Nevin Manimala

Clin Transplant. 2024 May;38(5):e15333. doi: 10.1111/ctr.15333.

ABSTRACT

BACKGROUND AND AIM: Stress cardiomyopathy in donors can potentially affect graft function and longevity. This study aims to investigate the association between echocardiographic left ventricular ejection fraction (LVEF) < 50%, and/or the presence of left ventricular regional wall motion abnormalities (RWMA) in organ donors, and short- and long-term liver and kidney graft survival. Our secondary aim was to link graft survival with donor and recipient characteristics.

METHODS: All donors considered for liver and kidney donation with echocardiographic records at Sahlgrenska University Hospital between 2006 and 2016 were matched with their recipients through the Scandiatransplant register. The studied outcomes were graft survival, re-transplantation, and recipient death. Kaplan-Meier curves were used to plot time to event. Multivariate Cox-regression was used to test independence.

RESULTS: There were 370 liver donors and 312 kidney donors (matched with 458 recipients) with echocardiographic records at Sahlgrenska University Hospital between June 2006 and November 2016. Of patients with LV dysfunction by echocardiography, there were 102 liver- and 72 kidney donors. Univariate survival analyses showed no statistical difference in the short- and long-term graft survival from donors with LV dysfunction compared to donors without. Donor age > 65 years, recipient re-transplantation and recipient liver tumor were predictors of worse outcome in liver transplants (p < .05). Donor age > 65, donor hypertension, recipient re-transplantation, and a recipient diagnosis of diabetes or nephritis/glomerulonephritis had a negative association with graft survival in kidney transplants (p < .05).

CONCLUSION: We found no significant association between donor LV dysfunction and short- and long-term graft survival in liver and kidney transplants, suggesting that livers and kidneys from such donors can be safely transplanted.

PMID:38739219 | DOI:10.1111/ctr.15333

Ecology. 2024 May 13:e4283. doi: 10.1002/ecy.4283. Online ahead of print.

ABSTRACT

As data and computing power have surged in recent decades, statistical modeling has become an important tool for understanding ecological patterns and processes. Statistical modeling in ecology faces two major challenges. First, ecological data may not conform to traditional methods, and second, professional ecologists often do not receive extensive statistical training. In response to these challenges, the journal Ecology has published many innovative statistical ecology papers that introduced novel modeling methods and provided accessible guides to statistical best practices. In this paper, we reflect on Ecology’s history and its role in the emergence of the subdiscipline of statistical ecology, which we define as the study of ecological systems using mathematical equations, probability, and empirical data. We showcase 36 influential statistical ecology papers that have been published in Ecology over the last century and, in so doing, comment on the evolution of the field. As data and computing power continue to increase, we anticipate continued growth in statistical ecology to tackle complex analyses and an expanding role for Ecology to publish innovative and influential papers, advancing the discipline and guiding practicing ecologists.

PMID:38738264 | DOI:10.1002/ecy.4283

J Thorac Dis. 2024 Apr 30;16(4):2341-2352. doi: 10.21037/jtd-23-1418. Epub 2024 Apr 28.

ABSTRACT

BACKGROUND: Intracardiac echocardiography (ICE) is a novel technology with certain advantages in treatment of atrial fibrillation (AF), yet there is limited research on the use of ICE in radiofrequency ablation for AF treatment in China. The aim of this study was to investigate the total fluoroscopy time and dose, safety, and effectiveness of ICE guided vs. traditional fluoroscopy (non-ICE) guided radiofrequency ablation for AF in China.

METHODS: We conducted a single-center retrospective analysis of patients who underwent ICE or traditional fluoroscopy-guided radiofrequency ablation for AF. The primary endpoint of this study was total fluoroscopy time, and the secondary endpoints included total fluoroscopy dose, acute surgery failure, transseptal puncture time, ablation time, total procedure time, and 6-month surgery success (no AF recurrence or atrial flutter). As an exploratory analysis, outcomes of interest by different types of AF were examined.

RESULTS: A total of 97 patients were included in the analysis. Forty-eight were in the ICE group and 49 were in the non-ICE group with comparable demographic and clinical characteristics at the baseline. None of patients experienced acute surgery failure with no major procedure-related complications occurred. The fluoroscopic time and dose were significantly lower in the ICE group compared to the non-ICE group (0.00 vs. 9.67±4.88 min, P<0.001; 0.00 vs. 77.10±44.28 mGy/cm², P<0.001, respectively). There were no statistically significant differences in transseptal puncture time, ablation time and total procedure time between the two groups. There were two AF recurrences observed during the 6-month follow-up in each group (P>0.99).

CONCLUSIONS: ICE significantly reduced the fluoroscopic time and dose for radiofrequency catheter ablation in AF patients. There were no significant differences in safety or effectiveness outcomes between the ICE and non-ICE groups.

PMID:38738257 | PMC:PMC11087636 | DOI:10.21037/jtd-23-1418

J Thorac Dis. 2024 Apr 30;16(4):2404-2420. doi: 10.21037/jtd-23-1516. Epub 2024 Apr 15.

ABSTRACT

BACKGROUND: Reinfection of coronavirus disease 2019 (COVID-19) has raised concerns about how reliable immunity from infection and vaccination is. With mass testing for the virus halted, understanding the current prevalence of COVID-19 is crucial. This study investigated 1,191 public health workers at the Xiamen Center for Disease Control, focusing on changes in antibody titers and their relationship with individual characteristics.

METHODS: The study began by describing the epidemiological characteristics of the study participants. Multilinear regression (MLR) models were employed to explore the associations between individual attributes and antibody titers. Additionally, group-based trajectory models (GBTMs) were utilized to identify trajectories in antibody titer changes. To predict and simulate future epidemic trends and examine the correlation of antibody decay with epidemics, a high-dimensional transmission dynamics model was constructed.

RESULTS: Analysis of epidemiological characteristics revealed significant differences in vaccination status between infected and non-infected groups (χ²=376.706, P<0.05). However, the distribution of antibody titers among the infected and vaccinated populations was not significantly different. The MLR model identified age as a common factor affecting titers of immunoglobulin G (IgG), immunoglobulin M (IgM), and neutralizing antibody (NAb), while other factors showed varying impacts. History of pulmonary disease and hospitalization influenced IgG titer, and factors such as gender, smoking, family history of pulmonary diseases, and hospitalization impacted NAb titers. Age was the sole determinant of IgM titers in this study. GBTM analysis indicated a “gradual decline type” trajectory for IgG (95.65%), while IgM and NAb titers remained stable over the study period. The high-dimensional transmission dynamics model predicted and simulated peak epidemic periods in Xiamen City, which correlated with IgG decay. Age-group-specific simulations revealed a higher incidence and infection rate among individuals aged 30-39 years during both the second and third peaks, followed by those aged 40-49, 50-59, 18-29, and 70-79 years.

CONCLUSIONS: Our study shows that antibody titer could be influenced by age, previous pulmonary diseases as well as smoking. Furthermore, the decline in IgG titers is consistent with epidemic trends. These findings emphasize the need for further exploration of these factors and the development of optimized self-protection countermeasures against reinfection.

PMID:38738254 | PMC:PMC11087623 | DOI:10.21037/jtd-23-1516

J Thorac Dis. 2024 Apr 30;16(4):2644-2653. doi: 10.21037/jtd-23-1659. Epub 2024 Apr 24.

ABSTRACT

BACKGROUND AND OBJECTIVE: Machine learning (ML) is increasingly being utilized to provide data driven solutions to challenges in medicine. Within the field of cardiac surgery, ML methods have been employed as risk stratification tools to predict a variety of operative outcomes. However, the clinical utility of ML in this domain is unclear. The aim of this review is to provide an overview of ML in cardiac surgery, particularly with regards to its utility in predictive analytics and implications for use in clinical decision support.

METHODS: We performed a narrative review of relevant articles indexed in PubMed since 2000 using the MeSH terms “Machine Learning”, “Supervised Machine Learning”, “Deep Learning”, or “Artificial Intelligence” and “Cardiovascular Surgery” or “Thoracic Surgery”.

KEY CONTENT AND FINDINGS: ML methods have been widely used to generate pre-operative risk profiles, consistently resulting in the accurate prediction of clinical outcomes in cardiac surgery. However, improvement in predictive performance over traditional risk metrics has proven modest and current applications in the clinical setting remain limited.

CONCLUSIONS: Studies utilizing high volume, multidimensional data such as that derived from electronic health record (EHR) data appear to best demonstrate the advantages of ML methods. Models trained on post cardiac surgery intensive care unit data demonstrate excellent predictive performance and may provide greater clinical utility if incorporated as clinical decision support tools. Further development of ML models and their integration into EHR’s may result in dynamic clinical decision support strategies capable of informing clinical care and improving outcomes in cardiac surgery.

PMID:38738250 | PMC:PMC11087616 | DOI:10.21037/jtd-23-1659

J Thorac Dis. 2024 Apr 30;16(4):2472-2481. doi: 10.21037/jtd-24-309. Epub 2024 Apr 26.

ABSTRACT

BACKGROUND: Esophageal malignancies have a high morbidity rate worldwide, and minimally invasive surgery has emerged as the primary approach for treating esophageal cancer. In recent years, there has been increasing discussion about the potential of employing inflatable mediastinoscopic and laparoscopic approaches as an option for esophagectomy. Building on the primary modification of the inflatable mediastinoscopic technique, we introduced a secondary modification to further minimize surgical trauma.

METHODS: We conducted a retrospective analysis of patients who underwent inflatable mediastinoscopy combined with laparoscopic esophagectomy at the Second Affiliated Hospital of Naval Medical University from March 2020 to March 2023. The patients were allocated to the following two groups: the traditional (primary modification) group, and the secondary modification group. Operation times, intraoperative bleeding, and postoperative complications were compared between the groups.

RESULTS: The procedure was successfully performed in all patients, and conversion to open surgery was not required in any case. There were no statistically significant differences in the surgical operation time, intraoperative bleeding, number of dissected lymph nodes, and rate of postoperative anastomotic leakage between the two groups. However, a statistically significant difference was observed in the length of the mobilized esophagus between the two groups. The mobilization of esophagus to the level of diaphragmatic hiatus via the cervical incision was successfully achieved in more patients in the secondary modification group than the primary modification group.

CONCLUSIONS: Inflatable mediastinoscopy combined with single-incision plus one-port laparoscopic esophagectomy is a safe and effective surgical procedure. The use of a 5-mm flexible endoscope, ultra-long five-leaf forceps, and LigaSure Maryland forceps facilitates esophageal mobilization and lymph node dissection through a single cervical incision.

PMID:38738243 | PMC:PMC11087624 | DOI:10.21037/jtd-24-309

Int J Numer Method Biomed Eng. 2024 May 12:e3824. doi: 10.1002/cnm.3824. Online ahead of print.

ABSTRACT

Thyroid nodules are commonly diagnosed with ultrasonography, which includes internal characteristics, varying looks, and hazy boundaries, making it challenging for a clinician to differentiate between malignant and benign forms based only on visual identification. The advancement of AI, particularly DL, provides significant breakthroughs in the domain of medical image identification. Yet, there are certain obstacles to achieving accuracy as well as efficacy in thyroid nodule detection. The thyroid nodules in this study are detected and classified using an inventive hybrid deep learning-assisted multi-classification method. The median blur method is applied in this work to eliminate the salt and pepper noise from the image. Then MPIU-Net-based segmentation is utilized to segment the image. The LGBPNP-based features are retrieved from the segmented image to obtain a single histogram sequence of the LGBP pattern in addition to other features like extraction of multi-texton and LTP-based features. After the feature extraction, the data augmentation process is applied and then the features are fed to the hybrid classification-based nodule classification model that comprises Deep Maxout and CNN, this hybrid classification trains the features and predicts the thyroid nodule. Additionally, the TIRADS score classification is used for the projected malignant thyroid nodule coupled with statistical features collected from the segmented. The DBNAAF with transfer learning model is employed to classify the grading of malignant thyroid nodules, where the weights of the model are learned with transfer learning. The MCC of the Hybrid Model is 0.9445, whereas the DCNN is 0.6858, YOLOV3-DMRF is 0.7229, CNN is 0.7780, DBN is 0.7601, Bi-GRU is 0.7038, Deep Maxout is 0.7528, and RNN is 0.8522, respectively.

PMID:38736034 | DOI:10.1002/cnm.3824

New Phytol. 2024 May 12. doi: 10.1111/nph.19806. Online ahead of print.

ABSTRACT

As temperature rises, net carbon uptake in tropical forests decreases, but the underlying mechanisms are not well understood. High temperatures can limit photosynthesis directly, for example by reducing biochemical capacity, or indirectly through rising vapor pressure deficit (VPD) causing stomatal closure. To explore the independent effects of temperature and VPD on photosynthesis we analyzed photosynthesis data from the upper canopies of two tropical forests in Panama with Generalized Additive Models. Stomatal conductance and photosynthesis consistently decreased with increasing VPD, and statistically accounting for VPD increased the optimum temperature of photosynthesis (T_opt) of trees from a VPD-confounded apparent T_opt of c. 30-31°C to a VPD-independent T_opt of c. 33-36°C, while for lianas no VPD-independent T_opt was reached within the measured temperature range. Trees and lianas exhibited similar temperature and VPD responses in both forests, despite 1500 mm difference in mean annual rainfall. Over ecologically relevant temperature ranges, photosynthesis in tropical forests is largely limited by indirect effects of warming, through changes in VPD, not by direct warming effects of photosynthetic biochemistry. Failing to account for VPD when determining T_opt misattributes the underlying causal mechanism and thereby hinders the advancement of mechanistic understanding of global warming effects on tropical forest carbon dynamics.

PMID:38736030 | DOI:10.1111/nph.19806

Pediatr Radiol. 2024 May 13. doi: 10.1007/s00247-024-05946-0. Online ahead of print.

ABSTRACT

BACKGROUND: Magnetic resonance imaging (MRI) findings associated with athletic pubalgia are well documented in the adult literature.

OBJECTIVE: To describe the spectrum of MRI findings in adolescents with pubic symphyseal injuries/athletic pubalgia.

MATERIALS AND METHODS: This is an institutional review board approved, retrospective study of all patients < 18 years who were referred for MRI, over the last 10 years. Two pediatric musculoskeletal radiologists evaluated the MRI in consensus for the following findings: Chronic Salter-Harris (SH)-I equivalent fracture or asymmetric parasymphyseal ossific fraying, non-retractile muscular tear or retraction, and edema of the aponeurosis and arcuate ligament. Radiographs were also reviewed for Risser stage.

RESULTS: Fifteen patients were identified (100% male, median age 17 years, IQR 16-17.6). Most patients (14/15, 93%) had either asymmetric parasymphyseal ossific fraying (4/15, 27%) or chronic SH-1 equivalent fracture (10/15, 67%) of the pubic symphysis, and all patients (15/15, 100%) had aponeurotic and arcuate ligament edema. Few patients had rectus abdominis muscular retraction (2/15, 13%), non-retractile muscular tear of the rectus abdominis (2/15, 13%), and/or adductor muscle (4/15, 27%). Risser stage was as follows: stages 0 (13%), 3 (7%), 4 (47%), and 5 (33%). The injuries in our limited data set were independent of skeletal maturity with no statistically significant association between any of the MRI findings and Risser stage.

CONCLUSION: The MR imaging spectrum of adolescent athletic pubalgia differs from the described findings in adults due to skeletal immaturity. The cleft sign described in adults manifests in adolescents as asymmetric parasymphyseal ossific fraying and chronic SH-1 equivalent fractures.

PMID:38736018 | DOI:10.1007/s00247-024-05946-0

Geroscience. 2024 May 13. doi: 10.1007/s11357-024-01191-3. Online ahead of print.

ABSTRACT

Stochastic epigenetic mutations (SEMs) have been proposed as novel aging biomarkers to capture heterogeneity in age-related DNA methylation changes. SEMs are defined as outlier methylation patterns at cytosine-guanine dinucleotide sites, categorized as hypermethylated (hyperSEM) or hypomethylated (hypoSEM) relative to a reference. Because SEMs are defined by their outlier status, it is critical to differentiate extreme values due to technical noise or data artifacts from those due to real biology. Using technical replicate data, we found SEM detection is not reliable: across 3 datasets, 24 to 39% of hypoSEM and 46 to 67% of hyperSEM are not shared between replicates. We identified factors influencing SEM reliability-including blood cell type composition, probe beta-value statistics, genomic location, and presence of SNPs. We used these factors in a training dataset to build a machine learning-based filter that removes unreliable SEMs, and found this filter enhances reliability in two independent validation datasets. We assessed associations between SEM loads and aging phenotypes in the Framingham Heart Study and discovered that associations with aging outcomes were in large part driven by hypoSEMs at baseline methylated probes and hyperSEMs at baseline unmethylated probes, which are the same subsets that demonstrate highest technical reliability. These aging associations were preserved after filtering out unreliable SEMs and were enhanced after adjusting for blood cell composition. Finally, we utilized these insights to formulate best practices for SEM detection and introduce a novel R package, SEMdetectR, which uses parallel programming for efficient SEM detection with comprehensive options for detection, filtering, and analysis.

PMID:38736015 | DOI:10.1007/s11357-024-01191-3