEXT Preoperative prediction of prolonged postoperative
opioid prescription helps identify patients for increased surveillance after surgery. The …

Machine learning algorithms predict clinically significant improvements in satisfaction after hip arthroscopy

KN Kunze, EM Polce, J Rasio, SJ Nho - Arthroscopy: The Journal of …, 2021 - Elsevier
Purpose To develop machine learning algorithms to predict failure to achieve clinically
significant satisfaction after hip arthroscopy. Methods We queried a clinical repository for …

Development of prediction models for clinically meaningful improvement in PROMIS scores after lumbar decompression

AV Karhade, HA Fogel, TD Cha, SH Hershman… - The Spine Journal, 2021 - Elsevier
ABSTRACT BACKGROUND The ability to preoperatively predict which patients will achieve
a minimal clinically important difference (MCID) after lumbar spine decompression surgery …

[HTML][HTML] An ensemble learning approach to improving prediction of case duration for spine surgery: algorithm development and validation

RA Gabriel, B Harjai, S Simpson, AL Du… - JMIR Perioperative …, 2023 - periop.jmir.org
Background Estimating surgical case duration accurately is an important operating room
efficiency metric. Current predictive techniques in spine surgery include less sophisticated …

Prediction of prolonged opioid use after surgery in adolescents: insights from machine learning

A Ward, T Jani, E De Souza, D Scheinker… - Anesthesia & …, 2021 - journals.lww.com
BACKGROUND: Long-term opioid use has negative health care consequences. Patients
who undergo surgery are at risk for prolonged opioid use after surgery (POUS). While risk …

Classifying High-Risk Patients for Persistent Opioid Use After Major Spine Surgery: A Machine-Learning Approach

S Simpson, W Zhong, S Mehdipour… - Anesthesia & …, 2024 - journals.lww.com
BACKGROUND: Persistent opioid use is a common occurrence after surgery and prolonged
exposure to opioids may result in escalation and dependence. The objective of this study …