Category: Nevin Manimala

Int J Gynecol Cancer. 2025 Apr 11;35(6):101821. doi: 10.1016/j.ijgc.2025.101821. Online ahead of print.

ABSTRACT

OBJECTIVE: Ovarian cancer surgery and the complexity of the procedure may be measured with the standardized Aletti score. The main objective of this study was to establish the influence of surgical complexity using the Aletti score on disease-free survival and overall survival.

METHODS: A retrospective observational study was conducted in a reference gynecologic oncology department, including advanced ovarian cancer patients, newly diagnosed who underwent a primary debulking surgery or interval debulking surgery between January 2010 and December 2019 (stage IIB-IV International Federation of Gynecology and Obstetrics classification), and epithelial histology. Incomplete medical records, loss to follow-up patients, and borderline histologies were excluded. Survival analysis and multivariate analysis were performed.

RESULTS: A total of 399 patients were included in the study. Regarding Aletti score complexity, no differences were observed in disease-free survival (median: 25 vs 24 months, p = .5) or overall survival (median: 56 vs 49 months, p = .6). Complete cytoreduction was associated with better disease-free survival (median: complete 26 vs optimal 14 vs sub-optimal 9 months, p < .0001) and overall survival (p < .0001). Furthermore, primary debulking surgery showed statistically better disease-free survival (median: 25 vs 16 months, p < .0001) and overall survival (median: 72 vs 38 months, p < .0001) compared to interval debulking surgery. The multivariable analysis showed that disease-free survival, overall survival, International Federation of Gynecology and Obstetrics classification, CA125 level at diagnosis, cytoreduction classification achieved after surgery, and the Clavien-Dindo complications did not significantly associate with the Aletti score.

CONCLUSIONS: Disease-free survival and overall survival were not influenced by the surgical complexity in patients undergoing cytoreduction after the first diagnosis of advanced ovarian cancer. A higher Aletti score was not associated with a higher rate of complications.

PMID:40319539 | DOI:10.1016/j.ijgc.2025.101821

Braz J Phys Ther. 2025 May 3;29(4):101226. doi: 10.1016/j.bjpt.2025.101226. Online ahead of print.

ABSTRACT

BACKGROUND: Therapeutic exercise (TE) is the only intervention with strong recommendation for fibromyalgia. However, there is controversy as to which type of exercise is the most beneficial.

OBJECTIVE: To determine which TE approach is the most effective in reducing pain intensity in women with fibromyalgia.

METHODS: A systematic review was performed with a network meta-analysis (NMA). Six databases were searched from inception until January 2024. Randomized controlled trials (RCTs) evaluating the effects of TE on pain intensity were included in women with fibromyalgia. Methodological quality was assessed using the Physiotherapy Evidence Database scale. The size of the effect and the clinically important difference were determined in the short-term (≤3 months) and long-term (>3 months).

RESULTS: Sixty-one studies were identified, of which 51 were included in the quantitative synthesis (n = 2873). Fifteen TE interventions and eight comparison interventions (comparators) were identified. Aquatic exercise (p-score: 0.8713) was found to provide best benefits in the short-term and resistance training in the long-term (p-score: 0.9749). Statistically significant differences were found in favor of aquatic exercise, Pilates, qigong, resistance training, virtual reality, mixed exercise, and aerobic exercise (in the short-term) and in favor of resistance training, dance, functional training, aquatic exercise, virtual reality, and aerobic exercise (in the long-term) compared to usual care.

CONCLUSION: With a moderate level of evidence, our NMA shows that, in the short-term, aquatic exercise is the most effective TE intervention to reduce pain intensity in women with fibromyalgia, while resistance training is the most effective in the long-term. More RCTs are needed to strengthen these findings.

PMID:40319533 | DOI:10.1016/j.bjpt.2025.101226

J Forensic Leg Med. 2025 Apr 15;113:102856. doi: 10.1016/j.jflm.2025.102856. Online ahead of print.

ABSTRACT

BACKGROUND: The International Classification of Diseases (ICD-11), developed by the WHO, is widely used to code and classify causes of death. While it is a suitable system for clinical data, it is not tailored for forensic diagnoses. This article explores the basic principles and methods for classification of cause of death in a forensic setting. An in-house Dutch coding system, the FDC system, was developed in the Netherlands.

PURPOSE: To determine the validity and applicability of the FDC system.

METHODS: The FDC system was used to code 138 deaths based on the forensic autopsy reports of the Netherlands Forensic Institute. This was performed by three investigators (one forensic pathologist and two forensic physicians, all of whom are forensic experts) to compute the inter-investigator agreement using Krippendorff’s alpha (kalpha) statistics. To measure the intra-investigator agreement, 46 cases per investigator (for each investigator different cases) were presented twice in random order. The coding system has five parameters: Main category, Subcategory, Other contributing factor category, Mode of death category, and Certainty of death category.

RESULTS: The Krippendorff’s alphas (kalphas) for the inter-investigator agreement were as follows: Main category 0.91, Subcategory 0.74, Mode category 0.49 and Certainty category 0.55. Inter-investigator agreement showed high kalpha scores for both Main category and Subcategory. There was a good intra-investigator agreement. The kalphas were as follows: Main category 0.95, Subcategory 0.87, Mode category 0.65, and Certainty category 0.78.

CONCLUSION: The FDC system is an in-house Dutch system that is useful for coding causes of death from a forensic perspective. This system could make the notation of forensic pathologists and forensic physicians less ambiguous, which could improve the understanding of cases by professionals such as public prosecutors, lawyers and judges who have to make decisions based on autopsy reports. In the future, this system could also be used in forensic medicine by forensic physicians and for (forensic) mortality reporting in public health statistics.

PMID:40319532 | DOI:10.1016/j.jflm.2025.102856

Orv Hetil. 2025 May 4;166(18):710-716. doi: 10.1556/650.2025.33287. Print 2025 May 4.

ABSTRACT

Bevezetés: A gerincfájdalmak, radiculopathiák hátterében gyakran degeneratív eltérések állnak, melyek gyakori javallatai a gerinc-MR-képalkotó vizsgálatoknak. A porckorong-degeneráció, a porckorong kitüremkedés/sérv, a gerinccsatorna-szűkület és a kisízületi arthrosis, valamint a csigolyákat, spinalis teret érintő kórfolyamatok kimutatása MR-vizsgálatot igényelhet. Célkitűzés: Bizonyos állapotok egyértelműen indokolják a gerinc MR-rel végzett leképezését, de vajon minden esetben megalapozott-e az MR-vizsgálat iránti igény? Módszer: Kórházunkban 2023-ban 2105 gerinc-MR-vizsgálat történt, melyeket egyesével értékeltünk a beutalás szempontjai és az eredmények áttanulmányozása alapján. Eredmények: Kórházunkban gerinc-MR-vizsgálatra beutalót különféle területek szakorvosai adtak. Az esetek 87%-ában ezek hátterében nem igazolódott neurológiai indok, és a képalkotók sem mutattak klinikailag releváns, műtéti beavatkozást igénylő eltérést. Mindezek következményeként a sok „felesleges” vizsgálat miatt a várólistánk több hónapra nyúlt, valamint sok esetben a daganatos betegekre vonatkozó „14 napos jogszabály” is sérült. Megbeszélés, következtetés: A beutaló orvosokat arra kell ösztönözni, hogy kövessék a szakma lefektetett szabályait és iránymutatásait, hogy ezáltal is csökkenthetők legyenek a várólisták és az ellátás költségei, továbbá könnyebben biztosítható legyen a valóban sürgős betegek időben történő ellátása. Orv Hetil. 2025; 166(18): 710–716.

PMID:40319466 | DOI:10.1556/650.2025.33287

Lab Med. 2025 May 4:lmaf009. doi: 10.1093/labmed/lmaf009. Online ahead of print.

ABSTRACT

INTRODUCTION: Iron-deficiency anemia (IDA) and non-transfusion-dependent thalassemia (NTDT) are the 2 most common types of microcytic hypochromic anemia, but they are difficult to distinguish by routine tests. It is reported that red blood cells (RBCs) in thalassemia tend to be more microcytic and polymorphic, which may interfere with impedance platelet count (PLT-I). To correct PLT-I, fluorescence platelet count (PLT-F) can be used.

METHODS: To establish a new discriminant formula based on the discrepancy between PLT-I and PLT-F (dPLT), this study retrospectively reviewed 350 patients: 145 with IDA and 205 with NTDT. The RBC and platelet parameters were obtained on a Sysmex XN-9000 system. Univariable and multivariable regression analyses were performed to screen the indicators. Diagnostic efficacy was analyzed using receiver operating characteristic curves.

RESULTS: We found that the interference with PLT-I by RBCs was greater in patients with NTDT. The dPLT of patients with NTDT was statistically significantly higher than that of patients with IDA. Based on erythrocyte indices and dPLT, the diagnosis model, called PRMH (a model incorporating platelet difference, RBC count, mean corpuscular hemoglobin concentration, and hematocrit), was established.

DISCUSSION: When compared with 11 reported formulas, the PRMH model showed better diagnostic efficacy, with a sensitivity of 88% and a specificity of 87%. Hence, the PRMH model can be used to distinguish NTDT from IDA.

PMID:40319461 | DOI:10.1093/labmed/lmaf009

Neurol Ther. 2025 May 4. doi: 10.1007/s40120-025-00756-4. Online ahead of print.

ABSTRACT

INTRODUCTION: With the advent of disease-modifying therapies for early Alzheimer’s disease (AD), a comprehensive characterization of patients initiating lecanemab in the USA is needed to understand its use in real-world settings.

METHODS: This retrospective observational study used administrative claims from the Komodo Research Database (1/1/2023-6/30/2024). Eligible patients had ≥ 1 lecanemab administration (first claim defined the index date) and ≥ 12 months of clinical activity/insurance eligibility before the index date. Patient characteristics, diagnostic process, and AD-related medications were evaluated within 12 months before the index date (baseline), whereas lecanemab treatment patterns and concomitant medications were evaluated on or after the index date (follow-up). Outcomes were reported using descriptive statistics and persistence to lecanemab was evaluated using Kaplan-Meier analysis.

RESULTS: Of 3155 patients included in the study, mean age was 75.0 years, 55.8% were female, 44.2% were male, and most (93.3%) received their index lecanemab administration in an urban setting. Diagnoses of AD (83.8%) and mild cognitive impairment (60.8%) were common at baseline, and 67.6% of patients used AD symptomatic medications. Average time from earliest diagnosis to first lecanemab administration was 4.9 months among patients with a diagnosis in January 2023 (accelerated approval date) or onwards. Over a mean follow-up of 138.8 days, the monthly mean number of administrations of lecanemab was 1.9, with an average of 16.5 days between consecutive administrations and 47.4 days to the first follow-up head magnetic resonance imaging. Persistence to lecanemab was 87.6% at 4 months after treatment initiation.

CONCLUSION: Lecanemab was utilized in appropriate patient populations according to the prescribing information approved by the US Food and Drug Administration. Findings from our study provide first insights into the real-world use of lecanemab in the USA and shed light on the need for increased and timely lecanemab initiation for the long-term management of early AD.

PMID:40319433 | DOI:10.1007/s40120-025-00756-4

Int Urol Nephrol. 2025 May 4. doi: 10.1007/s11255-025-04542-x. Online ahead of print.

ABSTRACT

BACKGROUND: Contrast-induced nephropathy (CIN) is a major risk for patients undergoing coronary angiography (CAG) and percutaneous coronary intervention (PCI).

METHODS: PubMed, MEDLINE, Embase, Google Scholar, and Web of Science were searched through May 2024 to include randomized controlled trials (RCTs) assessing the efficacy and safety of nicorandil administration in patients following CAG or PCI. Outcomes of interest included the CIN incidence, major adverse events, serum creatinine, serum cystatin C, BUN and eGFR. Risk ratios (RRs) and standard mean differences (SMDs) with 95% confidence intervals (CIs) were calculated using random-effects model. Statistical heterogeneity was assessed using I2 statistics.

RESULTS: Twelve studies (n = 2931 patients) were included in the final analysis. Nicorandil significantly reduced the CIN incidence (RR: 0.40 [0.31,0.52]; p < 0.00001), with consistent results for oral (RR: 0.35 [0.25,0.48]; p < 0.00001) and intravenous administration (RR: 0.52 [0.30,0.92]; p = 0.02) (p-interaction = 0.22). Oral nicorandil reduced the risk of major adverse events (RR: 0.71 [0.51,0.99]; p = 0.05). Among patients on nicorandil, serum creatinine levels were significantly lower at 48 h (SMD: -0.30 [-0.52,-0.07]; p = 0.009), and 72 h post-intervention (SMD: -0.42 [-0.71,-0.13]; p = 0.004). Nicorandil significantly reduced serum cystatin C levels at 48 h post-intervention (SMD: -0.56 [-1.01,-0.01]; p = 0.02). However, nicorandil did not significantly affect eGFR values at 24-h (SMD: 0.12 [-0.21,0.45]; p = 0.46), 48-h (SMD: 0.08 [-0.19,0.35]; p = 0.58), and 72-h (SMD: 0.34 [-0.13,0.81]; p = 0.16).

CONCLUSION: Nicorandil administration reduces the CIN incidence and improves renal biomarkers in patients undergoing CAG and PCI. Large-scale trials with longer follow-up periods are warranted to confirm renoprotective effects of nicorandil.

PMID:40319432 | DOI:10.1007/s11255-025-04542-x

Eur Radiol Exp. 2025 May 4;9(1):49. doi: 10.1186/s41747-025-00586-x.

ABSTRACT

BACKGROUND: Gunshot deaths due to homicide or military encounters are a major health concern. Noninvasive bullet characterization is of major importance for patients with lodged bullets or in mass disasters with multiple cadavers, which must be prioritized for autopsy. Therefore, the aim of this study was to investigate whether brass and lead bullets can be differentiated using photon-counting CT (PCCT).

METHODS: Nine different lead (n = 6) or brass (n = 3) bullets were investigated on a state-of-the-art PCCT using a clinically unavailable research mode. Here, four image sets were reconstructed for different energy thresholds (20, 55, 72, 90 keV). Three circular regions of interest were placed on the 20-keV threshold images by two readers and automatically copied to the three other threshold images. Based on measured HU mean and max values, dual-energy indices (DEI) were calculated for the low/high energy threshold pairs of 20/90, 55/90, and 72/90 keV.

RESULTS: Significant differences of DEIs between lead and brass projectiles were observed for the 20/90 keV DEI for HU mean ± standard deviation values (Qr40 kernel, lead: -0.085 ± 0.021, brass: 0.024 ± 0.048) and HU max values (Qr40 kernel, lead: -0.093 ± 0.011, brass: 0.023 ± 0.057) (p < 0.001 for both). Differences decreased for the 55/90 and 72/90 keV DEIs between the two projectile materials but remained statistically significant.

CONCLUSION: In this PCCT phantom study, significant differences were observed between lead and brass bullets in the different energy threshold images.

RELEVANCE STATEMENT: Photon-counting CT could be a promising tool for bullet identification as significant differences were found in the different energy threshold images for lead and brass bullets, with application in clinical and forensic radiology.

KEY POINTS: In emergency settings, noninvasive bullet characterization is of importance for law enforcement. Bullet material characterization can be performed using photon-counting CT. These characteristics can be quantified in the four different energy threshold images.

PMID:40319414 | DOI:10.1186/s41747-025-00586-x

Neurorehabil Neural Repair. 2025 May 4:15459683251331586. doi: 10.1177/15459683251331586. Online ahead of print.

ABSTRACT

BackgroundCognitive rehabilitation and exercise training are promising approaches for improving cognition in persons with progressive multiple sclerosis (MS). Identifying heterogeneity of change and factors that influence the effects of cognitive rehabilitation and/or exercise training on cognitive outcomes at the individual level have direct relevance for developing tailored and optimized rehabilitation interventions for improving cognition in progressive MS.ObjectiveThis study involved a secondary data analysis from the CogEx trial in progressive MS. This study first described heterogeneity of change in cognitive processing speed (CPS) across the intervention conditions and then identified possible adherence/compliance, baseline performance, and demographic/clinical variables as correlates of rehabilitation-related CPS changes.MethodsA total of 311 persons with progressive MS who were pre-screened for impaired CPS completed 12 weeks of combined cognitive rehabilitation (or sham) and exercise training (or sham). CPS was measured before and after the 12-week period. As potential correlates of CPS changes, we measured adherence/compliance (ie, treatment exposure), performance outcomes at baseline, as well as demographic and clinical characteristics at baseline.ResultsThere was heterogeneity of change in CPS across the 4 intervention conditions. We further identified baseline learning and memory impairment and premorbid intelligence quotient (IQ), but not adherence/compliance, other baseline performance outcomes, or demographic/clinical characteristics as significant correlates of CPS changes across the 4 intervention conditions.ConclusionsThe overall pattern of results suggests that future trials in this area might account for impaired learning and memory and/or premorbid IQ as potential covariates, or more carefully consider the role of reserve within rehabilitation interventions in progressive MS.

PMID:40319368 | DOI:10.1177/15459683251331586

J Anim Sci. 2025 May 4:skaf136. doi: 10.1093/jas/skaf136. Online ahead of print.

ABSTRACT

This study addresses the challenge of limited data availability in animal science, particularly in modeling complex biological processes such as methane emissions from ruminants. We propose a novel rank-based method for generating synthetic databases with correlated non-normal multivariate distributions aimed at enhancing the accuracy and reliability of predictive modeling tools. Our rank-based approach involves a four-step process: (1) fitting distributions to variables using normal or best-fit non-normal distributions, (2) generating synthetic databases, (3) preserving relationships among variables using Spearman correlations, and (4) cleaning datasets to ensure biological plausibility. We compare this method with copula-based approaches to maintain a pre-established correlation structure. The rank-based method demonstrated superior performance in preserving original distribution moments (mean, variance, skewness, kurtosis) and correlation structures compared to copula-based methods. We generated two synthetic databases (normal and non-normal distributions) and applied random forest (RF) and multiple linear model (LM) regression analyses. RF regression outperformed LM in predicting methane emissions, showing higher R² values (0.927 vs. 0.622) and lower standard errors. However, cross-testing revealed that RF regressions exhibit high specificity to distribution types, underperforming when applied to data with differing distributions. In contrast, LM regressions showed robustness across different distribution types. Our findings highlight the importance of understanding distributional assumptions in regression techniques when generating synthetic databases. The study also underscores the potential of synthetic data in augmenting limited samples, addressing class imbalances, and simulating rare scenarios. While our method effectively preserves descriptive statistical properties, we acknowledge the possibility of introducing artificial (unknown) relationships within subsets of the synthetic database. This research uncovered a practical solution for creating realistic, statistically sound datasets when original data is scarce or sensitive. Its application in predicting methane emissions demonstrates the potential to enhance modeling accuracy in animal science. Future research directions include integrating this approach with deep learning, exploring real-world applications, and developing adaptive machine-learning models for diverse data distributions.

PMID:40319357 | DOI:10.1093/jas/skaf136