Persistent Pain After Wrist or Hand Fracture: Development and Validation of a Prognostic Model

Peak alpha frequency is related to the degree of widespread pain, but not pain intensity or duration, among people with urologic chronic pelvic pain syndrome

Introduction

Effective prevention and management strategies for chronic pain remain elusive. This has prompted investigations into biomarkers to better understand the mechanisms underlying pain development and persistence. One promising marker is low peak alpha frequency (PAF), an electroencephalography (EEG) measure that has been associated with increased sensitivity during acute experimental pain. However, findings regarding the relationship between PAF and chronic pain are variable, potentially due to disparate levels of central sensitization among chronic pain populations. This is evidenced by the variable extent of widespread pain, a phenotypic marker for central sensitization, observed across individuals with chronic pain.

Objective

To explore the impact of widespread pain on PAF among people with chronic pain.

Method

Thirty-eight individuals with urologic chronic pelvic pain syndrome were categorized as having widespread (n = 24) or localized (n = 14) pain based upon self-reported body maps. Electroencephalography data were collected under resting conditions, and PAF was determined using spectral analysis.

Results

Participants with widespread pain had a significantly lower global average PAF than those with localized pain, after controlling for age and sex. This relationship persisted even when accounting for pain intensity and duration. Peak alpha frequency differences were observed across all EEG electrodes, particularly in the sensorimotor and occipital regions.

Conclusion

Preliminary findings suggest that PAF may represent a potential biomarker for central sensitization in chronic pain, highlighting the importance of considering pain distribution in chronic pain research. Future studies with larger samples should investigate the neural mechanisms underlying these observations and the clinical utility of PAF in diverse chronic pain populations.

Effectiveness of a telerehabilitation tablet app in combination with face-to-face physiotherapy for people with wrist, hand or finger injuries: A pragmatic multicentre clinical trial

OBJECTIVE

To evaluate whether, in patients with trauma and soft tissue injuries of the wrist, hand and/or fingers, an exercise program performed on a touchscreen tablet-based app reduces the consumption of face-to-face resources and improves clinical recovery, compared to a conventional home exercise program prescribed on paper.

DESIGN

Pragmatic, multicentre, parallel, two-group, controlled clinical trial with blinded assessor.

PARTICIPANTS AND SETTING

Eighty-one patients with traumatic bone and/or soft tissue injuries of the hand, wrist and/or fingers recruited in four hospitals of the Andalusian Public Health System.

INTERVENTIONS

The experimental group received a home exercise program using a touchscreen tablet application and the control group received a home exercise program on paper. Both groups received the same treatment of face-to-face physiotherapy.

PRIMARY OUTCOME

Number of physiotherapy sessions. Secondary outcomes were the duration of physiotherapy and clinical variables such as functional ability, grip strength, pain and manual dexterity.

RESULTS

The experimental group required fewer physiotherapy sessions (MD -11,5 sessions; 95% CI -21.4 to -1.4), showed a shorter duration of physiotherapy (MD -3.8 weeks, 95% CI -7 to -1) and had better recovery of grip strength, pain and dexterity compared to the control group.

CONCLUSIONS

In patients with trauma and soft tissue injuries of the wrist, hand and/or fingers, an exercise program performed on a touchscreen tablet-based app in combination with face-to-face physiotherapy reduces the consumption of face-to-face resources and improves clinical recovery, compared to conventional home exercise program prescribed on paper.

Prognostic factors for persistent pain after a distal radius fracture: a systematic review

Introduction

The aim of this systematic review was to synthesize the evidence regarding prognostic factors for persistent pain, including Complex Regional Pain Syndrome (CRPS), after a distal radius fracture (DRF), a common condition after which persistent pain can develop.

Methods

Medline, Pubmed, Embase, Psychinfo, CINAHL, BNI, AMED and the Cochrane Register of Clinical Trials were searched from inception to May 2021 for prospective longitudinal prognostic factor studies investigating persistent pain in adults who had sustained a DRF. The Quality in Prognostic Studies (QUIPS) tool and Grading of Recommendations, Assessment, Development and Evaluation (GRADE) framework were used to assess the strength of evidence.

Results

A search yielded 440 studies of which 7 studies met full eligibility criteria. From five studies we found low evidence for high baseline pain or an ulnar styloid fracture as prognostic factors for persistent pain, and very low evidence for diabetes or older age. From two studies, investigating an outcome of CRPS, there was low evidence for high baseline pain, slow reaction time, dysynchiria, swelling and catastrophising as prognostic factors, and very low evidence for depression. Sex was found not to be a prognostic factor for CRPS or persistent pain.

Conclusions

The associations between prognostic factors and persistent pain following a DRF are unclear. The small number of factors investigated in more than one study, along with poor reporting and methodological limitations contributed to an assessment of low to very low strength of evidence. Further prospective studies, investigating psychosocial factors as candidate predictors of multidimensional pain outcomes are recommended.

Data Science Methods for Nursing-Relevant Patient Outcomes and Clinical Processes: The 2019 Literature Year in Review

Data science continues to be recognized and used within healthcare due to the increased availability of large data sets and advanced analytics. It can be challenging for nurse leaders to remain apprised of this rapidly changing landscape. In this article, we describe our findings from a scoping literature review of papers published in 2019 that use data science to explore, explain, and/or predict 15 phenomena of interest to nurses. Fourteen of the 15 phenomena were associated with at least one paper published in 2019. We identified the use of many contemporary data science methods (eg, natural language processing, neural networks) for many of the outcomes. We found many studies exploring Readmissions and Pressure Injuries. The topics of Artificial Intelligence/Machine Learning Acceptance, Burnout, Patient Safety, and Unit Culture were poorly represented. We hope that the studies described in this article help readers: (1) understand the breadth and depth of data science's ability to improve clinical processes and patient outcomes that are relevant to nurses and (2) identify gaps in the literature that are in need of exploration.