Purpose: Hemiparesis in stroke survivors has been reported to affect respiratory function. The relationship between trunk control and respiratory function, however, is not well understood. We aimed to map the state of the association between the trunk and respiratory function as well as evaluate the effect of a respiratory function training intervention on trunk control for stroke survivors. Methods: A scoping review and meta-analysis of observational and interventional studies were performed. Cochrane Library, CINAHL with Full Text (EBSCO), Medline (Ovid), and PubMed were searched using the terms stroke, respiratory, and trunk control. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) checklist was used to examine the sections of each report. Results: A total of 102 studies were identified, of which 12, published between 2011 and 2022, were included in the meta-analysis or narrative synthesis. Three studies were included in the meta-analysis of the correlation between trunk control and respiratory function parameters (forced vital capacity [FVC], forced expiratory volume during the first breath [FEV1], maximal inspiratory pressure [MIP], and maximal expiratory pressure [MEP]) with effect sizes (Fisher's z) for all outcomes, which ranged from small to intermediate (between 0.21 and 0.39). Furthermore, five studies were included in the meta-analysis of the effect of respiratory function training intervention on trunk control. An overall effect size (Cohen's d) of 1.47 corresponds to a large effect. We also found significant improvements in MIP and MEP but not in FVC and FEV1 for stroke survivors with the interventions. Conclusions Respiratory training, use of diaphragmatic resistance exercise or abdominal breathing, use of a pressure threshold-loading device, and the performance of functional strengthening exercises for the trunk muscles were found to increase patients’ trunk control and improve their respiratory muscle strength.

Background/Aims: Nonalcoholic fatty liver disease (NAFLD) is a common disease with severe inflammatory processes associated with numerous gastrointestinal diseases, such as inflammatory bowel disease (IBD). Therefore, we investigated the relationship between NAFLD and IBD and the possible risk factors associated with the diagnosis of IBD. Methods: This longitudinal nationwide cohort study investigated the risk of IBD in patients with NAFLD alone. General characteristics, comorbidities, and incidence of IBD were also compared. Results: Patients diagnosed with NAFLD had a significant risk of developing IBD compared to control individuals, who were associated with a 2.245-fold risk of the diagnosis of IBD and a 2.260- and 2.231-fold of increased diagnosis of ulcerative colitis and Crohn’s disease, respectively (P< 0.001). The cumulative risk of IBD increased annually during the follow-up of patients with NAFLD (P< 0.001). Conclusions Our results emphasize that NAFLD significantly impacts its incidence in patients with NAFLD. If patients with NAFLD present with risk factors, such as diabetes mellitus and dyslipidemia, these conditions should be properly treated with regular follow-ups. Furthermore, we believe that these causes may be associated with the second peak of IBD.

Background/Aims: Nonalcoholic fatty liver disease (NAFLD) is a common disease with severe inflammatory processes associated with numerous gastrointestinal diseases, such as inflammatory bowel disease (IBD). Therefore, we investigated the relationship between NAFLD and IBD and the possible risk factors associated with the diagnosis of IBD. Methods: This longitudinal nationwide cohort study investigated the risk of IBD in patients with NAFLD alone. General characteristics, comorbidities, and incidence of IBD were also compared. Results: Patients diagnosed with NAFLD had a significant risk of developing IBD compared to control individuals, who were associated with a 2.245-fold risk of the diagnosis of IBD and a 2.260- and 2.231-fold of increased diagnosis of ulcerative colitis and Crohn’s disease, respectively (P< 0.001). The cumulative risk of IBD increased annually during the follow-up of patients with NAFLD (P< 0.001). Conclusions Our results emphasize that NAFLD significantly impacts its incidence in patients with NAFLD. If patients with NAFLD present with risk factors, such as diabetes mellitus and dyslipidemia, these conditions should be properly treated with regular follow-ups. Furthermore, we believe that these causes may be associated with the second peak of IBD.

Background/Aims: Nonalcoholic fatty liver disease (NAFLD) is a common disease with severe inflammatory processes associated with numerous gastrointestinal diseases, such as inflammatory bowel disease (IBD). Therefore, we investigated the relationship between NAFLD and IBD and the possible risk factors associated with the diagnosis of IBD. Methods: This longitudinal nationwide cohort study investigated the risk of IBD in patients with NAFLD alone. General characteristics, comorbidities, and incidence of IBD were also compared. Results: Patients diagnosed with NAFLD had a significant risk of developing IBD compared to control individuals, who were associated with a 2.245-fold risk of the diagnosis of IBD and a 2.260- and 2.231-fold of increased diagnosis of ulcerative colitis and Crohn’s disease, respectively (P< 0.001). The cumulative risk of IBD increased annually during the follow-up of patients with NAFLD (P< 0.001). Conclusions Our results emphasize that NAFLD significantly impacts its incidence in patients with NAFLD. If patients with NAFLD present with risk factors, such as diabetes mellitus and dyslipidemia, these conditions should be properly treated with regular follow-ups. Furthermore, we believe that these causes may be associated with the second peak of IBD.

OBJECTIVE: The objective was to identify risk factors that were associated with the progression from endometriosis to ovarian cancer based on medical insurance data. METHODS: The study was performed on a dataset obtained from the National Health Insurance Research Database, which covered all the inpatient claim data from 2000 to 2013 in Taiwan. The International Classification of Diseases (ICD) code 617 was used to screen the dataset for the patients who were admitted to hospital due to endometriosis. They were then tracked for subsequent diagnosis of ovarian cancer, and available biological, socioeconomic and clinical information was also collected. Univariate and multivariate analyses were then performed based on the Cox regression model to identify risk factors. C-index was calculated and cross validated. RESULTS: A total of 229,617 patients who were admitted to hospital due to endometriosis from 2000 to 2013 were included in the study, out of whom 1,473 developed ovarian cancer by the end of 2013. A variety of factors, including age, residence, hospital stratification, premium range, and various comorbidities had significant impact on the progression (p < 0.05). Among them, age, urbanization of residence, hospital stratification, premium range, post-endometriosis childbearing, pelvic inflammation, and depression all had independent, significant impact (p < 0.05). The validated C-index was 0.69. CONCLUSION: For a woman diagnosed with endometriosis, increased age, residing in a highly urbanized area, low or high income, depression, pelvic inflammation, and absence of childbearing post-endometriosis all put her at high-risk to develop ovarian cancer. The findings may be of help to gynecologists to identify high-risk patients.
Cohort Studies* ; Comorbidity ; Dataset ; Depression ; Diagnosis ; Endometriosis* ; Female ; Humans ; Inflammation ; Inpatients ; Insurance* ; International Classification of Diseases ; Multivariate Analysis ; National Health Programs ; Ovarian Neoplasms* ; Risk Factors* ; Taiwan ; Urbanization

Purpose: Stroke survivors and their informal family caregivers may share the impact of the disease, which may affect family functioning and quality of life (QoL) for both. This study compared the perceptions of stroke survivors and informal family caregivers regarding family functioning and QoL and examined the QoL of those reporting effective versus ineffective family functioning. Methods: A cross-sectional study design and convenience sampling were used. Stroke survivoreinformal family caregiver dyads were recruited from a medical university hospital. We assessed participants’ demographic and clinical variables, including disease severity, family functioning, and QoL. Independent t-test, paired t-test, Wilcoxon signed-rank test, and ManneWhitney U test were used to analyze the data. Results: Seventy-one stroke survivoreinformal family caregiver dyads participated in the current study. Most stroke survivors and informal family caregivers reported effective family functioning, with no significant differences. However, significant differences existed in the seven domains (physical functioning, role-physical, bodily pain, general health, vitality, social functioning, and role-emotional) of QoL, except emotional health. Stroke survivors reporting ineffective family functioning had a significantly lower mental component summary score, unlike informal family caregivers. Conclusions Our findings suggest that family functioning is crucial to ensure stroke survivors’ QoL, particularly regarding their mental health. Health professionals should prioritize mental health assessments and provide appropriate care interventions for stroke survivors in the first 1e6 months after stroke onset.

Background: The initiation of sodium-glucose cotransporter-2 inhibitors (SGLT2i) typically leads to a reversible initial dip in estimated glomerular filtration rate (eGFR). The implications of this phenomenon on clinical outcomes are not well-defined. Methods: We searched MEDLINE, Embase, and Cochrane Library from inception to March 23, 2023 to identify randomized controlled trials and cohort studies comparing kidney and cardiovascular outcomes in patients with and without initial eGFR dip after initiating SGLT2i. Pooled estimates were calculated using random-effect meta-analysis. Results: We included seven studies in our analysis, which revealed that an initial eGFR dip following the initiation of SGLT2i was associated with less annual eGFR decline (mean difference, 0.64; 95% confidence interval [CI], 0.437 to 0.843) regardless of baseline eGFR. The risk of major adverse kidney events was similar between the non-dipping and dipping groups but reduced in patients with a ≤10% eGFR dip (hazard ratio [HR], 0.915; 95% CI, 0.865 to 0.967). No significant differences were observed in the composite of hospitalized heart failure and cardiovascular death (HR, 0.824; 95% CI, 0.633 to 1.074), hospitalized heart failure (HR, 1.059; 95% CI, 0.574 to 1.952), or all-cause mortality (HR, 0.83; 95% CI, 0.589 to 1.170). The risk of serious adverse events (AEs), discontinuation of SGLT2i due to AEs, kidney-related AEs, and volume depletion were similar between the two groups. Patients with >10% eGFR dip had increased risk of hyperkalemia compared to the non-dipping group. Conclusion Initial eGFR dip after initiating SGLT2i might be associated with less annual eGFR decline. There were no significant disparities in the risks of adverse cardiovascular outcomes between the dipping and non-dipping groups.

Background: Therapeutic interventions for diabetes are most effective when administered in the newly onset phase, yet determining the exact onset moment can be elusive in practice. Spontaneous autoimmune diabetes among NOD mice appears randomly between 12 and 32 weeks of age with an incidence range from 60 to 90%. Furthermore, the disease often progresses rapidly to severe diabetes within days, resulting in a very short window of newly onset phase, that poses significant challenge in early diagnosis. Conventionally, extensive blood glucose (BG) testing is typically required on large cohorts throughout several months to conduct prospective survey. We incorporated ultrasensitive urine glucose (UG) testing into an ordinary BG survey process, initially aiming to elucidate the lag period required for excessive glucose leaking from blood to urine during diabetes progression in the mouse model. Results: The observations unexpectedly revealed that small amounts of glucose detected in the urine often coincide with, sometimes even a couple days prior than elevated BG is diagnosed. Accordingly, we conducted the UG-based survey protocol in another cohort that was validated to accurately identified every individual near onset, who could then be confirmed by following few BG tests to fulfill the consecutive BG + criteria. This approach required fewer than 95 BG tests, compared to over 700 tests with traditional BG survey, to diagnose all the 37–38 diabetic mice out of total 60. The average BG level at diagnosis was slightly below 350 mg/dl, lower than the approximately 400 mg/dl observed with conventional BG monitoring. Conclusions We demonstrated a near perfect correlation between BG + and ultrasensitive UG + results in prospective survey with no lag period detected under twice weekly of testing frequency. This led to the refined protocol based on surveying with noninvasive UG testing, allowing for the early identification of newly onset diabetic mice with only a few BG tests required per mouse. This protocol significantly reduces the need for extensive blood sampling, lancet usage, labor, and animal distress, aligning with the 3Rs principle. It presents a convenient, accurate, and animal-friendly alternative for early diabetes diagnosis, facilitating research on diagnosis, pathogenesis, prevention, and treatment.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.