Tag: statistics

Eur J Pediatr. 2025 Oct 12;184(11):679. doi: 10.1007/s00431-025-06516-8.

ABSTRACT

Despite vaccination advances, childhood meningitis remains a major global threat, disproportionately affecting low- and middle-income countries (LMICs). This study analyzes its burden trends from 1990 to 2021, with a focus on LMICs. Using data from the Global Burden of Disease Study 2021, we estimated mortality and disability-adjusted life years (DALYs) for children aged 0-14 years across 117 countries and territories grouped by low, low-middle, and middle Sociodemographic Index (SDI). Temporal trends were assessed with estimated annual percentage change (EAPC). We examined correlations between SDI and disease burden and applied decomposition analysis to attribute deaths and DALYs changes to aging, population growth, and epidemiological shifts. Frontier analysis was used to evaluate health system efficiency relative to SDI. Between 1990 and 2021, childhood meningitis deaths decreased in LMICs. Nevertheless, these regions accounted for 98.5% of global deaths in 2021, with low-SDI regions alone responsible for 61.0%. Streptococcus pneumoniae and Neisseria meningitidis were the leading pathogens. The disease burden was strongly inversely correlated with SDI, highlighting the key role of socioeconomic development. Decomposition analysis showed that in low-SDI regions, epidemiological improvements contributed substantially to mortality reduction (+ 513.02%), but were largely offset by population growth (- 417.38%), yielding only a modest net reduction. Frontier analysis revealed major health system inefficiencies in certain low-SDI countries, such as South Sudan and Nigeria.

CONCLUSION: The concentrated burden of childhood meningitis in LMICs calls for context-specific strategies. Health system inefficiencies and rapid population growth threaten to offset intervention gains. Precision public health approaches that combine targeted vaccination, health system strengthening, and socioeconomic development are essential to reduce inequities and achieve global control goals.

WHAT IS KNOWN: • Childhood meningitis remains a leading infectious cause of mortality and long-term disability globally, with the highest burden concentrated in low-income regions. • Significant progress has been made in vaccine development, leading to declines in mortality globally; yet implementation and coverage gaps persist in resource-limited settings.

WHAT IS NEW: • Decomposition analysis quantifies for the first time how rapid population growth in low-SDI regions nearly cancels out the benefits of epidemiological improvements, whereas middle-SDI regions achieved reductions almost solely through epidemiological progress. • Frontier analysis identifies profound health system inefficiencies in specific low-SDI countries (e.g., South Sudan, Nigeria), where observed mortality and DALYs rates are higher than the optimum achievable given their SDI level.

PMID:41076501 | DOI:10.1007/s00431-025-06516-8

Ann Biomed Eng. 2025 Oct 11. doi: 10.1007/s10439-025-03861-5. Online ahead of print.

ABSTRACT

PURPOSE: Emerging technologies to improve transbronchial sampling of lung lesions include mobile C-arm cone-beam CT (CBCT) and robotic assistance. Surgical Process Modeling (SPM) was used to quantify performance in such procedures performed using a conventional bronchoscope with guidance via 2D fluoroscopy and radial probe endobronchial ultrasound (RP-EBUS) (“Conventional Bronchoscopy”) compared to robot-assisted bronchoscopy with CBCT guidance (“CBCT-Guided RAB”).

METHOD: Statistical SPMs were implemented for Conventional Bronchoscopy and CBCT-Guided RAB for simulation and analysis of procedural outcomes, including cycle time, radiation dose, and geometric accuracy. The SPMs were parameterized and validated with respect to clinical observation, published literature, and expert input. 9000 simulation runs were computed for each method, analyzing differences in performance and evaluating the influence of body mass index (BMI), lesion location (upper, middle, or lower lobe), and lesion size.

RESULTS: The SPMs exhibited reasonable agreement with retrospective clinical evaluation of cycle time and dose, and variations in geometric accuracy were consistent with clinical literature. CBCT-Guided RAB resulted in a 14% increase in median cycle time (45.3 min) compared to Conventional Bronchoscopy (39.6 min) and increased median dose to the patient by 3.2 × (41.6 Gy cm² compared to 12.9 Gy cm²). Geometric targeting improved with CBCT-Guided RAB, reducing the rate of geometric miss from 22% under Conventional Bronchoscopy to 2%. 3D visualization of individual runs gave clear depiction of median and outlier performance and a basis for communicating and standardizing complex workflows.

CONCLUSIONS: SPMs yielded quantitative performance comparison in lung lesion biopsy by conventional and robot-assisted bronchoscopy. The approach quantified increases in cycle time and dose for CBCT-Guided RAB, accompanied by substantial gains in geometric accuracy. Such modeling provided valuable insight on the benefits of emerging technologies at early stages of implementation and a means to optimize and standardize clinical workflow.

PMID:41076493 | DOI:10.1007/s10439-025-03861-5

Eur J Orthop Surg Traumatol. 2025 Oct 11;35(1):431. doi: 10.1007/s00590-025-04518-8.

ABSTRACT

OBJECTIVE: This retrospective study aimed to compare the safety and cost-effectiveness of intramedullary fixation versus plate fixation in patients with rib fractures. Each technique was performed at a separate hospital center.

METHODS: We retrospectively reviewed consecutive patients who underwent surgical fixation for rib fractures from February 2021 to January 2024. Eligible patients had fractures meeting surgical criteria and were treated with either intramedullary or plate fixation. Intraoperative parameters, postoperative outcomes, and costs were compared between the two groups.

RESULTS: A total of 89 patients were included, with 45 receiving intramedullary fixation and 44 receiving plate fixation. Baseline characteristics were similar between the groups. Intraoperative and postoperative outcomes-including operative time, hospital stay, drain removal, complications, healing rates, and pain scores-were comparable. Notably, intramedullary fixation was significantly less expensive than plate fixation.

CONCLUSION: Intramedullary fixation offers similar safety and efficacy to plate fixation for rib fractures while providing a clear cost advantage, suggesting potential economic benefits for healthcare systems.

PMID:41076490 | DOI:10.1007/s00590-025-04518-8

Eur J Pediatr. 2025 Oct 11;184(11):677. doi: 10.1007/s00431-025-06511-z.

ABSTRACT

The respiratory management of neonates with hypoxic-ischemic encephalopathy (HIE) undergoing therapeutic hypothermia (TH) is a challenging issue, but remains poorly standardized. The aim of this study was to describe current practice regarding respiratory management, particularly tracheal intubation, in neonates undergoing TH in France and French-speaking Belgium. In this binational cross-sectional study, current practices about respiratory management were collected by an online-based survey sent to all tertiary neonatal intensive care units providing TH in France and French-speaking Belgium. Practices were analyzed to assess their heterogeneity and compared between centers that routinely intubate for TH and those that did not. The survey was completed by 57/68 (84%) centers. Routine intubation during TH was reported by 33 (58%) centers. Motivations behind routine intubation during TH included concerns about pain, discomfort, and neuroprotection. Among the 24 other centers, there was significant heterogeneity in the respiratory care of patients, while practices regarding sedation-analgesia appeared more consensual. The country was the only characteristic independently associated with routine intubation during TH (France vs Belgium: OR = 9.333, 95% CI 1.035-84.202, p = 0.047).

CONCLUSION: Respiratory management of neonates with HIE undergoing TH is highly heterogeneous. Most centers routinely intubate neonates undergoing TH, especially in France. These findings highlight the need for more evidence-based studies and guidelines to optimize respiratory care during TH.

WHAT IS KNOWN: • For neonates with hypoxic-ischemic encephalopathy, evidence to guide respiratory management during therapeutic hypothermia remains scarce. • Yet, ventilation is a crucial aspect of the neuroprotective management of these neonates.

WHAT IS NEW: • This binational survey reveals that most centers routinely intubate neonates undergoing therapeutic hypothermia. • Our findings also suggest significant heterogeneity and may help to design future studies.

PMID:41076488 | DOI:10.1007/s00431-025-06511-z

Environ Monit Assess. 2025 Oct 11;197(11):1198. doi: 10.1007/s10661-025-14644-9.

ABSTRACT

Understanding spatial and temporal patterns of river water quality over a multi-year period is crucial for effective basin management and pollution control. This study applies functional data analysis (FDA) to evaluate monthly water quality index (WQI) data from 16 monitoring stations across the Klang River Basin, Malaysia, covering the period from 2020 to 2023, which spans both pre- and post-pandemic conditions. By treating water quality index (WQI) measurements as smooth functions over time, FDA captures underlying trends and variations that are not readily detected using classical statistical techniques. Functional principal component analysis (FPCA) reveals that the first component accounts for 97% of the total variation, reflecting the dominant pattern in water quality over time, which is characterized by relatively stable upstream conditions and gradual deterioration downstream. The second and third components capture seasonal fluctuations and short-term disturbances, potentially linked to monsoonal cycles and shifts in human activities during the pandemic. Functional clustering based on FPCA scores groups stations according to their temporal behavior, distinguishing upstream areas with stable conditions from downstream areas experiencing greater variability. Spatial interpretation of these clusters offers additional insight into localized pollution sources and environmental stressors. Compared to classical PCA, FDA provides a more detailed, curve-based understanding of time-dependent and location-specific changes in water quality. The result underscore the value of FDA in environmental monitoring, particularly for detecting pre- and post-pandemic shifts, and support its application in guiding adaptive and spatially targeted management strategies for river basins.

PMID:41076480 | DOI:10.1007/s10661-025-14644-9

Eur Radiol. 2025 Oct 11. doi: 10.1007/s00330-025-12050-w. Online ahead of print.

ABSTRACT

OBJECTIVES: Accurate preoperative classification of pulmonary nodules (PNs) is critical for guiding clinical decision-making and preventing overtreatment. This study aims to evaluate the predictive performance of artificial intelligence (AI)-based quantitative computed tomography (CT) feature analysis in differentiating among four pathological types of PNs: atypical adenomatous hyperplasia and adenocarcinoma in situ (AAH + AIS), minimally invasive adenocarcinoma (MIA), invasive adenocarcinoma (IAC), and lung inflammatory nodules (IN).

MATERIALS AND METHODS: A total of 462 pathologically confirmed PNs were analyzed. Radiomic features, including CT attenuation metrics, 3D morphometrics, and texture parameters such as entropy and skewness, were extracted using a deep learning-based AI platform. Logistic regression models were constructed using both single- and multi-variable strategies to evaluate the classification accuracy of these features. Moreover, the inclusion of IN as a separate category significantly enhanced the clinical utility of AI in differentiating benign mimickers from malignant nodules. The combined model, which integrated AI-derived features with traditional CT signs, was used to assess the diagnostic performance of the radiomic features in differentiating the four pathological types of nodules.

RESULTS: The combined model demonstrated superior diagnostic performance, with area under the curve (AUC) values of 0.936 for IAC, 0.884 for AAH + AIS, and 0.865 for IN. Although MIA showed lower classification accuracy (AUC = 0.707), key features such as entropy, solid component ratio, and total volume effectively distinguished invasive from non-invasive lesions.

CONCLUSION: These findings highlight the potential of AI-enhanced radiomics for supporting non-invasive, objective, and individualized diagnosis of PNs.

KEY POINTS: Question Can artificial intelligence (AI)-based quantitative CT analysis reliably differentiate benign inflammatory nodules from the spectrum of lung adenocarcinoma subtypes, a common diagnostic challenge? Findings An integrated model combining AI-driven radiomic features and traditional CT signs demonstrated high accuracy in differentiating invasive adenocarcinoma (AUC = 0.936), pre-invasive lesions (AUC = 0.884), and inflammatory nodules (AUC = 0.865). Clinical relevance AI-enhanced radiomics provides a non-invasive, objective tool to improve preoperative risk stratification of pulmonary nodules, potentially guiding personalized management and reducing unnecessary surgeries for benign inflammatory lesions that mimic malignancy.

PMID:41076471 | DOI:10.1007/s00330-025-12050-w

Eur Radiol. 2025 Oct 11. doi: 10.1007/s00330-025-12048-4. Online ahead of print.

ABSTRACT

OBJECTIVES: Fractional flow reserve (FFR) and instantaneous wave-Free Ratio (iFR) pressure measurements during invasive coronary angiography (ICA) are the gold standard for assessing vessel-specific ischemia. Artificial intelligence has emerged to compute FFR based on coronary computed tomography angiography (CCTA) images (CT-FFR_AI). We assessed a CT-FFR_AI deep learning model for the prediction of vessel-specific ischemia compared to invasive FFR/iFR measurements.

MATERIALS AND METHODS: We retrospectively selected 322 vessels from 275 patients at two centers who underwent CCTA and invasive FFR and/or iFR measurements during ICA within three months. A junior and senior radiologist at each center supervised vessel centerline-building to generate curvilinear reformats that were processed for CT-FFR_AI binary outcomes (≤ 0.80 or > 0.80) prediction. Reliability for CT-FFR_AI outcomes based on radiologists’ supervision was assessed with Cohen’s κ. Diagnostic values of CT-FFR_AI were calculated using invasive FFR ≤ 0.80 (n = 224) and invasive iFR ≤ 0.89 (n = 238) as the gold standard. A multinomial logistic regression model, including all false-positive and false-negative cases, assessed the impact of patient- and CCTA-related factors on diagnostic values of CT-FFR_AI.

RESULTS: Concordance for CT-FFR_AI binary outcomes was substantial (κ = 0.725, p < 0.001). Sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy of CT-FFR_AI in predicting vessel-specific ischemia on a per-vessel analysis, based on senior radiologists’ evaluations, were 85% (58/68) and 91% (78/86), 82% (128/156) and 78% (119/152), 67% (58/86) and 70% (78/111), 93% (128/138) and 94% (119/127), and 83% (186/224) and 83% (197/238), respectively. Coronary calcifications significantly reduced the diagnostic accuracy of CT-FFR_AI (p < 0.001; OR, 1.002; 95% CI 1.001-1.003).

CONCLUSION: CT-FFR_AI demonstrates high diagnostic performance in predicting vessel-specific coronary ischemia compared to invasive FFR and iFR. Coronary calcifications negatively affect specificity, suggesting that further improvements in spatial resolution could enhance accuracy.

KEY POINTS: Question How accurately can a new deep learning model (CT-FFR_AI) assess vessel-specific ischemia from CCTA non-invasively compared to two validated pressure measurements during invasive coronary angiography? Findings CT-FFR_AI achieved high diagnostic accuracy in predicting vessel-specific ischemia, with high sensitivity and negative predictive value, independent of scanner type and radiologists’ experience. Clinical relevance CT-FFR_AI provides a non-invasive alternative to Fractional Flow Reserve and instantaneous wave-Free Ratio measurements during invasive coronary angiography for detecting vessel-specific ischemia, potentially reducing the need for invasive procedures, lowering healthcare costs, and improving patient safety.

PMID:41076470 | DOI:10.1007/s00330-025-12048-4

J Robot Surg. 2025 Oct 11;19(1):681. doi: 10.1007/s11701-025-02884-3.

ABSTRACT

The study design is retrospective study. Robotic spine surgery has evolved rapidly over the past two decades, with growing adoption. However, research on error sources in robotic-assisted pedicle screw placement remains scarce. This study investigates the incidence, risk factors, and intraoperative error types linked to screw malposition. We retrospectively analyzed patients who underwent robotic-assisted thoracic and lumbar spine surgeries at our center since Oct 2023. The incidence of screw breaches, intraoperative errors, and risk factors, such as BMI, pathology, and surgical approach, were assessed. Screw malpositions were identified on postoperative O-arm scans and classified by error cause. Intraoperative revision protocols were documented. A total of 1060 patients (5644 pedicle screws) were included. Screw malposition occurred in 13 patients (1.2%) involving 22 screws (0.39%). The mean BMI of patients with malposition was 27.3 versus 26.5 overall. Among the 13 cases, 8 had lumbar degenerative pathology, 3 scoliosis, 1 high-grade listhesis, and 1 revision for proximal junctional failure. Skiving was the most frequent error (6 cases), followed by arm shift (4), patient movement (2), and registration error (1). Learning curve had a significant role with 12/22 screw malpositioning happening in the initial 50 robotic cases. No significant correlation was found between malposition and pathology type or surgical approach. Robotic systems improve pedicle screw accuracy but are not immune to errors. Skiving is the most common issue and can be minimized by selecting flat bony entry points and avoiding sloping surfaces. Other causes include arm shift, patient movement, and registration errors.

PMID:41076469 | DOI:10.1007/s11701-025-02884-3

Clin Rheumatol. 2025 Oct 11. doi: 10.1007/s10067-025-07722-3. Online ahead of print.

ABSTRACT

AIM: This study aimed to compare talar cartilage thickness in patients with RA and healthy controls and to investigate its association with clinical and demographic variables.

METHOD: Thirty-seven healthy controls and 63 patients with RA diagnosed using the American College of Rheumatology’s (ACR) 2010 criteria were included in this cross-sectional observational study. All participants’ age, gender, and body mass index (BMI) were recorded. The hospital record system’s data was retrieved for the patient group, including medication use, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), seropositivity, and disease duration. VAS was used to assess pain, and DAS-28 was used to assess disease activity. Talar cartilage thickness measurement was performed by the same doctor as the ultrasound. Descriptive statistics of the data obtained from the study were given by mean, standard deviation for numerical variables, and frequency and percentage analysis for categorical variables. Mann-Whitney U test was used for categorical variables with two groups, and Kruskal Wallis test was used for categorical variables with three or more groups in the comparison of parameters according to categorical variables. Analyses were performed with the help of SPSS 22.0 program. p < 0.05 significance level was selected.

RESULTS: There was no discernible difference between the patient and control groups in terms of age, height, weight, gender, or BMI values (p > 0.05). Talar cartilage thickness did not significantly correlate with age, BMI, ESR, CRP, CCP, DAS-28 RF, number of swollen joints, or sensitive joints (p > 0,05). However, talar cartilage thickness, VAS, HAQ values, and disease duration were significantly correlated negatively (p < 0.05).

CONCLUSION: Our study showed that there is a significant decrease in talar cartilage thickness in RA patients, and this decrease is associated with disease duration, pain severity, and functional impairment. Key Points • Talar cartilage thickness was found to be lower in RA patients compared to the control group • Talar cartilage measurements were negatively correlated with disease duration, VAS and HAQ scores • Talar cartilage thickness may be a potential biomarker for assessing early joint damage and monitoring disease progression in RA.

PMID:41076467 | DOI:10.1007/s10067-025-07722-3

J Robot Surg. 2025 Oct 11;19(1):680. doi: 10.1007/s11701-025-02828-x.

ABSTRACT

Robotic-assisted total knee arthroplasty (RA-TKA) aims to improve outcomes and reduce costs, but its effect on in-hospital direct costs remains unclear. This study compares in-hospital direct costs between RA-TKA and conventional TKA (C-TKA). A retrospective review of elective TKAs from 1/2018-5/2023 at a single center was performed. RA-TKA and C-TKA patients were matched by demographics and surgery date. Cost metrics included total, fixed, variable direct costs and indirect costs. Operative times, length of stay (LOS), and in-hospital costs were compared using independent t-tests, Mann-Whitney U, and Chi-square tests. Pearson correlations assessed relationships between costs and clinical metrics. A hierarchical multilinear model was used to control for demographics, operative time, and LOS to isolate the cost of robotic assistance. Of 2590 primary TKAs, 440 used robotic assistance. After matching, 788 patients remained (397 RA-TKA, 391 C-TKA). Preoperative Knee Injury and Osteoarthritis Outcome Score for Joint Replacement (KOOS JR) and Veterans Rand 12 Item Health Survey (VR-12) scores were similar. RA-TKAs had longer operative times (“cut-to-close”: 128 vs. 110 min; “room-in to room-out”: 202 vs. 182 min; p < 0.001) and longer LOS (2.39 vs. 1.56 days; p < 0.001). RA-TKAs had 17.8% higher total direct costs and 18.5% higher variable direct costs (p < 0.001). After adjusting for operative time and LOS, robotic assistance independently increased total direct cost by 4.2% of median C-TKA cost (p < 0.001). Robotics remained an independent predictor of total and variable direct cost (p < 0.001). RA-TKA incurs higher in-hospital direct costs than C-TKA, largely due to increased variable costs. Even after adjusting for operative time and LOS, robotic assistance independently contributes to higher total direct cost.

PMID:41076447 | DOI:10.1007/s11701-025-02828-x