Peer review report 1 on “A case report of an unusual cause of postoperative leg pain after posterior lumbar fusion”

Study Design: Retrospective Cohort Study. Objectives: This study aimed to determine how the surgeon-determined and patient-rated location of predominant pain influences patient-rated outcomes at 1-year after posterior lumbar fusion in adult isthmic spondylolisthesis. Methods: We retrospectively reviewed consecutive patients prospectively enrolled in the Canadian Spine Outcomes and Research Network national registry between 2009 and 2017 that underwent posterior lumbar fusion for isthmic spondylolisthesis. Using longitudinal mixed-model repeated-measures analysis the change from baseline in patient-reported outcome measures (PROMs) at 1 year after surgery was compared between surgeon-determined groups (back vs. radicular) and between patient-rated pain groups (back, leg, and equal) derived from preoperative pain scores on the numerical rating scale (NRS). Results: 83/252 (33%) patients had a surgeon-determined chief complaint of back pain, while 103 (41%) patients rated their back pain as the predominant pain location, and 78 (31%) rated their back and leg pain to be equal. At baseline patients in the surgeon-determined radicular group had worse NRS-leg pain than those in the back-pain group but equal NRS-back pain. At baseline patients in the patient-rated equal pain group had similar back pain compared to the patient-rated back pain group and similar leg pain compared to the patient-rated leg pain group. All PROMs improved post-operatively and were not different between the 2 groups at 1 year. Conclusions: Our study found no difference in outcome, irrespective of whether a surgeon determines the patient’s primary pain complaint back or radicular dominant, or the patient rates pain in one location greater than another.

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Can Leg Pain Be the Sole Presenting Symptom of Infective Endocarditis? A Case Report

The Heart Surgery Forum ◽

10.1532/hsf98.20071100 ◽

2007 ◽

Vol 10 (6) ◽

pp. E434-E435

Author(s):

Cevdet Ugur Kocogullari ◽

Alaattin Avsar ◽

Ercüment Ayva ◽

Önder Sahin ◽

Ahmet Cekirdekci

Keyword(s):

Case Report ◽

Infective Endocarditis ◽

Leg Pain

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Effects of preoperative obesity and psychiatric comorbidities on minimum clinically important differences for lumbar fusion in grade 1 degenerative spondylolisthesis: analysis from the prospective Quality Outcomes Database registry

Journal of Neurosurgery Spine ◽

10.3171/2020.4.spine20296 ◽

2020 ◽

Vol 33 (5) ◽

pp. 635-642

Author(s):

Joseph Laratta ◽

Leah Y. Carreon ◽

Avery L. Buchholz ◽

Andrew Y. Yew ◽

Erica F. Bisson ◽

...

Keyword(s):

Spinal Fusion ◽

Preoperative Diagnosis ◽

Rating Scale ◽

Lumbar Fusion ◽

Degenerative Spondylolisthesis ◽

Leg Pain ◽

Quality Outcomes ◽

Medical Comorbidities ◽

Fusion Procedure ◽

Patient Reported

OBJECTIVEMedical comorbidities, particularly preoperatively diagnosed anxiety, depression, and obesity, may influence how patients perceive and measure clinical benefit after a surgical intervention. The current study was performed to define and compare the minimum clinically important difference (MCID) thresholds in patients with and without preoperative diagnoses of anxiety or depression and obesity who underwent spinal fusion for grade 1 degenerative spondylolisthesis.METHODSThe Quality Outcomes Database (QOD) was queried for patients who underwent lumbar fusion for grade 1 degenerative spondylolisthesis during the period from January 2014 to August 2017. Collected patient-reported outcomes (PROs) included the Oswestry Disability Index (ODI), health status (EQ-5D), and numeric rating scale (NRS) scores for back pain (NRS-BP) and leg pain (NRS-LP). Both anchor-based and distribution-based methods for MCID calculation were employed.RESULTSOf 462 patients included in the prospective registry who underwent a decompression and fusion procedure, 356 patients (77.1%) had complete baseline and 12-month PRO data and were included in the study. The MCID values for ODI scores did not significantly differ in patients with and those without a preoperative diagnosis of obesity (20.58 and 20.69, respectively). In addition, the MCID values for ODI scores did not differ in patients with and without a preoperative diagnosis of anxiety or depression (24.72 and 22.56, respectively). Similarly, the threshold MCID values for NRS-BP, NRS-LP, and EQ-5D scores were not statistically different between all groups. Based on both anchor-based and distribution-based methods for determination of MCID thresholds, there were no statistically significant differences between all cohorts.CONCLUSIONSMCID thresholds were similar for ODI, EQ-5D, NRS-BP, and NRS-LP in patients with and without preoperative diagnoses of anxiety or depression and obesity undergoing spinal fusion for grade 1 degenerative spondylolisthesis. Preoperative clinical and shared decision-making may be improved by understanding that preoperative medical comorbidities may not affect the way patients experience and assess important clinical changes postoperatively.

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Assessing the Performance of National Surgical Quality Improvement Program Surgical Risk Calculator in Elective Spine Surgery: Insights from Patients Undergoing Single-Level Posterior Lumbar Fusion

World Neurosurgery ◽

10.1016/j.wneu.2019.02.049 ◽

2019 ◽

Vol 126 ◽

pp. e323-e329 ◽

Cited By ~ 4

Author(s):

Arjun Sebastian ◽

Anshit Goyal ◽

Mohammed Ali Alvi ◽

Waseem Wahood ◽

Mohamed Elminawy ◽

...

Keyword(s):

Quality Improvement ◽

Spine Surgery ◽

Lumbar Fusion ◽

Quality Improvement Program ◽

Risk Calculator ◽

Improvement Program ◽

Surgical Quality ◽

Surgical Risk ◽

Posterior Lumbar Fusion ◽

Single Level

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Rheumatoid Arthritis Increases Risk of Medical Complications Following Posterior Lumbar Fusion

World Neurosurgery ◽

10.1016/j.wneu.2021.01.110 ◽

2021 ◽

Author(s):

Joshua Bell ◽

Sean Sequeira ◽

Pramod Kamalapathy ◽

Varun Puvanesarajah ◽

Hamid Hassanzadeh

Keyword(s):

Rheumatoid Arthritis ◽

Lumbar Fusion ◽

Medical Complications ◽

Posterior Lumbar Fusion

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A case report of multisite arterial thrombosis in a patient with coronavirus disease 2019 (COVID-19)

European Heart Journal - Case Reports ◽

10.1093/ehjcr/ytaa339 ◽

2020 ◽

Author(s):

Marco Angelillis ◽

Marco De Carlo ◽

Andrea Christou ◽

Michele Marconi ◽

Davide M Mocellin ◽

...

Keyword(s):

Myocardial Infarction ◽

Case Report ◽

Arterial Thrombosis ◽

Leg Pain ◽

Nasopharyngeal Swab ◽

Limb Ischaemia ◽

Total Occlusion ◽

Left Common Iliac Artery ◽

Acute Limb Ischaemia ◽

The Right

Abstract Background A systemic coagulation dysfunction has been associated with COVID-19. In this case report, we describe a COVID-19-positive patient with multisite arterial thrombosis, presenting with acute limb ischaemia and concomitant ST-elevation myocardial infarction and oligo-symptomatic lung disease. Case summary An 83-year-old lady with history of hypertension and chronic kidney disease presented to the Emergency Department with acute-onset left leg pain, pulselessness, and partial loss of motor function. Acute limb ischaemia was diagnosed. At the same time, a routine ECG showed ST-segment elevation, diagnostic for inferior myocardial infarction. On admission, a nasopharyngeal swab was performed to assess the presence of SARS-CoV-2, as per hospital protocol during the current COVID-19 pandemic. A total-body CT angiography was performed to investigate the cause of acute limb ischaemia and to rule out aortic dissection; the examination showed a total occlusion of the left common iliac artery and a non-obstructive thrombosis of a subsegmental pulmonary artery branch in the right basal lobe. Lung CT scan confirmed a typical pattern of interstitial COVID-19 pneumonia. Coronary angiography showed a thrombotic occlusion of the proximal segment of the right coronary artery. Percutaneous coronary intervention was performed, with manual thrombectomy, followed by deployment of two stents. The patient was subsequently transferred to the operating room, where a Fogarty thrombectomy was performed. The patient was then admitted to the COVID area of our hospital. Seven hours later, the swab returned positive for COVID-19. Discussion COVID-19 can have an atypical presentation with thrombosis at multiple sites.

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Using Predictive Modeling and Supervised Machine Learning to Identify Patients at Risk for Venous Thromboembolism Following Posterior Lumbar Fusion

Global Spine Journal ◽

10.1177/21925682211019361 ◽

2021 ◽

pp. 219256822110193

Author(s):

Kevin Y. Wang ◽

Ijezie Ikwuezunma ◽

Varun Puvanesarajah ◽

Jacob Babu ◽

Adam Margalit ◽

...

Keyword(s):

Machine Learning ◽

At Risk ◽

Venous Thromboembolism ◽

Risk Stratification ◽

Predictive Model ◽

Predictive Modeling ◽

Lumbar Fusion ◽

Posterior Lumbar Fusion ◽

Single Level ◽

Patients At Risk

Study Design: Retrospective review. Objective: To use predictive modeling and machine learning to identify patients at risk for venous thromboembolism (VTE) following posterior lumbar fusion (PLF) for degenerative spinal pathology. Methods: Patients undergoing single-level PLF in the inpatient setting were identified in the National Surgical Quality Improvement Program database. Our outcome measure of VTE included all patients who experienced a pulmonary embolism and/or deep venous thrombosis within 30-days of surgery. Two different methodologies were used to identify VTE risk: 1) a novel predictive model derived from multivariable logistic regression of significant risk factors, and 2) a tree-based extreme gradient boosting (XGBoost) algorithm using preoperative variables. The methods were compared against legacy risk-stratification measures: ASA and Charlson Comorbidity Index (CCI) using area-under-the-curve (AUC) statistic. Results: 13, 500 patients who underwent single-level PLF met the study criteria. Of these, 0.95% had a VTE within 30-days of surgery. The 5 clinical variables found to be significant in the multivariable predictive model were: age > 65, obesity grade II or above, coronary artery disease, functional status, and prolonged operative time. The predictive model exhibited an AUC of 0.716, which was significantly higher than the AUCs of ASA and CCI (all, P < 0.001), and comparable to that of the XGBoost algorithm ( P > 0.05). Conclusion: Predictive analytics and machine learning can be leveraged to aid in identification of patients at risk of VTE following PLF. Surgeons and perioperative teams may find these tools useful to augment clinical decision making risk stratification tool.

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