Multidimensional analysis of adult patients' care trajectories before a first diagnosis of schizophrenia.
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ABSTRACT:
SUBMITTER: Vanasse A
PROVIDER: S-EPMC9261102 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The identification of novel disease associations using big-data for patient care has had limited success. In this study, we created a longitudinal disease network of traced readmissions (disease trajectories), merging data from over 10.4 million inpatients through the Healthcare Cost and Utilization Project, which allowed the representation of disease progression mapping over 300 diseases. From these disease trajectories, we discovered an interesting association between schizophrenia and rhabdomyolysis, a rare muscle disease (incidence?<?1E-04) (relative risk, 2.21 [1.80-2.71, confidence interval?=?0.95], P-value 9.54E-15). We validated this association by using independent electronic medical records from over 830,000 patients at the University of California, San Francisco (UCSF) medical center. A case review of 29 rhabdomyolysis incidents in schizophrenia patients at UCSF demonstrated that 62% are idiopathic, without the use of any drug known to lead to this adverse event, suggesting a warning to physicians to watch for this unexpected risk of schizophrenia. Large-scale analysis of disease trajectories can help physicians understand potential sequential events in their patients.
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Project description:Patients with cardiovascular disease (CVD) are a heterogeneous group regarding their body mass index (BMI) levels at the time of diagnosis. To address the heterogeneity of CVD, we examined the trajectories of change in body mass index (BMI) and in other cardio-metabolic risk factors before CVD diagnosis. The study included 6126 participants from the prospective population-based Rotterdam Study, followed over 22 years with clinical examinations every 4 years. Latent class trajectory analysis and mixed-effect models were used to develop trajectories of BMI and other cardio-metabolic risk factors respectively. During follow-up, 1748 participants developed CVD, among whom we identified 3 distinct BMI trajectories. The majority of participants (n = 1534, 87.8 %) had steady BMI levels during follow-up, comprising the "stable weight" group. This group showed decrease in mean high-density lipoprotein (HDL) cholesterol over time. The second group, the "progressive weight gain" group (n = 112, 6.4 %), showed a progressive increase in BMI levels. In this group, mean waist circumference increased, mean HDL cholesterol decreased and mean fasting glucose levels were fluctuating over follow-up. In the third group, the "progressive weight loss" group (n = 102, 5.8 %), BMI levels decreased during follow-up. This group showed a decrease in mean waist circumference and in fasting glucose. In conclusion, the majority of individuals who developed CVD had a stable weight during follow-up, suggesting that BMI alone is not a good indicator for identifying middle-aged and elderly individuals at high risk of CVD. Waist circumference, HDL cholesterol, and glucose trajectories differed between the identified BMI subgroups, further highlighting that CVD is a heterogeneous disease with different pathophysiological pathways.
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Project description:BACKGROUND:Published methods to describe and visualize Care Trajectories (CTs) as patterns of healthcare use are very sparse, often incomplete, and not intuitive for non-experts. Our objectives are to propose a typology of CTs one year after a first hospitalization for Chronic Obstructive Pulmonary Disease (COPD), and describe CT types and compare patients' characteristics for each CT type. METHODS:This is an observational cohort study extracted from Quebec's medico-administrative data of patients aged 40 to 84?years hospitalized for COPD in 2013 (index date). The cohort included patients hospitalized for the first time over a 3-year period before the index date and who survived over the follow-up period. The CTs consisted of sequences of healthcare use (e.g. ED-hospital-home-GP-respiratory therapists, etc.) over a one-year period. The main variable was a CT typology, which was generated by a 'tailored' multidimensional State Sequence Analysis, based on the "6W" model of Care Trajectories. Three dimensions were considered: the care setting ("where"), the reason for consultation ("why"), and the speciality of care providers ("which"). Patients were grouped into specific CT types, which were compared in terms of care use attributes and patients' characteristics using the usual descriptive statistics. RESULTS:The 2581 patients were grouped into five distinct and homogeneous CT types: Type 1 (n =?1351, 52.3%) and Type 2 (n =?748, 29.0%) with low healthcare and moderate healthcare use respectively; Type 3 (n =?216, 8.4%) with high healthcare use, mainly for respiratory reasons, with the highest number of urgent in-hospital days, seen by pulmonologists and respiratory therapists at primary care settings; Type 4 (n =?100, 3.9%) with high healthcare use, mainly cardiovascular, high ED visits, and mostly seen by nurses in community-based primary care; Type 5 (n =?166, 6.4%) with high healthcare use, high ED visits and non-urgent hospitalisations, and with consultations at outpatient clinics and primary care settings, mainly for other reasons than respiratory or cardiovascular. Patients in the 3 highest utilization CT types were older, and had more comorbidities and more severe condition at index hospitalization. CONCLUSIONS:The proposed method allows for a better representation of the sequences of healthcare use in the real world, supporting data-driven decision making.
| S-EPMC7059729 | biostudies-literature
Project description:OBJECTIVE:The role of adiponectin in the natural history of diabetes is not well characterized. We set out to characterize prediagnosis trajectories of adiponectin in individuals who develop type 2 diabetes. RESEARCH DESIGN AND METHODS:In a case-cohort study (335 incident diabetes case and 2,474 noncase subjects) nested in the Whitehall II study, serum adiponectin was measured up to three times per participant (1991-1993, 1997-1999, and 2003-2004). Multilevel models adjusted for age and ethnicity were fitted to assess 13-year trajectories of log-transformed adiponectin preceding diabetes diagnosis or a randomly selected time point during follow-up (year(0)) based on 755/5,095 (case/noncase) person-examinations. RESULTS:Adiponectin levels were lower in diabetes case than in noncase subjects (median 7,141 [interquartile range 5,187-10,304] vs. 8,818 [6,535-12,369] ng/mL at baseline, P < 0.0001). Control subjects showed a modest decline in adiponectin throughout follow-up (0.3% per year, P < 0.0001) at higher levels in women than in men (difference at year(0): 5,358 ng/mL, P < 0.0001). Female case and early-onset case (age at diagnosis <52 years) subjects had a steeper decline than control subjects (slope difference -1.1% per year, P = 0.001 in females, -1.6% per year in early-onset case subjects, P = 0.034). In men, adiponectin slopes for case and noncase subjects were parallel. The slope differences by diabetes onset were largely attenuated after adjustment for changes in obesity, whereas the sex-specific slope differences were independent of obesity. CONCLUSIONS:Lower adiponectin levels were observed already a decade before the diagnosis of diabetes. The marked sex difference in trajectories suggests that sex-specific mechanisms affect the association between adiponectin levels and diabetes development.
| S-EPMC3507593 | biostudies-literature
Project description:BACKGROUND:The nature of symptoms in the prodromal period of first episode psychosis (FEP) remains unclear. The objective was to determine the patterns of symptoms recorded in primary care in the 5 years before FEP diagnosis. METHODS:The study was set within 568 practices contributing to a UK primary care health record database (Clinical Practice Research Datalink). Patients aged 16-45 years with a first coded record of FEP, and no antipsychotic prescription more than 1 year prior to FEP diagnosis (n = 3045) was age, gender, and practice matched to controls without FEP (n = 12,180). Fifty-five symptoms recorded in primary care in the previous 5 years, categorised into 8 groups (mood-related, 'neurotic', behavioural change, volition change, cognitive change, perceptual problem, substance misuse, physical symptoms), were compared between cases and controls. Common patterns of symptoms prior to FEP diagnosis were identified using latent class analysis. RESULTS:Median age at diagnosis was 30 years, 63% were male. Non-affective psychosis (67%) was the most common diagnosis. Mood-related, 'neurotic', and physical symptoms were frequently recorded (> 30% of patients) before diagnosis, and behavioural change, volition change, and substance misuse were also common (> 10%). Prevalence of all symptom groups was higher in FEP patients than in controls (adjusted odds ratios 1.33-112). Median time from the first recorded symptom to FEP diagnosis was 2-2.5 years except for perceptual problem (70 days). The optimal latent class model applied to FEP patients determined three distinct patient clusters: 'no or minimal symptom cluster' (49%) had no or few symptoms recorded; 'affective symptom cluster' (40%) mainly had mood-related and 'neurotic' symptoms; and 'multiple symptom cluster' (11%) consulted for three or more symptom groups before diagnosis. The multiple symptom cluster was more likely to have drug-induced psychosis, female, obese, and have a higher morbidity burden. Affective and multiple symptom clusters showed a good discriminative ability (C-statistic 0.766; sensitivity 51.2% and specificity 86.7%) for FEP, and many patients in these clusters had consulted for their symptoms several years before FEP diagnosis. CONCLUSIONS:Distinctive patterns of prodromal symptoms may help alert general practitioners to those developing psychosis, facilitating earlier identification and referral to specialist care, thereby avoiding potentially detrimental treatment delay.
| S-EPMC6894287 | biostudies-literature
Project description:OBJECTIVE:People with diabetes show great variability in weight gain and duration of obesity at the time of diagnosis. BMI trajectories and other cardiometabolic risk factors prior to type 2 diabetes were investigated. METHODS:A total of 6,223 participants from the Rotterdam Study cohort were included. BMI patterns before diagnosis of diabetes were identified through latent class trajectories. RESULTS:During a mean follow-up of 13.7 years, 565 participants developed type 2 diabetes. Three distinct trajectories of BMI were identified, including the "progressive overweight" group (n?=?481, 85.1%), "progressive weight loss" group (n?=?59, 10.4%), and "persistently high BMI" group (n?=?25, 4.4%). The majority, the progressive overweight group, was characterized by a steady increase of BMI in the overweight range 10 years before diabetes diagnosis. The progressive weight loss group had fluctuations of glucose and marked beta cell function loss. The persistently high BMI group was characterized by a slight increase in insulin levels and sharp increase of insulin resistance accompanied by a rapid decrease of beta cell function. CONCLUSIONS:Heterogeneity of BMI changes prior to type 2 diabetes was found in a middle-aged and elderly white population. Prevention strategies should be tailored rather than focusing only on high-risk individuals.
| S-EPMC7317538 | biostudies-literature
Project description:ObjectiveThe emphasis on reducing the duration of untreated psychosis (DUP) has highlighted complex barriers to accessing appropriate services. Internet and social media use by individuals with first-episode psychosis (FEP) was examined to explore how these platforms might be used to facilitate treatment initiation.MethodsParticipants ages 15-35 were interviewed with the Pathways to Care for Psychosis Questionnaire, an 81-item instrument designed to explore online activity during symptom emergence.ResultsOf 112 participants, 90% used the Internet and social media daily. The Internet was listed as the most used resource (62%) for information while symptoms were emerging. A minority (19%) shared concerns via social media, and 76% responded favorably to the possibility of receiving online mental health support.ConclusionsThe Internet and social media were part of daily life for participants with FEP. Activity continued throughout the DUP, offering the prospect of earlier intervention. Participants expressed positive attitudes toward Internet-based outreach and engagement efforts.
| S-EPMC6408281 | biostudies-literature
Project description:BackgroundLonger patient intervals can lead to more late-stage cancer diagnoses and higher mortality rates. Individuals may delay presenting to primary care with red flag symptoms and instead turn to the internet to seek information, purchase over-the-counter medication, and change their diet or exercise habits. With advancements in machine learning, there is the potential to explore this complex relationship between a patient's symptom appraisal and their first consultation at primary care through linkage of existing datasets (eg, health, commercial, and online).ObjectiveHere, we aimed to explore feasibility and acceptability of symptom appraisal using commercial- and health-data linkages for cancer symptom surveillance.MethodsA proof-of-concept study was developed to assess the general public's acceptability of commercial- and health-data linkages for cancer symptom surveillance using a qualitative focus group study. We also investigated self-care behaviors of ovarian cancer patients using high-street retailer data, pre- and postdiagnosis.ResultsUsing a high-street retailer's data, 1118 purchases-from April 2013 to July 2017-by 11 ovarian cancer patients and one healthy individual were analyzed. There was a unique presence of purchases for pain and indigestion medication prior to cancer diagnosis, which could signal disease in a larger sample. Qualitative findings suggest that the public are willing to consent to commercial- and health-data linkages as long as their data are safeguarded and users of this data are transparent about their purposes.ConclusionsCancer symptom surveillance using commercial data is feasible and was found to be acceptable. To test efficacy of cancer surveillance using commercial data, larger studies are needed with links to individual electronic health records.
| S-EPMC6354198 | biostudies-literature
Project description:BackgroundDecreased P300 amplitude is one of the most consistent findings in patients with schizophrenia. However, whether prolonged P300 latency occurs in patients with schizophrenia, especially first-episode schizophrenia (FES) patients, remains controversial.MethodsA meta-analyses of P300 aberration in FES patients and healthy control(HC) group was conducted. The meta-regression analysis was performed using a random effects model. The pooled standardized effect size (PSES) was calculated as the division of the difference between the means of the two groups by the common standard deviation.ResultsA total of 569 FES patients and 747 HCs were included in this meta-analysis. P300 amplitude was significantly reduced (PSES?=?-0.83, 95% CI: -1.02-0.65, P?=?0.00001) and P300 latency was delayed significantly in FES patients (PSES?=?-0.48, 95% CI: 0.14-0.81, P?=?0.005). The meta-regression analysis showed that task difficulty was a source of heterogeneity.ConclusionsThe meta-analysis confirms that disrupted information processing is found in FES patients, which is manifested by smaller P300 amplitude and delayed P300 latency.
| S-EPMC4059623 | biostudies-literature
Project description:BACKGROUND:To characterize functional trajectories in the year before and after a new cancer diagnosis among older adults and to identify risk factors for worsening disability post-diagnosis. METHODS:We identified 170 participants 70+ years with monthly assessments of thirteen basic, instrumental, and mobility activities and with a new cancer diagnosis from 1998 to 2014. A group-based trajectory model identified distinct functional trajectories based on a total disability score during the twelve months pre- and post-diagnosis. We evaluated associations between potential risk factors at the time of cancer diagnosis and worsening disability post-diagnosis, explored functional transitions from pre- to post-diagnosis and identified participants whose functional trajectories worsened. RESULTS:Three pre-diagnosis functional trajectories were identified among 170 participants (mean age at diagnosis: 83?years (range: 73-105?years): mild, moderate, and severe disability. Three post-diagnosis functional trajectories were identified among 158 non-decedents: mild, moderate, and severe disability. Most participants (93.9%) with severe disability pre-diagnosis had severe disability post-diagnosis. Risk factors independently associated with worsening disability post-diagnosis included moderate or severe disability pre-diagnosis (adjusted risk ratio, aRR: moderate: 2.96; 95%CI: 2.11-4.16; severe: 5.11; 95%CI: 3.07-8.52) vs. mild (reference), poor physical capability (aRR: 1.57; 95%CI: 1.07-2.30), and incurable stage (aRR:1.99; 95%CI: 1.41-2.80). 40% of participants with a mild or moderate disability trajectory pre-diagnosis transitioned to a worse functional trajectory post-diagnosis. CONCLUSION:Older adults followed distinct functional trajectories in the twelve months before and after cancer diagnosis. Functional trajectory pre-diagnosis, poor physical capability, and incurable stage were independent risk factors for worsening disability post-diagnosis.
| S-EPMC6526705 | biostudies-literature