Clinical Implementation Research Articles

Enhanced recovery after bariatric surgery: a comprehensive survey-based analysis of ERABS actual clinical implementation in Italian bariatric centers.

The escalating global prevalence of bariatric procedures necessitates an enhanced focus on optimizing perioperative care for improved patient outcomes. This study focuses on the implementation of Enhanced Recovery After Bariatric Surgery (ERABS) protocols in Italian bariatric centers to optimize perioperative care. An online survey comprising 19 items was conducted in October 2023, targeting managing surgeons in 139 registered bariatric centers. This survey explored geographic and center-type variations, knowledge, and application of ERABS protocols, along with perioperative, intraoperative, and postoperative practices. Statistical analysis employed included one-way ANOVA and Tukey post hoc tests. Responses from 72 centers (51.8%) revealed a strong awareness of ERABS protocols among managing surgeons. Adherence rates varied geographically (46.3-63%) and among center types (60.8-56.3%). Perioperative practices, including the abandonment of antibiotics for perioperative prophylaxis by 77.5% of surgeons and the adoption of the TAP block technique in 69% of centers, aligned well with ERABS recommendations. However, inconsistencies were noted in abdominal drain usage (61.5% after SG; 70.5% after RYGB/OAGB), with a substantial percentage not adhering to ERABS guidelines. Intraoperative habits generally adhered to ERABS protocols, yet preferences for certain tests, particularly the methylene blue test (70.4%), deviated. Postoperative practices displayed positive trends, with early reintroduction of oral feeding (71.8%) and opioid-free pain management (71.8%). Variations existed in discharge timing and patient monitoring, indicating areas for further improvement. This study offers a comprehensive snapshot of ERABS protocol adherence in Italy, emphasizing the positive trend toward optimizing recovery and reducing patient stress. Despite variations, a majority of centers demonstrated commitment to ERABS principles. Ongoing education, interdisciplinary collaboration, and nationwide dialogue are essential for standardizing ERABS protocols and advancing bariatric-metabolic surgery outcomes in Italy.

Clinical implementation and patient-specific quality assurance solutions for real-time target tracking and dynamic delivery in Radixact synchrony.

The installation and testing of the first Radixact with Synchrony system in Colombia marked a significant milestone in Latin America's medical landscape. There was a need to devise a robust quality assurance protocol to comprehensively evaluate both dose delivery and motion tracking accuracy. However, testing experiences under clinical conditions have not been extensively reported. Additionally, there are limited recommended measuring devices for Synchrony evaluation. To validate and implement an alternative setup for dynamic-PSQA while testing Synchrony's functionality under clinical scenarios, including real-patient motion traces, and to provide guidance to new centers undergoing clinical implementation of Helical Synchrony. This approach involves using the Iba miniPhantomR with strategically placed fiducial markers for configuring Gafchromic-films and array-based setups. When paired with the CIRS Dynamic Platform, this enables an innovative dynamic setup with trackable features for Synchrony delivery testing. Assessment scenarios, including compensation (M1S1) and no-motion compensation (M1S0), were evaluated using 2D-gamma pass rate analysis with multiple clinical gamma criteria. The Synchrony-Simulation feature was used to assess pre-treatment performance and capture the patient's target motion pattern. Synchrony for common clinical cases with patient's motion-traces was validated. The results for M1S0 and M1S1 demonstrated consistency with previous studies evaluating Synchrony functionality. Analysis using different gamma criteria unveiled dosimetric differences and impacts across various motion ranges. The application of effective kV-dose subtraction for array-based methods is of upmost importance when evaluating dynamic-PSQA with stringent gamma-criteria. However, no significant kV-dose impact on EBT3-Film was detectable. Two implemented configurations for dynamic-PSQA setups were validated and successfully integrated into our clinic. We addressed both the benefits and limitations of array-based and film-based methods. The functionality and limitations of Synchrony were evaluated using the proposed setups. The potential utility of Synchrony-Simulation, along with the proposed patient-case classification table, can offer valuable support for new users during the clinical implementation of Synchrony treatments.

Impact of doxycycline post-exposure prophylaxis for sexually transmitted infections on the gut microbiome and antimicrobial resistome.

Doxycycline post-exposure prophylaxis (doxy-PEP) reduces bacterial sexually transmitted infections among men who have sex with men and transgender women. Although poised for widespread clinical implementation, the impact of doxy-PEP on antimicrobial resistance remains a primary concern as its effects on the gut microbiome and resistome, or the antimicrobial resistance genes (ARGs) present in the gut microbiome, are unknown. To investigate these effects, we studied participants from the DoxyPEP trial, a randomized clinical trial comparing doxy-PEP use, a one-time doxycycline 200-mg dose taken after condomless sex (DP arm, n = 100), to standard of care (SOC arm, n = 50) among men who have sex with men and transgender women. From self-collected rectal swabs at enrollment (day-0) and after 6 months (month-6), we performed metagenomic DNA sequencing (DNA-seq) or metatranscriptomic RNA sequencing (RNA-seq). DNA-seq data were analyzable from 127 samples derived from 89 participants, and RNA-seq data were analyzable from 86 samples derived from 70 participants. We compared the bacterial microbiome and resistome between the two study arms and over time. The median number of doxycycline doses taken since enrollment by participants with DNA-seq data was zero (interquartile range (IQR): 0-7 doses) for the SOC arm and 42 (IQR: 27-64 doses) for the DP arm. Tetracycline ARGs were detected in all day-0 DNA-seq samples and in 85% of day-0 RNA-seq samples. The proportional mass of tetracycline ARGs in the resistome increased between day-0 and month-6 in DP participants from 46% to 51% in the metagenome (P = 2.3 × 10-2) and from 4% to 15% in the metatranscriptome (P = 4.5 × 10-6), but no statistically significant increases in other ARG classes were observed. Exposure to a higher number of doxycycline doses correlated with proportional enrichment of tetracycline ARGs in the metagenome (Spearman's ρ = 0.23, P = 9.0 × 10-3) and metatranscriptome (Spearman's ρ = 0.55, P = 3.7 × 10-8). Bacterial microbiome alpha diversity, beta diversity and total bacterial mass did not differ between day-0 and month-6 samples from DP participants when assessed by either DNA-seq or RNA-seq. In an abundance-based correlation analysis, we observed an increase over time in the strength of the correlation between tetracycline ARGs and specific bacterial taxa, including some common human pathogens. In sum, doxy-PEP use over a 6-month period was associated with an increase in the proportion of tetracycline ARGs comprising the gut resistome and an increase in the expression of tetracycline ARGs. At 6 months of doxy-PEP use, no residual differences were observed in alpha and beta diversity or taxonomic composition of the gut microbiome. As doxy-PEP is implemented as a public health strategy, further studies and population-level surveillance of doxycycline-resistant pathogens are needed to understand the implications of these findings. ClinicalTrials.gov registration number: NCT03980223 .

B-080 Development and Validation of a GQ1b IgG ELISA as a Diagnostic Aid for Subacute Demyelinating Polyneuropathies

Abstract Background Autoimmunity targeting GQ1b is associated with group of disorders that includes Miller-Fisher Syndrome (MFS), Bickerstaff Brainstem Encephalitis (BBE) and classic Guillain Barre Syndrome (GBS) with ophthalmoplegia. Collectively these are referred to as GQ1B-IgG related syndromes. The prevalence of GQ1b-IgG in this population of patients is high and has been reported to be >80% in well-defined clinical cohorts. Clinical phenotypic presentation is diverse and requires highly accurate antibody testing. The objective of this study was to evaluate a newly developed custom GQ1b-IgG assay, using a semi-quantitative ELISA-based method. Methods A GQ1b-IgG ELISA was developed and validated. Patient sera along with assay controls and a single-point calibrator are diluted and incubated in duplicate wells in a 96-well plate coated with GQ1b antigen. The plate is washed and incubated with anti-human-IgG secondary antibody conjugated with HRP. After a colorimetric reaction, optical densities (OD) are read. The OD of patient samples are compared against the calibrator, generating a cut-off index (COI). Samples ≥1.0 COI are considered positive. During the validation phase, analytical and clinical performance characteristics were evaluated. Studies included assessment of imprecision at multiple concentrations of GQ1b-IgG, accuracy using method comparison, analytical sensitivity and specificity, reference range, common interferences, plate drift, and clinical performance in relevant disease and control cohorts. Results Intra-assay imprecision (coefficient of variation; %CV) ranged from 1.0 - 16% across all concentrations of GQ1b-IgG. Inter-assay imprecision (%CV) ranged from 12.4 - 44.5% but was <20% at or above the assay cut-off. We found perfect qualitative agreement with an independent ELISA reference method (20 positive and 20 negative samples selected based on reference method results [reference interval <1:100]). Limit of detection (LOD) was calculated at a COI of 0.22. To assess analytical specificity, 40 samples with high concentrations of immunoglobulins (hypergammaglobulinemia [N=15], IgG M-protein [N=15] and systemic lupus erythematosus [N=10] were tested and all were negative. A reference interval study was performed on 140 healthy donor serums, all were negative. Interference studies were conducted on 2 positive and 2 negative serum samples, spiked for highly hemolytic (1000 mg/dL), lipemic (2000 mg/dL) and icteric (60 mg/dL) conditions. There was no impact on the assay even with high levels of a given interferent. Plate drift on 2 distinct patient pools tested across the plate (COI range 0.7 - 1.3) had overall plate CV’s ≤10%. ROC analysis was performed on a cohort of 278 patient samples (15 MFS cases and 263 controls [suspected demyelinating neuropathy or disease mimics]). A cut-off value of 1.0 (COI) was selected based on the Youden index. At this cut-off, clinical sensitivity for MFS was 87% while clinical specificity was 99.2%. Conclusions The observed performance of the GQ1b-IgG ELISA was acceptable for clinical laboratory implementation. A COI of ≥ 1.0 was selected for clinical use.

Glucose-6-phosphate dehydrogenase deficiency detection using fluorocytometric assay: Evaluation after 1 year of clinical implementation.

Glucose-6-phosphate dehydrogenase (G6PD) deficiency is a common enzymopathy that affects red blood cells (RBCs) and renders them susceptible to oxidative stress. G6PD deficiency can cause hemolytic anemia, especially after exposure to certain drugs or infections. The diagnosis of G6PD deficiency is usually based on spectrophotometric measurement of enzyme activity, but this method has limitations in heterozygous females and in patients with other hematological disorders. In this study, we evaluated the use of flow cytometry as an alternative method for detecting G6PD deficiency in 514 samples (265 females and 249 males) from a clinical laboratory. We compared the results of flow cytometry with those of spectrophotometry and molecular analysis, and assessed the performance of flow cytometry in different subgroups of patients. We found that flow cytometry was able to identify G6PD deficiency in most cases, with high sensitivity and specificity. Flow cytometry also allowed the quantification of the percentage of G6PD-deficient RBCs, which varied among heterozygous females due to X-chromosome inactivation. Moreover, flow cytometry detected several cases of G6PD deficiency that were missed by spectrophotometry, especially in heterozygous females with normal or subnormal enzyme activity. However, flow cytometry also showed some false negative results, mainly in patients with sickle cell disease. Therefore, flow cytometry is a reliable and efficient tool for screening G6PD deficiency, but some precautions should be taken in interpreting the results in patients with other hematological conditions.

A-005 Comparison of Performance of High Sensitive Troponin I (cTNIH) by “Point of care” (POC) and Automated cTNIH Immunoassays in Patients at Low Risk of Heart Attack in a Chilean Emergency Unit; Impact on E.R Department Efficiency

Abstract Background Most cases of death from Acute Myocardial Infarction (AMI) occur in the first hours after the manifestation of clinical symptoms, constituting 40 to 65% in the first hour and approximately 80% in the first 24 hours. For the safe, effective, and rapid diagnosis of a patient with suspected AMI, international guidelines recommend that it be done based on clinical symptoms, together with electrocardiogram and analysis of biomarkers in the context of suspected of non-ST-elevation myocardial infarction (NSTEMI). Troponins are the biomarkers of choice with level A level evidence and the ability to perform screening in patients complaining of chest pain and refer it to the correct clinical approach based on the 0h/1h algorithm. To date, the successful clinical implementation of these rapid algorithms is restricted to hospitals working with well-defined workflows and a robust central laboratory structure. The Atellica® vTLi analyzer is based on the chemiluminescence methodology for the quantification of hs-cTnI levels with low sample volume, low complexity, and may enable the rapid management of patients with chest pain and application of 0h/1h algorithm. Objectives The aim of the study is to evaluate clinical performance in effectiveness and efficiency of the hs-cTnI Atellica® vTLi point of care test to rule out acute myocardial infarction in subjects with low-risk chest pain established with a validated predictive rule, in an adult-Chilean emergency unit, compared to clinical evaluation and the commonly used ADVIA Centaur® troponin test. Methods Descriptive, observational, longitudinal study. Patients over 18 years of age, consulting with acute chest pain of at least one hour from symptom onset and a HEART SCORE less than or equal to 3 points were recruited. A venous blood sample was requested for hs-cTnI analysis by Atellica® vTLi Siemens Healthineers and ADVIA Centaur® Siemens Healthineers. The time difference between sample collection and start of sample analysis; the time difference between sample collection and release of sample results was recorded and the concordance between the two results was determined. Results 50 subjects were included in the study. The difference between blood sampling and start of sample analysis was 5 minutes with Atellica® vTLi POC and 68 minutes with ADVIA Centaur®. The concordance of hs-cTnI Atellica® vTLi POC and ADVIA Centaur® was 94% for predicting medical discharge and confirmed acute myocardial infarction. Conclusions The study findings support the safety and efficiency of the hs-cTnI POC test by providing faster results than central laboratory tests with the same analytical quality, with direct impact on reducing care times in patients consulting for low-risk chest pain.

B-099 Validation and Clinical Implementation of Organ Procurement Serology Testing: Our Analytical and Regulatory Experience in Implementing a New Donor Testing Program

Abstract Background The Mount Sinai Hospital recently implemented a comprehensive organ donor testing program to service the clinical needs of transplant services in the New York City metro area. Conventional serology testing is not approved by the FDA for donor testing. To support this program, the MSH Chemistry Laboratory implemented and validated a comprehensive donor testing panel on the Abbott Alinity S donor testing platform. We validated donor serology testing for the following assays: HIV-1/2 (HIV), Anti-Hepatitis B Core (Anti-HBc), Hepatitis B Surface Antigen (HBsAg), Human T-lymphotropic virus I and II (HTLV-I/II), Anti-Hepatitis C (Anti-HCV), and Trypanosoma cruzi antibodies (T.Cruzi). The Alinity S System is an automated immunoassay-based analyzer FDA-approved for donor testing. The analyzer consists of two distinct sample ‘paths’ and is effectively two instruments combined in one analyzer. The analyzer is approved for use in living donor serum and plasma and in cadaveric serum. Prior to going live, we found that there was limited guidance on laboratory quality assurance programs related to donor testing. In addition to confirming assay analytical performance, we designed and implemented a comprehensive quality assurance program prior to satisfy compliance with regulatory guidelines, addressing proficiency compliance, sample TAT, and control ranges, amongst other quality indicators. Methods Inter and Intraday precision was assessed through replicate analysis of positive and negative controls, where 10 replicates of both controls were assayed on a single day, and one replicate of each control was assayed daily for 7 distinct days, results were represented as %CV. Result accuracy was assessed through split sample analysis of known serologically positive (n=20) and negative samples (n=40). Each sample was assayed on two distinct lots of reagents, each with its own unique calibration curve. Accuracy was confirmed in both living donor (n=30), and cadaveric samples (n=10). In addition, split sample analysis was performed between the Alinity S and FDA-approved donor testing assays in a reference laboratory (N=7). A carryover study was performed through the analysis of triplicate replicates of low, high, and then low controls. These analyses were performed for all 6 assays. Results Intraday precision using assay general controls afforded the following %CV: HIV: 3.1%, 6.5%; Anti-HBc: 1.3%, 2.6%; Anti-HCV: 3.3%, 11.7%; HTLV-I,II: 2.5%, 5.9%; T.Cruzi: 2.8%, 0%; HBsAg: 3.2%, 11.6%. Interday precision yielded the following in %CV: HIV: 2.9%, 10.0%; Anti-HBc: 3.0%, 5.6%; Anti-HCV: 3.3%, 3.4%; HTLV-I,II: 2.8%, 4.6%; T.Cruzi: 2.4%, 0%; HBsAg: 4.7%, 7.8%. Accuracy studies yielded 100% positive and negative correlation for all 6 assays in both living donor and cadaveric samples. In addition, there was a 100% serological correlation for samples compared to reference laboratories. Carryover studies showed no evidence of sample carryover. Conclusions The Abbott Alinity S shows acceptable assay precision on all 6 validated assays. The assays are serologically accurate in both cadaveric and living donor samples. As such, the assays and platform are acceptable for use in donor screening. We designed a unique quality assurance program including a comprehensive self-proficiency and instrument crosscheck program to ensure analyzer accuracy, as well as adherence to regulatory guidelines.

Recommendations for clinical implementation of blood-based biomarkers for Alzheimer's disease.

Blood-based biomarkers (BBM) for Alzheimer's disease (AD) are being increasingly used in clinical practice to support an AD diagnosis. In contrast to traditional diagnostic modalities, such as amyloid positron emission tomography and cerebrospinal fluid biomarkers, BBMs offer a more accessible and lower cost alternative for AD biomarker testing. Their unique scalability addresses the anticipated surge in demand for biomarker testing with the emergence of disease-modifying treatments (DMTs) that require confirmation of amyloid pathology. To facilitate the uptake of BBMs in clinical practice, The Global CEO Initiative on Alzheimer's Disease convened a BBM Workgroup to provide recommendations for two clinical implementational pathways for BBMs: one for current use for triaging and another for future use to confirm amyloid pathology. These pathways provide a standardized diagnostic approach with guidance on interpreting BBM test results. Integrating BBMs into clinical practice will simplify the diagnostic process and facilitate timely access to DMTs for eligible patients.

Publication bias in pharmacogenetics of statin-associated muscle symptoms, an umbrella review with a meta-epidemiological study

Background and aimsStatin-associated muscle symptoms (SAMS) are a major cause of treatment discontinuation. Clinical Pharmacogenetics Implementation Consortium (CPIC) recommend dose adjustment for statin treatment according to known SLCO1B1 genotype to reduce SAMS. We hypothesized that the association between SLCO1B1 genotype and SAMS is misestimated because of publication bias. MethodsWe searched published systematic reviews on the association between SLCO1B1 genotype and SAMS. To assessed publication bias, we used funnel plot visual inspection, Egger’s test, and the Bayes Factor (BFPublication-bias) from Robust Bayesian Meta-Analysis (RoBMA). We compared the odds ratios (ORUncorrected) from meta-analyses before and after correcting for publication bias using trim-and-fill (ORTrim&Fill) and RoBMA (ORRoBMA) methods. ResultsWe included 8 cohort and 11 case-control studies, totaling 62 OR of three SLCO1B1 genotypes and six statin drugs. In the primary analysis, the funnel plot was suggestive of publication bias, confirmed by Egger’s test (p=0.001) and RoBMA (BFPublication-bias=18). Correcting the estimate for publication bias resulted in loss of the association, from a significant ORUncorrected (1.31 95%CI [1.13–1.53]) to corrected ORs suggesting no difference: ORTrim&Fill (1.07 95%CI [0.89–1.30]) and ORRoBMA (1.02 95%CI [1.00–1.33]). This suggested that publication bias overestimated the association by 18% and 23%, respectively. Similar results were found for genotype rs4149056, simvastatin and atorvastatin. ConclusionsThe effect of the SLCO1B1 genotype on the risk of developing SAMS is overestimated in the published literature, especially rs4149056. This could lead prescribers to incorrectly decreasing statin doses or even avoiding statin use, leading to a loss of the potential cardiovascular benefit of statins.

Usability Of A Web-based Application For The Clinical Implementation Of Blood Flow Restriction Exercise

Usability Of A Web-based Application For The Clinical Implementation Of Blood Flow Restriction Exercise

Geometric and dosimetric evaluation for breast and regional nodal auto-segmentation structures.

The accuracy of artificial intelligence (AI) generated contours for intact-breast and post-mastectomy radiotherapy plans was evaluated. Geometric and dosimetric comparisons were performed between auto-contours (ACs) and manual-contours (MCs) produced by physicians for target structures. Breast and regional nodal structures were manually delineated on 66 breast cancer patients. ACs were retrospectively generated. The characteristics of the breast/post-mastectomy chestwall (CW) and regional nodal structures (axillary [AxN], supraclavicular [SC], internal mammary [IM]) were geometrically evaluated by Dice similarity coefficient (DSC), mean surface distance, and Hausdorff Distance. The structures were also evaluated dosimetrically by superimposing the MC clinically delivered plans onto the ACs to assess the impact of utilizing ACs with target dose (Vx%) evaluation. Positive geometric correlations between volume and DSC for intact-breast, AxN, and CW were observed. Little or anti correlations between volume and DSC for IM and SC were shown. For intact-breast plans, insignificant dosimetric differences between ACs and MCs were observed for AxNV95% (p=0.17) and SCV95% (p=0.16), while IMNV90% ACs and MCs were significantly different. The average V95% for intact-breast MCs (98.4%) and ACs (97.1%) were comparable but statistically different (p=0.02). For post-mastectomy plans, AxNV95% (p=0.35) and SCV95% (p=0.08) were consistent between ACs and MCs, while IMNV90% was significantly different. Additionally, 94.1% of AC-breasts met ΔV95% variation<5% when DSC>0.7. However, only 62.5% AC-CWs achieved the same metrics, despite AC-CWV95% (p=0.43) being statistically insignificant. The AC intact-breast structure was dosimetrically similar to MCs. The AC AxN and SC may require manual adjustments. Careful review should be performed for AC post-mastectomy CW and IMN before treatment planning. The findings of this study may guide the clinical decision-making process for the utilization of AI-driven ACs for intact-breast and post-mastectomy plans. Before clinical implementation of this auto-segmentation software, an in-depth assessment of agreement with each local facilities MCs is needed.

A critical systematic review of extracellular vesicle clinical trials.

This systematic review examines the landscape of extracellular vesicle (EV)-related clinical trials to elucidate the field's trends in clinical applications and EV-related methodologies, with an additional focus on the acknowledgement of EV subpopulations. By analysing data from public reporting repositories, we catalogued 471 EV-related clinical trials to date, with indications for over 200 diseases. Diagnostics and companion diagnostics represented the bulk of EV-related clinical trials with cancer being the most frequent application. EV-related therapeutics trials mainly utilized mesenchymal stromal cell (MSC) EVs and were most frequently used for treatment of respiratory illnesses. Ultracentrifugation and RNA-sequencing were the most common isolation and characterization techniques; however, methodology for each was not frequently reported in study records. Most of the reported characterization relied on bulk characterization of EV isolates, with only 11% utilizing EV subpopulations in their experimental design. While this may be connected to a lack of available techniques suitable for clinical implementation, it also highlights the opportunity for use of EV subpopulations to improve translational efforts. As academic research identifies more chemically distinct subpopulations and technologies for their enrichment, we forecast to more refined EV trials in the near future. This review emphasizes the need for meticulous methodological reporting and consideration of EV subpopulations to enhance the translational success of EV-based interventions, pointing towards a paradigm shift in personalized medicine.

Development and comprehensive evaluation of a national DBCG consensus-based auto-segmentation model for lymph node levels in breast cancer radiotherapy

Background and purposeThis study aimed at training and validating a multi-institutional deep learning (DL) auto segmentation model for nodal clinical target volume (CTVn) in high-risk breast cancer (BC) patients with both training and validation dataset created with multi-institutional participation, with the overall aim of national clinical implementation in Denmark. Materials and methodsA gold standard (GS) dataset and a high-quality training dataset were created by 21 BC delineation experts from all radiotherapy centres in Denmark. The delineations were created according to ESTRO consensus delineation guidelines. Four models were trained: One per laterality and extension of CTVn internal mammary nodes. The DL models were tested quantitatively in their own test-set and in relation to interobserver variation (IOV) in the GS dataset with geometrical metrics, such as the Dice Similarity Coefficient (DSC). A blinded qualitative evaluation was conducted with a national board, presented to both DL and manual delineations. ResultsA median DSC > 0.7 was found for all, except the CTVn interpectoral node in one of the models. In the qualitative evaluation ‘no corrections needed’ were acquired for 297 (36 %) in the DL structures and 286 (34 %) for manual delineations. A higher rate of ‘major corrections’ and ‘easier to start from scratch’ was found in the manual delineations. The models performed within the IOV of an expert group, with two exceptions. ConclusionDL models were developed on a national consensus cohort and performed on par with the IOV between BC experts and had a comparable or higher clinical acceptance than expert manual delineations.

Outcome prediction following lumbar disc surgery: a longitudinal study of outcome trajectories, prognostic factors, and risk models.

This study aimed to 1) describe the 2-year postoperative trajectories of leg pain and overall clinical outcome after surgery for radiculopathy, 2) identify the preoperative prognostic factors that predict trajectories representing poor clinical outcomes, and 3) develop and internally validate multivariable prognostic models to assist with clinical decision-making. This retrospective cohort study included patients enrolled in the Canadian Spine Outcomes and Research Network who were diagnosed with lumbar disc pathology and radiculopathy and had undergone lumbar discectomy at one of 18 spine centers. Potential outcome predictors included preoperative demographic, health-related, and clinical prognostic factors. Clinical outcomes were 1) 2-year univariable latent trajectories of leg pain intensity (numeric pain rating scale) and 2) overall outcomes comprising multivariable trajectories showing the combined postoperative courses of leg and back pain intensity (numeric pain rating scale) together with pain-related disability (Oswestry Disability Index). Each outcome model identified a subgroup of patients classified as experiencing a poor outcome based on minimal change in their clinical status after surgery. Multivariable risk model performance and internal validity were evaluated with discrimination and calibration statistics based on bootstrap shrinkage with 500 resamplings. The authors included data from 1142 patients (47.6% female). The trajectory models identified 3 subgroups based on the patients' postoperative courses of pain or disability: 88.6% of patients in the leg pain model and 71.9% in the overall outcome model experienced a good-to-excellent outcome. The models classified 11.4% (leg pain outcome) and 28.2% (overall outcome) of patients as experiencing a poor clinical outcome, which was defined as minimal improvement in pain or disability after surgery. Eleven individual demographic, health, and clinical factors predicted patients' poor leg pain and overall outcomes. The performance of the multivariable risk model for leg pain was inadequate, while the overall outcome model had acceptable discrimination, calibration, and internal validity for predicting a poor surgical outcome. Patients with lumbar radiculopathy experience heterogeneous postoperative trajectories of pain and disability after lumbar discectomy. Individual preoperative factors are associated with postoperative outcomes and can be combined within a multivariable risk model to predict overall patient outcome. These results may inform clinical practice but require external validation before confident clinical implementation.

Patient-managed interventions for adults with bronchiectasis: evidence, challenges and prospects.

Bronchiectasis is a chronic lung condition which is characterised by recurrent chest infections, chronic sputum production and cough, and limited exercise tolerance. While bronchiectasis may be caused by various aetiologies, these features are shared by most patients with bronchiectasis regardless of the cause. This review consolidates the existing evidence on patient-managed interventions for adults with bronchiectasis, while also outlining areas for future research. Airway clearance techniques and hyperosmolar agents are key components of the bronchiectasis management and consistently recommended for clinical implementation. Questions around their prescription, such as optimal sequence of delivery, are still to be answered. Pulmonary rehabilitation and exercise are also recommended for patients with bronchiectasis. Relatively strong evidence underpins this recommendation during a clinically stable stage of the disease, although the role of pulmonary rehabilitation following an exacerbation is still unclear. Additionally, self-management programmes feature prominently in bronchiectasis treatment, yet the lack of consensus regarding their definition and outcomes presents hurdles to establishing a cohesive evidence base. Moreover, cough, a cardinal symptom of bronchiectasis, warrants closer examination. Although managing cough in bronchiectasis may initially appear risky, further research is necessary to ascertain whether strategies employed in other respiratory conditions can be safely and effectively adapted to bronchiectasis, particularly through identifying patient responder populations and criteria where cough may not enhance airway clearance efficacy and its control is needed. Overall, there is a growing recognition of the importance of patient-managed interventions in the bronchiectasis management. Efforts to improve research methodologies and increase research funding are needed to further advance our understanding of these interventions, and their role in optimising patient care and outcomes.

A Modification to the Assessment of Problem-Solving in Play to Enhance Its Utility: Evaluation of Validity, Responsiveness, and Reliability.

This study investigated the psychometric properties of a 4-second interval scoring modification of the Assessment of Problem-Solving in Play (ie, Assessment of Problem-Solving in Play 4-second interval scoring [APSP-4]). A total of 95 children (3-48 months) with or at high risk for neuromotor delay were assessed with the APSP-4 and Bayley Scales of Infant and Toddler Development-III (Bayley). APSP-4 and Bayley cognitive raw scores were compared by age (construct validity) and over time (responsiveness). Twenty percent of videos were scored twice for intra- and interrater reliability. The APSP-4 demonstrated excellent interrater (intraclass correlations [ICCs]≥0.96) and intrarater (ICCs≥0.99) reliability and performed similar to Bayley cognitive raw scores at different ages ( r s>0.5), and over time ( r =0.81). The motor delay had similar effects on APSP-4 and Bayley scores. Results support the validity and reliability evidence of the APSP-4 for use over time in tracking problem-solving skills in young children aged 3 to 48months. Future research investigating clinical implementation of the APSP-4 is needed.

Advancing diagnostics: integrating microRNA profiling and protein markers in ectopic pregnancy detection

IntroductionEctopic pregnancy (EP) poses significant health risks, particularly in developing nations, necessitating improved diagnostic methods. This study aimed to explore potential biomarkers for EP diagnosis.MethodsA case–control study was conducted at...

ID: 342500 Clinical Implementation of a Fully Implanted Bidirectional Somatosensory Neuroprosthetic System

ID: 342500 Clinical Implementation of a Fully Implanted Bidirectional Somatosensory Neuroprosthetic System

Clinical Implementation Framework of Anemia Control Model in Singapore

Clinical Implementation Framework of Anemia Control Model in Singapore

Reconstructing and analyzing the invariances of low-dose CT image denoising networks.

Deep learning-based methods led to significant advancements in many areas of medical imaging, most of which are concerned with the reduction of artifacts caused by motion, scatter, or noise. However, with most neural networks being black boxes, they remain notoriously difficult to interpret, hindering their clinical implementation. In particular, it has been shown that networks exhibit invariances w.r.t. input features, that is, they learn to ignore certain information in the inputdata. To improve the interpretability of deep learning-based low-dose CT image denoisingnetworks. We learn a complete data representation of low-dose input images using a conditional variational autoencoder (cVAE). In this representation, invariances of any given denoising network are then disentangled from the information it is not invariant to using a conditional invertible neural network (cINN). At test time, image-space invariances are generated by applying the inverse of the cINN and subsequent decoding using the cVAE. We propose two methods to analyze sampled invariances and to find those that correspond to alterations of anatomicalstructures. The proposed method is applied to four popular deep learning-based low-dose CT image denoising networks. We find that the networks are not only invariant to noise amplitude and realizations, but also to anatomicalstructures. The proposed method is capable of reconstructing and analyzing invariances of deep learning-based low-dose CT image denoising networks. This is an important step toward interpreting deep learning-based methods for medical imaging, which is essential for their clinical implementation.