Patient Care Decisions Research Articles

Heartbeat classification using various machine learning models: A comparative study

Cardiac arrhythmias, known as irregular heartbeats, pose a notable health threat that necessitates prompt diagnosis, as untreated arrhythmias can lead to severe heart complications. Among the various methods for arrhythmia detection, electrocardiography is the most prevalent due to its non-invasive monitoring of heart activity. However, manual electrocardiogram (ECG) analysis is inefficient and prone to errors, prompting the exploration of machine learning (ML) models for ECG feature recognition. Integrating ML models with ECG analysis can revolutionize cardiac diagnostics by improving healthcare efficiency and outcomes by enhancing the accuracy and consistency of existing approaches as well as their processing speed for large datasets. Unfortunately, current ML methods encounter two key limitations: prolonged training times and the need for manual feature selection. To address these issues, we propose using ML models enhanced with innovative techniques such as the Fourier transform (FT) and Gaussian noise injection for improved cardiac health assessment. To validate this approach, we utilized statistical tools, including Pearson correlation and p-values, to uncover relationships within the data. In addition, we employed the FT technique to extract and analyze frequency-domain features. Our comparative study of different ML models relied on metrics such as accuracy, precision, recall, F1 score, and receiver operating characteristic area under the receiver operating characteristic curve, demonstrating XGBoost’s impressive average recall of 0.956 with 99.96% overall accuracy. An average precision of 0.956 further underscored the accuracy of XGBoost’s predictions, indicating its high level of reliability in distinguishing various cardiac conditions. These results highlight the considerable potential of ML techniques for precise ECG-based clinical diagnoses, helping healthcare professionals make more accurate and timely decisions in patient care.

The Impact of Healthcare Pressures on the COVID-19 Hospitalisation Fatality Risk in England.

As the impact of the SARS-CoV-2 pandemic extends into 2023 and beyond, the treatment and outcomes of infected patients continues to evolve. Unlike earlier in the pandemic there are now further infectious disease pressures placed on hospitals, which influence patient care and triage decisions. The manuscript uses individual patient records linked with associated hospital management information of system pressure characteristics to attribute COVID-19 hospitalisation fatality risks (HFR) to patients and hospitals, using generalised additive mixed effects models. Between 01 September 2022 and 09 October 2023, the COVID-19 hospitalisation fatality risk in England was estimated as 12.71% (95% confidence interval (CI) 12.53%, 12.88%). Staff absences had an adjusted odds ratio of 1.038 (95% CI 1.017, 1.060) associatedwith the HFR when accounting for patient and hospital characteristics. This observational research presents evidence that a range of local hospital effects can have a meaningful impact on the risk of death from COVID-19 once hospitalised and should be accounted for when reporting estimates. We show that both the patient case mix and hospital pressures impact estimates of patient outcomes.

A Survey of Patient Utilization and Trust of Emergency Medical Services

Little is known about patients’ decisions to come to the Emergency Department (ED) via emergency medical services (EMS) versus privately owned vehicle (POV); this is problematic as trust in EMS systems impacts patient care decisions. Furthermore, no studies exist that evaluate patients’ trust of the EMS system as it relates to a patient’s race. Patients completed a multi-method survey during their ED stay. Quantitative data included: patient demographics (age, gender, race) income, insurance status, previous medical training, highest level of education, self-reported medical and social history, number of ED visits in the past three months, and two scales assessing trust and empathy: the Group-Based Medical Mistrust Scale and the Jefferson Scale. Characteristics of patients who came to the ED via EMS versus POV were shown. A Wilcoxon signed rank test described differences in EMS trust scales by race. Logistic regression showed which factors contribute to the decision of EMS or POV. Qualitative comments described patients’ rationale for EMS versus POV. 23/72 (31.94%) patients utilized EMS transport and 49/72 (68.06%) utilized POV. 59.09% of patients self-identified as Black and 40.91% self-identified as White. The Group-Based Medical Mistrust Scale found Black patients had less trust in the EMS system (p=0.0001), while the Jefferson Scale of Patient Perception of Physician Empathy showed no significant difference in patient perceptions of EMS provider empathy (p=0.608). Logistic regression indicated that age predicted the use of EMS over POV (p<0.001). Lack of access to POV, physical limitations, cost, speed, perception of emergency, and fear were identified as reasons that supportg patients’ decision to use EMS or POV. Many factors can influence patients’ transportation decisions and this study highlights trust, age, and other social and economic factors. These findings could inform policy decisions and ensure emergency care systems that are accessible for all patients.

Utilization of genomic tumor testing (GTT) among community oncologists participating in SWOG S2108CD.

320 Background: As targeted therapy options increase in oncology, GTT use is also increasing; however, the strategies and barriers to ordering GTT can vary across clinics. S2108CD is a cluster randomized trial comparing an educationally enhanced genomic tumor board intervention to usual practice to increase evidence-based genome-informed therapy based on GTT results. This analysis seeks to understand the utilization of GTT by physicians in rural and community oncology clinics. Methods: Physicians at sites enrolled on S2108CD completed baseline questionnaires collecting demographics, practice characteristics, and physicians’ experience with and use of GTT in practice. We also conducted semi-structured interviews at baseline and mid-study with select physicians in both arms to understand how and when physicians are ordering GTT and how it guides treatment decision making. Descriptive statistics were generated for survey data. Interviews were analyzed using conventional content analysis to identify recurring themes. Results: Surveys were completed by 117 physicians across 18 Recruitment Centers, with 57 from the usual practice and 60 from the intervention arm. Interviews were conducted with 10 physicians at baseline and 10 within 12-18 months of start of the study. Physicians reported feeling confident in determining whether GTT is clinically appropriate for a patient (42% moderately confident, 50% very confident). Some physicians utilize GTT from multiple vendors, with the following vendors used most frequently: Tempus (50% of physicians), Caris Life Sciences (61%), Foundation Medicine (62%) and Guardant Health (69%). Over two-thirds of physicians reported that professional guidelines were “very important” in the decision to utilize GTT. Reasons for not ordering GTT included “not relevant for the patient” (36%) and “difficulty in obtaining sufficient tissue” (20%) as “often” reasons. Notably, lack of access and cost/insurance coverage were “never” or “rarely” a reason for not ordering GTT in 80% physicians. Long waits to receive GTT results reportedly caused a delay in making patient care decisions (47% sometimes and 26% often). Physicians rely on the following sources to learn about new GTT panels: scientific meetings (91%), peer-reviewed literature (92%), and professional societies (90%). Interview data confirmed that physicians are generally confident ordering GTT but there is variability in the processes for ordering GTT and receipt of GTT results amongst clinics. Conclusions: Physicians enrolled on S2108CD self-reported high genomic confidence in ordering GTT. Access to GTT and coverage of GTT do not appear to be barriers to utilization. However, physicians did report delays in decision-making due to result turn-around times, which were sometimes attributed to length of time to tissue sendout and receipt of results into health record. Funding : NIH/NCI/NCORP grant UG1CA189974. Clinical trial information: NCT05455606 .

Shared Decision-Making in Patient Care: Advantages, Barriers and Potential Solutions

Shared Decision-Making (SDM) is a collaborative process where physicians integrate scientific evidence with patients’ goals, preferences, and values to make healthcare decisions. This approach contrasts with traditional methods, enhancing patient involvement and understanding. The BRAN questions (Benefits, Risks, Alternatives, Nothing) effectively facilitate SDM across various clinical settings, promoting patient safety. While time constraints and low health literacy pose barriers, strategies like visual aids, extended appointments, and cognitive assessments can mitigate these challenges. Training for physicians in SDM skills has been shown to improve patient outcomes and satisfaction, underscoring the importance of personalized care in outpatient and inpatient contexts.

Sinonasal Tumors: What the Multidisciplinary Cancer Care Board Wants to Know.

Sinonasal neoplasms are a remarkably heterogeneous group, reflecting the numerous tissue types present in the nasal cavity and paranasal sinuses. These entities can be relatively benign (ie, respiratory epithelial adenomatoid hamartoma) or can be exceedingly aggressive (ie, NUT carcinoma). Certain sinonasal tumors have a propensity to spread through local invasion and destruction, while others have a high likelihood of perineural spread. The genetic and molecular mechanisms underlying sinonasal tumor behavior have recently become better understood, and new tumor types have been described using these genetic and molecular data. This has prompted an expansion in the number of tumors included in the World Health Organization fifth edition classification system for head and neck tumors, along with a new classification structure. Radiologists' familiarity with this classification structure is crucial to understanding the expected behavior of these tumors and to collaboration with the multidisciplinary cancer care board in making decisions for optimal patient care. ©RSNA, 2024.

Effectiveness of electrocardiogram interpretation education program using mixed learning methods and webpage

AimThis study was conducted to develop an electrocardiogram education program that incorporates an HTML webpage and blended learning methods to enhance electrocardiogram interpretation skills. Through continual and efficient education, the program aims to assist nurses in providing appropriate care and treatment to patients.DesignPre-post design study.MethodsWe developed an electrocardiogram interpretation HTML webpage based on an electrocardiogram interpretation algorithm and implemented an 18-week (2023.5.15 ~ 2023.9.22) electrocardiogram education program, which included daily 5-minute training sessions. Twenty-seven ward nurses were provided with the URL (https://ecgweb.github.io/ECGwebEN) to the electrocardiogram interpretation HTML webpage and shared one electrocardiogram case daily for self-interpretation. Electrocardiogram interpretation performance and confidence were evaluated through questionnaires at three phases: before the program, after 6 weeks of basic electrocardiogram and arrhythmia education, and after 12 weeks of application of the electrocardiogram interpretation HTML webpage and case-based lecture education. The statistical tests used were repeated-measures ANOVA or the Wilcoxon signed-rank test.ResultsThe average score for electrocardiogram interpretation performance before the electrocardiogram education program was 11.89(SD = 3.50), after 6 weeks of basic electrocardiogram and arrhythmia education it was 14.15(SD = 3.68), and after 12 weeks of application of the electrocardiogram interpretation HTML webpage and case-based lecture education, it was 15.56(SD = 3.04). This shows that electrocardiogram interpretation performance significantly improved over time (p < .001). Additionally, post-hoc analysis revealed significant differences in electrocardiogram interpretation performance at each stage, i.e., before, during, and after the application of an electrocardiogram education program. Furthermore, the electrocardiogram interpretation confidence questionnaire score (pre-Median 18, IQR = 5; post-Median 23, IQR = 3) was improved significantly after the completion of the 18-week education program (p < .001).ConclusionsBased on the results of this study, we believe that an electrocardiogram education program using HTML webpage, and a blended teaching method would be very beneficial for maintaining and improving electrocardiogram interpretation skills of clinical nurses. Such a program can help nurses interpret electrocardiograms more effectively and assist them in making important decisions in patient care.

Real-world response assessment of immune checkpoint inhibition: comparing iRECIST and RECIST 1.1 in melanoma and non-small cell lung cancer patients.

To compare immune response evaluation criteria in solid tumors (iRECIST) and response evaluation criteria in solid tumors (RECIST) 1.1 for response assessment of immune checkpoint inhibitor (ICI) therapy in a real-world setting in patients with melanoma and non-small cell lung cancer (NSCLC). Two-hundred fifty-two patients with melanoma and NSCLC who received CTLA-4 inhibitor ipilimumab or PD-1 inhibitors nivolumab or pembrolizumab and who underwent staging CT of the chest and abdomen were retrospectively included. Treatment response evaluation according to the RECIST 1.1 and iRECIST guidelines was performed for all patients. Response patterns, as well as overall response rate (ORR), disease control rate (DCR), and time to progression (TTP), were compared between RECIST 1.1 and iRECIST. Out of 143 patients with progressive disease (PD) according to RECIST 1.1, 48 (33.6%) did not attain confirmation of progression (iCPD) as per iRECIST and six patients who were treated beyond RECIST 1.1 progression reached PD at a later point in time in iRECIST, resulting in a significant difference in TTP between iRECIST and RECIST 1.1 (618.3 ± 626.9 days vs. 538.1 ± 617.9 days, respectively (p < 0.05)). The number of non-responders as per RECIST 1.1 was 79, whereas it was 60 when using iRECIST. ORR was 28.5% for RECIST 1.1 and 34.1% for iRECIST, and corresponding DCR of 67.4% for RECIST 1.1 and 74.6% for iRECIST. iRECIST was more suitable than RECIST 1.1 for capturing atypical response patterns to ICI therapy in patients with melanoma and NSCLC, resulting in differences in the assessment of treatment response. Compared to RECIST 1.1, iRECIST may improve patient care and treatment decisions for patients with NSCLC or melanoma who are treated with immune checkpoint inhibitors in clinical routine. RECIST 1.1 may incorrectly assess atypical treatment patterns to immune checkpoint inhibitors. iRECIST better captured atypical response patterns compared to RECIST 1.1. iRECIST was more suitable for assessing response to immune checkpoint inhibitors in non-small cell lung carcinoma and melanoma.

Challenges for pathologists in implementing clinical microbiome diagnostic testing.

Recent research has established that the microbiome plays potential roles in the pathogenesis of numerous chronic diseases, including carcinomas. This discovery has led to significant interest in clinical microbiome testing among physicians, translational investigators, and the lay public. As novel, inexpensive methodologies to interrogate the microbiota become available, research labs and commercial vendors have offered microbial assays. However, these tests still have not infiltrated the clinical laboratory space. Here, we provide an overview of the challenges of implementing microbiome testing in clinical pathology. We discuss challenges associated with preanalytical and analytic sample handling and collection that can influence results, choosing the appropriate testing methodology for the clinical context, establishing reference ranges, interpreting the data generated by testing and its value in making patient care decisions, regulation, and cost considerations of testing. Additionally, we suggest potential solutions for these problems to expedite the establishment of microbiome testing in the clinical laboratory.

2024 Guidelines for reporting radiation therapy in veterinary medicine.

Evidence-based medicine drives patient care decision-making; thus, accurate and complete reporting in scientific publications is paramount. A checklist for complete reporting of veterinary radiation therapy was proposed in 2012 using the recommendations of the International Commission of Radiation Units and Measurements (ICRU). The purpose of this study is to review the 2012 checklist and propose updates based on changes in technology. Significant technology advancements have gained traction in veterinary medicine, including intensity-modulated radiation therapy (IMRT) and stereotactic radiation therapy (SRT), both of which have related modality-specific ICRU reporting recommendations. The 2012 checklist and proposed 2024 checklist are then used to assess the completeness of reporting in veterinary radiation oncology publications between 2015 and 2022, of which one hundred and eight publications met the inclusion criteria. Prior to the publication of the 2012 checklist (2005-2010), only nine checklist items showed a good level of completeness in reporting, and from 2015 to 2022, this increased to 16 items. Encouraging and/or requiring the use of reporting checklists at the time of manuscript submission may be responsible for this improvement in reporting. Using the 2024 checklist, which is more relevant to publications discussing IMRT and SRT treatments, only 14 of the analyzed checklist items (34%) show a good level of completeness in reporting, suggesting there is a need for updated guidelines to capture the nuances of advanced techniques. This study proposes a 2024 checklist that can be used as a guideline for future reporting of radiation therapy in veterinary medicine.

Integrating the melanoma 31-gene expression profile test with clinical and pathologic features can provide personalized precision estimates for sentinel lymph node positivity: an independent performance cohort.

Up to 88% of sentinel lymph node biopsies (SLNBs) are negative. The 31-gene expression profile (31-GEP) test can help identify patients with a low risk of SLN metastasis who can safely forego SLNB. The 31-GEP classifies patients as low (Class 1A), intermediate (Class 1B/2A), or high risk (Class 2B) for recurrence, metastasis, and SLN positivity. The integrated 31-GEP (i31-GEP) combines the 31-GEP risk score with clinicopathologic features using a neural network algorithm to personalize SLN risk prediction. Patients from a single surgical center with 31-GEP results were included (n = 156). An i31-GEP risk prediction < 5% was considered low risk of SLN positivity. Chi-square was used to compare SLN positivity rates between groups. Patients considered low risk by the i31-GEP had a 0% (0/30) SLN positivity rate compared to a 31.9% (30/94, p < 0.001) positivity rate in those with > 10% risk. Using the i31-GEP to guide SLNB decisions could have significantly reduced the number of unnecessary SLNBs by 19.2% (30/156, p < 0.001) for all patients and 33.0% (30/91, p < 0.001) for T1-T2 tumors. Patients with T1-T2 tumors and an i31-GEP-predicted SLN positivity risk > 10% had a similar SLN positivity rate (33.3%) as patients with T3-T4 tumors (31.3%). The i31-GEP identified patients with < 5% risk of SLN positivity who could safely forego SLNB. Combining the 31-GEP with clinicopathologic features for a precise risk estimate can help guide risk-aligned patient care decisions for SLNB to reduce the number of unnecessary SLNBs and increase the SLNB positivity yield if the procedure is performed.

Multi-Objective Performance Optimization of Machine Learning Models in Healthcare.

Multi-objective optimization holds particular significance for medical applications, wherein enhancing sensitivity is crucial to avoid costly missed diagnoses, and maintaining high specificity is imperative to prevent unnecessary procedures. In particular, when optimizing machine learning architectures for clinical diagnostics, it becomes essential to balance target quality measures such as accuracy, sensitivity, and specificity. Therefore, we developed MOOF, a multi-objective optimization framework that employs NSGA-II and TOPSIS to simultaneously optimize the model parameters of three selected ML algorithms: random forest, support vector machine, and multilayer perceptron. Finally, we evaluated the performance of the optimized MOOF models compared to gold standard methods such as multi-score grid search and single objective optimizations. Our results show that MOOF generally outperforms other approaches by inherently providing optimal solutions, representing the trade-offs between the target objectives. In conclusion, the study supports the importance of multi-objective optimization in medical informatics, with MOOF as a powerful tool for precise ML models, potentially improving patient care and clinical decision support systems.

Exploring Pediatric Vertebral, Sacral, and Pelvic Osteosarcomas through the NCDB: Demographics, Treatment Utilization, and Survival Outcomes.

Retrieve data from the National Cancer Database (NCDB) to examine information on the epidemiological prevalence, treatment strategies, and survival outcomes of pediatric vertebral, sacral and pelvic osteosarcomas. We reviewed NCDB data from 2008 to 2018, concentrating on vertebral, sacral, and pelvic osteosarcomas in children 0 to 21 years. Our analysis involved logistic and Poisson regression, Kaplan-Meier survival estimates, and Cox proportional hazards models. The study population included 207 patients. For vertebral osteosarcomas, 62.5% of patients were female, and 78.1% were white. Regional lymph node involvement predicted 80 times higher mortality hazard (p = 0.021). Distant metastasis predicted 25 times higher mortality hazard (p = 0.027). For sacral and pelvic osteosarcomas, 58.3% of patients were male, and 72% were white. Patients with residual tumor were 4 times more likely to have prolonged LOS (p = 0.031). No residual tumor (HR = 0.53, p = 0.03) and radiotherapy receipt (HR = 0.46, p = 0.034) were associated with lower mortality hazards. Distant metastasis predicted 3 times higher mortality hazard (p < 0.001). Hispanic ethnicity was linked to lower resection odds (OR = 0.342, p = 0.043), possibly due to language barriers affecting patient understanding and care decisions. In conclusion, our examination of NCDB offers a thorough exploration of demographics, treatment patterns, and results, highlighting the importance of personalized approaches to enhance patient outcomes.

Enhancing precision through AI-enhanced method verification validating iron determination on the Alinity ci® Analyzer: Experience of the central laboratory of Mohammed VI University Hospital of Oujda

This study meticulously assessed the analytical performance of iron determination on the Alinity ci® analyzer, employing advanced AI-powered method verification techniques. Conducted at Mohammed VI University Hospital's central laboratory in Oujda, Morocco, the validation process strictly adhered to the rigorous guidelines outlined in the French accreditation committee's (COFRAC) Accreditation Technical Guide (GTA) 04. Through comprehensive assessments of repeatability and reproducibility, we definitively confirmed the assay's precision and reliability. Our evaluation yielded highly satisfactory results, consistently exceeding the established criteria set forth by both the instrument manufacturer and esteemed professional organizations like SFBC and RICOS. This unequivocally validates the laboratory's capability to deliver accurate and reproducible iron concentration measurements, crucial for enhanced clinical diagnostics and, ultimately, well-informed patient care decisions. This study underscores the importance of stringent validation processes in ensuring the reliability of diagnostic assays, thereby bolstering confidence in laboratory medicine practices and patient outcomes.

Risk of new-onset diabetes and efficacy of pharmacological weight loss therapy.

To develop a clinical risk model to identify individuals at higher risk of developing new-onset diabetes and who might benefit more from weight loss pharmacotherapy. A total of 21 143 patients without type 2 diabetes at baseline from two TIMI clinical trials of stable cardiovascular patients were divided into a derivation (~2/3) and validation (~1/3) cohort. The primary outcome was new-onset diabetes. Twenty-seven candidate risk variables were considered, and variable selection was performed using multivariable Cox regression. The final model was evaluated for discrimination and calibration, and for its ability to identify patients who experienced a larger benefit from the weight loss medication lorcaserin in terms of risk of new-onset diabetes. During a median (interquartile range) follow-up of 2.3 (1.8-2.7) years, new-onset diabetes occurred in 1013 patients (7.7%). The final model included five independent predictors (glycated haemoglobin, fasting glucose, age, body mass index, and triglycerides/high-density lipoprotein). The clinical risk model showed good discrimination (Harrell's C-indices 0.802, 95% confidence interval [CI] 0.788-0.817 and 0.807, 95% CI 0.788-0.826) in the derivation and validation cohorts. The calibration plot demonstrated adequate calibration (2.5-year area under the curve was 81.2 [79.1-83.5]). While hazard ratios for new-onset diabetes with a weight-loss therapy were comparable across risk groups (annual risks of <1%, 1%-5%, and >5%), there was a sixfold gradient in absolute risk reduction from lowest to highest risk group (p = 0.027). The developed clinical risk model effectively predicts new-onset diabetes, with potential implications for personalized patient care and therapeutic decision making.

Investigating distinct clinical features and constructing a nomogram model for survival probability in adults with cerebellar high-grade gliomas

BackgroundThe clinical features of cerebellar high-grade gliomas (cHGGs) in adults have not been thoroughly explored. This large-scale, population-based study aimed to comprehensively outline these traits and construct a predictive model.MethodsPatient records diagnosed with gliomas were collected from various cohorts and analyzed to compare the features of cHGGs and supratentorial HGGs (sHGGs). Cox regression analyses were employed to identify prognostic factors for overall survival and to develop a nomogram for predicting survival probabilities in patients with cHGGs. Multiple machine learning methods were applied to evaluate the efficacy of the predictive model.ResultsThere were significant differences in prognosis, with SEER-cHGGs showing a median survival of 7.5 months and sHGGs 14.9 months (p < 0.001). Multivariate Cox regression analyses revealed that race, WHO grade, surgical procedures, radiotherapy, and chemotherapy were independent prognostic factors for cHGGs. Based on these factors, a nomogram was developed to predict 1-, 3-, and 5-year survival probabilities, with AUC of 0.860, 0.837, and 0.810, respectively. The model’s accuracy was validated by machine learning approaches, demonstrating consistent predictive effectiveness.ConclusionsAdult cHGGs are distinguished by distinctive clinical features different from those of sHGGs and are associated with an inferior prognosis. Based on these risk factors affecting cHGGs prognosis, the nomogram prediction model serves as a crucial tool for clinical decision-making in patient care.

How Do Exercise, Sleep and Depression Affect Disease Scores and Quality of Life in Primary Sjögren's Syndrome Patients?

Primary Sjögren's syndrome (PSS) has many effects such as fatigue, pain, physical activity limitation and sleep disturbance, which limit patient's daily and social lives. The aim of our study was to assess fatigue, depression, physical activity status and quality of life in patients with PSS, and to determine the relationship between these data and disease-related parameters. This study was conducted with 117 primary Sjögren's syndrome patients. Demographic and anthropometric characteristics, disease activity (ESSDAI), quality of life scale (SF36), depression (Beck Depression Scale), physical activity status (International Physical Activity Questionnaire Short Form (IPAQ) score) and sleep status (Pittsburgh Sleep Quality Scale) of PSS patients were evaluated and relationships have been examined. According to the results of our study, we found that sleep disorders are common in PSS patients (74.4%). Overweight patients, particularly higher lean mass sleep better (r:-0.201, p:0.043). Poor sleep causes fatigue (p=0.062) and depression (p=0.030). Sleep disturbance could not be explained by depressive state alone. However, after controlling for depression, the effect of sleep on fatigue seriously decreases (p=0.311). Exercise did not improve sleep quality (p=0.35) and the rate of poor sleep was higher among who exercised (p=0.192). Based on the results of our study, we believe that, treating depression in PSS patients is crucial for reducing fatigue. Patients need education on performing the correct exercises and weight gain should done in a professional manner. Gaining a deeper understanding of the multisystem involvement of the disease and the impact of exercise on the disease, will have positive effects on patient care and treatment decisions.

Quantitative analysis of the impact of infectious disease physicians on patients in the emergency department fast-track parenteral antibiotics program

IntroductionThe outpatient parenteral antibiotic therapy (OPAT) program of Vancouver General Hospital (VGH) was supervised by emergency physicians (EPs) until 2017 when infectious disease (ID) physicians began assisting in management. We designed a retrospective study to determine whether ID involvement led to improved outcomes.MethodsThis study analyzes the impact of ID involvement by comparing the mean days patients spent on OPAT with ID involvement versus EPs alone through a retrospective chart review. Secondary research objectives were to compare patient care decisions, e.g., antibiotic choice, tests ordered, and final diagnosis.ResultsThere was no difference between the mean number of days on OPAT between physician types. Compared to historic patterns, patients seen in OPAT after increased ID consultation spent an average of 0.5 fewer days in the program. However, when grouped by the first day of ID assessment, the average total days in OPAT was closely aligned with the day of first ID assessment, implying that ID frequently discharged patients close to initial assessment. Patients seen by ID were less likely to return within one month of discharge compared to those not seen by ID. Secondary findings include ID physicians prescribing a greater range of antibiotics, providing more varied final diagnoses, prescribing antibiotics less frequently, as well as ordering more cultures, diagnostic imaging and specialist consults.DiscussionThe findings of this study support the hypothesis that ID involvement in OPAT programs leads to changes in care that may have beneficial outcomes for patients and the healthcare system.

Factors Associated with Inappropriate Urine Culture Orders in Hospitalized Patients with Indwelling Urinary Catheters

Background: Catheter-associated urinary tract infection (CAUTI) is among the most prevalent healthcare-associated infections. Clinical diagnosis of CAUTI and National Healthcare Safety Network (NHSN) definitions do not always align. Most patients with indwelling urinary catheters ultimately develop asymptomatic bacteriuria (ASB) due to bacterial colonization and may be misattributed as CAUTI. Urine cultures ordered on patients with ASB may lead to reporting of non-clinically significant CAUTI to NHSN. We sought to examine factors associated with ordering inappropriate urine cultures in patients with urinary catheters. Methods: All CAUTIs that were reported to the NHSN at a large academic medical center in Eastern North Carolina were evaluated from October 2021-July 2023. A logistic regression model was fit for patients treated for urinary tract infection (UTI) with the following covariates: age, sex, time of urine culture order, provider type, and days that the urinary catheter was in place. All data analysis was performed in SAS (SAS Institute Inc., SAS 9.4, Cary, NC: SAS Institute Inc., 2002-2023). Results: Table 1 demonstrates patient characteristics stratified by treatment for UTI. The analysis suggests that abnormalresults from urine cultures ordered overnight were less likely to be treated with antibiotics,and this result was statistically significant in both the adjusted and unadjusted analyses – see table 2 and 3. The model also suggests abnormal results from urine cultures ordered by housestaff and older patients were more likely to be treated for UTI, but these results were not statistically significant – see table 3. Finally, the longer a catheter was in place the less likely an abnormalurine culture was to be treated and this finding was statistically significant – see table 3. Conclusion: Cultures that did not prompt antimicrobial treatment did not impact patient care decisions and could be considered as inappropriate orders. This can result in CAUTIs reported to NHSN that were not clinically significant. Abnormal results from cultures that were ordered by the overnight team were less likely to be treated for clinical UTI and this may represent an important target for diagnostic stewardship interventions.

Long-term functional outcomes and predictors of efficacy in thulium laser enucleation of the prostate (ThuLEP) for benign prostatic hyperplasia (BPH): a retrospective observational study.

Benign prostatic hyperplasia (BPH) is a common urological condition affecting aging men worldwide. Among the treatment options available for BPH, transurethral resection of the prostate (TURP) is the gold-standard invasive intervention. To reduce the TURP-related non-negligible morbidity, loss-of-ejaculation rate, hospitalization, blood loss and catheterization time several laser techniques have been developed, such as the Thulium Laser Enucleation of the Prostate (ThuLEP). To investigate the efficacy outcomes of the ThuLEP as a treatment option for benign prostatic hyperplasia (BPH) we performed a retrospective observational study at Moriggia Pelascini Hospital (Como, Italy) between January 2015 and September 2018. We included 265 patients who underwent ThuLEP at a specific hospital between defined dates. Data on various parameters, including post-void residue volume, peak urinary flow rate (Qmax), International Prostate Symptom Score (IPSS) for urinary symptoms, IPSS Quality of Life (QoL) score, and International Index of Erectile Function (IIEF) score for erectile dysfunction, were collected at baseline and follow-up. The analysis revealed significant improvements in voiding efficiency, urinary flow, urinary symptoms, quality of life, and erectile function following ThuLEP. Furthermore, certain baseline characteristics, such as post-void residue, peak urinary flow rate, age, prostate volume, and aspirin usage, were found to influence treatment outcomes. Despite the study's limitations, these findings contribute to understanding ThuLEP's effectiveness in managing BPH and can aid in making informed clinical decisions for patient care. Prospective studies with longer follow-up periods are recommended to validate and extend these results.