Tag: statistics

Nutr Clin Pract. 2024 Jul 7. doi: 10.1002/ncp.11184. Online ahead of print.

ABSTRACT

BACKGROUND: Initiation of feeding after percutaneous endoscopic gastrostomy (PEG) placement has been debated. Randomized controlled trials (RCTs) have been performed on early feeding compared with delayed feeding after PEG placement with varying results. Therefore, a meta-analysis was conducted examining early vs delayed feeding after placement of a PEG.

METHODS: A comprehensive search of databases was conducted in January 2024. Peer-reviewed published RCTs comparing early feeding (≤4 h) with delayed feeding (>4 h) were identified and included in the meta-analysis. Meta-analysis was completed using pooled estimates of overall complications, individual complications, mortality ≤72 h, and number of day 1 significant gastric residual volumes.

RESULTS: Six RCTs (n = 467) were included in the analysis. Comparison of early feeding with delayed feeding after PEG showed no statistically significant differences for overall complications (P = 0.18), mortality ≤72 h (P = 0.3), and number of day 1 significant gastric residual volumes (P = 0.05). No differences were also noted for individual complications, including vomiting, wound infection, bleeding, or diarrhea.

CONCLUSION: Feeding ≤4 h after PEG have no differences in minor and major complications compared with that of delayed feeding. Early feeding ≤4 h is safe and should be recommended in future guidelines.

PMID:38971978 | DOI:10.1002/ncp.11184

Nord J Psychiatry. 2024 Jul 6:1-6. doi: 10.1080/08039488.2024.2371872. Online ahead of print.

ABSTRACT

PURPOSE: To access the attitudes of service users about the sharing of health records for research and to foster collaboration between municipal health services and the specialist health services in Norway.

METHODS: Members (n ≈ 2000) of the Norwegian mental health service users’ organizations (SUO’s), ADHD Norway, the Autism Association and the Tourette Association, representing Central Norway, participated in the study, (N = 108, 5.4% response rate). Descriptive statistics were used to evaluate distributions of responses to the questionnaire.

RESULTS: Service users reported being aware that municipal health services collaborate with the specialist health service (62%), with mental health care in the specialist health service (57%), and child and adolescent psychiatric services (61%). A large proportion of individuals were aware of the benefits of sharing their health records (93%), have trust in the use of data by health authorities (81%), and were willing to share records to benefit fellow patients (84%). Personal experience (69%) and impressions from mainstream media (55%) had the most influential impact on users’ views of the Health Platform, an electronic health communication system. A majority of users had a negative perception of the Health Platform, even though some expect it to become a valuable tool in the future (50%).

CONCLUSIONS: Service users are aware of and positive about benefiting others by sharing health records. They trust the health authorities, however, have negative attitudes about the Health Platform, apparently based on personal experiences and media influence. However, service users can see the potential usefulness of the Health Platform in the future.

PMID:38971971 | DOI:10.1080/08039488.2024.2371872

Prostate Cancer Prostatic Dis. 2024 Jul 6. doi: 10.1038/s41391-024-00857-5. Online ahead of print.

ABSTRACT

BACKGROUND: Prostatic inflammation is an important etiological component of benign prostatic hyperplasia (BPH) and lower urinary tract symptoms (LUTS). The Prostatic Inflammation Nomogram Study (PINS) aimed to develop and validate a nomogram for predicting the presence of prostatic inflammation in men with LUTS.

METHODS: This non-interventional, cross-sectional, prospective study was conducted in six secondary/tertiary centers across Cyprus, Greece, Italy, Portugal, and Spain. Men (≥40 years) with BPH/LUTS scheduled to undergo prostatic surgery or transrectal ultrasound-guided (TRUS) prostate biopsy were included. Fifteen demographic and clinical participant characteristics were selected as possible predictors of prostatic inflammation. The presence of inflammation (according to Irani score) in the prostatic tissue samples obtained from surgery/TRUS biopsy was determined. The effect of each characteristic on the likelihood a prostate specimen demonstrated inflammation (classified by Irani score into two categories, 0-2 [no/minimal inflammation] or 3-6 [moderate/severe inflammation]) was assessed using multiple logistic regression. A nomogram was developed and its discriminatory ability and validity were assessed.

RESULTS: In total, 423 patients (mean age 68.9 years) were recruited. Prostate volume ultrasound (PVUS) > 50 mL, history of urinary tract infection (UTI) treatment, presence of diabetes, and International Prostate Symptom Score (IPPS) Storage score were statistically significant predictors of Irani classification. Logistic regression demonstrated a statistically significant effect for leucocytes detected via urine dipstick, presence of diabetes, PVUS > 50 mL, history of UTIs, and higher IPSS Storage score for the odds of an inflammatory score category of 3-6 versus 0-2. The nomogram had a concordance index of 0.71, and good internal validity.

CONCLUSIONS: The nomogram developed from PINS had good predictive ability and identified various characteristics to be predictors of prostatic inflammation. Use of the nomogram may aid in individualizing treatment for LUTS, by identifying individuals who are candidates for therapies targeting prostatic inflammation.

PMID:38971935 | DOI:10.1038/s41391-024-00857-5

Insights Imaging. 2024 Jul 6;15(1):167. doi: 10.1186/s13244-024-01753-1.

ABSTRACT

OBJECTIVES: Detection of liver metastases is crucial for guiding oncological management. Computed tomography through iterative reconstructions is widely used in this indication but has certain limitations. Deep learning image reconstructions (DLIR) use deep neural networks to achieve a significant noise reduction compared to iterative reconstructions. While reports have demonstrated improvements in image quality, their impact on liver metastases detection remains unclear. Our main objective was to determine whether DLIR affects the number of detected liver metastasis. Our secondary objective was to compare metastases conspicuity between the two reconstruction methods.

METHODS: CT images of 121 patients with liver metastases were reconstructed using a 50% adaptive statistical iterative reconstruction (50%-ASiR-V), and three levels of DLIR (DLIR-low, DLIR-medium, and DLIR-high). For each reconstruction, two double-blinded radiologists counted up to a maximum of ten metastases. Visibility and contour definitions were also assessed. Comparisons between methods for continuous parameters were performed using mixed models.

RESULTS: A higher number of metastases was detected by one reader with DLIR-high: 7 (2-10) (median (Q₁-Q₃); total 733) versus 5 (2-10), respectively for DLIR-medium, DLIR-low, and ASiR-V (p < 0.001). Ten patents were detected with more metastases with DLIR-high simultaneously by both readers and a third reader for confirmation. Metastases visibility and contour definition were better with DLIR than ASiR-V.

CONCLUSION: DLIR-high enhanced the detection and visibility of liver metastases compared to ASiR-V, and also increased the number of liver metastases detected.

CRITICAL RELEVANCE STATEMENT: Deep learning-based reconstruction at high strength allowed an increase in liver metastases detection compared to hybrid iterative reconstruction and can be used in clinical oncology imaging to help overcome the limitations of CT.

KEY POINTS: Detection of liver metastases is crucial but limited with standard CT reconstructions. More liver metastases were detected with deep-learning CT reconstruction compared to iterative reconstruction. Deep learning reconstructions are suitable for hepatic metastases staging and follow-up.

PMID:38971933 | DOI:10.1186/s13244-024-01753-1

Commun Med (Lond). 2024 Jul 6;4(1):132. doi: 10.1038/s43856-024-00537-4.

ABSTRACT

BACKGROUND: The widespread use of physical activity trackers enables the collection of high-resolution health data, such as hourly step counts, to evaluate health promotion programmes. We aim to investigate how participants meet their daily step goals.

METHODS: We used 24-h steps data from the National Steps Challenge^TM Season 3, wherein participants were rewarded with vouchers when achieving specified goals of 5000, 7500, and 10,000 steps per day. We extracted data from 3075 participants’ including a total of 52,346 participant-days. We modelled the hourly step counts using a two-part model, in which the distribution for step counts was allowed to depend on the sum of step counts up to the previous hour and participant demographics.

RESULTS: Participants have a mean age of 44.2 years (standard deviation = 13.9), and 40.4% are males. We show that on weekdays, the hourly mean step counts among participants aged 60 and above are higher than participants aged 30 to 59 from the start of the day till 6 p.m. We also find that participants who accumulate at least 7000 steps by 7 p.m. are associated with higher success of achieving 10,000 steps.

CONCLUSIONS: We provide recommendations on the hourly targets to achieve daily goals, based on different participants’ characteristics. Future studies could experimentally test if prompts and nudges at the recommended times of day could promote reaching step goals.

PMID:38971929 | DOI:10.1038/s43856-024-00537-4

Aesthetic Plast Surg. 2024 Jul 7. doi: 10.1007/s00266-024-04202-y. Online ahead of print.

ABSTRACT

INTRODUCTION: The rising use of soft tissue fillers for aesthetic procedures has seen an increase in complications, including vascular occlusions and neurological symptoms that resemble stroke. This study synthesizes information on central nervous system (CNS) complications post-filler injections and evaluates the effectiveness of hyaluronidase (HYAL) treatment.

METHODS: A thorough search of multiple databases, including PubMed, EMBASE, Scopus, Web of Science, Google Scholar, and Cochrane, focused on publications from January 2014 to January 2024. Criteria for inclusion covered reviews and case reports that documented CNS complications related to soft tissue fillers. Advanced statistical and computational techniques, including logistic regression, machine learning, and Bayesian analysis, were utilized to dissect the factors influencing therapeutic outcomes.

RESULTS: The analysis integrated findings from 20 reviews and systematic analyses, with 379 cases reported since 2018. Hyaluronic acid (HA) was the most commonly used filler, particularly in nasal region injections. The average age of patients was 38, with a notable increase in case reports in 2020. Initial presentation data revealed that 60.9% of patients experienced no light perception, while ptosis and ophthalmoplegia were present in 54.3 and 42.7% of cases, respectively. The statistical and machine learning analyses did not establish a significant linkage between the HYAL dosage and patient recovery; however, the injection site emerged as a critical determinant.

CONCLUSION: The study concludes that HYAL treatment, while vital for managing complications, varies in effectiveness based on the injection site and the timing of administration. The non-Newtonian characteristics of HA fillers may also affect the incidence of complications. The findings advocate for tailored treatment strategies incorporating individual patient variables, emphasizing prompt and precise intervention to mitigate the adverse effects of soft tissue fillers.

LEVEL OF EVIDENCE III: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

PMID:38971925 | DOI:10.1007/s00266-024-04202-y

Mol Psychiatry. 2024 Jul 6. doi: 10.1038/s41380-024-02640-3. Online ahead of print.

ABSTRACT

Previous studies have shown an association between the thalamocortical dysconnectivity and treatment-resistant depression (TRD). Whether a single subanesthetic dose of ketamine may change thalamocortical connectivity among patients with TRD is unclear. Whether these changes in thalamocortical connectivity is associated with the antidepressant and antisuicidal effects of ketamine treatment is also unclear. Two resting-state functional MRIs were collected in two clinical trials of 48 patients with TRD (clinical trial 1; 32 receiving ketamine, 16 receiving a normal saline placebo) and 48 patients with TRD and strong suicidal ideation (clinical trial 2; 24 receiving ketamine, 24 receiving midazolam), respectively. All participants underwent rs-fMRI before and 3 days after infusion. Seed-based functional connectivity (FC) was analyzed in the left/right thalamus. FCs between the bilateral thalamus and right middle frontal cortex (BA46) and between the left thalamus and left anterior paracingulate gyrus (BA8) increased among patients in the ketamine group in clinical trials 1 and 2, respectively. FCs between the right thalamus and bilateral frontal pole (BA9) and between the right thalamus and left rostral paracingulate gyrus (BA10) decreased among patients in the ketamine group in clinical trials 1 and 2, respectively. However, the associations between those FC changes and clinical symptom changes did not survive statistical significance after multiple comparison corrections. Whether ketamine-related changes in thalamocortical connectivity may be associated with ketamine’s antidepressant and antisuicidal effects would need further investigation. Clinical trials registration: UMIN Clinical Trials Registry (UMIN-CTR): Registration number: UMIN000016985 and UMIN000033916.

PMID:38971895 | DOI:10.1038/s41380-024-02640-3

Psychometrika. 2024 Jul 6. doi: 10.1007/s11336-024-09985-2. Online ahead of print.

ABSTRACT

The Ising model has become a popular psychometric model for analyzing item response data. The statistical inference of the Ising model is typically carried out via a pseudo-likelihood, as the standard likelihood approach suffers from a high computational cost when there are many variables (i.e., items). Unfortunately, the presence of missing values can hinder the use of pseudo-likelihood, and a listwise deletion approach for missing data treatment may introduce a substantial bias into the estimation and sometimes yield misleading interpretations. This paper proposes a conditional Bayesian framework for Ising network analysis with missing data, which integrates a pseudo-likelihood approach with iterative data imputation. An asymptotic theory is established for the method. Furthermore, a computationally efficient Pólya-Gamma data augmentation procedure is proposed to streamline the sampling of model parameters. The method’s performance is shown through simulations and a real-world application to data on major depressive and generalized anxiety disorders from the National Epidemiological Survey on Alcohol and Related Conditions (NESARC).

PMID:38971882 | DOI:10.1007/s11336-024-09985-2

Sci Rep. 2024 Jul 6;14(1):15589. doi: 10.1038/s41598-024-66596-8.

ABSTRACT

Federated learning (FL) has emerged as a significant method for developing machine learning models across multiple devices without centralized data collection. Candidemia, a critical but rare disease in ICUs, poses challenges in early detection and treatment. The goal of this study is to develop a privacy-preserving federated learning framework for predicting candidemia in ICU patients. This approach aims to enhance the accuracy of antifungal drug prescriptions and patient outcomes. This study involved the creation of four predictive FL models for candidemia using data from ICU patients across three hospitals in China. The models were designed to prioritize patient privacy while aggregating learnings across different sites. A unique ensemble feature selection strategy was implemented, combining the strengths of XGBoost’s feature importance and statistical test p values. This strategy aimed to optimize the selection of relevant features for accurate predictions. The federated learning models demonstrated significant improvements over locally trained models, with a 9% increase in the area under the curve (AUC) and a 24% rise in true positive ratio (TPR). Notably, the FL models excelled in the combined TPR + TNR metric, which is critical for feature selection in candidemia prediction. The ensemble feature selection method proved more efficient than previous approaches, achieving comparable performance. The study successfully developed a set of federated learning models that significantly enhance the prediction of candidemia in ICU patients. By leveraging a novel feature selection method and maintaining patient privacy, the models provide a robust framework for improved clinical decision-making in the treatment of candidemia.

PMID:38971879 | DOI:10.1038/s41598-024-66596-8

Insights Imaging. 2024 Jul 6;15(1):171. doi: 10.1186/s13244-024-01749-x.

ABSTRACT

OBJECTIVES: To evaluate the effectiveness of cryoablation compared to partial nephrectomy in patients with stage IA papillary and chromophobe renal cell carcinoma (pRCC; chRCC).

MATERIAL AND METHODS: The 2004-2016 National Cancer Database was queried for adult patients with stage IA pRCC or chRCC treated with cryoablation or partial nephrectomy. Patients receiving systemic therapy or radiotherapy, as well as those with bilateral RCC or prior malignant disease were excluded. Overall survival (OS) was assessed using Kaplan-Meier plots and Cox proportional hazard regression models. Nearest neighbor propensity matching (1:1 cryoablation:partial nephrectomy, stratified for pRCC and chRCC) was used to account for potential confounders.

RESULTS: A total of 11122 stage IA renal cell carcinoma patients were included (pRCC 8030; chRCC 3092). Cryoablation was performed in 607 (5.5%) patients, and partial nephrectomy in 10515 (94.5%) patients. A higher likelihood of cryoablation treatment was observed in older patients with non-private healthcare insurance, as well as in those with smaller diameter low-grade pRCC treated at non-academic centers in specific US geographic regions. After propensity score matching to account for confounders, there was no statistically significant difference in OS comparing cryoablation vs partial nephrectomy in patients with pRCC (HR = 1.3, 95% CI: 0.96-1.75, p = 0.09) and those with chRCC (HR = 1.38, 95% CI: 0.67-2.82, p = 0.38).

CONCLUSION: After accounting for confounders, cryoablation, and partial nephrectomy demonstrated comparable OS in patients with stage IA papillary and chromophobe RCC. Cryoablation is a reasonable treatment alternative to partial nephrectomy for these histological RCC subtypes when radiologically suspected or diagnosed after biopsy.

CRITICAL RELEVANCE STATEMENT: Cryoablation might be considered as an upfront treatment alternative to partial nephrectomy in patients with papillary and chromophobe stage IA renal cell carcinoma, as both treatment approaches yield comparable oncological outcomes.

KEY POINTS: The utilization of cryoablation for stage IA papillary and chromophobe RCC increases. In the National Cancer Database, we found specific patterns of use of cryoablation. Cryoablation and partial nephrectomy demonstrate comparable outcomes after accounting for confounders.

PMID:38971873 | DOI:10.1186/s13244-024-01749-x