Category: Nevin Manimala

Adv Clin Exp Med. 2026 Jan 5. doi: 10.17219/acem/203217. Online ahead of print.

ABSTRACT

BACKGROUND: Acute cholecystitis (AC) is a common biliary disorder, most often caused by gallstones obstructing the cystic duct and leading to gallbladder inflammation.

OBJECTIVES: This study aimed to compare the therapeutic efficacy and complication rates of laparoscopic cholecystectomy (LC) performed using the Calot’s triangle approach vs traditional LC techniques in the treatment of AC.

MATERIAL AND METHODS: A retrospective analysis was conducted on 120 patients diagnosed with AC, with 60 patients undergoing LC using the Calot’s triangle approach (study group) and 60 patients treated with traditional LC techniques (control group). Surgical parameters, including operation time, intraoperative hemorrhage, postoperative recovery times, and 30-day postoperative complications were recorded. Intraoperative adhesion formation was evaluated through direct visualization and graded based on severity. Postoperative pain was assessed using the visual analogue scale (VAS).

RESULTS: There was no statistically significant difference in the baseline characteristics between the 2 groups, confirming their comparability. The study group (Calot’s triangle approach) demonstrated significantly shorter average operation time, postoperative exhaust time, and diet recovery time compared to the control group. Additionally, patients in the study group had significantly lower intraoperative bleeding, lower VAS pain scores at 24 h and 72 h postoperatively, and a lower overall complication rate compared to the control group (p < 0.05).

CONCLUSIONS: The LC Calot’s triangle approach demonstrated shorter operation times and lower rates of certain complications compared with traditional LC techniques. However, the absence of statistically significant differences in some key outcomes highlights the need for further research to fully evaluate its clinical advantages and long-term benefits.

PMID:41489865 | DOI:10.17219/acem/203217

Adv Clin Exp Med. 2026 Jan 5. doi: 10.17219/acem/203397. Online ahead of print.

ABSTRACT

BACKGROUND: Noninvasive ventilation (NIV) is an important treatment modality in the management of chronic obstructive pulmonary disease (COPD) by reducing respiratory distress, improving gas exchange and reducing exacerbations without the need for intubation and invasive airways.

OBJECTIVES: To synthesize data from randomized controlled trials (RCTs) and perform a meta-analysis to understand the beneficial effects of NIV across different COPD stages.

MATERIAL AND METHODS: A systematic literature review was performed using MEDLINE (PubMed) and Cochrane Register of Controlled Trials (CENTRAL) al databases for RCTs that involved the administration of NIV vs usual treatment (oxygen supplementation, pharmacological agents, nasal cannulation) in patients with stable COPD, acute exacerbations of COPD (AECOPD), and post-exacerbation COPD (PECOPD). Mortality, exacerbation and intubation rates, and arterial blood gases (PaCO2 and PaO2 levels) were assessed in both groups. RevMan software was used to assess the risk of bias and calculate the pooled odds ratio (OR), mean differences (MDs) and subgroup analyses with a random-effects model.

RESULTS: A total of 51 RCTs were included in the meta-analysis with information from 3,775 patients. Meta-analysis of the data showed that there was a significant decrease in mortality outcomes (p < 0.001), intubation frequency (p < 0.001) and PaCO2 levels (p < 0.001) but no significant improvement in exacerbation frequency (p = 0.12) and PaO2 levels (p = 0.69). Subgroup analyses demonstrated no significant difference between COPD stage on mortality outcomes (p = 0.32), PaCO2 level (p = 0.12) and PaO2 level (p = 0.64). There was a significant decrease in intubation rate in AECOPD patients receiving NIV and a statistically nonsignificant difference in exacerbation frequency in stable COPD patients using NIV.

CONCLUSION: The findings of this meta-analysis indicate a substantial overall enhancement in the frequency of exacerbations and intubations, mortality outcomes, and arterial gas levels among patients in various stages of COPD. Consequently, it is imperative to identify patients with COPD that are most likely to benefit from the use of NIV.

PMID:41489863 | DOI:10.17219/acem/203397

Adv Clin Exp Med. 2026 Jan 5. doi: 10.17219/acem/203504. Online ahead of print.

ABSTRACT

BACKGROUND: Hyperlipidemia is a major risk factor for cardiovascular diseases and is associated with complications such as atherosclerosis and tendon injury. Though atorvastatin reduces cholesterol, genetic variants (CYP2D6-4, SULT1A1, CYP2C192) affect its response. These genetic variations influence atorvastatin metabolism, thereby affecting its therapeutic effectiveness.

OBJECTIVES: To advance personalized therapeutic drug monitoring and improve lipid profile management, this study aims to develop a robust and LC-MS/MS method for quantifying atorvastatin levels in human plasma. Additionally, to investigate the influence of genetic polymorphisms – particularly CYP2D6-4-on plasma concentrations of atorvastatin in patients with hyperlipidemia.

MATERIAL AND METHODS: Ethical approval for the study was obtained from the appropriate institutional review boards, and written informed consent was obtained from all participants. Atorvastatin was measured using LC-MS/MS. PCR-based methods were used for genotyping. Statistical analyses were performed to evaluate relationships between plasma atorvastatin levels and genetic variants.

RESULTS: The LC-MS/MS method demonstrated excellent linearity, accuracy, precision, and stability, for the quantification of atorvastatin in human plasma. Higher atorvastatin concentrations were tied to CYP2D6-4. Furthermore, the study validated the analytical method for consistent and reliable measurement of atorvastatin levels in clinical samples.

CONCLUSIONS: This study successfully developed and validated a straightforward and reliable LC-MS/MS method for quantifying atorvastatin levels in human plasma. Significant CYP2D64 – atorvastatin links highlight the value of pharmacogenetic dosing. Integrating pharmacogenetics – especially in the Jordanian population – may enhance the safety, efficacy, and individualization of atorvastatin therapy.

PMID:41489862 | DOI:10.17219/acem/203504

AIDS Behav. 2026 Jan 5. doi: 10.1007/s10461-025-04941-2. Online ahead of print.

ABSTRACT

While urban refugee youth face HIV vulnerabilities spanning socio-ecological levels, knowledge gaps persist in HIV prevention outcomes. We conducted a baseline analysis of a cohort enrolled in Tushirikiane-4-Uthabiti, an intervention focused on HIV testing practices among urban refugee youth aged 16-24 in Kampala, Uganda (N = 330). Using regression models, we examined the societal, community, and interpersonal factors associated with condom use self-efficacy [CUSE], consistent condom use, HIV self-testing [HIVST] kit access, and recent HIV testing. Most participants were women (53.3%), with a mean age of 21.3 years (SD = 2.9). One-fifth reported consistent condom use (19.1%), over half accessed HIVST kits (56.4%), and recent HIV testing (50.6%). Statistically significant results showed that higher education (β = 0.18, p < 0.001) and financial resilience (β = 0.18, p < 0.001) were positively associated with CUSE, whereas food insecurity (β = – 0.21, p < 0.05) was negatively associated with CUSE. Being in a casual relationship (adjusted odds ratio [aOR] 3.33, p < 0.05) and CUSE (aOR 1.12, p < 0.010) were associated with increased odds of consistent condom use. Higher education (aOR 2.45, p < 0.001), adolescent sexual and reproductive health stigma (aOR 1.16, p < 0.010), and perceived HIV stigma (aOR 1.05, p < 0.05) were associated with increased odds of recent HIVST kit access. Financial resilience (aOR 1.05, p < 0.010) and young parenthood (aOR = 2.32, p < 0.010) were associated with increased odds of recent last year HIV testing. The findings demonstrate suboptimal HIV prevention outcomes and highlight the need for tailored multilevel interventions to improve the sexual health of urban refugee youth.

PMID:41489850 | DOI:10.1007/s10461-025-04941-2

Eur Radiol. 2026 Jan 5. doi: 10.1007/s00330-025-12255-z. Online ahead of print.

ABSTRACT

OBJECTIVES: To assess healthcare costs of patients screened for cervical spine (C-spine) fractures using CT, and estimate the change in in-hospital costs if an artificial intelligence (AI) algorithm for C-spine fracture detection would assist the radiologist as concurrent reader.

MATERIALS AND METHODS: This retrospective, early health technology assessment included 2321 consecutive patients (2007-2014; median age 49 years; 61% male) screened for C-spine fractures using CT, of whom 219 patients with fractures. Healthcare costs were calculated per diagnostic category (true positive, true negative, false positive and false negative) based on the diagnosis made by the attending radiologists, and by AI analysis, compared to the reference standard. The potential diagnostic accuracy measures with 95% confidence intervals (CI) for diagnoses made by radiologists assisted by AI and the potential average cost per diagnostic category in this scenario were estimated.

RESULTS: Radiologists identified 193/219 fractures and 2085/2102 scans without fractures. AI identified 23 fractures and 16 scans without fractures that had been misclassified by the radiologists. This resulted in a potential sensitivity of 216/219 (98.6%, 95% CI: 95.7-99.6, 10.5% increase compared to radiologists) and specificity of 2101/2102 (100.0%, 95% CI: 99.7-100, 0.8% increase compared to radiologists) for the AI-assisted scenario. The total cost for the AI-assisted scenario was €60,862 (0.3%) higher than for radiologists alone.

CONCLUSION: In this scenario analysis, the addition of AI as concurrent reader to radiologists was estimated to potentially increase sensitivity by 10.5% and specificity by 0.8% together with a 0.3% increase in in-hospital costs due to more detected fractures.

KEY POINTS: Question The impact of artificial intelligence to detect cervical spine fractures on CT on in-hospital healthcare resource use and costs is unknown. Findings Assistance by AI could potentially improve radiologists’ sensitivity and specificity by 10.5% and 0.8%, respectively, for an additional healthcare cost increase of just 0.3%. Clinical relevance Using artificial intelligence as concurrent reader to radiologists to detect cervical spine fractures on CT could potentially increase diagnostic accuracy to nearly 100% with a minimal increase in in-hospital healthcare resource costs.

PMID:41489842 | DOI:10.1007/s00330-025-12255-z

Eur Spine J. 2026 Jan 5. doi: 10.1007/s00586-025-09608-z. Online ahead of print.

ABSTRACT

PURPOSE: This study aimed to incorporate cartoon visuals into nursing instructions for degenerative disc herniation surgery and test whether cartoon visuals in preoperative nursing instructions can help improve patients ‘ knowledge, satisfaction, and anxiety during hospitalization.

METHODOLOGY: The experimental study was conducted from January to June 2024 and involved 84 patients undergoing surgery for degenerative disc herniation. Participants were randomly assigned by computer into two groups, and preoperative and postoperative tests were conducted to understand the patients’ anxiety, self-care knowledge, and satisfaction: the “traditional group” received standard paper-based nursing instructions, while the “experimental group” received cartoon visual nursing instructions.

RESULTS: The study results were statistically significant differences in self-care knowledge (P = .02) and satisfaction (p < .001) among the experimental and traditional groups. There were no statistical differences in situational and trait anxiety, but the experimental group scores decreased. Another unexpected finding was a statistically significant difference (P = .02) in the experimental group, where the number of days of hospital stay was lower than that in the traditional group.

CONCLUSION: This study showed patients could improve their self-knowledge, reduce situational anxiety, increase satisfaction through cartoon visuals, and reduce the number of hospitalized days. Therefore, the engaging content of cartoon visuals can relieve patients’ nervousness about surgery, increase their trust and cooperation, and further improve the effect of doctor-patient communication.

PMID:41489831 | DOI:10.1007/s00586-025-09608-z

J Am Soc Mass Spectrom. 2026 Jan 5. doi: 10.1021/jasms.5c00304. Online ahead of print.

ABSTRACT

In recent publications, we have demonstrated applications of multiplexed affinity selection electrospray mass spectrometry based on three different principles: size-exclusion chromatography, flow-induced dispersion analysis, and Taylor/non-Taylor dispersion. To enable this multiplexing─i.e., simultaneous measurement of pools of ligands, with their masses acting as selective labels─higher resolving power was required than is typically achievable in native MS; therefore, we worked under conditions that promoted gas-phase ejection of protein-bound ligands, allowing their detection with high mass accuracy in the low-m/z region of the spectrum. Subsequent data analysis required correlation of the extracted ion chromatograms (EICs) of candidate ligands with the EIC of the target protein. Even when relying on simple visual inspection, generating these EICs manually is laborious even for only a few dozen ligand candidates, and a quantitative correlation based on statistical tests quickly becomes very time-consuming. Performing such an experiment for a larger compound library or even without a defined target list, but by instead extracting the chromatogram for every low-m/z signal present, is entirely impractical. Here, we present CATALYST (Computer-Assisted Time Alignment for Ligand Yield and Screening Tool), an open-source software package that can perform this type of analysis─in either targeted or untargeted mode─in a matter of seconds. CATALYST performs several statistical tests to correlate EICs and identify protein-binding ligands and then visualizes the results, greatly accelerating affinity selection mass spectrometry workflows.

PMID:41489822 | DOI:10.1021/jasms.5c00304

Saudi Dent J. 2026 Jan 5;38(1):2. doi: 10.1007/s44445-025-00109-9.

ABSTRACT

Artificial intelligence (AI)-driven genetic analysis is crucial for the advancement of personalized dental treatments. Despite progress in genetic research, its clinical application remains limited. This case-control study utilized an association-rule mining algorithm (Apriori) implemented using Python software (version 0.22.0, 2024) to predict dental impaction based on MSX1, PAX9, and AXIN2 polymorphisms. The study was carried out at two centers in Saudi Arabia in October 2023 and involved 106 participants (42 males, 64 females; mean ± standard deviation age = 20.56 ± 8.07 years). Participants were categorized into 52 controls and 54 individuals with hypodontia, among whom 13 had impacted teeth. Saliva samples were analyzed for three single nucleotide polymorphisms: AXIN2 (rs2240308), PAX9 (rs61754301), and MSX1 (rs12532). Although multinomial logistic regression analysis indicated genotypic variations, no statistically significant associations with dental impaction were identified (P = 0.112). However, association-rule mining identified notable genotype patterns with the MSX1 A/A genotype (support = 0.224, confidence = 0.827, lift = 1.475). The combination of PAX9 (C/C) and MSX1 (A/A) had the highest predictive value (lift = 1.671), followed by MSX1 (A/A) with AXIN2 (G/G) (lift = 1.646), and PAX9 (C/C) with AXIN2 (G/G) (lift = 1.475). Based on available scholarly literature, this is among the pioneering studies to use association-rule algorithms to predict dental impaction, highlighting the potential of AI in genetics-based orthodontic diagnostics.

PMID:41489795 | DOI:10.1007/s44445-025-00109-9

Environ Manage. 2026 Jan 5;76(2):56. doi: 10.1007/s00267-025-02352-6.

ABSTRACT

The willingness and behavior of residents to engage in environmental governance and protection are the most direct drivers of environmental improvement, and constitute a vital foundation for achieving ecologically livable conditions and the reform of ecological civilization systems. Based on survey data from 769 respondents collected in Chongqing, this study aims to explore the relationship among social capital, environmental awareness, government satisfaction, and residents’ participation in environmental governance, in order to reveal the key factors that promote eco-friendly behaviors. This paper uses SPSS25.0 to conduct descriptive statistics, one-factor analysis of variance, correlation analysis, multiple regression analysis, mediation effect tests and other statistical methods. The results demonstrate that social capital exerts a significant positive impact on residents’ participation in environmental governance. Moreover, social capital is significantly positively correlated with key factors such as environmental awareness and government satisfaction. In particular, participation willingness has a significant positive effect on participation behavior, highlighting the importance of motivating individual willingness to participate. Further analysis reveals that environmental awareness plays a partial mediating role between social capital and participation willingness, whereas the mediating effect of government satisfaction is not significant, indicating that enhancing environmental awareness is one of the key pathways to promote participation behavior. The findings of this study are significant for formulating and implementing more effective environmental protection policies and measures, emphasizing the strategy of promoting residents’ participation in environmental governance by enhancing social capital and raising public environmental awareness.

PMID:41489790 | DOI:10.1007/s00267-025-02352-6

Int J Biometeorol. 2026 Jan 5;70(1):13. doi: 10.1007/s00484-025-03092-2.

ABSTRACT

Studies worldwide have reported an increase in suicide during hot weather. In summer, high temperature and intense sunlight often coincide, with the latter being a prerequisite for the former formation. However, little is known about whether and to what extent high temperature mediates the effect of sunlight on suicide. We obtained daily suicide death data in Anhui Province of China for the period from January 1, 2017 to December 31, 2020. Both daily sunshine hours and daily solar radiation were employed to measure the sunlight exposure. The space-time-stratified case-crossover analysis was used to estimate the association between sunlight exposure and suicide deaths in high- and non-high-temperature weather during the warm season (May through September). A linear regression was then utilized to estimate the extent to which the association was mediated through temperature. Sunlight during the warm season demonstrated a protective effect on suicide in non-high-temperature weather but a hazardous effect in high-temperature weather. Further mediation analysis in high-temperature weather showed that the direct effect of sunlight on suicide deaths was more pronounced than the effect mediated through temperature. The proportion mediated through temperature in the association between sunshine hours and suicide deaths ranged from 11.27% to 18.37%, while the range for solar radiation and suicide deaths was lower (0.50% to 0.89%). Sunlight not only affects suicide risk but also has an indirect effect that is partially mediated through high temperature. Our findings need to be proven in distinct regions, aiming to better understand the role of sunlight and high temperature in triggering suicide.

PMID:41489789 | DOI:10.1007/s00484-025-03092-2