bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantification of cooling effects on basic tissue measurements and exposed cross-sectional brain area of cadaver heads from Holstein cows &gt; 30 mo of age
Authors: Anderson Karly N , Hamilton Emma M , Kirk Ashlynn A , Reyes Arquimides A , Woiwode Ruth , Zhitnitskiy Perle E , Vogel Kurt D 
Published: March 2024

AbstractPenetrating captive bolt (PCB) is the primary method of preslaughter stunning for cattle and is also used for on-farm euthanasia. The objective of this study was to quantify the impact of cooling on the soft tissue thickness, cranial thickness, total tissue thickness, and cross-sectional brain area of cadaver heads collected from mature (&gt; 30 mo of age) dairy cows following the application of a PCB stun in a frontal placement. Hide-on cadaver heads were obtained from culled dairy cows (N = 37) stunned in a frontal location using a handheld PCB device (Jarvis Model PAS—Type C 0.25R Caliber Captive Bolt, Long Bolt) at a commercial slaughter establishment. Following transport to the University of Wisconsin—River Falls, heads were split at midline along the bolt path by a bandsaw and then underwent FRESH, CHILL24, CHILL48, and CHILL72 refrigeration treatments. The FRESH treatment involved images collected immediately after splitting each head, the CHILL24 treatment involved images collected after 24 h of refrigeration, the CHIL48 treatment involved images collected after 48 h of refrigeration, and the CHILL72 treatment involved images collected after 72 h of refrigeration. Measurements of soft tissue thickness, cranial thickness, total tissue thickness, and cross-sectional brain area were recorded for each refrigeration treatment. Soft tissue thickness did not differ caudal to (P = 0.3751) or rostral to (P = 0.2555) the bolt path. Cranial thickness did not differ caudal to (P = 0.9281) or rostral to (P = 0.9051) the bolt path. Total tissue thickness did not differ caudal to (P = 0.9225; FRESH: 24.77 mm, CHILL24: 23.93 mm, CHILL48: 24.27 mm, CHILL72: 42.30, SE: 0.86) or rostral to (P = 0.8931; FRESH: 24.09 mm, CHILL24: 23.99, CHILL48: 24.26, CHILL72: 24.43 mm, SE: 0.79 mm) the bolt path. Cross-sectional brain area was not different (P = 0.0971) between refrigeration treatments (FRESH: 9,829.65 ± 163.87 mm2, CHILL24: 10,012.00 ± 163.87 mm2, CHILL48: 9,672.43 ± 163.87 mm2, CHILL72: 10,235.00 ± 166.34 mm2). This study demonstrated that FRESH tissue parameters can be determined from cattle cadaver heads refrigerated for 24, 48, or 72 h.
Exosomes in tumor‐stroma crosstalk: Shaping the immune microenvironment in colorectal cancer
Authors: Zhang Yawei , Huo Mingyu , Li Wenchao , Zhang Hongyu , Liu Qi , Jiang Jianwu , Fu Yang , Huang Changjun 
Published: March 2024

AbstractColorectal cancer (CRC) is a multifaceted disease characterized by a complex interaction between tumor cells and the surrounding microenvironment. Within this intricate landscape, exosomes have emerged as pivotal players in the tumor‐stroma crosstalk, influencing the immune microenvironment of CRC. These nano‐sized vesicles, secreted by both tumoral and stromal cells, serve as molecular transporters, delivering a heterogeneous mix of biomolecules such as RNAs, proteins, and lipids. In the CRC context, exosomes exert dual roles: they promote tumor growth, metastasis, and immune escape by altering immune cell functions and activating oncogenic signaling pathways and offer potential as biomarkers for early CRC detection and treatment targets. This review delves into the multifunctional roles of exosomes in the CRC immune microenvironment, highlighting their potential implications for future therapeutic strategies and clinical outcomes.
Modified Tap-drilling Technique for Mid-cervical Pedicle Screw Placement
Authors: Sucu Hasan Kâmil , Sevin İsmail Ertan , Gürkan Gökhan 
Published: March 2024

Study Design:
Retrospective cohort study.

Objection:
To report our modified tap-drilling technique for mid-cervical pedicle screw placement and to evaluate its safety and accuracy.

Summary of Background Data:
Cervical pedicle screw fixation, which provides a strong stabilization, has been a major concern due to the potential risks to neurovascular structures despite its increasing use. Several insertion techniques have been described so far to improve the cervical pedicle screw placement accuracy.

Methods:
This study retrospectively reviewed patients who underwent mid-cervical (C3–C6) pedicle screw fixation between September 2005 and September 2020. Laminectomy, laminoforaminotomy, or notch-referred anatomic landmark methods were used to adjust the entry point and the direction of the screws. After the cortical bone was removed at the entry point with a diamond burr, the cancellous bone was slowly drilled with a hand drill starting from 8 to 10 millimeters in length. Then, all of the bone walls were checked with a ball-tip probe to determine if there was any breach. The procedure was repeated several times. After completing the drilling, the screw was inserted without tapping. The breach rate of pedicle screws was analyzed on postoperative computed tomography scans.

Results:
A total of 473 mid-cervical pedicle screws were placed in 122 consecutive patients. No navigation or computer-assisted system was used, and the first 2 authors inserted all of the screws. All patients completed the surgery, and no evident intraoperative complications occurred. Postoperative CT scans were obtained for 405 screws. Although deviation was observed for 131 pedicle screws, a critical deviation was observed for only 25 pedicle screws.

Conclusions:
Cervical pedicle screw insertion is a risky but applicable technique. Checking all of the bone walls with a ball-tip probe before gradually advancing the hand drill in small amounts, as presented in this article, may lead to the safe and effective placement of cervical pedicle screws.
Risk Factors for Readmission Following Surgical Decompression for Spinal Epidural Abscesses
Authors: Ng Mitchell K. , Rodriguez Ariel , Lam Aaron , Emara Ahmed , Wellington Ian J. , Ahn Nicholas U. , Khalsa Amrit S. , Houten John K. , Saleh Ahmed , Razi Afshin E. 
Published: March 2024

Study Design:
Retrospective cohort study.

Objectives:
The study aimed to (1) compare baseline demographics of patients undergoing surgery for SEA who were/were not readmitted; (2) identify risk factors for 90-day readmissions; and (3) quantify 90-day episode-of-care health care costs.

Background:
Spinal epidural abscess (SEA), while rare, occurring ~2.5–5.1/10,000 admissions, may lead to permanent neurologic deficits and mortality. Definitive treatment often involves surgical intervention via decompression.

Methods:
A search of the PearlDiver database from 2010 to 2021 for patients undergoing decompression for SEA identified 4595 patients. Cohorts were identified through the International Classification of Disease, Ninth Revision (ICD-9), ICD-10, and Current Procedural Terminology codes. Baseline demographics of patients who were/were not readmitted within 90 days following decompression were aggregated/compared, identifying factors associated with readmission. Using Bonferroni correction, a P-value<0.001 was considered statistically significant.

Results:
Readmission within 90 days of surgical decompression occurred in 36.1% (1659/4595) of patients. While age/gender were not associated with readmission rate, alcohol use disorder, arrhythmia, chronic kidney disease, ischemic heart disease, and obesity were associated with readmission. Readmission risk factors included fluid/electrolyte abnormalities, obesity, paralysis, tobacco use, and pathologic weight loss (P<0.0001). Mean same-day total costs ($17,920 vs. $8204, P<0.001) and mean 90-day costs ($46,050 vs. $15,200, P<0.001) were significantly higher in the readmission group.

Conclusion:
A substantial proportion of patients (36.1%) are readmitted within 90 days following surgical decompression for SEA. The top 5 risk factors in descending order are fluid/electrolyte abnormalities, pathologic weight loss, tobacco use, pre-existing paralysis, and obesity. This study highlights areas for perioperative medical optimization that may reduce health care utilization.
AM-PAC Mobility Score <13 Predicts Development of Ileus Following Adult Spinal Deformity Surgery
Authors: Olson Jarod , Mo Kevin C. , Schmerler Jessica , Harris Andrew B. , Lee Jonathan S. , Skolasky Richard L. , Kebaish Khaled M. , Neuman Brian J. 
Published: March 2024

Study Design:
Retrospective review.

Objective:
To determine whether the Activity Measure for Post-Acute Care (AM-PAC) “6-Clicks” score is associated with the development of postoperative ileus.

Summary of Background Data:
Adult spinal deformity (ASD) surgery has a high complication rate. One common complication is postoperative ileus, and poor postoperative mobility has been implicated as a modifiable risk factor for this condition.

Methods:
Eighty-five ASD surgeries in which ≥5 levels were fused were identified in a single institution database. A physical therapist/physiatrist collected patients’ daily postoperative AM-PAC scores, for which we assessed first, last, and daily changes. We used multivariable linear regression to determine the marginal effect of ileus on continuous AM-PAC scores; threshold linear regression with Bayesian information criterion to identify a threshold AM-PAC score associated with ileus; and multivariable logistic regression to determine the utility of the score thresholds when controlling for confounding variables.

Results:
Ten of 85 patients (12%) developed ileus. The mean day of developing ileus was postoperative day 3.3±2.35. The mean first and last AM-PAC scores were 16 and 18, respectively. On bivariate analysis, the mean first AM-PAC score was lower in patients with ileus than in those without (13 vs. 16; P<0.01). Ileus was associated with a first AM-PAC score of 3 points lower (Coef. −2.96; P<0.01) than that of patients without ileus. Patients with an AM-PAC score<13 had 8 times greater odds of developing ileus (P=0.023). Neither the last AM-PAC score nor the daily change in AM-PAC score was associated with ileus.

Conclusions:
In our institutional cohort, a first AM-PAC score of <13, corresponding to an inability to walk or stand for more than 1 minute, was associated with the development of ileus. Early identification of patients who cannot walk or stand after surgery can help determine which patients would benefit from prophylactic management.

Level of Evidence:
Level—III.
Perennial Disaster Patterns in Central Europe since 2000: Implications for Hospital Preparedness Planning – A cross sectional Analysis
Authors: von der Forst M , Dietrich M , Schmitt FCF , Popp E , Ries M 
Published: March 2024

AbstractIntroductionHospitals are vital components of a country’s critical infrastructure, essential for maintaining resilient public services. Emergency planning for hospitals is crucial to ensure their functionality under special circumstances. The impact of climate change and seasonal variations in the utilization of hospital services further complicate emergency planning. Therefore, the knowledge of perennial disaster patterns could help strengthening the resilience of health care facilities.MethodsWe conducted a cross-sectional analysis of the Emergency Events Database EM-DAT for disasters in Central Europe between January 2000 and December 2023 (defined as Germany and bordering countries). Primary endpoint was the average month of occurrence of disasters across the overall study period.ResultsOut of 474 events, 83% were associated with a natural cause and only 80 events (=17%) were technological. More than 50 % of the technological disasters were categorized in the transport accident subgroup. Technological disasters were spread equally over the whole year. The vast majority of natural disasters (N=394) were due to storm (n=178, 45%), flood (n=101, 26%) and extreme temperatures (n=93, 24%) with peaks occurring during summer and winter months, while less disasters were registered during autumn and especially spring seasons.DiscussionLooking at the three most common disaster types, extreme temperatures, floods, and storms are clearly dominating and cause over 90% of the natural disasters in central Europe. An overlap of hospital admissions due to seasonal effects and catastrophic events, mainly triggered by natural disasters in the vulnerable periods may lead to a partial collapse of the health care system. To deal with such a variety of different and potentially simultaneous hazards using an “all hazards” approach could be promising and often has been seen as the most effective strategy for hospital emergency planning.
Predicting Postoperative Delirium in Older Patients: a multicenter retrospective cohort study
Authors: Wu Shun-Chin Jim , Sharma Nitin , Bauch Anne , Yang Hao-Chun , Hect Jasmine L. , Thomas Christine , Wagner Sören , Förstner Bernd R. , von Arnim Christine A.F. , Kaufmann Tobias , Eschweiler Gerhard W. , Wolfers Thomas ,   the PAWEL Study Group
Published: March 2024

AbstractBackgroundThe number of elective surgeries for older individuals is on the rise globally. Machine learning may improve risk assessment with an impact on surgical planning and postoperative care. Preoperative cognitive assessment may facilitate early identification of postoperative delirium (POD). This study aims to estimate the predictive ability of machine learning models for POD using pre-and/or perioperative features, with a specific focus on adding neuropsychological assessments prior to surgery.Materials and MethodsThis retrospective cohort study analyzed data from the multicenter PAWEL study and its PAWEL-R substudy, encompassing older patients (≥70 years) undergoing elective surgeries across five medical centers from July 2017 to April 2019. A total of 1624 patients were included, with POD diagnosis made before discharge. Data included demographics, clinical, surgical, and neuropsychological features collected pre- and perioperatively. Machine learning model performance was evaluated using the area under the receiver operating characteristic curve (AUC), with permutation testing for significance and SHapley Additive exPlanations (SHAP) to identify effective neuropsychological assessments.ResultsIn this cohort of 1624 patients, 52.3% (N=850) were male, with a mean [SD] age of 77.9 [4.9] years. Predicting POD before surgery using demographic, clinical, surgical, and neuropsychological features achieved an AUC of 0.79. Incorporating all pre- and perioperative features into the model yielded a slightly higher AUC of 0.82, with no significant difference observed (P= .19). Notably, cognitive factors alone were not strong predictors (AUC=0.61). However, specific tests within neuropsychological assessments, such as the Montreal Cognitive Assessment memory subdomain and Trail Making Test Part B, were found to be crucial for prediction according to SHAP analysis.Conclusion and RelevancePreoperative risk prediction for POD can increase risk awareness in presurgical assessment and improve postoperative management in patients with a high risk for delirium.HighlightsAnalyzed 1624 older patients (≥70 years) undergoing elective surgeries across five medical centers from July 2017 to April 2019.Established machine learning model to predict postoperative delirium before surgery.Preoperative cognition enhances predictive performance, comparable to models incorporating all pre- and perioperative features.Montreal Cognitive Assessment memory subdomain and Trail Making Test Part B drive the cognition-based prediction.Perioperative surgical features, such as the duration of the surgery, are important predictors.
Normalizing Spinal Cord Compression Morphometric Measures: Application in Degenerative Cervical Myelopathy
Authors: Bédard Sandrine , Valošek Jan , Seif Maryam , Curt Armin , Schading Simon , Pfender Nikolai , Freund Patrick , Hupp Markus , Cohen-Adad Julien 
Published: March 2024

AbstractObjectiveAutomatic and robust characterization of spinal cord shape from MRI images is relevant to assess the severity of spinal cord compression in degenerative cervical myelopathy (DCM) and to guide therapeutic strategy. Despite its popularity, the maximum spinal cord compression (MSCC) index has practical limitations to objectively assess the severity of cord compression. Firstly, it is computed by normalizing the anteroposterior cord diameter by that above and below the level of compression, but it does not account for the fact that the spinal cord itself varies in size along the superior-inferior axis, making this MSCC sensitive to the level of compression. Secondly, spinal cord shape varies across individuals, making MSCC also sensitive to the size and shape of every individual. Thirdly, MSCC is typically computed by the expert-rater on a single sagittal slice, which is time-consuming and prone to inter-rater variability. In this study, we propose a fully automatic pipeline to compute MSCC.MethodsWe extended the traditional MSCC (based on the anteroposterior diameter) to other shape metrics (transverse diameter, area, eccentricity, and solidity), and proposed a normalization strategy using a database of healthy adults (n=203) to address the variability of the spinal cord anatomy between individuals. We validated the proposed method in a cohort of DCM patients (n=120) with manually derived morphometric measures and predicted the therapeutic decision (operative/conservative) using a stepwise binary logistic regression including demographics, clinical scores, and electrophysiological assessment.ResultsThe automatic and normalized MSCC measures significantly correlated with clinical scores and predicted the therapeutic decision with higher accuracy than the manual MSCC. Results show that the sensory dysfunction of the upper extremities (mJOA subscore), the presence of myelopathy and the proposed MRI-based normalized morphometric measures were significant predictors of the therapeutic decision. The model yielded an area under the curve of the receiver operating characteristic of 80%.ConclusionThe study introduced an automatic method for computation of normalized MSCC measures of cord compression from MRI scans, which is an important step towards better informed therapeutic decisions in DCM patients. The method is open-source and available in the Spinal Cord Toolbox v6.0.
A Computational Framework for Intraoperative Pupil Analysis in Cataract Surgery
Authors: Giap Binh Duong , Srinivasan Karthik , Mahmoud Ossama , Ballouz Dena , Lustre Jefferson , Likosky Keely , Mian Shahzad I. , Tannen Bradford L. , Nallasamy Nambi 
Published: March 2024

ABSTRACTPurposePupillary instability is a known risk factor for complications in cataract surgery. This study aims to develop and validate an innovative and reliable computational framework for the automated assessment of pupil morphologic changes during the various phases of cataract surgery.DesignRetrospective surgical video analysis.SubjectsTwo hundred forty complete surgical video recordings, among which 190 surgeries were conducted without the use of pupil expansion devices and 50 were performed with the use of a pupil expansion device.MethodsThe proposed framework consists of three stages: feature extraction, deep learning (DL)-based anatomy recognition, and obstruction detection/compensation. In the first stage, surgical video frames undergo noise reduction using a tensor-based wavelet feature extraction method. In the second stage, DL-based segmentation models are trained and employed to segment the pupil, limbus, and palpebral fissure. In the third stage, obstructed visualization of the pupil is detected and compensated for using a DL-based algorithm. A dataset of 5,700 intraoperative video frames across 190 cataract surgeries in the BigCat database was collected for validating algorithm performance.Main Outcome MeasuresThe pupil analysis framework was assessed on the basis of segmentation performance for both obstructed and unobstructed pupils. Classification performance of models utilizing the segmented pupil time series to predict surgeon use of a pupil expansion device was also assessed.ResultsAn architecture based on the FPN model with VGG16 backbone integrated with the AWTFE feature extraction method demonstrated the highest performance in anatomy segmentation, with Dice coefficient of 96.52%. Incorporation of an obstruction compensation algorithm improved performance further (Dice 96.82%). Downstream analysis of framework output enabled the development of an SVM-based classifier that could predict surgeon usage of a pupil expansion device prior to its placement with 96.67% accuracy and AUC of 99.44%.ConclusionsThe experimental results demonstrate that the proposed framework 1) provides high accuracy in pupil analysis compared to human-annotated ground truth, 2) substantially outperforms isolated use of a DL segmentation model, and 3) can enable downstream analytics with clinically valuable predictive capacity.
Feasibility of a Cluster Randomised Trial on the Effect of Trauma Life Support Training: A Pilot Study
Authors:   Trauma life support training Effectiveness Research Network (TERN) collaborators, Gerdin Wärnberg Martin , Basak Debojit , Berg Johanna , Chatterjee Shamita , Felländer-Tsai Li , Ghag Geeta , Khajanchi Monty , Khan Tamal , Juillard Catherine , Nandu Vipul , Roy Nobhojit , Singh Rajdeep , Dev Soni Kapil , Strömmer Lovisa 
Published: March 2024

AbstractImportanceThere is no high-quality evidence to show that trauma life support training programmes improve patient outcomes.ObjectiveTo assess the feasibility of conducting a cluster randomised controlled trial comparing the effect of Advanced Trauma Life Support®(ATLS®) and Primary Trauma Care (PTC) with standard care on patient outcomes, and to estimate probable effect sizes and other measures needed for the sample size calculations of a full-scale trial.DesignA pilot pragmatic three-armed parallel, cluster randomised, controlled trial between April 2022 and February 2023. Patient follow up was 30 days.SettingTertiary care hospitals across metropolitan areas in India.ParticipantsAdult trauma patients and residents managing these patients.InterventionsATLS®or PTC training for residents in the intervention arms.Main Outcomes and MeasuresThe outcomes were consent rate, lost to follow up rate, pass rate, missing data rates, differences in distribution between observed and data extracted from medical records as well as all cause and in-hospital mortality at 30 days from the time of arrival to the emergency department.ResultsTwo hospitals were randomised to ATLS®, two to PTC, and three to standard care. We included 376 patients and 22 residents. The percentage of patients who consented to follow up was 77% and the percentage of residents who consented to training was 100%. The lost to follow up rate was 14%. The pass rate was 100%. The missing data was overall low for key variables. Data collected through observations were similar to data extracted from medical records, but there was more missing data in the extracted data. Twenty-two (16%) patients died within 30 days in the standard care arm, one (4%) patient in the ATLS®arm, and three (5%) patients in the PTC arm.Conclusions and RelevanceConducting a full-scale cluster randomised controlled trial comparing the effects of ATLS®, PTC, and standard care on patient outcomes will be feasible, especially if such a trial would use data and outcomes available in medical records.Key PointsQuestionIs it feasible to conduct a cluster randomised trial comparing trauma life support training with standard care?FindingsIn this pilot cluster randomized trial that included 376 patients and 22 residents from seven hospitals, we found high consent rates, low lost to follow up rates, and low missing data for key variables.MeaningConducting a full-scale cluster cluster trial comparing the effects of trauma life support training with standard care on patient outcomes will be feasible, especially if such a trial would use data and outcomes available in medical records.