Hospital admission risk stratification of patients with gout presenting to the emergency department

Abstract To characterise gout patients at high risk of hospitalisation and to develop a web-based prognostic model to predict the likelihood of gout-related hospital admissions. This was a retrospective single-centre study of 1417 patients presenting to the emergency department (ED) with a gout flare between 2015 and 2017 with a 1-year look-back period. The dataset was randomly divided, with 80% forming the derivation and the remaining forming the validation cohort. A multivariable logistic regression model was used to determine the likelihood of hospitalisation from a gout flare in the derivation cohort. The coefficients for the variables with statistically significant adjusted odds ratios were used for the development of a web-based hospitalisation risk estimator. The performance of this risk estimator model was assessed via the area under the receiver operating characteristic curve (AUROC), calibration plot, and brier score. Patients who were hospitalised with gout tended to be older, less likely male, more likely to have had a previous hospital stay with an inpatient primary diagnosis of gout, or a previous ED visit for gout, less likely to have been prescribed standby acute gout therapy, and had a significant burden of comorbidities. In the multivariable-adjusted analyses, previous hospitalisation for gout was associated with the highest odds of gout-related admission. Early identification of patients with a high likelihood of gout-related hospitalisation using our web-based validated risk estimator model may assist to target resources to the highest risk individuals, reducing the frequency of gout-related admissions and improving the overall health-related quality of life in the long term. Key points • We reported the characteristics of gout patients visiting a tertiary hospital in Singapore. • We developed a web-based prognostic model with non-invasive variables to predict the likelihood of gout-relatedhospital admissions.

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How to Predict Cancer-Specific Death of Patients with Chondrosarcoma: A Prognostic Model Based on Competing Risk

10.21203/rs.3.rs-851215/v1 ◽

2021 ◽

Author(s):

Binxiang Zhu ◽

Yinmin Dong ◽

Hongyu Zhu ◽

Zijian Dong ◽

Feng Li

Keyword(s):

Prognostic Model ◽

Risk Model ◽

Current Model ◽

Characteristic Curve ◽

Radical Resection ◽

Competing Risk ◽

Brier Score ◽

Calibration Plot ◽

Plot Area ◽

Probability Of Cancer

Abstract Background. As chondrosarcoma is the second highest primary malignant tumor of bone, it is necessary to find a way to predict the prognosis of chondrosarcoma. But the current model rarely involves the study of competing risk. This is a retrospective study with the aim of establishing a prognostic model and a nomogram based on competing risk to predict the probability of cancer-specific death (CSD) at 3 and 5 years. The Fine and Gray regression is a targeted statistical method, which makes the results more authentic and reliable.Methods. A total of 1674 chondrosarcoma patients were identified from the SEER database, and they were divided into training cohort and validation cohort by year of diagnosis. These two cohorts were used to develop and validate the prognostic model to predict the 3-year and 5-year probabilities of CSD, with non-CSD as the competing risk. Model accuracy made use of some verification functions, such as C-index, receiver operating characteristic curve (ROC), calibration plot, area under curve (AUC) and Brier score.Results. According to the outcomes of the model: older age (subdistribution hazards ratio(95%CI): 1.02 (1.01-1.03); P<0.001), dedifferentiated CHS (SHR(95%CI): 2.16 (1.30-3.59); P=0.003), high grade (SHR(95%CI): 2.60 (1.83-3.68); P<0.001), Regional involvement (SHR(95%CI): 3.15 (2.01-4.93); P<0.001), Distant metastasis (SHR(95%CI): 11.56 (6.82-19.59); P<0.001), tumor excision (SHR(95%CI): 0.47 (0.25-0.87); P=0.02) and Radical resection (SHR(95%CI): 0.54 (0.32-0.90); P=0.02) were significantly. They obviously promoted the increase of CSD.Conclusion. This prognostic model considered the competing risks of chondrosarcoma, and the nomogram can effectively predict the probability of CSD in patients with chondrosarcoma, which is suitable for clinical application.

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Risk factors of hospital admissions and recurrent emergency department visits among pediatric asthma patients

International Journal of Medicine in Developing Countries ◽

10.24911/ijmdc.51-1586725862 ◽

2020 ◽

pp. 1011-1015

Author(s):

Abdullah Aldamigh ◽

Afaf Alnefisah ◽

Abdulrahman Almutairi ◽

Fatima Alturki ◽

Suhailah Alhtlany ◽

...

Keyword(s):

Risk Factors ◽

Emergency Department ◽

Hospital Admissions ◽

Pediatric Asthma ◽

Emergency Department Visits ◽

Asthma Patients

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First Surveillance of Violence against Women during COVID-19 Lockdown: Experience from “Niguarda” Hospital in Milan, Italy

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18073801 ◽

2021 ◽

Vol 18 (7) ◽

pp. 3801

Author(s):

Giulio Nittari ◽

Getu Gamo Sagaro ◽

Alessandro Feola ◽

Mattia Scipioni ◽

Giovanna Ricci ◽

...

Keyword(s):

Emergency Department ◽

Violence Against Women ◽

Social Problem ◽

Medical Records ◽

Hospital Admissions ◽

Daily News ◽

The People ◽

Notable Increase

Violence against women emerges with tragic regularity in the daily news. It is now an evident trace of a dramatic social problem, the characteristics of which are not attributable to certain economic, cultural, or religious conditions of the people involved but affect indiscriminately, in a unanimous way, our society. The study is a survey about the number of hospital admissions due to episodes attributable to violence against women, recorded by the Niguarda Hospital in Milan in the period 1 March–30 May from 2017 to 2020. This period, in 2020, corresponds to the coronavirus Lockdown in Italy. All the medical records of the Emergency department were reviewed, and the extracted data classified in order to identify the episodes of violence against women and the features of the reported injuries and the characteristics of the victims. The data did not show an increase in the number of cases in 2020 compared to previous years, but we did find a notable increase in the severity of injuries.

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Functional Decline in Emergency Department Patients with Dyspnea; a Register-Based Cohort

International Journal for Quality in Health Care ◽

10.1093/intqhc/mzab047 ◽

2021 ◽

Author(s):

Karoline Stentoft Rybjerg Larsen ◽

Marianne Lisby ◽

Hans Kirkegaard ◽

Annemette Krintel Petersen

Keyword(s):

Emergency Department ◽

Electronic Patient Record ◽

Hospital Admissions ◽

Functional Decline ◽

Patient Characteristics ◽

Risk Of Death ◽

Record Data ◽

Emergency Department Patients ◽

One Year ◽

Historic Cohort

Abstract Background Functional decline is associated with frequent hospital admissions and elevated risk of death. Presumably patients acutely admitted to hospital with dyspnea have a high risk of functional decline. The aim of this study was to describe patient characteristics, hospital trajectory, and use of physiotherapy services of dyspneic patients in an emergency department. Furthermore, to compare readmission and death among patients with and without a functional decline, and to identify predictors of functional decline. Methods Historic cohort study of patients admitted to a Danish Emergency Department using prospectively collected electronic patient record data from a Business Intelligence Registry of the Central Denmark Region. The study included adult patients that due to dyspnea in 2015 were treated at the emergency department (ED). The main outcome measures were readmission, death, and functional decline. Results In total 2,048 dyspneic emergency treatments were registered. Within 30 days after discharge 20% was readmitted and 3.9% had died. Patients with functional decline had a higher rate of 30-day readmission (31.2% vs. 19.1%, p<0.001) and mortality (9.3% vs. 3.6%, p=0.009) as well as mortality within one year (36.1% vs. 13.4%, p<0.001). Predictors of functional decline were age ≥60 years and hospital stay ≥6 days. Conclusion Patients suffering from acute dyspnea are seen at the ED at all hours. In total one in five patients were readmitted and 3.9% died within 30 days. Patients with a functional decline at discharge seems to be particularly vulnerable.

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Predicting hospital admissions from individual patient data (IPD): an applied example to explore key elements driving external validity

BMJ Open ◽

10.1136/bmjopen-2020-045572 ◽

2021 ◽

Vol 11 (8) ◽

pp. e045572

Author(s):

Andreas Daniel Meid ◽

Ana Isabel Gonzalez-Gonzalez ◽

Truc Sophia Dinh ◽

Jeanet Blom ◽

Marjan van den Akker ◽

...

Keyword(s):

Prognostic Model ◽

Prediction Models ◽

Hospital Admissions ◽

Absolute Risk ◽

External Validation ◽

Baseline Risk ◽

Study Heterogeneity ◽

Related Quality ◽

Individual Participant ◽

Risk Predictor

ObjectiveTo explore factors that potentially impact external validation performance while developing and validating a prognostic model for hospital admissions (HAs) in complex older general practice patients.Study design and settingUsing individual participant data from four cluster-randomised trials conducted in the Netherlands and Germany, we used logistic regression to develop a prognostic model to predict all-cause HAs within a 6-month follow-up period. A stratified intercept was used to account for heterogeneity in baseline risk between the studies. The model was validated both internally and by using internal-external cross-validation (IECV).ResultsPrior HAs, physical components of the health-related quality of life comorbidity index, and medication-related variables were used in the final model. While achieving moderate discriminatory performance, internal bootstrap validation revealed a pronounced risk of overfitting. The results of the IECV, in which calibration was highly variable even after accounting for between-study heterogeneity, agreed with this finding. Heterogeneity was equally reflected in differing baseline risk, predictor effects and absolute risk predictions.ConclusionsPredictor effect heterogeneity and differing baseline risk can explain the limited external performance of HA prediction models. With such drivers known, model adjustments in external validation settings (eg, intercept recalibration, complete updating) can be applied more purposefully.Trial registration numberPROSPERO id: CRD42018088129.

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Integrated analysis of methylation-driven genes and pretreatment prognostic factors in patients with hepatocellular carcinoma

BMC Cancer ◽

10.1186/s12885-021-08314-5 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Dongsheng He ◽

Shengyin Liao ◽

Lifang Cai ◽

Weiming Huang ◽

Xuehua Xie ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Prognostic Factors ◽

Risk Score ◽

Prognostic Model ◽

Cox Regression ◽

The Cancer Genome Atlas ◽

Integrated Analysis ◽

Calibration Plot ◽

Clinical Parameters ◽

T Stage

Abstract Background The potential reversibility of aberrant DNA methylation indicates an opportunity for oncotherapy. This study aimed to integrate methylation-driven genes and pretreatment prognostic factors and then construct a new individual prognostic model in hepatocellular carcinoma (HCC) patients. Methods The gene methylation, gene expression dataset and clinical information of HCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Methylation-driven genes were screened with a Pearson’s correlation coefficient less than − 0.3 and a P value less than 0.05. Univariable and multivariable Cox regression analyses were performed to construct a risk score model and identify independent prognostic factors from the clinical parameters of HCC patients. The least absolute shrinkage and selection operator (LASSO) technique was used to construct a nomogram that might act to predict an individual’s OS, and then C-index, ROC curve and calibration plot were used to test the practicability. The correlation between clinical parameters and core methylation-driven genes of HCC patients was explored with Student’s t-test. Results In this study, 44 methylation-driven genes were discovered, and three prognostic signatures (LCAT, RPS6KA6, and C5orf58) were screened to construct a prognostic risk model of HCC patients. Five clinical factors, including T stage, risk score, cancer status, surgical method and new tumor events, were identified from 13 clinical parameters as pretreatment-independent prognostic factors. To avoid overfitting, LASSO analysis was used to construct a nomogram that could be used to calculate the OS in HCC patients. The C-index was superior to that from previous studies (0.75 vs 0.717, 0.676). Furthermore, LCAT was found to be correlated with T stage and new tumor events, and RPS6KA6 was found to be correlated with T stage. Conclusion We identified novel therapeutic targets and constructed an individual prognostic model that can be used to guide personalized treatment in HCC patients.

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81 Integrating A Front Door Frailty Service in the Emergency Department: Results of A Pilot Study

Age and Ageing ◽

10.1093/ageing/afab030.42 ◽

2021 ◽

Vol 50 (Supplement_1) ◽

pp. i12-i42

Author(s):

L Dunnell ◽

A Shrestha ◽

E Li ◽

Z Khan ◽

N Hashemi

Keyword(s):

Emergency Department ◽

Hospital Admissions ◽

Admission Rate ◽

Community Services ◽

Service Improvement ◽

Specialist Nurse ◽

Front Door ◽

Medication Changes ◽

Health Service Improvement

Abstract Introduction Increasing old age and frailty is putting pressure on health services with 5–10% of patients attending the emergency department (ED) and 30% of patients in acute medical units classified as older and frail. National Health Service improvement mandates that by 2020 hospital trusts with type one EDs provide at least 70 hours of acute frailty service each week. Methodology A two-week pilot (Monday–Friday 8 am-5 pm) was undertaken, with a “Front Door Frailty Team” comprising a consultant, junior doctor, specialist nurse and pharmacist, with therapy input from the existing ED team. They were based in the ED seeing patients on arrival, referrals from the ED team and patients in the ED observation ward—opposed to the usual pathway of referral from the ED team to medical team. Data was captured using “Cerner” electronic healthcare records. A plan, do, study, act methodology was used throughout with daily debrief and huddle sessions. Results 95 patients were seen over two weeks. In the over 65 s, average time to be seen was 50 minutes quicker than the ED team over the same period, with reduced admission rate (25.7% vs 46.5%). The wait between decision to admit and departure was shortened by 119 minutes. Overall, this led to patients spending on average 133 minutes less in the ED. 64 patients were discharged, of which 44 had community follow-up (including 37.5% of 64 referred to acute elderly clinic and 25% to rapid response). 47 medications were stopped across 25 patients. Conclusion The pilot shows that introduction of an early comprehensive geriatric assessment in the ED can lead to patients being seen sooner, with more timely decisions over their care and reduction in hospital admissions. It allowed for greater provision of acute clinics and community services as well as prompt medication review and real time medication changes.

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Developing a scoring tool to estimate the risk of deterioration for normotensive patients with acute pulmonary embolism on admission

Respiratory Research ◽

10.1186/s12931-020-01602-x ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Yizhuo Gao ◽

Chao Ji ◽

Hongyu Zhao ◽

Jun Han ◽

Haitao Shen ◽

...

Keyword(s):

Pulmonary Embolism ◽

Acute Pulmonary Embolism ◽

Clinical Laboratory ◽

Systolic Pressure ◽

Adverse Outcomes ◽

Web Based ◽

Derivation Cohort ◽

Risk Scoring ◽

Scoring Tool ◽

Acute Pe

Abstract Background It is important to identify deterioration in normotensive patients with acute pulmonary embolism (PE). This study aimed to develop a tool for predicting deterioration among normotensive patients with acute PE on admission. Methods Clinical, laboratory, and computed tomography parameters were retrospectively collected for normotensive patients with acute PE who were treated at a Chinese center from January 2011 to May 2020 on admission into the hospital. The endpoint of the deterioration was any adverse outcome within 30 days. Eligible patients were randomized 2:1 to derivation and validation cohorts, and a nomogram was developed and validated by the aforementioned cohorts, respectively. The areas under the curves (AUCs) with 95% confidence intervals (CIs) were calculated. A risk-scoring tool for predicting deterioration was applied as a web-based calculator. Results The 845 eligible patients (420 men, 425 women) had an average age of 60.05 ± 15.43 years. Adverse outcomes were identified for 81 patients (9.6%). The nomogram for adverse outcomes included heart rate, systolic pressure, N-terminal-pro brain natriuretic peptide, and ventricle/atrial diameter ratios at 4-chamber view, which provided AUC values of 0.925 in the derivation cohort (95% CI 0.900–0.946, p < 0.001) and 0.900 in the validation cohort (95% CI 0.883–0.948, p < 0.001). A risk-scoring tool was published as a web-based calculator (https://gaoyzcmu.shinyapps.io/APE9AD/). Conclusions We developed a web-based scoring tool that may help predict deterioration in normotensive patients with acute PE.

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Comparative 4-year risk and type of hospital admission among homeless and housed emergency department attendees: longitudinal study of hospital records in England 2013–2018

BMJ Open ◽

10.1136/bmjopen-2021-049811 ◽

2021 ◽

Vol 11 (7) ◽

pp. e049811

Author(s):

Charlie Moss ◽

Matt Sutton ◽

Sudeh Cheraghi-Sohi ◽

Caroline Sanders ◽

Thomas Allen

Keyword(s):

Emergency Department ◽

Hospital Admissions ◽

Primary Diagnosis ◽

Secondary Outcome ◽

Emergency Admissions ◽

Incident Rate Ratio ◽

Chronic Angina ◽

Access To Primary Care ◽

Incident Rate ◽

Preventable Admissions

ObjectivesPeople experiencing homelessness are frequent users of secondary care. Currently, there is no study of potentially preventable admissions for homeless patients in England. We aim to estimate the number of potentially preventable hospital admissions for homeless patients and compare to housed patients with similar characteristics.DesignRetrospective matched cohort study.SettingHospitals in England.Participants16 161 homeless patients and 74 780 housed patients aged 16–75 years who attended an emergency department (ED) in England in 2013/2014, matched on the basis of age, sex, ED attended and primary diagnosis.Primary and secondary outcome measuresAnnual counts of admissions, emergency admissions, ambulatory care-sensitive (ACS) emergency admissions, acute ACS emergency admissions and chronic ACS emergency admissions over the following 4 years (2014/2015–2017/2018). We additionally compare the prevalence of specific ACS conditions for homeless and housed patients.ResultsMean admissions per 1000 patients per year were 470 for homeless patients and 230 for housed patients. Adjusted for confounders, annual admissions were 1.79 times higher (incident rate ratio (IRR)=1.79; 95% CI 1.69 to 1.90), emergency admissions 2.08 times higher (IRR=2.08; 95% CI 1.95 to 2.21) and ACS admissions 1.65 times higher (IRR=1.65; 95% CI 1.51 to 1.80), compared with housed patients. The effect was greater for acute (IRR=1.78; 95% CI 1.64 to 1.93) than chronic (IRR=1.45; 95% CI 1.27 to 1.66) ACS conditions. ACS conditions that were relatively more common for homeless patients were cellulitis, convulsions/epilepsy and chronic angina.ConclusionsHomeless patients use hospital services at higher rates than housed patients, particularly emergency admissions. ACS admissions of homeless patients are higher which suggests some admissions may be potentially preventable with improved access to primary care. However, these admissions comprise a small share of total admissions.

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