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Nevin Manimala Statistics

Frailty and checkpoint inhibitor toxicity in older patients with melanoma

Cancer. 2022 Apr 19. doi: 10.1002/cncr.34230. Online ahead of print.

ABSTRACT

BACKGROUND: Immune checkpoint inhibitors (ICIs) can cause immune-related adverse events (irAEs) that range from mild to life-threatening. Age itself does not seem to be a predictor for the occurrence of irAEs. It is unknown whether frailty plays a role in the occurrence of irAEs. Therefore, the authors assessed whether irAEs and their sequelae occur more often in frail patients than in fit patients according to the Geriatric 8 (G8) assessment.

METHODS: Patients with melanoma aged 70 years and older who were about to start ICI therapy and were screened with the G8 assessment were enrolled in this prospective, observational study. Patients were classified by the G8 as either fit or frail. The primary outcome was the occurrence of grade ≥3 irAEs.

RESULTS: In total, 92 patients were included for statistical analyses, 26 (29%) of whom were classified as frail. Grade ≥3 irAEs occurred in 20% of patients. There was no significant difference in the occurrence of grade ≥3 irAEs between fit and frail patients (17% vs 27%; P = .26). Frail patients were admitted to the hospital because of irAEs significantly more often than fit patients (29% vs 54%; P = .02) and showed a trend toward increased length of hospitalization (5 vs 8 days; P = .06) and more frequent use of immunosuppressants or ICI discontinuation for irAEs (36% vs 58%; P = .06).

CONCLUSIONS: Although frailty appears to be unrelated to the occurrence of severe irAEs, it is an indicator of irAE-related adverse sequelae, such as hospital admission. Screening for frailty can be of added value in the shared decision-making process for older patients who qualify for ICI treatment.

PMID:35439334 | DOI:10.1002/cncr.34230

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Nevin Manimala Statistics

Health Care Navigation of Black and White Adolescents After Sport-Related Concussion: A Path Toward Health Equity

J Athl Train. 2022 Apr 1;57(4):352-359. doi: 10.4085/1062-6050-0330.21.

ABSTRACT

CONTEXT: Care-seeking behaviors for sport-related concussion (SRC) are not consistent across demographic subgroups. Not only may these differences stem from health inequities, but they can perpetuate disparities in care for SRCs.

OBJECTIVE: To determine whether racial differences existed in the care pathway from injury to SRC clinic of adolescent athletes.

DESIGN: Retrospective cohort study.

SETTING: Regional SRC center.

PATIENTS OR OTHER PARTICIPANTS: Of 582 total athletes, 96 (16.5%) Black and 486 (83.5%) White adolescent athletes were diagnosed with SRC and evaluated within 3 months at the SRC clinic.

MAIN OUTCOME MEASURE(S): Race was the defined exposure, dichotomized as Black or White. The 4 primary outcomes were (1) location of the first health system contact, (2) time from injury to the first health system contact, (3) time to the in-person SRC clinic visit, and (4) whether the athlete established care (>1 visit), was released immediately to an athletic trainer, or was lost to follow-up.

RESULTS: Black and White athletes mostly presented directly to the SRC clinic (61.5% versus 62.3%) at a median (interquartile range) of 3 (1-5) and 4 (1-8) days, respectively (P = .821). Similar proportions of Black and White athletes also first presented to the emergency department (30.2% and 27.2%) at a median of 0 (0-1) versus 0 (0-1) days, respectively (P = .941). Black athletes more frequently had care transferred to their athletic trainer than White athletes (39.6% versus 29.6%) and less frequently established care (56.3% versus 64.0%), respectively; however, these differences were not statistically significant (P = .138). Loss to follow-up was uncommon among Black (4.2%) and White (6.4%) athletes alike.

CONCLUSIONS: Within an established SRC referral network and multidisciplinary clinic, no racial disparities were observed in how athletes were initially managed or ultimately presented to the SRC clinic despite racial differences in school type and insurance coverage. The SRC center assimilation and affiliation with school systems may be helpful in improving access and providing equitable care across diverse patient demographics.

PMID:35439315 | DOI:10.4085/1062-6050-0330.21

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Nevin Manimala Statistics

Predicting Anterior Cruciate Ligament Reinjury From Return-to-Activity Assessments at 6 Months Postsurgery: A Prospective Cohort Study

J Athl Train. 2022 Apr 1;57(4):325-333. doi: 10.4085/1062-6050-0407.20.

ABSTRACT

CONTEXT: Return-to-activity (RTA) assessments are commonly administered after anterior cruciate ligament reconstruction (ACLR) to manage the patient’s postoperative progressions back to activity. To date, few data are available on the clinical utility of these assessments to predict patient outcomes such as secondary anterior cruciate ligament (ACL) injury once the athlete has returned to activity.

OBJECTIVE: To identify the measures of patient function at 6 months post-ACLR that best predict RTA and second ACL injury at a minimum of 2 years after ACLR.

DESIGN: Prospective cohort study.

SETTING: Laboratory.

PATIENTS OR OTHER PARTICIPANTS: A total of 234 patients with primary, unilateral ACLR completed functional assessments at approximately 6 months post-ACLR. Of these, 192 (82.1%) completed follow-up at ≥2 years post-ACLR.

MAIN OUTCOME MEASURE(S): The 6-month functional assessments consisted of patient-reported outcomes, isokinetic knee-flexor and -extensor strength, and single-legged hopping. We collected RTA and secondary ACL injury data at ≥2 years after ACLR.

RESULTS: Of the patients who were able to RTA (n = 155), 44 (28.4%) had a subsequent ACL injury, 24 (15.5%) to the ipsilateral graft ACL and 20 (12.9%) to the contralateral ACL. A greater proportion of females had a secondary injury to the contralateral ACL (15/24, 62.5%), whereas a greater proportion of males reinjured the ipsilateral ACL graft (15/20, 75.0%; P = .017). Greater knee-extension symmetry at 6 months increased the probability of reinjury (B = 0.016, P = .048). Among patients with RTA at <8 months, every 1% increase in quadriceps strength symmetry at 6 months increased the risk of reinjury by 2.1% (B = 0.021, P = .05). Among patients with RTA at >8 months, every month that RTA was delayed reduced the risk of reinjury by 28.4% (B = -0.284, P = .042). Descriptive statistics of patient function stratified between the early and delayed RTA groups can be found in the Supplemental Table (available online at http://dx.doi.org/10.4085/1062-6050-0407.20.S1).

CONCLUSIONS: Patients with more symmetric quadriceps strength at 6 months post-ACLR were more likely to experience another ACL rupture, especially those who returned to sport at <8 months after the index surgery. Clinicians should be cognizant that returning high-functioning patients to activity at <8 months post-ACLR may place them at an increased risk for reinjury.

PMID:35439312 | DOI:10.4085/1062-6050-0407.20

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Nevin Manimala Statistics

Population genomics of New Zealand pouched lamprey (kanakana; piharau; Geotria australis)

J Hered. 2022 Apr 19:esac014. doi: 10.1093/jhered/esac014. Online ahead of print.

ABSTRACT

Pouched lamprey (Geotria australis) or kanakana/piharau is a culturally and ecologically significant jawless fish that is distributed throughout Aotearoa New Zealand. Despite its importance, much remains unknown about historical relationships and gene flow between populations of this enigmatic species within New Zealand. To help inform management, we assembled a draft Geotria australis genome and completed the first comprehensive population genomics analysis of pouched lamprey within New Zealand using targeted gene sequencing (Cyt-b and COI) and restriction site-associated DNA sequencing (RADSeq) methods. Employing 16,000 genome-wide single nucleotide polymorphisms (SNPs) derived from RADSeq (n=186) and sequence data from Cyt-b (766 bp, n=94) and COI (589 bp, n=20), we reveal low levels of structure across 10 sampling locations spanning the species range within New Zealand. F-statistics, outlier analyses, and STRUCTURE suggest a single panmictic population, and Mantel and EEMS tests reveal no significant isolation by distance. This implies either ongoing gene flow among populations or recent shared ancestry among New Zealand pouched lamprey. We can now use the information gained from these genetic tools to assist managers with monitoring effective population size, managing potential diseases, and conservation measures such as artificial propagation programs. We further demonstrate the general utility of these genetic tools for acquiring information about elusive species.

PMID:35439308 | DOI:10.1093/jhered/esac014

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Nevin Manimala Statistics

Cost-effectiveness of a medication event monitoring system for tuberculosis management in Morocco

PLoS One. 2022 Apr 19;17(4):e0267292. doi: 10.1371/journal.pone.0267292. eCollection 2022.

ABSTRACT

BACKGROUND: Digital health technologies have been used to enhance adherence to TB medication, but the cost-effectiveness remains unclear.

METHODS: We used the real data from the study conducted from April 2014 to December 2020 in Morocco using a smart pillbox with a web-based medication monitoring system, called Medication Event Monitoring Systems (MEMS). Cost-effectiveness was evaluated using a decision analysis model including Markov model for Multi-drug resistant (MDR) TB from the health system perspective. The primary outcome was the incremental cost-effectiveness ratio (ICER) per disability adjusted life-year (DALY) averted. Two-way sensitive analysis was done for the treatment success rate between MEMS and standard of care.

RESULTS: The average total per-patient health system costs for treating a new TB patient under MEMS versus standard of care were $398.70 and $155.70, respectively. The MEMS strategy would reduce the number of drug-susceptible TB cases by 0.17 and MDR-TB cases by 0.01 per patient over five years. The ICER of MEMS was $434/DALY averted relative to standard of care, and was most susceptible to the TB treatment success rate of both strategies followed by the managing cost of MEMS.

CONCLUSION: MEMS is considered cost-effective for managing infectious active TB in Morocco.

PMID:35439273 | DOI:10.1371/journal.pone.0267292

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Nevin Manimala Statistics

Predicting diarrhoea outbreaks with climate change

PLoS One. 2022 Apr 19;17(4):e0262008. doi: 10.1371/journal.pone.0262008. eCollection 2022.

ABSTRACT

BACKGROUND: Climate change is expected to exacerbate diarrhoea outbreaks across the developing world, most notably in Sub-Saharan countries such as South Africa. In South Africa, diseases related to diarrhoea outbreak is a leading cause of morbidity and mortality. In this study, we modelled the impacts of climate change on diarrhoea with various machine learning (ML) methods to predict daily outbreak of diarrhoea cases in nine South African provinces.

METHODS: We applied two deep Learning DL techniques, Convolutional Neural Networks (CNNs) and Long-Short term Memory Networks (LSTMs); and a Support Vector Machine (SVM) to predict daily diarrhoea cases over the different South African provinces by incorporating climate information. Generative Adversarial Networks (GANs) was used to generate synthetic data which was used to augment the available data-set. Furthermore, Relevance Estimation and Value Calibration (REVAC) was used to tune the parameters of the ML methods to optimize the accuracy of their predictions. Sensitivity analysis was also performed to investigate the contribution of the different climate factors to the diarrhoea prediction method.

RESULTS: Our results showed that all three ML methods were appropriate for predicting daily diarrhoea cases with respect to the selected climate variables in each South African province. However, the level of accuracy for each method varied across different experiments, with the deep learning methods outperforming the SVM method. Among the deep learning techniques, the CNN method performed best when only real-world data-set was used, while the LSTM method outperformed the other methods when the real-world data-set was augmented with synthetic data. Across the provinces, the accuracy of all three ML methods improved by at least 30 percent when data augmentation was implemented. In addition, REVAC improved the accuracy of the CNN method by about 2.5% in each province. Our parameter sensitivity analysis revealed that the most influential climate variables to be considered when predicting outbreak of diarrhoea in South Africa were precipitation, humidity, evaporation and temperature conditions.

CONCLUSIONS: Overall, experiments indicated that the prediction capacity of our DL methods (Convolutional Neural Networks) was found to be superior (with statistical significance) in terms of prediction accuracy across most provinces. This study’s results have important implications for the development of automated early warning systems for diarrhoea (and related disease) outbreaks across the globe.

PMID:35439258 | DOI:10.1371/journal.pone.0262008

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Prevalence of Burnout Among Cardiothoracic Radiologists: Stress Factors, Career Satisfaction, and Modality-specific Imaging Volumes

J Thorac Imaging. 2022 May 1;37(3):194-200. doi: 10.1097/RTI.0000000000000638. Epub 2022 Jan 28.

ABSTRACT

PURPOSE: We investigated the impact of modality-specific volumes and other potential stressors on burnout and career-choice satisfaction.

MATERIALS AND METHODS: An anonymous survey of 36 questions was sent by email to all 875 faculty members of the STR. These included 11 multiple-choice questions, 23 Likert questions, and 2 free-text questions. The Maslach Burnout Index was used to assess the prevalence of the 3 components of burnout (emotional exhaustion, depersonalization, and low professional accomplishment), and we assessed variations among the potential sources of stress with respect to the respondent sex, career stage, and practice setting. Respondents were asked to estimate daily work volume as if interpreting only chest radiographs (CXRs) or only chest/cardiac computed tomography (CT). Statistical analysis was performed using Excel (Microsoft), open-source statistical computing package pandas and SciPy for Python, and Jupyter Notebook, an open-source interactive computing platform.

RESULTS: Although financial concerns (49.3%), lack of input into decisions (48.6%), and inadequate staffing (45.2%) were additional stressors, the major sources were work-life balance (67.4%) and workload (66.8%), which were more frequently cited by women than men (78.9% vs. 60.8%, P=0.001). Emotional exhaustion and depersonalization were related to higher CXR volumes. Although 83.2% were satisfied being a diagnostic radiologist, 18.8% had thought of leaving medicine. More than half of all radiologists interpreted ≥150 CXRs daily (51.1% vs. 53.6%); more in private practice read ≥200 CXRs (23.2% vs. 14.7%). Of the academic radiologists, 80.2% interpreted 21 to 49 CTs; twice as many in private practice read ≥50 CTs (25.5% vs. 12.7%).

CONCLUSIONS: The contributing factors to cardiothoracic radiologist burnout vary by sex, career stage, and practice setting. Several stressors, especially work-life balance, were associated with higher burnout prevalence. Most respondents expressed career-choice satisfaction. Defining threshold work volumes associated with higher rates of burnout is an important first step in defining burnout prevention guardrails.

PMID:35439240 | DOI:10.1097/RTI.0000000000000638

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Nevin Manimala Statistics

Factors Affecting the Health-Related Quality of Life of Cancer Survivors According to Metabolic Syndrome

Cancer Nurs. 2022 Apr 12. doi: 10.1097/NCC.0000000000001098. Online ahead of print.

ABSTRACT

BACKGROUND: Cancer survivors face an increased risk of non-cancer-related deaths, particularly associated with metabolic syndrome. With increased cancer survivors having metabolic syndrome, health-related quality of life beyond cancer diagnosis and treatment has assumed greater importance.

OBJECTIVE: This study evaluated the prevalence rate of metabolic syndrome in cancer survivors. It examined the correlation between health-related quality of life and influencing factors according to the prevalence of metabolic syndrome.

METHODS: This is a cross-sectional national study using secondary data from the 2010-2018 Korean National Health and Nutrition Examination Survey by the Korea Disease Control and Prevention Agency. We analyzed a final sample of 1293 cancer survivors using multiple regression.

RESULTS: The prevalence rate of metabolic syndrome in cancer survivors was measured at 32.1%. Cancer survivors with metabolic syndrome had a lower health-related quality of life than those without it. The difference was statistically significant. Compared with cancer survivors without metabolic syndrome, those with it experienced substantial negative effects from stress, reducing health-related quality of life. Walking and muscle-building workouts had a positive effect on stress and improved quality of life.

CONCLUSIONS: Cancer survivors’ metabolic syndrome should be monitored closely. Development of a customized intervention program including stress management and physical activities improves their health-related quality of life.

IMPLICATIONS FOR PRACTICE: Stress management and physical activities increase health-related quality of life among cancer survivors with metabolic syndrome; thus, healthcare providers should implement intervention programs that promote exercise engagement and stress management for this population.

PMID:35439201 | DOI:10.1097/NCC.0000000000001098

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Nevin Manimala Statistics

Exploiting Sparse Self-Representation and Particle Swarm Optimization for CNN Compression

IEEE Trans Neural Netw Learn Syst. 2022 Apr 19;PP. doi: 10.1109/TNNLS.2022.3165530. Online ahead of print.

ABSTRACT

Structured pruning has received ever-increasing attention as a method for compressing convolutional neural networks. However, most existing methods directly prune the network structure according to the statistical information of the parameters. Besides, these methods differentiate the pruning rates only in each pruning stage or even use the same pruning rate across all layers, rather than using learnable parameters. In this article, we propose a network redundancy elimination approach guided by the pruned model. Our proposed method can easily tackle multiple architectures and is scalable to the deeper neural networks because of the use of joint optimization during the pruning procedure. More specifically, we first construct a sparse self-representation for the filters or neurons of the well-trained model, which is useful for analyzing the relationship among filters. Then, we employ particle swarm optimization to learn pruning rates in a layerwise manner according to the performance of the pruned model, which can determine optimal pruning rates with the best performance of the pruned model. Under this criterion, the proposed pruning approach can remove more parameters without undermining the performance of the model. Experimental results demonstrate the effectiveness of our proposed method on different datasets and different architectures. For example, it can reduce 58.1% FLOPs for ResNet50 on ImageNet with only a 1.6% top-five error increase and 44.1% FLOPs for FCN_ResNet50 on COCO2017 with a 3% error increase, outperforming most state-of-the-art methods.

PMID:35439146 | DOI:10.1109/TNNLS.2022.3165530

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Population growth and competition models with decay and competition consistent delay

J Math Biol. 2022 Apr 19;84(5):39. doi: 10.1007/s00285-022-01741-3.

ABSTRACT

We derive an alternative expression for a delayed logistic equation in which the rate of change in the population involves a growth rate that depends on the population density during an earlier time period. In our formulation, the delay in the growth term is consistent with the rate of instantaneous decline in the population given by the model. Our formulation is a modification of Arino et al. (J Theor Biol 241(1):109-119, 2006) by taking the intraspecific competition between the adults and juveniles into account. We provide a complete global analysis showing that no sustained oscillations are possible. A threshold giving the interface between extinction and survival is determined in terms of the parameters in the model. The theory of chain transitive sets and the comparison theorem for cooperative delay differential equations are used to determine the global dynamics of the model. We extend our delayed logistic equation to a system modeling the competition between two species. For the competition model, we provide results on local stability, bifurcation diagrams, and adaptive dynamics. Assuming that the species with shorter delay produces fewer offspring at a time than the species with longer delay, we show that there is a critical value, [Formula: see text], such that the evolutionary trend is for the delay to approach [Formula: see text].

PMID:35438310 | DOI:10.1007/s00285-022-01741-3