Early Detection of Scoliosis-What the USPSTF "I" Means for Us

Investigating the Differential Circulating microRNA Expression in Adolescent Females with Severe Idiopathic Scoliosis: A Proof-of-Concept Observational Clinical Study

Adolescent Idiopathic Scoliosis (AIS) is the most common form of three-dimensional spinal disorder in adolescents between the ages of 10 and 18 years of age, most commonly diagnosed in young women when severe disease occurs. Patients with AIS are characterized by abnormal skeletal growth and reduced bone mineral density. The etiology of AIS is thought to be multifactorial, involving both environmental and genetic factors, but to date, it is still unknown. Therefore, it is crucial to further investigate the molecular pathogenesis of AIS and to identify biomarkers useful for predicting curve progression. In this perspective, the relative abundance of a panel of microRNAs (miRNAs) was analyzed in the plasma of 20 AIS patients and 10 healthy controls (HC). The data revealed a significant group of circulating miRNAs dysregulated in AIS patients compared to HC. Further bioinformatic analyses evidenced a more restricted expression of some miRNAs exclusively in severe AIS females. These include some members of the miR-30 family, which are considered promising regulators for treating bone diseases. We demonstrated circulating extracellular vesicles (EVs) from severe AIS females contained miR-30 family members and decreased the osteogenic differentiation of mesenchymal stem cells. Proteomic analysis of EVs highlighted the expression of proteins associated with orthopedic disease. This study provides preliminary evidence of a miRNAs signature potentially associated with severe female AIS and suggests the corresponding vesicular component may affect cellular mechanisms crucial in AIS, opening the scenario for in-depth studies on prognostic differences related to gender and grade.

An Examination of the Number of Adolescent Scoliotic Curves That Are Braceable at First Presentation to a Scoliosis Service

Adolescent idiopathic scoliosis (AIS) affects between 0.5% and 5.2% of adolescents and is progressive in two-thirds of cases. Bracing is an effective non-operative treatment for AIS and has been shown to prevent up to 72% of curves from requiring surgery. This paper explores the presentation of AIS in the UK and identifies who would be suitable for bracing, as per guidelines published by the Scoliosis Research Society (SRS) and British Scoliosis Society (BSS), through curve severity and skeletal maturity at presentation. There were 526 patients with AIS eligible for inclusion across three tertiary referral centres in the UK. The study period was individualised to each centre, between January 2012 and December 2021. Only 10% were appropriate for bracing via either SRS or BSS criteria. The rest were either too old, skeletally mature or had a curve size too large to benefit. By the end of data collection, 38% had undergone surgery for their scoliosis. In the UK, bracing for AIS is only suitable for a small number at presentation. Future efforts to minimise delays in specialist review and intervention will increase the number of those with AIS suitable for bracing and reduce the number and burden of operative interventions for AIS in the UK.

Idiopathic Scoliosis Trends One Year After COVID-19: A Retrospective Study

Introduction The reorganization of healthcare services during the COVID-19 pandemic was associated with compromised management of conditions not related to the pandemic. Methods A retrospective descriptive case series study was carried out that included patients followed up at the Spine Deformities (SD) consultation at Centro Hospitalar e Universitário Lisboa Central from January 2019 through December 2021 regarding diagnosis, treatment, referral, and the number of consultations performed. Results Referrals significantly dropped in 2020 (p<0.001). The average number of consultations per patient was found to not vary significantly in 2020 despite the reorganization of our healthcare unit due to the pandemic. 22% of the consultations were performed online. Idiopathic scoliosis (IS) was the primary diagnosis in 50% of the patients observed for the first time during the three-year time period. An increase of 18% was found in the number of IS patients that required bracing in 2021. However, late referrals, defined as the patient meeting surgical criteria at the time of initial presentation, did not increase. Conclusion Despite the significant decrease in primary care referrals during 2020, an overcompensation increase in referrals was not observed in 2021. However, the increase in the percentage of patients needing bracing might reflect a delayed initial presentation to the SD consultation.

Novel Screening Tool for Adolescent Idiopathic Scoliosis: A Reliability Study

OBJECTIVE

The aim of this study was to assess the agreement between a web-based scoliosis screening tool and a standard screening procedure.

METHODS

Sixty participants were selected (median age, 12 years; 75% were women) and separated into 2 groups: those with unknown spinal curvature status and those with confirmed scoliosis. Each participant was assessed by 2 blinded assessors, with one measuring the angle of trunk rotation using a scoliometer and the second using a web-based screening application. The app provided a relative risk score for having scoliosis based on a weighted algorithm. Those with an angle of trunk rotation ≥7° or risk score >2 were deemed as being at risk for having scoliosis.

RESULTS

There was fair agreement (kappa = 0.34; 95% confidence interval [CI], 0.14-0.55; P < .001) between the app and the scoliometer among the unconfirmed cases. The McNemar test indicated a difference in the proportion of positive tests (P = .001), whereby the screening app produced a significantly higher number of positive tests (15/53 = 28.3%) compared to the standard screening procedure (4/53 = 7.5%) for unconfirmed cases. Among the confirmed cases, the app correctly identified 5 out of 7 (sensitivity: 71%; 95% CI, 29%-96%) participants, whereas the scoliometer correctly identified 6 out of 7 (sensitivity: 86%; 95% CI, 42%-100%) participants.

CONCLUSION

These findings indicate fair agreement between the app and the scoliometer, though it was not possible to precisely estimate the sensitivity of the app in this study.

No Recommendation Is (at Least Presently) the Best Recommendation: An Updating Quality Appraisal of Recommendations on Screening for Scoliosis

Recommendations addressing screening for scoliosis differ substantially. Systematically developed guidelines are confronted by consensus and opinion-based statements. This paper elaborates on the issue of the standards of development and reporting of current guidelines and recommendation statements, as well as on the methodological quality of the corresponding evidence syntheses. The SORT classification and the AMSTAR 2 tool were used for those purposes, respectively. Publications included in the analysis differed substantially in terms of their methodological quality. Based on the SORT and AMSTAR 2 scores, the 2018 US PSTF recommendation statement and systematic review on screening for scoliosis are trustworthy and high-quality sources of evidence and aid for decision making. The recommendation statement on insufficient evidence to formulate any recommendations is, paradoxically, very informative. Significantly, updated opinion-based position statements supporting screening for scoliosis acknowledged the importance of research evidence as a basis for recommendation formulation and are more cautious and balanced than formerly. Expert opinions, not built on properly presented analyses of evidence, are at odds with evidence-based practice. Nonetheless, contemporary principles of screening programs, especially those addressing people's values and preferences, and the possible harms of screening, remain underrepresented in both research and recommendations addressing screening for scoliosis.

Screening for scoliosis - New recommendations, old dilemmas, no straight solutions

This opinion review considers the prevailing question of whether to screen or not to screen for adolescent idiopathic scoliosis. New and improved standards of people-oriented care and person-centredness, as well as improved principles of preventive screening and guideline development, have been postulated and implemented in health care systems and cultures. Recommendations addressing screening for scoliosis differ substantially, in terms of their content, standards of development and screening principles. Some countries have discontinued issuing recommendations. In the last decade, a number of updated and new recommendations and statements have been released. Systematically developed guidelines and recommendations are confronted by consensus and opinion-based statements. The dilemmas and discrepancies prevail. The arguments concentrate on the issues of the need for early detection through screening in terms of the effectiveness of early treatment, on costs and cost-effectiveness issues, scientific and epidemiologic value of screenings, and the credibility of the sources of evidence. The problem matter is of global scale and applies to millions of people. It regards clinical and methodological dilemmas, but also the matter of vulnerable and fragile time of adolescence and, more generally, children's rights. The decisions need to integrate people's values and preferences - screening tests need to be acceptable to the population, and treatments need to be acceptable for patients. Therefore we present one more crucial, but underrepresented in the discussion, issue of understanding and implementation of the contemporary principles of person-centred care, standards of preventive screening, and guideline development, in the context of screening for scoliosis.

Development and validation of deep learning algorithms for scoliosis screening using back images

Adolescent idiopathic scoliosis is the most common spinal disorder in adolescents with a prevalence of 0.5-5.2% worldwide. The traditional methods for scoliosis screening are easily accessible but require unnecessary referrals and radiography exposure due to their low positive predictive values. The application of deep learning algorithms has the potential to reduce unnecessary referrals and costs in scoliosis screening. Here, we developed and validated deep learning algorithms for automated scoliosis screening using unclothed back images. The accuracies of the algorithms were superior to those of human specialists in detecting scoliosis, detecting cases with a curve ≥20°, and severity grading for both binary classifications and the four-class classification. Our approach can be potentially applied in routine scoliosis screening and periodic follow-ups of pretreatment cases without radiation exposure.