Category: Statistics

Exp Dermatol. 2023 Aug 16. doi: 10.1111/exd.14904. Online ahead of print.

ABSTRACT

The risk of diabetes mellitus (DM) in vitiligo patients is higher than that in non-vitiligo population. Our goal was to explore the influencing factors for DM in vitiligo patients. A matched-pair design of 107 cases with DM and 428 controls without DM was conducted among vitiligo patients in Xijing hospital from January 2010 to October 2021. The baseline characteristics of patients were analysed based on standard descriptive statistics. The vitiligo-associated characteristics were analysed by logistic regression to identify influencing factors of DM. Interaction analysis was performed to explore the additive interactions between vitiligo-associated characteristics and baseline characteristics. After adjustment for the baseline characteristics, the severity of vitiligo [odds ratio (OR) = 2.47, 95% confidence interval (CI): 1.47-4.14] and onset age of vitiligo (OR = 0.98, 95% CI: 0.97-0.99) had a significant correlation with occurrence of DM. The severity of vitiligo had additive interaction with family history of diabetes [relative excess risk due to interaction (RERI) = 132.51 (95% CI: 5.51-1100.20), attributable proportion (AP) = 0.91 (95% CI: 0.17-0.95), synergy index (S) = 11.53 (95% CI: 1.32-100.5)] and with smoking history [RERI = 6.54 (95% CI: 0.67-19.83), AP = 0.64 (95% CI: 0.04-0.80), S = 3.48 (95% CI: 1.17-10.36)]. Earlier onset age of vitiligo and greater BSA involvement might be two independent risk factors for DM in vitiligo patients. Interaction assessment identified the severity of vitiligo as additive interaction factors with diabetes family history and with smoking history for the DM occurrence.

PMID:37584091 | DOI:10.1111/exd.14904

Cancer Commun (Lond). 2023 Aug 16. doi: 10.1002/cac2.12478. Online ahead of print.

NO ABSTRACT

PMID:37584087 | DOI:10.1002/cac2.12478

Hong Kong Physiother J. 2023 Jun;43(1):53-60. doi: 10.1142/S1013702523500075. Epub 2023 Mar 31.

ABSTRACT

BACKGROUND: Low-back pain (LBP) continues to be one of the main problems for which sufferers seek treatment in primary care. It can be treated with different physiotherapy mechanisms.

OBJECTIVE: The purpose of the study is to compare the effect of isotonic and isometric exercise on the reported pain of patients with low back pain.

METHODS: Thirty participants, 16 males and 14 females aged between 22 and 50 years suffering from nonspecific low back pain were included. The sample was divided randomly into two groups, group A isometric exercises and group B isotonic exercises, both groups received conservative therapy of TENS and infrared (IR) therapy. The following outcome measures were used: Visual analogue scale, modified Oswestry disability index (MODI) and Endurance Test Measurement were administered pre-treatment and at the end of four weeks of treatment.

RESULTS: Both groups were comparable in terms of demographic data, except for weight. Inter group analysis was done using the Mann-Whitney test. When comparing pre- and post-treatments using VAS scores, there were no significant differences between group A and group B (pre-test: $P=0.285$; Post-test: $P=0.838$). Mann-Whitney test was used to calculate the P-value test between pre-treatment and post- treatment for MODI and there was no significant difference between group A and group B, where the pre-test P-value was 0.061, and post-treatment was 0.077. Comparing between groups, pre- and post-abdominal endurance scores were done using the Mann-Whitney test. The pre-treatment scores revealed P value of 0.345, and the post-treatment scores revealed P value of 0.305. Therefore, there is no statistically significant difference between group A and group B in endurance scores.

CONCLUSION: There was no difference between the use isotonic and isometric exercises on LBP patients.

PMID:37584053 | PMC:PMC10423680 | DOI:10.1142/S1013702523500075

Hong Kong Physiother J. 2023 Jun;43(1):61-71. doi: 10.1142/S1013702523500087. Epub 2023 Mar 31.

ABSTRACT

BACKGROUND: Lower Back Pain (LBP) with radiculopathy is a potentially more serious form of mechanical low back pain. A paucity of literature exists about the effect of the gross myofascial release (MFR) technique on the management of LBP.

OBJECTIVE: The study aimed to evaluate the effect of gross MFR when given as an adjunct to conventional physical therapy in subjects with low back pain with radiculopathy.

METHODS: Forty subjects ($n=40$) clinically diagnosed with LBP with radiculopathy were enrolled and randomly allocated to either the control group ($n=20$) or the experimental group ($n=20$). Both study groups received 5 sessions of intervention. The control group received conventional physical therapy while the experimental group received gross MFR of the trunk and lower limb along with conventional physical therapy. The outcome measures included were pressure pain threshold for the lower back and lower extremity, lumbar flexion and extension range of motion (ROM), percentage disability, and patient satisfaction towards the treatment which were measured pre-intervention (day 1) and post-treatment (day 5). The interaction between group and time was analysed using two-way mixed ANOVA.

RESULTS: The results suggested that the experimental group was statistically significant over the control group in terms of pressure pain threshold in the lower back ($p<0.001$) and lower limb ($p=0.003$), disability ($p<0.001$), and patient satisfaction ($p=0.034$) and lumbar flexion ($p=0.002$) except lumbar extension ROM ($p=0.973$).

CONCLUSION: When given as an adjuvant to conventional physical therapy, gross myofascial release proved to provide a significant and faster short-term improvement over conventional treatment alone in subjects diagnosed with low back pain with radiculopathy.

PMID:37584046 | PMC:PMC10423682 | DOI:10.1142/S1013702523500087

Proc IEEE Int Conf Acoust Speech Signal Process. 2023 Jun;2023. doi: 10.1109/icassp49357.2023.10096888. Epub 2023 May 5.

ABSTRACT

Time-series are commonly susceptible to various types of corruption due to sensor-level changes and defects which can result in missing samples, sensor and quantization noise, unknown calibration, unknown phase shifts etc. These corruptions cannot be easily corrected as the noise model may be unknown at the time of deployment. This also results in the inability to employ pre-trained classifiers, trained on (clean) source data. In this paper, we present a general framework and models for time-series that can make use of (unlabeled) test samples to estimate the noise model-entirely at test time. To this end, we use a coupled decoder model and an additional neural network which acts as a learned noise model simulator. We show that the framework is able to “clean” the data so as to match the source training data statistics and the cleaned data can be directly used with a pre-trained classifier for robust predictions. We perform empirical studies on diverse application domains with different types of sensors, clearly demonstrating the effectiveness and generality of this method.

PMID:37584045 | PMC:PMC10426275 | DOI:10.1109/icassp49357.2023.10096888

Psychol Res Behav Manag. 2023 Aug 10;16:3171-3183. doi: 10.2147/PRBM.S420711. eCollection 2023.

ABSTRACT

PURPOSE: This paper investigated the prevalence of mobile phone dependence (MPD) and its associated with learning burnout under the “double reduction” policy among adolescents in Guizhou Province in western China. In addition, the influence of the mediating mechanism of social support on this relationship was investigated.

METHODS: The sample was collected from 16,216 adolescents in West China’s Guizhou province, from December 2021 to January 2022 via multistage stratified random sampling. The Self-rating Questionnaire for Adolescent Problematic Mobile Phone Use (SQAPMPU) was used to assess the MPD, the Adolescent Student Burnout Scale (ASBI) was used to assess the learning burnout, and the Social Support Scale (SSS) was used to assess the social support. A hierarchical linear regression model was used to analyze the relationship between MPD, learning burnout, and social support. The mediating effect of social support between MPD and learning burnout was analyzed by structural equation model.

RESULTS: Prevalence of MPD was 26.4% among adolescents in Guizhou province in western China. After adjusting for confounding variables like demographics, multiple linear regression model has revealed that learning burnout positively predicted MPD and social support negatively predicted MPD. The structural equation model showed that 10.9% of the effect was explained by the mediating effect of social support.

CONCLUSION: These findings could inform service delivery and policy formulation to reduce learning and avoid MPD in adolescents.

PMID:37584040 | PMC:PMC10424684 | DOI:10.2147/PRBM.S420711

Front Hum Neurosci. 2023 Jul 31;17:1201344. doi: 10.3389/fnhum.2023.1201344. eCollection 2023.

ABSTRACT

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) on the dorsolateral prefrontal cortex (DLPFC) is an effective treatment for depression that has been proposed to work via the enhancement of cognitive control. Cognitive control training (CCT) can also alleviate depression by relying on DLPFC activation. As the additive effects of rTMS and CCT are unclear, we set out to conduct a within-subject pilot study in healthy controls.

METHODS: Seventeen participants received two sessions of individualized resting-state connectivity-guided high-frequency rTMS, while randomly performing CCT or a control task. After each session, a negative mood was induced.

RESULTS: We found effects on mood and cognitive control after rTMS + CCT as well as rTMS + control, which were indiscriminative between conditions. Based on the statistical evidence for the absence of an additive effect of CCT, we did not perform a full study.

CONCLUSION: Our results demonstrate no differential effects of single sessions combining rTMS and CCT in a healthy population, even with the methodological improvement of individualized neuronavigation. The improvement in cognitive control seen in both conditions could indicate that a simple cognitive task is sufficient when studying additive rTMS effects. Future studies should focus on augmenting the effects of various cognitive tasks and compare the present interventions with rTMS or cognitive tasks alone.

PMID:37584029 | PMC:PMC10423931 | DOI:10.3389/fnhum.2023.1201344

Heart Views. 2023 Jul-Sep;24(3):125-135. doi: 10.4103/heartviews.heartviews_91_22. Epub 2023 Jul 5.

ABSTRACT

BACKGROUND: Cardiovascular disease patients are more likely to be readmitted within 30 days of being discharged alive. This causes an enormous burden on health-care systems in terms of poor care of patients and misutilization of resources.

AIMS AND OBJECTIVE: This study aims to find out the risk factors associated with 30-day readmission in cardiac patients at Heart Hospital, Qatar.

METHODS: A total of 10,550 cardiac patients who were discharged alive within 30 days at the heart hospital in Doha, Qatar, from January 2015 and December 2019 were analyzed. The bootstrap method, an internal validation statistical technique, was applied to present representative estimates for the population.

RESULTS: Out of the 10,550 cardiac patients, there were 8418 (79.8%) index admissions and 2132 (20.2%) re-admitted at least once within 30 days after the index admission. The re-admissions group was older than the index admission group (65.6 ± 13.2 vs. 56.0 ± 13.5, P = 0.001). Multinomial regression analysis showed that females were 30% more likely to be re-admitted than males (adjusted odds ratio [aOR] 1.30, 95% confidence interval [CI]: 1.11-1.50, P = 0.001). Diabetes (aOR 1.36, 95% CI: 1.20-1.53, P = 0.001), chronic renal failure (aOR 1.93, 95% CI: 1.66-2.24, P = 0.001), previous MI (aOR 3.22, 95% CI: 2.85-3.64, P = 0.001), atrial fibrillation (aOR 2.17, 95% C.I. : 1.10-2.67, P = 0.01), cardiomyopathy (aOR 1.72, 95% CI 1.47-2.02, P = 0.001), and chronic heart failure (aOR 1.56, 95% C.I.: 1.33-1.82, P = 0.001) were also independent predictors for re-admission in the regression model. C-statistics showed these variables could predict 82% accurately hospital readmissions within 30 days after being discharged alive.

CONCLUSION: The model was more than 80% accurate in predicting 30-day readmission after being discharged alive. The presence of five or more risk factors was found to be crucial for readmissions within 30 days. The study may help design interventions that may result in better outcomes with fewer resources in the population.

PMID:37584026 | PMC:PMC10424753 | DOI:10.4103/heartviews.heartviews_91_22

World J Clin Cases. 2023 Jul 16;11(20):4824-4832. doi: 10.12998/wjcc.v11.i20.4824.

ABSTRACT

BACKGROUND: Spinal osteoporosis is a prevalent health condition characterized by the thinning of bone tissues in the spine, increasing the risk of fractures. Given its high incidence, especially among older populations, it is critical to have accurate and effective predictive models for fracture risk. Traditionally, clinicians have relied on a combination of factors such as demographics, clinical attributes, and radiological characteristics to predict fracture risk in these patients. However, these models often lack precision and fail to include all potential risk factors. There is a need for a more comprehensive, statistically robust prediction model that can better identify high-risk individuals for early intervention.

AIM: To construct and validate a model for forecasting fracture risk in patients with spinal osteoporosis.

METHODS: The medical records of 80 patients with spinal osteoporosis who were diagnosed and treated between 2019 and 2022 were retrospectively examined. The patients were selected according to strict criteria and categorized into two groups: Those with fractures (n = 40) and those without fractures (n = 40). Demographics, clinical attributes, biochemical indicators, bone mineral density (BMD), and radiological characteristics were collected and compared. A logistic regression analysis was employed to create an osteoporotic fracture risk-prediction model. The area under the receiver operating characteristic curve (AUROC) was used to evaluate the model’s performance.

RESULTS: Factors significantly associated with fracture risk included age, sex, body mass index (BMI), smoking history, BMD, vertebral trabecular alterations, and prior vertebral fractures. The final risk-prediction model was developed using the formula: (logit [P] = -3.75 + 0.04 × age – 1.15 × sex + 0.02 × BMI + 0.83 × smoking history + 2.25 × BMD – 1.12 × vertebral trabecular alterations + 1.83 × previous vertebral fractures). The AUROC of the model was 0.93 (95%CI: 0.88-0.96, P < 0.001), indicating strong discriminatory capabilities.

CONCLUSION: The fracture risk-prediction model, utilizing accessible clinical, biochemical, and radiological information, offered a precise tool for the evaluation of fracture risk in patients with spinal osteoporosis. The model has potential in the identification of high-risk individuals for early intervention and the guidance of appropriate preventive actions to reduce the impact of osteoporosis-related fractures.

PMID:37583999 | PMC:PMC10424038 | DOI:10.12998/wjcc.v11.i20.4824

Front Neurol. 2023 Jul 31;14:1230574. doi: 10.3389/fneur.2023.1230574. eCollection 2023.

ABSTRACT

BACKGROUND: Some papers have highlighted a possible causal relationship between the onset of ischemic stroke and weather conditions. This study aimed to elucidate the onset mechanism of cerebral infarction from a meteorological approach. We focused on the atmospheric pressure distribution patterns (APDPs).

METHODS: The subjects are 221 cases diagnosed as cardiogenic cerebral embolism (Group A) and 612 cases diagnosed as atherosclerotic cerebral thrombosis (Group B). We investigated the APDP on the date closest to the date and time of onset of cerebral infarction in each patient on the website and chose the most similar one from the reported 11 APDPs. Groups A and B were compared for clinical characteristics and the appearance rate of each APDP in each group.

RESULTS: The clinical characteristics of Groups A and B were consistent with some previously reported clinical characteristics of cerebral embolism and cerebral thrombosis except for smoking. The appearance rate of the other high-pressure type, which cannot be classified as either the anticyclone belt type or the migratory anticyclone type, in Group B was statistically significantly higher than that in Group A, and the appearance rate of the anticyclone belt type in Group A was statistically significantly higher than that in Group B (p < 0.05, Fisher’s exact probability method, respectively).

CONCLUSIONS: Cerebral embolism and cerebral thrombosis exhibited significant differences in APDPs on the day of onset. Dehydration particularly in the other high-pressure type or in the anticyclone belt type should be prevented. Further investigation should focus on the other meteorological factors.

PMID:37583952 | PMC:PMC10423876 | DOI:10.3389/fneur.2023.1230574