Identifying "Real" Patients in the Real World.
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ABSTRACT:
SUBMITTER: Callahan SJ
PROVIDER: S-EPMC6961738 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description: Not available
| S-EPMC6961735 | biostudies-literature
Project description:With the publication of the 2014 Focused Update of the Canadian Cardiovascular Society Guidelines for the Management of Atrial Fibrillation, the Canadian Cardiovascular Society Atrial Fibrillation Guidelines Committee has introduced a new triage and management algorithm; the so-called "CCS Algorithm". The CCS Algorithm is based upon expert opinion of the best available evidence; however, the CCS Algorithm has not yet been validated. Accordingly, the purpose of this study is to evaluate the performance of the CCS Algorithm in a cohort of real world patients.We compared the CCS Algorithm with the European Society of Cardiology (ESC) Algorithm in 172 hospital inpatients who are at risk of stroke due to non-valvular atrial fibrillation in whom anticoagulant therapy was being considered.The CCS Algorithm and the ESC Algorithm were concordant in 170/172 patients (99% of the time). There were two patients (1%) with vascular disease, but no other thromboembolic risk factors, which were classified as requiring oral anticoagulant therapy using the ESC Algorithm, but for whom ASA was recommended by the CCS Algorithm.The CCS Algorithm appears to be unnecessarily complicated in so far as it does not appear to provide any additional discriminatory value above and beyond the use of the ESC Algorithm, and its use could result in under treatment of patients, specifically female patients with vascular disease, whose real risk of stroke has been understated by the Guidelines.
| S-EPMC5497178 | biostudies-other
Project description:Background:A growing body of research suggests that major depressive disorder (MDD) is one of the most common psychiatric conditions associated with suicide ideation (SI). However, how a combination of easily accessible variables built a utility clinically model to estimate the probability of an individual patient with SI via machine learning is limited. Methods:We used the electronic medical record database from a hospital located in western China. A total of 1916 Chinese patients with MDD were included. Easily accessible data (demographic, clinical, and biological variables) were collected at admission (on the first day of admission) and were used to distinguish SI with MDD from non-SI using a machine learning algorithm (neural network). Results:The neural network algorithm distinguished 1356 out of 1916 patients translating into 70.08% accuracy (70.68% sensitivity and 67.09% specificity) and an area under the curve (AUC) of 0.76. The most relevant predictor variables in identifying SI from non-SI included free thyroxine (FT4), the total scores of Hamilton Depression Scale (HAMD), vocational status, and free triiodothyronine (FT3). Conclusion:Risk for SI among patients with MDD can be identified at an individual subject level by integrating demographic, clinical, and biological variables as possible as early during hospitalization (at admission).
| S-EPMC7061409 | biostudies-literature
Project description:BACKGROUND:Real-world data (RWD) play important roles in evaluating treatment effectiveness in clinical research. In recent decades, with the development of more accurate diagnoses and better treatment options, inpatient surgery for cervical degenerative disease (CDD) has become increasingly more common, yet little is known about the variations in patient demographic characteristics associated with surgical treatment. OBJECTIVE:This study aimed to identify the characteristics of surgical patients with CDD using RWD collected from electronic medical records. METHODS:This study included 20,288 inpatient surgeries registered from January 1, 2000, to December 31, 2016, among patients aged 18 years or older, and demographic data (eg, age, sex, admission time, surgery type, treatment, discharge diagnosis, and discharge time) were collected at baseline. Regression modeling and time series analysis were conducted to analyze the trend in each variable (total number of inpatient surgeries, mean age at surgery, sex, and average length of stay). A P value <.01 was considered statistically significant. The RWD in this study were collected from the Orthopedic Department at Peking University Third Hospital, and the study was approved by the institutional review board. RESULTS:Over the last 17 years, the number of inpatient surgeries increased annually by an average of 11.13%, with some fluctuations. In total, 76.4% (15,496/20,288) of the surgeries were performed in patients with CDD aged 41 to 65 years, and there was no significant change in the mean age at surgery. More male patients were observed, and the proportions of male and female patients who underwent surgery were 64.7% (13,126/20,288) and 35.3% (7162/20,288), respectively. However, interestingly, the proportion of surgeries performed among female patients showed an increasing trend (P<.001), leading to a narrowing sex gap. The average length of stay for surgical treatment decreased from 21 days to 6 days and showed a steady decline from 2012 onward. CONCLUSIONS:The RWD showed its capability in supporting clinical research. The mean age at surgery for CDD was consistent in the real-world population, the proportion of female patients increased, and the average length of stay decreased over time. These results may be valuable to guide resource allocation for the early prevention and diagnosis, as well as surgical treatment of CDD.
| S-EPMC7165306 | biostudies-literature
Project description:OBJECTIVE:The aim was to compare multimorbidity patterns identified with the two most commonly used methods: hierarchical cluster analysis (HCA) and exploratory factor analysis (EFA) in a large primary care database. Specific objectives were: (1) to determine whether choice of method affects the composition of these patterns and (2) to consider the potential application of each method in the clinical setting. DESIGN:Cross-sectional study. Diagnoses were based on the 263 corresponding blocks of the International Classification of Diseases version 10. Multimorbidity patterns were identified using HCA and EFA. Analysis was stratified by sex, and results compared for each method. SETTING AND PARTICIPANTS:Electronic health records for 408 994 patients with multimorbidity aged 45-64 years in 274 primary health care teams from 2010 in Catalonia, Spain. RESULTS:HCA identified 53 clusters for women, with just 12 clusters including at least 2 diagnoses, and 15 clusters for men, all of them including at least two diagnoses. EFA showed 9 factors for women and 10 factors for men. We observed differences by sex and method of analysis, although some patterns were consistent. Three combinations of diseases were observed consistently across sex groups and across both methods: hypertension and obesity, spondylopathies and deforming dorsopathies, and dermatitis eczema and mycosis. CONCLUSIONS:This study showed that multimorbidity patterns vary depending on the method of analysis used (HCA vs EFA) and provided new evidence about the known limitations of attempts to compare multimorbidity patterns in real-world data studies. We found that EFA was useful in describing comorbidity relationships and HCA could be useful for in-depth study of multimorbidity. Our results suggest possible applications for each of these methods in clinical and research settings, and add information about some aspects that must be considered in standardisation of future studies: spectrum of diseases, data usage and methods of analysis.
| S-EPMC5875653 | biostudies-literature
Project description:Materials and methodsPatients with a primary diagnosis of AR (ICD-9-CM code: 477.9) in 2010 were included, and the National Health Insurance Research Database in Taiwan was used as the data source. Association rule mining and social network analysis were used to establish and explore the CHM network. Possible molecular pathways of the CHM network were summarized and compared with commonly used western medicine (WM) by conducting overrepresentation analysis in the Reactome pathway database. The potential proteins acted by CHMs were obtained from the CHM ingredient-protein databases, including STITCH, TCMSP, TCMID, and TCM@Taiwan.ResultsThere were 89,148 AR subjects found in 2010, and a total of 33,507 patients ever used CHM. On an average, 5.6 types of CHMs were utilized per prescription. Xin-Yi-Qing-Fei-Tang was used most frequently (25.5% of 222,279 prescriptions), while Xiao-Qing-Long-Tang with Xin-Yi-San was the most commonly prescribed CHM-CHM combination. Up to six distinctive clusters could be found among the CHM network, and core CHMs could be found for AR, such as Xiao-Qing-Long-Tang and Xin-Yi-Qing-Fei-Tang. A total of 140 molecular pathways were covered by the CHM network (2,432 ingredients from 31 kinds of CHMs), while 39 WMs covered 55 pathways. Among pathways responding to the immune system, WM mainly acted on cytokine signaling-related pathways, while CHM mostly acted on neutrophil/macrophage-related innate pathways and dendritic cell-related adaptive immunity pathways.ConclusionOur study demonstrated and analyzed the CHM network for AR. Core CHM for AR and possible molecular pathways were presented as well, and this information is crucial for researchers to select candidates for CHM-related studies.
| S-EPMC7665915 | biostudies-literature
Project description:The purpose of this study was to understand patient treatment patterns, outcomes, and healthcare resource use in cases of metastatic and/or locally recurrent, unresectable gastric cancer (MGC) in South Korea.Thirty physicians reviewed charts of eligible patients to collect de-identified data. Patients must have received platinum/fluoropyrimidine first-line therapy followed by second-line therapy or best supportive care, had no other primary cancer, and not participated in a clinical trial following MGC diagnosis. Data were summarized using descriptive statistics. Kaplan-Meier analysis was used to describe survival.Of 198 patients, 73.7% were male, 78.3% were diagnosed with MGC after age 55 (mean, 61.3 years), and 47.0% were current or former smokers. The majority of tumorswere located in the antrum/pylorus (51.5%). Metastatic sites most often occurred in the peritoneum (53.5%), lymph nodes (47.5%), and liver (38.9%). At diagnosis, the mean Charlson comorbidity indexwas 0.4 (standard deviation, 0.6). The most common comorbidities were chronic gastritis (22.7%) and cardiovascular disease (18.7%). Most patients (80.3%) received second-line treatment. Single-agent fluoropyrimidine was reported for 22.0% of patients, while 19.5% were treated with irinotecan and a fluoropyrimidine or platinum agent. The most common physician-reported symptoms during second-line treatment were nausea/vomiting (44.7%) and pain (11.3%), with antiemetics (44.7%), analgesics (36.5%), and nutritional support (11.3%) most often used as supportive care. Two-thirds of inpatient hospitalizations were for chemotherapy infusion. Outpatient hospitalization (31.6%) and visits to the oncologist (58.8%) were common among second-line patients.Most patients received second-line treatment, although regimens varied. Understanding MGC patient characteristics and treatment patterns in South Korea will help address unmet needs.
| S-EPMC5512370 | biostudies-other
Project description:Systemic lupus erythematosus (SLE) might increase deep neck infection (DNI) risk, but evidence supporting this hypothesis is limited. In this retrospective follow-up study, the SLE-DNI association was investigated using data from the Registry for Catastrophic Illness Patients, which is a subset of the Taiwan National Health Insurance Research Database. All patients newly diagnosed as having SLE in 1997-2011 were identified, and every SLE patient was individually matched to four patients without SLE according to sex, age, and socioeconomic status. The study outcome was DNI occurrence. DNI treatment modalities and prognoses in SLE and non-SLE patients, along with the association of steroid dose with DNI risk, were also studied. In total, 17,426 SLE and 69,704 non-SLE patients were enrolled. Cumulative DNI incidence was significantly higher in the SLE cohort than in the non-SLE cohort (p?<?0.001). The Cox regression model demonstrated that SLE significantly increased DNI risk (hazard ratio: 4.70; 95% confidence interval: 3.50-6.32, p?<?0.001). Moreover, in the sensitivity and subgroup analyses, the effect of SLE on DNI was stable. Relatively few SLE-DNI patients received surgical interventions (15.6% vs. 28.6%, p?=?0.033). The between-group differences in tracheostomy use and hospitalisation duration were nonsignificant. In SLE patients, high steroid doses significantly increased DNI incidence (?3 vs. <3?mg/day?=?2.21% vs. 0.52%, p?<?0.001). This is the first study demonstrating that SLE increases DNI risk by approximately five times and that high steroid dose increases DNI incidence in SLE patients.
| S-EPMC7058067 | biostudies-literature
Project description:Introduction:An abnormal serum potassium (S-K) level is an important electrolyte disturbance. However, its relation to clinical outcomes in real-world patients, particularly hyperkalemia burden, is not extensively studied. Methods:An observational retrospective cohort study using a Japanese hospital claims database was done (April 2008-September 2017; N = 1,022,087). Associations between index S-K level and 3-year survival were modeled using cubic spline regression. Cox regression model was applied to estimate the time to death according to different S-K levels. Prevalence, patient characteristics, treatment patterns, and management of patients with hyperkalemia from first episode were assessed. Results:Hyperkalemia prevalence was 67.9 (95% confidence interval [CI]: 67.1-68.8) per 1000 and increased in patients with chronic kidney disease (CKD) (227.9; 95% CI: 224.3-231.5), heart failure (134.0; 95% CI: 131.2-136.8), and renin-angiotensin-aldosterone system inhibitor (RAASi) use (142.2; 95% CI: 139.6-144.7). U-shaped associations between S-K level and 3-year survival were observed with nadir 4.0 mEq/l. The risk of death was increased at S-K 5.1-5.4 mEq with hazard ratio of 7.6 (95% CI: 7.2-8.0). The 3-year mortality rate in patients with CKD stages 3a, 3b, 4, and 5 with normokalemia were 1.51%, 3.93%, 10.86%, and 12.09%, whereas that in patients with CKD stage 3a at S-K 5.1-5.4, 5.5-5.9, and ?6.0 mEq/l increased to 10.31%, 11.43%, and 22.64%, respectively. Despite treatment with loop diuretics (18.5%) and potassium binders (5.8%), >30% of patients had persistently high S-K (?5.1 mEq/l). Conclusion:This study provides real-world insight on hyperkalemia based on a large number of patients with various medical backgrounds.
| S-EPMC6734103 | biostudies-literature
Project description:Cancer of unknown primary (CUP) is a heterogeneous malignancy in which the primary site of the tumor cannot be identified through standard work-up. The survival outcome of CUP is generally poor, and there is no consensus for treatment. Here, we comprehensively analyzed the real-world data of 218 patients with CUP (median age, 62 years [range, 19-91]; male, 62.3%). Next-generation sequencing was conducted in 22 (10%) patients, one of whom showed level 1 genetic alteration. Most (60.3%) patients were treated with empirical cytotoxic chemotherapy, and two patients received targeted therapy based on the NGS results. The median OS was 8.3 months (95% confidence interval [CI] 6.2-11.4), and the median progression-free survival of patients treated with chemotherapy was 4.4 months (95% CI 3.4-5.3). In multivariate Cox regression analysis, Eastern Cooperative Oncology Group performance status (ECOG PS) of 0 or 1 and localized disease were significantly associated with favorable survival outcomes. Collectively, we found that CUP patients had a poor prognosis after standard treatment, and those with localized disease who received local treatment and those with better PS treated with multiple lines of chemotherapy had better survival outcomes. Targeted therapies based on NGS results are expected to improve survival outcomes.
| S-EPMC8630084 | biostudies-literature