METHODS: We included 23,288 patients with incident stroke admitted between 2005 and 2017 and 68,675 matched nonstroke controls. Information on mental disorders was obtained from medical claims data within the 3 years before the stroke incidence. Cox proportional hazards models considering death as a competing risk event were constructed to estimate the hazard ratio of AP incidence by the end of 2018 associated with stroke and selected mental disorders.
RESULTS: After ≤14 years of follow-up, AP incidence was higher in the patients with stroke than in the controls (11.30/1000 vs. 1.51/1000 person-years), representing a covariate-adjusted subdistribution hazard ratio (sHR) of 3.64, with no significant sex difference. The sHR significantly decreased with increasing age in both sexes. Stratified analyses indicated schizophrenia but not depression or bipolar affective disorder increased the risk of AP in the patients with stroke.
CONCLUSION: Compared with their corresponding counterparts, the patients with schizophrenia only, stroke only, and both stroke and schizophrenia had a significantly higher sHR of 4.01, 5.16, and 8.01, respectively. The risk of AP was higher in younger stroke patients than those older than 60 years. Moreover, schizophrenia was found to increase the risk of AP in patients with stroke.
METHODS: In a sample of 9448 participants followed for a mean of 15.3 years (186,158.5 person-years) from the Monitoring of Trends and Determinants in Cardiovascular Disease Augsburg/Cooperative Health Research in the Region of Augsburg population-based cohort conducted in Germany, we investigated the association of social connectivity, measured by the Social Network Index, and body mass index (BMI) with the risk of clinically validated T2D incidence using stratified Cox proportional hazards regression models adjusted for sociodemographic, life-style, cardiometabolic, and psychosocial risk factors.
RESULTS: During a mean follow-up of 14.1 years (186,158.5 person-years), 975 (10.3%) participants developed T2D. Participants with low social connectivity developed T2D at a higher rate than socially connected participants (10.0 versus 8.0 cases/10,000 person-years); however, BMI played a significant role in the association of social connectivity with T2D ( p < .001). In comparison to their socially connected counterparts, low social connectivity was associated with a higher rate of T2D incidence in normal-weight (6.0 versus 2.0 cases/10,000 person-years), but not overweight (13.0 versus 13.0 cases/10,000 person-years) or obese participants (32.0 versus 30.0 cases/10,000 person-years). Correspondingly, Cox regression analysis showed that 5-unit increments in BMI increased the risk of T2D in socially connected participants (hazard ratio = 3.03, 95% confidence interval = 2.48-3.79, p < .001) at a substantially higher rate than in low socially connected participants (hazard ratio = 1.77, 95% confidence interval = 1.45-2.16, p < .001).
CONCLUSION: The detrimental link between low social connectivity and increased risk of T2D is substantially stronger in participants with a lower BMI.
AIM: We aimed to compare the effectiveness and safety of early versus late caffeine therapy on preterm infants' clinical outcomes.
METHOD: A retrospective matched cohort study was conducted using data of patients admitted to neonatal intensive care units of two tertiary care hospitals between January 2016 and December 2018. The clinical outcomes and mortality risk between early caffeine (initiation within 2 days of life) and late caffeine (initiation ≥ 3 days of life) were compared.
RESULTS: Ninety-five pairs matched based on gestational age were included in the study. Compared to late initiation, preterm infants with early caffeine therapy had: a shorter duration of non-invasive mechanical ventilation (median 5 days vs. 12 days; p
OBJECTIVE: To develop and validate a deep learning model using readily available clinical information to predict treatment success with the first ASM for individual patients.
DESIGN, SETTING, AND PARTICIPANTS: This cohort study developed and validated a prognostic model. Patients were treated between 1982 and 2020. All patients were followed up for a minimum of 1 year or until failure of the first ASM. A total of 2404 adults with epilepsy newly treated at specialist clinics in Scotland, Malaysia, Australia, and China between 1982 and 2020 were considered for inclusion, of whom 606 (25.2%) were excluded from the final cohort because of missing information in 1 or more variables.
EXPOSURES: One of 7 antiseizure medications.
MAIN OUTCOMES AND MEASURES: With the use of the transformer model architecture on 16 clinical factors and ASM information, this cohort study first pooled all cohorts for model training and testing. The model was trained again using the largest cohort and externally validated on the other 4 cohorts. The area under the receiver operating characteristic curve (AUROC), weighted balanced accuracy, sensitivity, and specificity of the model were all assessed for predicting treatment success based on the optimal probability cutoff. Treatment success was defined as complete seizure freedom for the first year of treatment while taking the first ASM. Performance of the transformer model was compared with other machine learning models.
RESULTS: The final pooled cohort included 1798 adults (54.5% female; median age, 34 years [IQR, 24-50 years]). The transformer model that was trained using the pooled cohort had an AUROC of 0.65 (95% CI, 0.63-0.67) and a weighted balanced accuracy of 0.62 (95% CI, 0.60-0.64) on the test set. The model that was trained using the largest cohort only had AUROCs ranging from 0.52 to 0.60 and a weighted balanced accuracy ranging from 0.51 to 0.62 in the external validation cohorts. Number of pretreatment seizures, presence of psychiatric disorders, electroencephalography, and brain imaging findings were the most important clinical variables for predicted outcomes in both models. The transformer model that was developed using the pooled cohort outperformed 2 of the 5 other models tested in terms of AUROC.
CONCLUSIONS AND RELEVANCE: In this cohort study, a deep learning model showed the feasibility of personalized prediction of response to ASMs based on clinical information. With improvement of performance, such as by incorporating genetic and imaging data, this model may potentially assist clinicians in selecting the right drug at the first trial.
METHODS: In this analysis of 2-year retrospective cohort studies, we extracted data from the TriNetX electronic health records network, an international network of de-identified data from health-care records of approximately 89 million patients collected from hospital, primary care, and specialist providers (mostly from the USA, but also from Australia, the UK, Spain, Bulgaria, India, Malaysia, and Taiwan). A cohort of patients of any age with COVID-19 diagnosed between Jan 20, 2020, and April 13, 2022, was identified and propensity-score matched (1:1) to a contemporaneous cohort of patients with any other respiratory infection. Matching was done on the basis of demographic factors, risk factors for COVID-19 and severe COVID-19 illness, and vaccination status. Analyses were stratified by age group (age <18 years [children], 18-64 years [adults], and ≥65 years [older adults]) and date of diagnosis. We assessed the risks of 14 neurological and psychiatric diagnoses after SARS-CoV-2 infection and compared these risks with the matched comparator cohort. The 2-year risk trajectories were represented by time-varying hazard ratios (HRs) and summarised using the 6-month constant HRs (representing the risks in the earlier phase of follow-up, which have not yet been well characterised in children), the risk horizon for each outcome (ie, the time at which the HR returns to 1), and the time to equal incidence in the two cohorts. We also estimated how many people died after a neurological or psychiatric diagnosis during follow-up in each age group. Finally, we compared matched cohorts of patients diagnosed with COVID-19 directly before and after the emergence of the alpha (B.1.1.7), delta (B.1.617.2), and omicron (B.1.1.529) variants.
FINDINGS: We identified 1 487 712 patients with a recorded diagnosis of COVID-19 during the study period, of whom 1 284 437 (185 748 children, 856 588 adults, and 242 101 older adults; overall mean age 42·5 years [SD 21·9]; 741 806 [57·8%] were female and 542 192 [42·2%] were male) were adequately matched with an equal number of patients with another respiratory infection. The risk trajectories of outcomes after SARS-CoV-2 infection in the whole cohort differed substantially. While most outcomes had HRs significantly greater than 1 after 6 months (with the exception of encephalitis; Guillain-Barré syndrome; nerve, nerve root, and plexus disorder; and parkinsonism), their risk horizons and time to equal incidence varied greatly. Risks of the common psychiatric disorders returned to baseline after 1-2 months (mood disorders at 43 days, anxiety disorders at 58 days) and subsequently reached an equal overall incidence to the matched comparison group (mood disorders at 457 days, anxiety disorders at 417 days). By contrast, risks of cognitive deficit (known as brain fog), dementia, psychotic disorders, and epilepsy or seizures were still increased at the end of the 2-year follow-up period. Post-COVID-19 risk trajectories differed in children compared with adults: in the 6 months after SARS-CoV-2 infection, children were not at an increased risk of mood (HR 1·02 [95% CI 0·94-1·10) or anxiety (1·00 [0·94-1·06]) disorders, but did have an increased risk of cognitive deficit, insomnia, intracranial haemorrhage, ischaemic stroke, nerve, nerve root, and plexus disorders, psychotic disorders, and epilepsy or seizures (HRs ranging from 1·20 [1·09-1·33] to 2·16 [1·46-3·19]). Unlike adults, cognitive deficit in children had a finite risk horizon (75 days) and a finite time to equal incidence (491 days). A sizeable proportion of older adults who received a neurological or psychiatric diagnosis, in either cohort, subsequently died, especially those diagnosed with dementia or epilepsy or seizures. Risk profiles were similar just before versus just after the emergence of the alpha variant (n=47 675 in each cohort). Just after (vs just before) the emergence of the delta variant (n=44 835 in each cohort), increased risks of ischaemic stroke, epilepsy or seizures, cognitive deficit, insomnia, and anxiety disorders were observed, compounded by an increased death rate. With omicron (n=39 845 in each cohort), there was a lower death rate than just before emergence of the variant, but the risks of neurological and psychiatric outcomes remained similar.
INTERPRETATION: This analysis of 2-year retrospective cohort studies of individuals diagnosed with COVID-19 showed that the increased incidence of mood and anxiety disorders was transient, with no overall excess of these diagnoses compared with other respiratory infections. In contrast, the increased risk of psychotic disorder, cognitive deficit, dementia, and epilepsy or seizures persisted throughout. The differing trajectories suggest a different pathogenesis for these outcomes. Children have a more benign overall profile of psychiatric risk than do adults and older adults, but their sustained higher risk of some diagnoses is of concern. The fact that neurological and psychiatric outcomes were similar during the delta and omicron waves indicates that the burden on the health-care system might continue even with variants that are less severe in other respects. Our findings are relevant to understanding individual-level and population-level risks of neurological and psychiatric disorders after SARS-CoV-2 infection and can help inform our responses to them.
FUNDING: National Institute for Health and Care Research Oxford Health Biomedical Research Centre, The Wolfson Foundation, and MQ Mental Health Research.
OBJECTIVE: To investigate the association of sitting time with mortality and major CVD in countries at different economic levels using data from the Prospective Urban Rural Epidemiology study.
DESIGN, SETTING, AND PARTICIPANTS: This population-based cohort study included participants aged 35 to 70 years recruited from January 1, 2003, and followed up until August 31, 2021, in 21 high-income, middle-income, and low-income countries with a median follow-up of 11.1 years.
EXPOSURES: Daily sitting time measured using the International Physical Activity Questionnaire.
MAIN OUTCOMES AND MEASURES: The composite of all-cause mortality and major CVD (defined as cardiovascular death, myocardial infarction, stroke, or heart failure).
RESULTS: Of 105 677 participants, 61 925 (58.6%) were women, and the mean (SD) age was 50.4 (9.6) years. During a median follow-up of 11.1 (IQR, 8.6-12.2) years, 6233 deaths and 5696 major cardiovascular events (2349 myocardial infarctions, 2966 strokes, 671 heart failure, and 1792 cardiovascular deaths) were documented. Compared with the reference group (<4 hours per day of sitting), higher sitting time (≥8 hours per day) was associated with an increased risk of the composite outcome (hazard ratio [HR], 1.19; 95% CI, 1.11-1.28; Pfor trend < .001), all-cause mortality (HR, 1.20; 95% CI, 1.10-1.31; Pfor trend < .001), and major CVD (HR, 1.21; 95% CI, 1.10-1.34; Pfor trend < .001). When stratified by country income levels, the association of sitting time with the composite outcome was stronger in low-income and lower-middle-income countries (≥8 hours per day: HR, 1.29; 95% CI, 1.16-1.44) compared with high-income and upper-middle-income countries (HR, 1.08; 95% CI, 0.98-1.19; P for interaction = .02). Compared with those who reported sitting time less than 4 hours per day and high physical activity level, participants who sat for 8 or more hours per day experienced a 17% to 50% higher associated risk of the composite outcome across physical activity levels; and the risk was attenuated along with increased physical activity levels.
CONCLUSIONS AND RELEVANCE: High amounts of sitting time were associated with increased risk of all-cause mortality and CVD in economically diverse settings, especially in low-income and lower-middle-income countries. Reducing sedentary time along with increasing physical activity might be an important strategy for easing the global burden of premature deaths and CVD.
METHODS: A total of 603 participants from the United States completed the IES-2, alongside measures of body appreciation, body acceptance from others, and self-esteem. Our analyses compared the fit of various hypothesised models of IES-2 scores.
RESULTS: Models of IES-2 scores based on confirmatory factor analysis (CFA) uniformly showed poor fit. ESEM models showed superior fit to CFA representations and a B-ESEM model showed improved fit over higher-order CFA and B-CFA representations of IES-2 scores. The optimal model was a B-ESEM model that accounted for, through correlated uniqueness (CU), the methodological artefact introduced by negatively-worded IES-2 items. This B-ESEM-CU model was fully invariant across gender and showed adequate construct validity.
CONCLUSION: The B-ESEM-CU framework appears well-suited to understand the multidimensionality of IES-2 scores. A model of IES-2 scores that yields a reliable latent indicator of global intuitive eating while allowing for simultaneous consideration of additional specific factors will likely provide more accurate accounting of the nature and outcomes of intuitive eating.
LEVEL OF EVIDENCE: Level III, cohort study.
METHODS: Participants enrolled in a regional Asian HIV-infected cohort with weight and height measurements at ART initiation were eligible for inclusion in the analysis. Factors associated with weight changes and incident MetS (according to the International Diabetic Federation (IDF) definition) were analysed using linear mixed models and Cox regression, respectively. Competing-risk regression models were used to investigate the association of MetS with all-cause mortality.
RESULTS: Among 4931 people living with HIV (PLWH), 66% were male. At ART initiation, the median age was 34 [interquartile range (IQR) 29-41] years, and the median (IQR) weight and body mass index (BMI) were 55 (48-63) kg and 20.5 (18.4-22.9) kg/m2 , respectively. At 1, 2 and 3 years of ART, overall mean (± standard deviation) weight gain was 2.2 (±5.3), 3.0 (±6.2) and 3.7 (±6.5) kg, respectively. Participants with baseline CD4 count ≤ 200 cells/µL [weight difference (diff) = 2.2 kg; 95% confidence interval (CI) 1.9-2.5 kg] and baseline HIV RNA ≥ 100 000 HIV-1 RNA copies/mL (diff = 0.6 kg; 95% CI 0.2-1.0 kg), and those starting with integrase strand transfer inhibitor (INSTI)-based ART (diff = 2.1 kg; 95% CI 0.7-3.5 kg vs. nonnucleoside reverse transcriptase inhibitors) had greater weight gain. After exclusion of those with abnormal baseline levels of MetS components, 295/3503 had incident MetS [1.18 (95% CI 1.05-1.32)/100 person-years (PY)]. The mortality rate was 0.7 (95% CI 0.6-0.8)/100 PY. MetS was not significantly associated with all-cause mortality in the adjusted model (P = 0.236).
CONCLUSIONS: Weight gain after ART initiation was significantly higher among those initiating ART with lower CD4 count, higher HIV RNA and an INSTI-based regimen after controlling for baseline BMI. Greater efforts to identify and manage MetS among PLWH are needed.
METHODS: We used prospective data from the first 1,500 patients included in IGOS, aged ≥6 years and unable to walk independently. We evaluated whether the mEGOS at entry and week 1 could predict the inability to walk unaided at 4 and 26 weeks in the full cohort and in regional subgroups, using 2 measures for model performance: (1) discrimination: area under the receiver operating characteristic curve (AUC) and (2) calibration: observed vs predicted probability of being unable to walk independently. To improve the model predictions, we recalibrated the model containing the overall mEGOS score, without changing the individual predictive factors. Finally, we assessed the predictive ability of the individual factors.
RESULTS: For validation of mEGOS at entry, 809 patients were eligible (Europe/North America [n = 677], Asia [n = 76], other [n = 56]), and 671 for validation of mEGOS at week 1 (Europe/North America [n = 563], Asia [n = 65], other [n = 43]). AUC values were >0.7 in all regional subgroups. In the Europe/North America subgroup, observed outcomes were worse than predicted; in Asia, observed outcomes were better than predicted. Recalibration improved model accuracy and enabled the development of a region-specific version for Europe/North America (mEGOS-Eu/NA). Similar to the original mEGOS, severe limb weakness and higher age were the predominant predictors of poor outcome in the IGOS cohort.
DISCUSSION: mEGOS is a validated tool to predict the inability to walk unaided at 4 and 26 weeks in patients with GBS, also in countries outside the Netherlands. We developed a region-specific version of mEGOS for patients from Europe/North America.
CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that the mEGOS accurately predicts the inability to walk unaided at 4 and 26 weeks in patients with GBS.
TRIAL REGISTRATION INFORMATION: NCT01582763.
METHODS: Electronic databases were searched up to July 2021 for meta-analyses of cohort studies and/or randomised controlled trials (RCTs). Summary effect sizes from a random-effects model, between-study heterogeneity, 95% prediction interval, small-study effect, excess significance and credibility ceilings were devised to classify the credibility of evidence from meta-analyses of cohort studies, whereas the GRADE approach was used for meta-analyses of RCTs.
RESULTS: In meta-analyses of cohort studies, 52 of the 91 examined associations were statistically significant (P ≤ .05). Convincing evidence emerged from main analysis for the association between PPI use and risk of all-site fracture and chronic kidney disease in the elderly population. However, none of these associations remained supported by convincing evidence after sensitivity analyses. The use of PPI is also associated with an increased risk of mortality due to COVID-19 infection and other related adverse outcomes, but the quality of evidence was weak. In meta-analyses of RCTs, 38 of the 63 examined associations were statistically significant. However, no associations were supported by high or moderate-quality evidence.
CONCLUSION: This study's findings imply that most putative adverse outcomes associated with PPI use may not be supported by high-quality evidence and are likely to have been affected by underlying confounding factors. Future research is needed to confirm the causal association between PPI use and risk of fracture and chronic kidney disease.
METHODS: We conducted an in-depth qualitative interview on 20 participants from a cohort study. An ecological framework was used to construct the semi-structured topic guide. The interviews were audio-recorded and transcribed verbatim. Thematic analysis with theoretical saturation was used in data analysis.
RESULTS: The participants were found to have variable dietary practices that either followed or did not follow dietary recommendations. The social environment was critical as most women relied on family and friends for food choices; additionally, individuals in charge of food preparation had to prepare food based on their family member preferences. Furthermore, individuals had difficulty sustaining healthy dietary changes during the acute survivorship phase due to a lack of health consciousness and difficulty in healthy food access. Notably, there was a lack of dietary guidance from health care professionals, especially dietitians, in long-term survivorship care.
CONCLUSION: This study highlights the lack of breast cancer survivors' healthy diet and lifestyle knowledge. A holistic multidisciplinary approach involving individual, social, physical, and macro-level environmental elements are crucial to influencing healthy eating behaviours.
METHODS: This was a retrospective cohort study of severe COVID-19 patients who were admitted to a single tertiary centre from 1 January 2021 to 30 June 2021. The clinical data of the patients during admission and clinic follow-up, including radiological images, were traced using electronic medical records.
RESULTS: In our cohort, the mortality rate for those with severe COVID-19 was 23.1% (173/749). Among the survivors, 46.2% (266/576) had persistent respiratory failure (PRF) after 14 days of illness. Of them, 70.3% (187/266) were followed up, and 68% (128/187) received oral corticosteroid (prednisolone) maintenance treatment. OP pattern made up the majority (81%) of the radiological pattern with a mean severity CT score of 10 (SD±3). The mean prednisolone dose was 0.68mg/kg/day with a mean treatment duration of 47 days (SD±18). About one-third of patients (67/187) had respiratory symptoms at 4 weeks (SD±3). Among 78.1% (146/187) who had a repeated CXR during follow-up, only 12 patients (8.2%, SD±3) had radiological improvement of less than 50% at 6 weeks (SD±3), with 2 of them later diagnosed as pulmonary tuberculosis. Functional assessments, such as the 6-minute walk test and the spirometry, were only performed in 52.4% and 15.5% of the patients, respectively.
CONCLUSION: Almost half of the patients with severe COVID-19 had PRF, with a predominant radiological OP pattern. More than two-thirds of the PRF patients required prolonged oral corticosteroid treatment. Familiarising clinicians with the disease course, radiological patterns, and potential outcomes of this group of patients may better equip them to manage their patients.
METHODS: This was a retrospective open cohort study from 2013 to 2017 among T2D patients in public primary health care clinics in Negeri Sembilan state, Malaysia. Linear mixed-effects modelling was conducted to determine the LDL-C trend and its predictors. The LDL-C target for patients without CVD was <2.6 mmol/L, whereas <1.8 mmol/L was targeted for those with CVD.
RESULTS: Among 18,312 patients, there were more females (55.9%), adults ≥60 years (49.4%), Malays (64.7%), non-smokers (93.6%), and 45.3% had diabetes for <5 years. The overall LDL-C trend reduced by 6.8% from 2.96 to 2.76 mmol/L. In 2017, 16.8% (95% CI: 13.2-21.0) of patients without CVD and 45.8% (95% CI: 44.8-46.8) of patients with CVD achieved their respective LDL-C targets. The predictors for a higher LDL-C trend were younger adults, Malay and Indian ethnicities, females, dyslipidemia, and diabetes treatment with lifestyle modification and insulin. Longer diabetes duration, obesity, hypertension, retinopathy, statin therapy, achievement of HbA1c target and achievement of BP target were independent predictors for a lower LDL-C trend.
CONCLUSIONS: The LDL-C trend has improved, but there are still gaps between actual results and clinical targets. Interventions should be planned and targeted at the high-risk populations to control their LDL-C.
PARTICIPANTS: A total of 1210 Japanese lactating women who satisfied the inclusion criteria, were invited across the country at various participating sites, between 2014 and 2019. Finally a total of 1122 women were enrolled in this study.
FINDINGS TO DATE: Among 1122 eligible participants, mean age at delivery was 31.2 (SD 4.4) years and mean prepregnancy BMI was 20.8 (SD 2.7). Among these women, 35% were previously nulliparous and 77.7% had college, university or higher education. The mean gestational period was 39.0 (SD 1.3) weeks. Caesarean section was reported among 11.9%; mean infant birth weight was 3082 (SD 360) g. Of the infants, 53.7% were male. Overall, our participants appeared to be healthier than the general population in Japan. Analyses of the 1079 eligible human milk samples obtained at the first and second months postpartum showed the following composition: carbohydrate, 8.13 (SD 0.32) g/100 mL; fat, 3.77 (SD 1.29) g/100 mL; and crude protein, 1.20 (SD 0.23) g/100 mL. We also analysed osteopontin, fatty acid, vitamin D and phospholipid levels in limited subcohorts of the samples.
FUTURE PLANS: Follow-up surveys will be conducted to obtain milk samples every 2 months for 12 months and to investigate mother and child health until the children reach 5 years of age. These will be completed in 2024. We plan to longitudinally analyse the composition of macronutrients and various bioactive factors in human milk and investigate the lifestyle and environmental factors that influence breastfeeding practices, maternal and child health, and child development.
TRIAL REGISTRATION NUMBER: UMIN000015494; pre-results.