Individual Clinical Factors Research Articles

Outcome prediction following lumbar disc surgery: a longitudinal study of outcome trajectories, prognostic factors, and risk models.

This study aimed to 1) describe the 2-year postoperative trajectories of leg pain and overall clinical outcome after surgery for radiculopathy, 2) identify the preoperative prognostic factors that predict trajectories representing poor clinical outcomes, and 3) develop and internally validate multivariable prognostic models to assist with clinical decision-making. This retrospective cohort study included patients enrolled in the Canadian Spine Outcomes and Research Network who were diagnosed with lumbar disc pathology and radiculopathy and had undergone lumbar discectomy at one of 18 spine centers. Potential outcome predictors included preoperative demographic, health-related, and clinical prognostic factors. Clinical outcomes were 1) 2-year univariable latent trajectories of leg pain intensity (numeric pain rating scale) and 2) overall outcomes comprising multivariable trajectories showing the combined postoperative courses of leg and back pain intensity (numeric pain rating scale) together with pain-related disability (Oswestry Disability Index). Each outcome model identified a subgroup of patients classified as experiencing a poor outcome based on minimal change in their clinical status after surgery. Multivariable risk model performance and internal validity were evaluated with discrimination and calibration statistics based on bootstrap shrinkage with 500 resamplings. The authors included data from 1142 patients (47.6% female). The trajectory models identified 3 subgroups based on the patients' postoperative courses of pain or disability: 88.6% of patients in the leg pain model and 71.9% in the overall outcome model experienced a good-to-excellent outcome. The models classified 11.4% (leg pain outcome) and 28.2% (overall outcome) of patients as experiencing a poor clinical outcome, which was defined as minimal improvement in pain or disability after surgery. Eleven individual demographic, health, and clinical factors predicted patients' poor leg pain and overall outcomes. The performance of the multivariable risk model for leg pain was inadequate, while the overall outcome model had acceptable discrimination, calibration, and internal validity for predicting a poor surgical outcome. Patients with lumbar radiculopathy experience heterogeneous postoperative trajectories of pain and disability after lumbar discectomy. Individual preoperative factors are associated with postoperative outcomes and can be combined within a multivariable risk model to predict overall patient outcome. These results may inform clinical practice but require external validation before confident clinical implementation.

Abstract A025: Trends in liver cancer mortality by sex, race, and ethnicity in California from 2000-2019

Abstract Background: Liver cancer disproportionately affects foreign-born individuals and racial and ethnic minoritized groups, with higher incidence among Asian American/Pacific Islander (AAPI) and Hispanic populations than non-Hispanic (NH) White populations. California has one of the highest overall mortality rates from liver cancer and a large proportion of AAPI and Hispanic residents compared to other U.S states. While prior studies have examined racial and ethnic disparities in liver cancer incidence and treatment, few studies have examined trends in liver cancer mortality in California by sex, race, and ethnicity. Methods: Adults aged 20+ years diagnosed with first primary malignant liver and intrahepatic bile duct cancer from January 2000 through December 2019 were identified through the California Cancer Registry, a statewide population-based cancer registry. We used SEER*Stat software to compute age-adjusted mortality rates (per 100,000 population; standardized to the 2000 U.S. standard million population) by sex, race, and ethnicity. To analyze temporal trends of mortality rates, we calculated annual percent change (APC) using Joinpoint regression. Results: Overall, the mortality rate of liver cancer increased from 8.05 to 10.75 per 100,000 (average APC=1.53, 95% CI 1.23, 1.82) from 2000-2019. For males, rates increased from 11.39 in 2000 to 15.77 until 2013 (APC=2.53, 95% CI 2.07, 3.21), and stabilizing thereafter (APC=-0.74, 95% CI -2.37, 0.30). In contrast, for females, mortality rates increased continuously from 2000-2019 from 5.27 to 7.17 (APC=1.63, 95% CI 1.27, 2.04). Across racial and ethnic groups, the mortality rate for liver cancer was highest for the AAPI adults at 16.77 in 2000, and this decreased over time to 12.29 in 2019 (APC=-3.17, 95% CI -5.36, -2.24). Similarly, the liver cancer mortality rate among Hispanic adults increased initially and then decreased. Mortality among non-Hispanic Black adults increased from 10.98 in 2000 to 12.99 in 2019 (APC=0.89, 95% CI -0.07, 2.02), though this did not reach statistical significance. The liver cancer mortality rate was lowest among non-Hispanic White adults from 5.65 in 2000 but increased over time to 7.87 in 2019 (APC=1.76, 95% CI 1.39, 2.08), which is still the lowest compared to other racial and ethnic groups. Discussion: In contrast to studies that show a decline in liver cancer mortality in recent years, liver cancer mortality rates have continued to increase in California, particularly for females. Liver cancer mortality rates initially increased for AAPI and Hispanic populations but have started to stabilize. Next steps are to understand multilevel drivers contributing to these trends in liver cancer mortality in California, including individual sociodemographic and clinical factors, healthcare system factors, and neighborhood factors, including neighborhood socioeconomic status and ethnic enclaves. Citation Format: Janet N. Chu, Meera Sangaramoorthy, Meg Mckinley, Stephen Li, Mindy C. DeRouen, Alice Guan, Michele M. Tana, Ma Somsouk, Caroline A. Thompson, Chanda Ho, Hashem B. El-Serag, Iona Cheng, Scarlett L. Gomez, Salma Shariff-Marco. Trends in liver cancer mortality by sex, race, and ethnicity in California from 2000-2019 [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A025.

Impact of motion management strategies on abdominal organ at risk delineation for magnetic resonance-guided radiotherapy

Background and purposeThe impact of respiratory motion management strategies for abdominal radiotherapy, such as abdominal compression (AC) and breath hold (BH), on abdominal organ at risk (OAR) delineation on magnetic resonance imaging (MRI) is unknown. This feasibility study compared the inter- and intra- observer delineation variation on MRI acquired with AC, BH for three critical abdominal OAR. Materials and methodsT2-weighted (W) 3D MRI in free-breathing (FB) and with AC, and T1W 3D mDixon exhale BH were acquired. Four observers blinded to motion management strategy used, delineated stomach, liver, and duodenum on all MRI. One case per strategy was repeated over 6 weeks later to quantify intra-observer variation. Simultaneous truth and performance level estimation (STAPLE) contours for each OAR were generated, median and IQR mean distance to agreement (mDTA) and maximum Hausdorff distance (HD) between observer and STAPLE contours were calculated. Observers scored organ visibility on each MRI using a four-point Likert scale. ResultsA total of 27 scans including repeats were delineated. Pooled mDTA for all OARs was 1.3 mm (0.5 mm) with AC, 1.4 mm (1.0 mm) with BH, and 1.3 mm (0.5 mm) in FB. Intra-observer mDTA was highest for all organs in FB with 10.8 mm for duodenum, 1.8 mm for liver, and 2.7 mm for stomach. The pooled mean perceptual quality score value was highest for AC across organs. ConclusionsNo motion management strategy demonstrated superior similarity across OAR, emphasizing the need for personalised approaches based on individual clinical and patient factors.

Society of Family Planning Clinical Recommendation: Induction of fetal asystole before abortion Jointly developed with the Society for Maternal-Fetal Medicine

This document serves as a revision to the Society of Family Planning’s 2010 guidelines, integrating literature on new techniques and research and addressing the clinical, medical, and sociolegal questions surrounding the induction of fetal asystole. Insufficient evidence exists to recommend routine induction of fetal asystole before previable medication and procedural abortion. However, at periviable gestations and after fetal viability, inducing fetal asystole before abortion prevents the infrequent but serious occurrence of unanticipated expulsion of a fetus with cardiorespiratory activity (Best Practice). Defining viability is complicated as it represents a physiological continuum impacted by gestational duration along with multiple other individual clinical factors and circumstances; therefore, the exact gestational duration to offer fetal asystole will depend on the setting and clinical circumstances. If induction of fetal asystole before abortion is available, we recommend engaging in patient-centered counseling regarding the risks and benefits of induction of fetal asystole in the setting of each unique pregnancy scenario and the patient’s beliefs and priorities (Best Practice). We recommend that clinicians identify the optimal pharmacologic agent to administer for a given clinical scenario based on factors such as availability of each agent; the time frame in which fetal asystole needs to be established; and clinicians’ technical ability, preferences, and practice (Best Practice). Potassium chloride, lidocaine, and digoxin are all acceptable pharmaceutical agents to induce fetal asystole before abortion. To establish asystole rapidly, we suggest the use of potassium chloride (via intracardiac or intrafunic injection) or lidocaine (via intracardiac or intrafunic injection) (GRADE 2C), although intrathoracic administration of lidocaine may be acceptable. We recommend potassium chloride not be used if intracardiac or intrafunic location cannot be achieved to avoid the risk of accidental administration to the pregnant individual and because insufficient data support its efficacy via other intrafetal locations (GRADE 1C). When using digoxin, we recommend intrafetal administration (GRADE 1C), although intraamniotic administration may be acceptable depending on a clinician’s technical ability and setting. Because digoxin may take several hours to induce asystole, an alternative agent should be considered in settings where fetal asystole must be confirmed rapidly.

Timing of Loop Ileostomy Closure Does Not Play a Pivotal Role in Terms of Complications-Results of the Liquidation of iLEOstomy (LILEO) Study.

Loop ileostomy is commonly performed by colorectal and general surgeons to protect newly created large bowel anastomoses. The optimal timing for ileostomy closure remains debatable. Defining the timing associated with the best postoperative outcomes can significantly improve the clinical results for patients undergoing ileostomy closure. The LILEO study was a prospective multicenter cohort study conducted in Poland from October 2022 to December 2023. Full data analysis involved 159 patients from 19 surgical centers. Patients were categorized based on the timing of ileostomy reversal: early (<4 months), standard (4-6 months), and delayed (>6 months). Data on demographics, clinical characteristics, and perioperative outcomes were analyzed for each group separately and compared. No significant differences were observed in length of hospital stay (p = 0.22), overall postoperative complications (p = 0.43), or 30-day reoperation rates (p = 0.28) across the three groups. Additional analysis of Clavien-Dindo complication grades was performed and did not show significant differences in complication severity (p = 0.95), indicating that the timing of ileostomy closure does not significantly impact perioperative complications or hospital stay. Decisions on ileostomy reversal timing should be personalized and should consider individual clinical factors, including the type of adjuvant oncological treatment and the preventive measures performed for common postoperative complications.

Clinical and social characteristics of patients with pulmonary tuberculosis and anxiety-depressive disorders

The purpose of the study was to investigate the complex interrelationships of clinical, psychopathological, and socio-psychological characteristics in patients with pulmonary tuberculosis (TB) and anxiety-depressive disorders (ADD). The study involved 145 patients: 85 patients were diagnosed with pulmonary tuberculosis (the study group) and 60 patients – with anxiety-depressive disorders without tuberculosis (the comparison group). The study assessed the level of anxiety and depressive disorders, asthenia, the nature and intensity of somatic complaints, and signs of vegetative changes; the Personal and Social Performance Scale (PSP) and the WHOQOL-BREF questionnaire were used. A cluster analysis of clinical and social factors in patients with tuberculosis and ADD showed that they had an "infiltration" of individual psychological, socio-demographic, and clinical factors that demonstrated close affinity with each other. Notably, subjective indicators of social and physical well-being were mostly related to the clinical manifestations of ADD, while objective socio-demographic indicators showed greater affinity with the clinical manifestations of the tuberculosis process. In the comparison group, a more significant autonomy of the studied individually and socially oriented parameters, as well as clinical factors, was revealed compared with the study group. A cluster analysis of the entire patient sample (145 patients) allowed obtaining results that complement and largely confirm the results of the analysis of the two samples (the study and the comparison groups). Almost all TB patients are concentrated in clusters characterized by the most severe clinical manifestations and impaired social functioning. TB patients were characterized by the most severe manifestations of ADD with severe asthenia, a high level of somatic complaints on the exhaustion scale, and pronounced signs of vegetative changes. Despite the good formal indicators of social adaptation (family, household), they are characterized by an extremely low level of socially oriented and social functioning and indicators of quality of life. The assessment of the parameters of quality of life and social functioning, their correlations with clinical characteristics, and the establishment of a hierarchy of their relationships should be taken into account when conducting a complex of therapeutic and rehabilitation measures for patients with pulmonary tuberculosis and ADD, which contributes to a more differentiated approach to rehabilitation and the development of optimal therapeutic strategies.

Machine Learning Predicts Unplanned Care Escalations for Post-Anesthesia Care Unit Patients during the Perioperative Period: A Single-Center Retrospective Study

Background: Despite low mortality for elective procedures in the United States and developed countries, some patients have unexpected care escalations (UCE) following post-anesthesia care unit (PACU) discharge. Studies indicate patient risk factors for UCE, but determining which factors are most important is unclear. Machine learning (ML) can predict clinical events. We hypothesized that ML could predict patient UCE after PACU discharge in surgical patients and identify specific risk factors. Methods: We conducted a single center, retrospective analysis of all patients undergoing non-cardiac surgery (elective and emergent). We collected data from pre-operative visits, intra-operative records, PACU admissions, and the rate of UCE. We trained a ML model with this data and tested the model on an independent data set to determine its efficacy. Finally, we evaluated the individual patient and clinical factors most likely to predict UCE risk. Results: Our study revealed that ML could predict UCE risk which was approximately 5% in both the training and testing groups. We were able to identify patient risk factors such as patient vital signs, emergent procedure, ASA Status, and non-surgical anesthesia time as significant variable. We plotted Shapley values for significant variables for each patient to help determine which of these variables had the greatest effect on UCE risk. Of note, the UCE risk factors identified frequently by ML were in alignment with anesthesiologist clinical practice and the current literature. Conclusions: We used ML to analyze data from a single-center, retrospective cohort of non-cardiac surgical patients, some of whom had an UCE. ML assigned risk prediction for patients to have UCE and determined perioperative factors associated with increased risk. We advocate to use ML to augment anesthesiologist clinical decision-making, help decide proper disposition from the PACU, and ensure the safest possible care of our patients.

Systemic racism and Non-Hispanic Black to Non-Hispanic White disparities in infant mortality at the county level.

To use a novel measure of systemic racism to examine its relationship with Non-Hispanic Black (NHB) to Non-Hispanic White (NHW) racial disparities in infant mortality across U.S. counties. In this cross-sectional study, a composite, multi-dimensional measure of systemic racism at the county level was developed using confirmatory factor analysis based on indicators across five dimensions of systemic racism. Using linear regression analysis, we examined the relationship between the systemic racism factor scores and the NHB to NHW racial disparities in county-level infant mortality rates. Additionally, we performed a multi-level analysis of infant mortality, with births nested within counties by running a random intercept model that controlled for factors at both the individual and county levels to take into account the clustered nature of the data. There were 325 counties that met inclusion criteria for the county level analysis and 1181 counties for the individual level analysis. Each one standard deviation increase in the Systemic Racism Index was associated with an increase of 10.4% in the Non-Hispanic Black to Non-Hispanic White infant mortality rate ratio at the county level (aOR 1.104, 95% CI [1.061-1.148]). After controlling for individual level clinical factors and county level factors, each one standard deviation increase in the systemic racism index score was associated with a decrease of 3.5% in the NHW infant mortality rate (aOR 0.965, 95% CI [0.943-0.988]). Systemic racism is significantly associated with differences between counties in the magnitude of their Non-Hispanic Black to Non-Hispanic White racial disparities in infant mortality rates.

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity.

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.

Development and validation of HPV-associated and HPV-independent penile squamous cell carcinoma prognostic nomogram.

The aim of this study was to introduce HPV-associated and HPV-independent histologic classifications to analyze prognostic factors and develop a prognostic nomogram for patients with penile squamous cell carcinoma (PSCC). Data of 1502 PSCC patients between 2010 and 2020 were accessed from the SEER database, and the patients were randomly divided into a training set and a validation set. Independent risk factors for PSCC patients prognosis were analyzed by using univariate and multivariate COX proportional hazards regression, and was used for the construction of the nomogram, and the predictive performance of the model was evaluated by C-index, calibration curve and ROC curve. Kaplan-Meier analysis was applied to explore the impact of HPV-related factors on patient survival, while propensity score matching (PSM) and inverse probability treatment weighting (IPTW) techniques were used to balance other confounding factors like individual clinical and pathological factors, and to evaluate the differences in overall survival (OS) and cause-specific survival (CSS) between subgroups. The results indicated that histologic type, Grade classification, T/M stage, surgical methods and chemotherapy were independent risk factors affecting OS and CSS in PSCC patients. In addition, age and marital status were significantly associated with OS, while lymph node metastasis was an independent prognostic factor for CSS, the validation results of the model showed that the nomogram had a superior predictive performance compared with the American Joint Committee on Cancer staging system. In addition, subgroup analyses prior to and after IPTW and PSM adjustments showed that HPV-associated group had better OS and CSS than HPV-independent group. Our study developed and validated a nomogram using a novel histologic classification and achieved satisfactory results, which can better help clinicians to predict the prognosis of penile squamous cell carcinoma patients.

Construction of a prognostic model based on memory CD4+ T cell-associated genes for lung adenocarcinoma and its applications in immunotherapy.

The association between memory CD4+ T cells and cancer prognosis is increasingly recognized, but their impact on lung adenocarcinoma (LUAD) prognosis remains unclear. In this study, using the cell-type identification by estimating relative subsets of RNA transcripts algorithm, we analyzed immune cell composition and patient survival in LUAD. Weighted gene coexpression network analysis helped identify memory CD4+ T cell-associated gene modules. Combined with module genes, a five-gene LUAD prognostic risk model (HOXB7, MELTF, ABCC2, GNPNAT1, and LDHA) was constructed by regression analysis. The model was validated using the GSE31210 data set. The validation results demonstrated excellent predictive performance of the risk scoring model. Correlation analysis was conducted between the clinical information and risk scores of LUAD samples, revealing that LUAD patients with disease progression exhibited higher risk scores. Furthermore, univariate and multivariate regression analyses demonstrated the model independent prognostic capability. The constructed nomogram results demonstrated that the predictive performance of the nomogram was superior to the prognostic model and outperformed individual clinical factors. Immune landscape assessment was performed to compare different risk score groups. The results revealed a better prognosis in the low-risk group with higher immune infiltration. The low-risk group also showed potential benefits from immunotherapy. Our study proposes a memory CD4+ T cell-associated gene risk model as a reliable prognostic biomarker for personalized treatment in LUAD patients.

Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study

Schizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenia’s alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work outlines potential pathways to better understand macroscale structural alterations, and inter- individual variability in schizophrenia.

Assessment of the incidence and risk factors of postoperative urosepsis in patients undergoing ureteroscopic lithotripsy.

Ureteroscopic lithotripsy (URSL) is an approved, minimally invasive, low-risk procedure for urolithiasis treatment. However, some patients may develop urinary tract infection (UTI) post-procedure, eventually leading to urosepsis. Determining the predictors of infection after URSL would help identify patients at a high risk of urosepsis, thereby enabling the early implementation of effective treatment. Therefore, we aimed to establish the incidence and predictors of urosepsis after URSL. We assessed 231 patients who underwent URSL using a holmium laser. The incidence of urosepsis during the 30-day post-treatment period was analysed, and potential predictors of urosepsis, including patient characteristics and individual clinical factors, were examined. Statistical analysis revealed that 16.88% of patients had a confirmed positive urine culture before the procedure. Post-procedure urosepsis occurred in 4.76% of patients. Univariable analysis revealed that 3 factors were significantly associated with the risk of postoperative urosepsis: double-J stent insertion before URSL, pre-operative positive urine culture, and MDR pathogen found preoperatively. In multivariable analysis, only positive urine culture remained significantly associated with the risk of urosepsis after URSL. Patients with positive urine culture before URSL are at significantly higher risk of urosepsis in the postoperative period. Hence, urine culture should be routinely performed before planned endoscopic urolithiasis treatment.

Development and Validation of a Nomogram for the Failed Conversion of Labor Analgesia to Cesarean Section Anesthesia.

The conversion of epidural labor analgesia (ELA) to epidural surgical anesthesia (ESA) for intrapartum cesarean section (CS) often encounters failures. This study aimed to develop a nomogram for predicting the failure rate of this conversion. A retrospective analysis was conducted on data from the Fujian Maternity and Child Health Hospital. Pregnant women (n=214) who underwent cesarean section after receiving labor analgesia. We performed correlation heat map and Lasso regression in terms of exclusion confounding factors and screening independent variables. A nomogram was developed to predict the occurrence. The developed nomogram incorporated variables such as pregnant history, weight, premature rupture of membranes (PROM), dural puncture epidural (DPE), anesthesiologist level of cesarean section (ALOCS), and Anesthesiologist level of labor analgesia (ALOLA). The model demonstrated good predictive performance, providing a practical tool for assessing the risk of failure in converting labor analgesia to cesarean section anesthesia. The nomogram can aid anesthesiologists in making informed decisions and optimizing patient care. By utilizing the nomogram, clinicians can estimate the probability of conversion failure based on individual patient characteristics and clinical factors.

Pretreatment Fibrinogen Level Is a Prognostic Factor for Esophageal Cancer Patients Who Receive Curative Treatment.

Pretreatment fibrinogen levels are a promising prognostic marker for some malignancies. The aim of the present study was to evaluate the clinical impact of fibrinogen levels before treatment in patients with esophageal cancer who underwent curative resection. This study included 123 patients who underwent curative treatment for esophageal cancer between 2005 and 2020. The prognosis and clinicopathological parameters in the high fibrinogen and low fibrinogen groups were analyzed. Overall survival (OS) stratified by individual clinical factors was compared using the log-rank test, and a significant difference was observed when a pretreatment fibrinogen level of 400 g/dl was used as a cutoff value. The comparison of the patient background factors between the high fibrinogen (400 g/dl) and low fibrinogen (<400 g/dl) groups revealed significant differences in pathological T status and lymph node metastasis. In the low fibrinogen group, the OS rates at 3 and 5 years after surgery (71.4% and 58.1%, respectively) were significantly higher than those in the high fibrinogen group (38.3% and 32.4%, respectively). Univariate and multivariate analyses for OS showed that the fibrinogen level prior to treatment was a significant prognostic factor. Similar results were observed for recurrence-free survival. In addition, when the first recurrence site was compared, there were marginally significant differences in hematologic recurrence. Pretreatment fibrinogen levels are a significant risk factor in patients with esophageal cancer. Therefore, pretreatment fibrinogen levels are a promising prognostic factor for patients with esophageal cancer.

Real-World Evaluation of an Automated Algorithm to Detect Patients With Potentially Undiagnosed Hypertension Among Patients With Routine Care in Hawai'i.

This real-world evaluation considers an algorithm designed to detect patients with potentially undiagnosed hypertension, receiving routine care, in a large health system in Hawai'i. It quantifies patients identified as potentially undiagnosed with hypertension; summarizes the individual, clinical, and health system factors associated with undiagnosed hypertension; and examines if the COVID-19 pandemic affected detection. We analyzed the electronic health records of patients treated across 6 clinics from 2018 to 2021. We calculated total patients with potentially undiagnosed hypertension and compared patients flagged for undiagnosed hypertension to those with diagnosed hypertension and to the full patient panel across individual characteristics, clinical and health system factors (eg, clinic of care), and timing. Modified Poisson regression was used to calculate crude and adjusted risk ratios. Among the eligible patients (N=13 364), 52.6% had been diagnosed with hypertension, 2.7% were flagged as potentially undiagnosed, and 44.6% had no evidence of hypertension. Factors associated with a higher risk of potentially undiagnosed hypertension included individual characteristics (ages 40-84 compared with 18-39 years), clinical (lack of diabetes diagnosis) and health system factors (clinic site and being a Medicaid versus a Medicare beneficiary), and timing (readings obtained after the COVID-19 Stay-At-Home Order in Hawai'i). This evaluation provided evidence that a clinical algorithm implemented within a large health system's electronic health records could detect patients in need of follow-up to determine hypertension status, and it identified key individual characteristics, clinical and health system factors, and timing considerations that may contribute to undiagnosed hypertension among patients receiving routine care.

Factors affecting adherence to psychotropics in trauma-affected refugees: data from a randomized controlled trial

Non-adherence to psychotropic drugs may reduce treatment effectiveness and may cause exacerbation of illness. Among migrant populations, studies have identified low adherence to psychotropic drugs. This study aimed to identify factors that were associated with the three basic components of adherence: non-initiation, non-implementation (blood sample), and discontinuation in a clinical sample of trauma-affected refugees diagnosed with posttraumatic stress disorder. The data for this study is derived from a randomized controlled trial (n = 108). Based on existing literature, individual sociodemographic and clinical candidate predictor variables that may affect the initiation, continuation, and implementation to psychotropics were selected as exposure variables. Logistic regression was used to assess the risk relation between non-initiation, non-implementation, discontinuation, and the individual sociodemographic and clinical factors. Three factors – level of education, turn-up rate for medical doctor sessions, and discomfort in relation to the psychotropics – were associated with non-initiation, non-implementation, or discontinuation. The relatively small sample size poses a limitation. Furthermore, factors not examined in the current study may have affected non-initiation, non-implementation, and discontinuation. The study identified level of education, turn-up rate for medical doctor sessions, and discomfort in relation to medicine as important factors in relation to treatment with psychotropics in trauma-affected refugees. Factors contributing to a low turn-up rate, and factors that are consequences of a low turn-up rate, as well as communication and trust in the patient-provider interaction need further research attention. Furthermore, there is a need for research on interventions addressing adherence for refugees with mental illness.

Abstract 12275: Neighborhood Deprivation Predicts All-Cause and Cardiovascular Mortality in a Low-Income Population in the Southeastern United States

Background: Neighborhood disadvantage impacts individuals’ morbidity and mortality and contributes to health disparities, but prospective cohort data from individuals of low socioeconomic status (SES) are limited. Hypothesis: Greater neighborhood deprivation associates with higher all-cause and cardiovascular (CV) mortality beyond individual SES, lifestyle, and clinical factors in a multi-racial, low-income population. Methods: The Southern Community Cohort Study is a population-based cohort of mostly low SES individuals recruited from 12 southeastern US states between 2002-2009. Participant addresses were linked with a census tract-based neighborhood deprivation index (NDI) derived from neighborhood level income, education, employment, housing, and occupation data. Date and cause of death were ascertained via the National Death Index. Cox proportional hazard models were used to test associations between NDI and death adjusted for enrollment age, sex, self-reported race, education, income, insurance, smoking, physical activity, alcohol intake, diet, sleep duration, BMI, and diabetes, hypertension, depression, cancer, heart disease, and stroke. Results: Among 79,631 participants, median age was 51 years (25 th -75 th percentiles: 45-58), 69% were Black, and 60% were female. Over a median 13-year follow-up, 23,356 participants died, of which 7,214 (30.9%) were CV. With adjustment for age, sex, and race, per standard deviation (SD) increase in NDI was associated with a 19% increase in all-cause mortality (HR 1.19, 95% CI 1.18-1.21) and 16% increase in CV mortality (HR 1.16, 95% CI 1.13-1.19). Even with adjustment for individual SES, lifestyle, and clinical factors, NDI was associated with a 6% increased risk in all-cause mortality (HR per SD increase 1.06, 95% CI 1.03-1.08) and 8% increase in CV mortality (HR 1.08, 95% CI 1.05-1.11). NDI showed similar significant associations with all-cause and CV mortality in Black and White participants. Conclusion: Among low-income Americans, greater neighborhood deprivation associates with higher all-cause and CV mortality independent of individual SES, lifestyle, and clinical risk factors. More research is needed to examine factors underlying the health effects of neighborhood deprivation.

Determining patient preferences for the medical management of osteoporosis using conjoint analysis

SummaryWe used conjoint analysis—a method that assesses complex decision making—to quantify patients’ choices when selecting an osteoporosis therapy. While 60% of people prioritized medication efficacy when deciding among treatments, the remaining 40% highly valued factors other than efficacy, suggesting the need for personalized shared decision-making tools.IntroductionIn this study, we aimed to examine patient decision-making surrounding osteoporosis medications using conjoint analysis.MethodsWe enrolled osteoporosis patients at an academic medical center to complete an online conjoint exercise which calculated each patient’s relative importance score of 6 osteoporosis medication attributes (higher = greater relative importance in decision-making). We used latent class analysis to identify distinct segments of patients with similar choice patterns and then used logistic regression to determine if demographics and osteoporosis disease features were associated with latent class assignment.ResultsOverall, 304 participants completed the survey. The rank order of medication attributes by importance score was the following: efficacy at preventing hip fractures (accounted for 31.0% of decision making), mode of administration (17.5%); risk of serious side effects (16.6%); dose frequency (13.9%); efficacy at preventing spine fractures (12.5%); risk of non-serious side effects (8.4%). We found that 60.9% of the cohort prioritized medication efficacy as their top factor when selecting among the therapies. Being a college graduate, having stronger beliefs on the necessity of using medications for osteoporosis, and never having used osteoporosis medicines were the only factors associated with prioritizing medication efficacy for fracture prevention over the other factors in the decision-making process.ConclusionsWhile about 60% of patients prioritized efficacy when selecting an osteoporosis therapy, the remaining 40% valued other factors more highly. Furthermore, individual patient characteristics and clinical factors did not reliably predict patient decision making, suggesting that development and implementation of shared decision-making tools is warranted.

Integrated approach to pharmacotherapy in smoking cessation: the role of varenicline, bupropion, cytisine, and nicotine replacement therapy

Introduction: Smoking tobacco is a significant global health issue, contributing to various diseases, including heart disease, cancer, and respiratory disorders. Quitting smoking is not only a beneficial decision for an individual's health but also for society as a whole. Pharmacological therapy plays a crucial role in the smoking cessation process by supporting and increasing the chances of success. Aim: To compare four medications used in smoking cessation: varenicline, bupropion, cytisine, and nicotine replacement therapy, in terms of their characteristics, mechanism of action, efficacy, and adverse effects. Materials and Methods: A review of available data in the PubMed database regarding medications registered in Poland for the treatment of nicotine addiction. Key Results: The efficacy of all four medications in smoking cessation was demonstrated. Individuals using varenicline, bupropion, cytisine, or nicotine replacement therapy had higher chances of quitting smoking compared to placebo groups. Specifically, varenicline showed the highest efficacy among all the medications studied. Despite a high level of safety profile, each therapy can cause various adverse effects, with the most serious being the risk of seizures associated with bupropion. Conclusions: Varenicline, bupropion, cytisine, and nicotine replacement therapy are valuable tools in the process of smoking cessation and increase the chances of successfully quitting the addiction. The choice of a specific medication may depend on individual patient preferences and clinical factors. These findings should be taken into consideration when making therapeutic decisions in the field of smoking cessation.