Experience of Pain and Satisfaction with Pain Management in Patients After a Lumbar Disc Herniation Surgery

Outcomes of Pain Management Among Postoperative Patients: A Cross-sectional Study

PURPOSE

Postoperative pain management has always been a significant challenge for both hospital staff and surgical patients. Determination of pain management outcomes among surgically treated patients may help develop pain management strategies, improve health services that would yield better outcomes, and increase patient satisfaction. This study aimed to assess the outcomes of pain management among postoperative patients.

DESIGN

The study was a descriptive cross-sectional study.

METHODS

The research was performed on postoperative patients at two university hospitals in North Cyprus from July to September 2019. The study sample consisted of 90 patients from both hospitals. The Turkish Version of the revised American Pain Society Patient Outcome Questionnaire (APS-POQ-R-TR) was used for data collection. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist was used to report the present study.

FINDINGS

This study showed that the overall mean for pain severity and the worst pain experienced by patients after 24 hours was slightly higher than medium. Examination of interference of the pain with functions demonstrated that patients experienced problems with physical activities and sleeping. The most experienced side effects were nausea and drowsiness, and the most common emotions were anxiety and helplessness during the postsurgery period. The satisfaction rate of the patients with postoperative pain management was relatively high.

CONCLUSIONS

A holistic approach with evidence-based practices is crucial for adequate postoperative pain management. The recommendations include the development of individual pain outcome strategies to improve overall satisfaction with pain management among postoperative patients.

The challenges of nursing care for patients with lumbar discectomy: A qualitative study

AIM

Patients with lumbar disc surgery experience many different problems during their hospital stay. Nurses also face different challenges in providing care to them. Nonetheless, no study has yet specifically addressed these challenges to the best of our knowledge. This study aimed at exploring the challenges of nursing care for patients with lumbar discectomy.

DESIGN

This qualitative study was conducted in 2022 using content analysis.

METHODS

Eight nurses, three patients with lumbar discectomy, and one physician were purposively selected from the neurosurgery wards of the hospitals affiliated to Golestan University of Medical Sciences, Gorgan, Iran. Semi-structured interviews were conducted for data analysis and the content analysis method recommended by Elo and Kyngas was used for data analysis. The main phases of this method are open coding, grouping, categorization, and abstraction. The MAXQDA 10 software was employed to facilitate data management. Data collection continued to reach data saturation.

RESULTS

The challenges of nursing care for patients with lumbar discectomy were categorized into eleven subcategories and three main categories, namely dominant routine-based practice in the healthcare system, futile attempt for team-based care, and shortages as a major barrier to quality care. There are different personal, professional, financial, structural, and organizational challenges in nursing care for patients with lumbar discectomy which can negatively affect postoperative patient recovery.

Morphometric similarity networks discriminate patients with lumbar disc herniation from healthy controls and predict pain intensity

We used a recently advanced technique, morphometric similarity (MS), in a large sample of lumbar disc herniation patients with chronic pain (LDH-CP) to examine morphometric features derived from multimodal MRI data. To do so, we evenly allocated 136 LDH-CPs to exploratory and validation groups with matched healthy controls (HC), randomly chosen from the pool of 157 HCs. We developed three MS-based models to discriminate LDH-CPs from HCs and to predict the pain intensity of LDH-CPs. In addition, we created analogous models using resting state functional connectivity (FC) to perform the above discrimination and prediction of pain, in addition to comparing the performance of FC- and MS-based models and investigating if an ensemble model, combining morphometric features and resting-state signals, could improve performance. We conclude that 1) MS-based models were able to discriminate LDH-CPs from HCs and the MS networks (MSN) model performed best; 2) MSN was able to predict the pain intensity of LDH-CPs; 3) FC networks constructed were able to discriminate LDH-CPs from HCs, but they could not predict pain intensity; and 4) the ensemble model neither improved discrimination nor pain prediction performance. Generally, MSN is sensitive enough to uncover brain morphology alterations associated with chronic pain and provides novel insights regarding the neuropathology of chronic pain.

Brain Network Changes in Lumbar Disc Herniation Induced Chronic Nerve Roots Compression Syndromes

Lumbar disc herniation (LDH) induced nerve compression syndromes have been a prevalent problem with complex neural mechanisms. Changes in distributed brain areas are involved in the occurrence and persistence of syndromes. The present study aimed to investigate the changes of brain functional network in LDH patients with chronic sciatica using graph theory analysis. A total of thirty LDH adults presenting L4 and/or L5 root (s) compression syndromes (LDH group) and thirty age-, sex-, BMI- and education-matched healthy control (HC group) were recruited for functional MRI scan. Whole-brain functional network was constructed for each participant using Pearson's correlation. Global and nodal properties were calculated and compared between two groups, including small-worldness index, clustering coefficient, characteristic path length, degree centrality (DC), betweenness centrality (BC) and nodal efficiency. Both LDH and HC groups showed small-world architecture in the functional network of brain. However, LDH group showed that nodal centralities (DC, BC and nodal efficiency) increased in opercular part of inferior frontal gyrus; and decreased in orbital part of inferior frontal gyrus, lingual cortex and inferior occipital gyrus. The DC and efficiency in the right inferior occipital gyrus were negatively related with the Oswestry Disability Index in LDH group. In conclusion, the LDH-related chronic sciatica syndromes may induce regional brain alterations involving self-referential, emotional responses and pain regulation functions. But the whole-brain small-world architecture was not significantly disturbed. It may provide new insights into LDH patients with radicular symptoms from new perspectives.

Logistic Model and Gradient Boosting Machine Model for Physical Therapy of Lumbar Disc Herniation

Objective. Physical therapy is a common clinical treatment for patients with lumbar disc herniation. The study is aimed at exploring the feasibility of mathematical expression and curative effect prediction of physical therapy in patients with lumbar disc herniation using a logistic model and gradient boosting machine (GBM). Methods. A total of 142 patients with lumbar disc herniation were treated with physical therapy. The pain was evaluated by the visual analogue scale (VAS) before each treatment. The logistic model was used to conduct a global regression analysis on patients with lumbar disc herniation. The final results of the whole course of treatment were predicted by the measured values of 2-9 times of treatment. The GBM model was used to predict and analyze the curative effect of physical therapy. Results. The mathematical expression ability of the logistic regression model for patients with lumbar disc herniation undergoing physical therapy was sufficient, and the global determination coefficient was 0.721. The results would be better for more than five measurements. The AUC of GBM mode logistic regression analysis was 0.936 and 0.883, and the prediction effect is statistically significant. Conclusion. Both the logistic and GBM model can fully express the changes in patients with lumbar disc herniation during physical therapy.