Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 203
Filtrar
1.
Heart Lung Circ ; 2024 Apr 04.
Artículo en Inglés | MEDLINE | ID: mdl-38580581

RESUMEN

BACKGROUND: In Australia, transcatheter aortic valve implantation (TAVI) is only performed in a limited number of specialised metropolitan centres, many of which are private hospitals, making it likely that TAVI patients who require readmission will present to another (non-index) hospital. It is important to understand the impact of non-index readmission on patient outcomes and healthcare resource utilisation. METHOD: We analysed linked hospital and death records for residents of New South Wales, Australia, aged ≥18 years, who had an emergency readmission within 90 days following a TAVI procedure in 2013-2022. Mixed-effect, multi-level logistic regression models were used to evaluate predictors of non-index readmission, and associations between non-index readmission and readmission length of stay, 90-day mortality, and 1-year mortality. RESULTS: Of 4,198 patients (mean age, 82.7 years; 40.6% female) discharged alive following TAVI, 933 (22.2%) were readmitted within 90 days of discharge. Over three-quarters (76.0%) of those readmitted returned to a non-index hospital, with no significant difference in readmission principal diagnosis between index hospital and non-index hospital readmissions. Among readmitted patients, independent predictors of non-index readmission included: residence in regional or remote areas, lower socio-economic status, having a pre-procedure transfer, and a private index hospital. Readmission length of stay (median, 4 days), 90-day mortality (adjusted odds ratio [OR] 1.04, 95% confidence interval [CI] 0.56-1.96) and 1-year mortality (adjusted OR 1.01, 95% CI 0.64-1.58) were similar between index and non-index readmissions. CONCLUSIONS: Non-index readmission following TAVI was highly prevalent but not associated with increased mortality or healthcare utilisation. Our results are reassuring for TAVI patients in regional and remote areas with limited access to return to index TAVI hospitals.

2.
Hum Reprod ; 2024 Mar 20.
Artículo en Inglés | MEDLINE | ID: mdl-38509860

RESUMEN

Researchers interested in causal questions must deal with two sources of error: random error (random deviation from the true mean value of a distribution), and bias (systematic deviance from the true mean value due to extraneous factors). For some causal questions, randomization is not feasible, and observational studies are necessary. Bias poses a substantial threat to the validity of observational research and can have important consequences for health policy developed from the findings. The current piece describes bias and its sources, outlines proposed methods to estimate its impacts in an observational study, and demonstrates how these methods may be used to inform debate on the causal relationship between medically assisted reproduction (MAR) and health outcomes, using cancer as an example. In doing so, we aim to enlighten researchers who work with observational data, especially regarding the health effects of MAR and infertility, on the pitfalls of bias, and how to address them. We hope that, in combination with the provided example, we can convince readers that estimating the impact of bias in causal epidemiologic research is not only important but necessary to inform the development of robust health policy and clinical practice recommendations.

3.
Med J Aust ; 2024 Mar 21.
Artículo en Inglés | MEDLINE | ID: mdl-38514449

RESUMEN

OBJECTIVE: To assess the impact of the Health Care Homes (HCH) primary health care initiative on quality of care and patient outcomes. DESIGN, SETTING: Quasi-experimental, matched cohort study; analysis of general practice data extracts and linked administrative data from ten Australian primary health networks, 1 October 2017 - 30 June 2021. PARTICIPANTS: People with chronic health conditions (practice data extracts: 9811; linked administrative data: 10 682) enrolled in the HCH 1 October 2017 - 30 June 2019; comparison groups of patients receiving usual care (1:1 propensity score-matched). INTERVENTION: Participants were involved in shared care planning, provided enhanced access to team care, and encouraged to seek chronic condition care at the HCH practice where they were enrolled. Participating practices received bundled payments based on clinical risk tier. MAIN OUTCOME MEASURES: Access to care, processes of care, diabetes-related outcomes, hospital service use, risk of death. RESULTS: During the first twelve months after enrolment, the mean numbers of general practitioner encounters (rate ratio, 1.14; 95% confidence interval [CI], 1.11-1.17) and Medicare Benefits Schedule claims for allied health services (rate ratio, 1.28; 95% CI, 1.24-1.33) were higher for the HCH than the usual care group. Annual influenza vaccinations (relative risk, 1.20; 95% CI, 1.17-1.22) and measurements of blood pressure (relative risk, 1.09; 95% CI, 1.08-1.11), blood lipids (relative risk, 1.19; 95% CI, 1.16-1.21), glycated haemoglobin (relative risk, 1.06; 95% CI, 1.03-1.08), and kidney function (relative risk, 1.13; 95% CI, 1.11-1.15) were more likely in the HCH than the usual care group during the twelve months after enrolment. Similar rate ratios and relative risks applied in the second year. The numbers of emergency department presentations (rate ratio, 1.09; 95% CI, 1.02-1.18) and emergency admissions (rate ratio, 1.13; 95% CI, 1.04-1.22) were higher for the HCH group during the first year; other differences in hospital use were not statistically significant. Differences in glycaemic and blood pressure control in people with diabetes in the second year were not statistically significant. By 30 June 2021, 689 people in the HCH group (6.5%) and 646 in the usual care group (6.1%) had died (hazard ratio, 1.07; 95% CI, 0.96-1.20). CONCLUSIONS: The HCH program was associated with greater access to care and improved processes of care for people with chronic diseases, but not changes in diabetes-related outcomes, most measures of hospital use, or risk of death.

5.
Heart Lung Circ ; 2024 Feb 15.
Artículo en Inglés | MEDLINE | ID: mdl-38365498

RESUMEN

BACKGROUND AND AIM: To develop prognostic survival models for predicting adverse outcomes after catheter ablation treatment for non-valvular atrial fibrillation (AF) and/or atrial flutter (AFL). METHODS: We used a linked dataset including hospital administrative data, prescription medicine claims, emergency department presentations, and death registrations of patients in New South Wales, Australia. The cohort included patients who received catheter ablation for AF and/or AFL. Traditional and deep survival models were trained to predict major bleeding events and a composite of heart failure, stroke, cardiac arrest, and death. RESULTS: Out of a total of 3,285 patients in the cohort, 177 (5.3%) experienced the composite outcome-heart failure, stroke, cardiac arrest, death-and 167 (5.1%) experienced major bleeding events after catheter ablation treatment. Models predicting the composite outcome had high-risk discrimination accuracy, with the best model having a concordance index >0.79 at the evaluated time horizons. Models for predicting major bleeding events had poor risk discrimination performance, with all models having a concordance index <0.66. The most impactful features for the models predicting higher risk were comorbidities indicative of poor health, older age, and therapies commonly used in sicker patients to treat heart failure and AF and AFL. DISCUSSION: Diagnosis and medication history did not contain sufficient information for precise risk prediction of experiencing major bleeding events. Predicting the composite outcome yielded promising results, but future research is needed to validate the usefulness of these models in clinical practice. CONCLUSIONS: Machine learning models for predicting the composite outcome have the potential to enable clinicians to identify and manage high-risk patients following catheter ablation for AF and AFL proactively.

6.
Lancet Reg Health West Pac ; 44: 101013, 2024 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-38384947

RESUMEN

Fragmented care delivery is a barrier to improving health system performance worldwide. Investment in meso-level organisations is a potential strategy to improve health system integration, however, its effectiveness remains unclear. In this paper, we provide an overview of key international and Australian integrated care policies. We then describe Collaborative Commissioning - a novel health reform policy to integrate primary and hospital care sectors in New South Wales (NSW), Australia and provide a case study of a model focussed on older person's care. The policy is theorised to achieve greater integration through improved governance (local stakeholders identifying as part of one health system), service delivery (communities perceive new services as preferable to status quo) and incentives (efficiency gains are reinvested locally with progressively higher value care achieved). If effectively implemented at scale, Collaborative Commissioning has potential to improve health system performance in Australia and will be of relevance to similar reform initiatives in other countries.

7.
Sci Rep ; 14(1): 2493, 2024 01 30.
Artículo en Inglés | MEDLINE | ID: mdl-38291336

RESUMEN

We investigated the impact of distance covered in the six-minute walk test (6mWT) before being discharged from the hospital after cardiac surgery on the risk of all-cause mortality. Our study included 1127 patients who underwent cardiac surgery and then took part in a standardised physiotherapist-supervised inpatient rehabilitation programme during 2007-2017. The percentage of the predicted 6mWT distance, and the lower limit of normal distance was calculated based on individual patients' age, sex, and body mass index. We used Cox regression with adjustment for confounders to determine multivariable-adjusted hazard ratios (HRs) for mortality. Over a median follow-up period of 6.4 (IQR: 3.5-9.2) years, 15% (n = 169) patients died. We observed a strong and independent inverse association between 6mWT distance and mortality, with every 10 m increase in distance associated to a 4% reduction in mortality (HR: 0.96, 95% CI 0.94-0.98, P < 0.001). Those in the top tertile for predicted 6mWT performance had a 49% reduced risk of mortality (HR: 0.51, 95% CI 0.33-0.79) compared to those in the bottom tertile. Patients who met or exceeded the minimum normal 6mWT distance had 36% lower mortality risk (HR: 0.64, 95% CI 0.45-0.92) compared to those who did not meet this benchmark. Subgroup analysis showed that combined CABG and valve surgery patients walked less in the 6mWT compared to those undergoing isolated CABG or valve surgeries, with a significant association between 6mWT and mortality observed in the isolated procedure groups only. In conclusion, the longer the distance covered in the 6mWT before leaving the hospital, the lower the risk of mortality.


Asunto(s)
Procedimientos Quirúrgicos Cardíacos , Alta del Paciente , Humanos , Prueba de Paso , Caminata , Factores de Tiempo , Prueba de Esfuerzo
8.
Bone Jt Open ; 5(1): 60-68, 2024 Jan 24.
Artículo en Inglés | MEDLINE | ID: mdl-38265059

RESUMEN

Aims: It is unclear whether mortality outcomes differ for patients undergoing total hip arthroplasty (THA) or total knee arthroplasty (TKA) surgery who are readmitted to the index hospital where their surgery was performed, or to another hospital. Methods: We analyzed linked hospital and death records for residents of New South Wales, Australia, aged ≥ 18 years who had an emergency readmission within 90 days following THA or TKA surgery between 2003 and 2022. Multivariable modelling was used to identify factors associated with non-index readmission and to evaluate associations of readmission destination (non-index vs index) with 90-day and one-year mortality. Results: Of 394,248 joint arthroplasty patients (THA = 149,456; TKA = 244,792), 9.5% (n = 37,431) were readmitted within 90 days, and 53.7% of these were admitted to a non-index hospital. Non-index readmission was more prevalent among patients who underwent surgery in private hospitals (60%). Patients who were readmitted for non-orthopaedic conditions (62.8%), were more likely to return to a non-index hospital compared to those readmitted for orthopaedic complications (39.5%). Factors associated with non-index readmission included older age, higher socioeconomic status, private health insurance, and residence in a rural or remote area. Non-index readmission was significantly associated with 90-day (adjusted odds ratio (aOR) 1.69; 95% confidence interval (CI) 1.39 to 2.05) and one-year mortality (aOR 1.31; 95% CI 1.16 to 1.47). Associations between non-index readmission and mortality were similar for patients readmitted with orthopaedic and non-orthopaedic complications (90-day mortality aOR 1.61; 95% CI 0.98 to 2.64, and aOR 1.67; 95% CI 1.35 to 2.06, respectively). Conclusion: Non-index readmission was associated with increased mortality, irrespective of whether the readmission was for orthopaedic complications or other conditions.

9.
JMIR Med Educ ; 10: e51388, 2024 Jan 16.
Artículo en Inglés | MEDLINE | ID: mdl-38227356

RESUMEN

Large-scale medical data sets are vital for hands-on education in health data science but are often inaccessible due to privacy concerns. Addressing this gap, we developed the Health Gym project, a free and open-source platform designed to generate synthetic health data sets applicable to various areas of data science education, including machine learning, data visualization, and traditional statistical models. Initially, we generated 3 synthetic data sets for sepsis, acute hypotension, and antiretroviral therapy for HIV infection. This paper discusses the educational applications of Health Gym's synthetic data sets. We illustrate this through their use in postgraduate health data science courses delivered by the University of New South Wales, Australia, and a Datathon event, involving academics, students, clinicians, and local health district professionals. We also include adaptable worked examples using our synthetic data sets, designed to enrich hands-on tutorial and workshop experiences. Although we highlight the potential of these data sets in advancing data science education and health care artificial intelligence, we also emphasize the need for continued research into the inherent limitations of synthetic data.


Asunto(s)
Inteligencia Artificial , Infecciones por VIH , Humanos , Ciencia de los Datos , Infecciones por VIH/tratamiento farmacológico , Educación en Salud , Ejercicio Físico
10.
BMJ Open ; 14(1): e074624, 2024 01 06.
Artículo en Inglés | MEDLINE | ID: mdl-38184309

RESUMEN

OBJECTIVE: Timely access to primary care and supporting specialist care relative to need is essential for health equity. However, use of services can vary according to an individual's socioeconomic circumstances or where they live. This study aimed to quantify individual socioeconomic variation in general practitioner (GP) and specialist use in New South Wales (NSW), accounting for area-level variation in use. DESIGN: Outcomes were GP use and quality-of-care and specialist use. Multilevel logistic regression was used to estimate: (1) median ORs (MORs) to quantify small area variation in outcomes, which gives the median increased risk of moving to an area of higher risk of an outcome, and (2) ORs to quantify associations between outcomes and individual education level, our main exposure variable. Analyses were adjusted for individual sociodemographic and health characteristics and performed separately by remoteness categories. SETTING: Baseline data (2006-2009) from the 45 and Up Study, NSW, Australia, linked to Medicare Benefits Schedule and death data (to December 2012). PARTICIPANTS: 267 153 adults aged 45 years and older. RESULTS: GP (MOR=1.32-1.35) and specialist use (1.16-1.18) varied between areas, accounting for individual characteristics. For a given level of need and accounting for area variation, low education-level individuals were more likely to be frequent users of GP services (no school certificate vs university, OR=1.63-1.91, depending on remoteness category) and have continuity of care (OR=1.14-1.24), but were less likely to see a specialist (OR=0.85-0.95). CONCLUSION: GP and specialist use varied across small areas in NSW, independent of individual characteristics. Use of GP care was equitable, but specialist care was not. Failure to address inequitable specialist use may undermine equity gains within the primary care system. Policies should also focus on local variation.


Asunto(s)
Médicos Generales , Web Semántica , Adulto , Anciano , Humanos , Análisis Multinivel , Programas Nacionales de Salud , Australia , Escolaridad
11.
Ann Intern Med ; 176(10): 1308-1320, 2023 10.
Artículo en Inglés | MEDLINE | ID: mdl-37812776

RESUMEN

BACKGROUND: More than 2 million children are conceived annually using assisted reproductive technologies (ARTs), with a similar number conceived using ovulation induction and intrauterine insemination (OI/IUI). Previous studies suggest that ART-conceived children are at increased risk for congenital anomalies (CAs). However, the role of underlying infertility in this risk remains unclear, and ART clinical and laboratory practices have changed drastically over time, particularly there has been an increase in intracytoplasmic sperm injection (ICSI) and cryopreservation. OBJECTIVE: To investigate the role of underlying infertility and fertility treatment on CA risks in the first 2 years of life. DESIGN: Propensity score-weighted population-based cohort study. SETTING: New South Wales, Australia. PARTICIPANTS: 851 984 infants (828 099 singletons and 23 885 plural children) delivered between 2009 and 2017. MEASUREMENTS: Adjusted risk difference (aRD) in CAs of infants conceived through fertility treatment compared with 2 naturally conceived (NC) control groups-those with and without a parental history of infertility (NC-infertile and NC-fertile). RESULTS: The overall incidence of CAs was 459 per 10 000 singleton births and 757 per 10 000 plural births. Compared with NC-fertile singleton control infants (n = 747 018), ART-conceived singleton infants (n = 31 256) had an elevated risk for major genitourinary abnormalities (aRD, 19.0 cases per 10 000 births [95% CI, 2.3 to 35.6]); the risk remained unchanged (aRD, 22 cases per 10 000 births [CI, 4.6 to 39.4]) when compared with NC-infertile singleton control infants (n = 36 251) (that is, after accounting for parental infertility), indicating that ART remained an independent risk. After accounting for parental infertility, ICSI in couples without male infertility was associated with an increased risk for major genitourinary abnormalities (aRD, 47.8 cases per 10 000 singleton births [CI, 12.6 to 83.1]). There was some suggestion of increased risk for CAs after fresh embryo transfer, although estimates were imprecise and inconsistent. There were no increased risks for CAs among OI/IUI-conceived infants (n = 13 574). LIMITATIONS: This study measured the risk for CAs only in those children who were born at or after 20 weeks' gestation. Observational study design precludes causal inference. Many estimates were imprecise. CONCLUSION: Patients should be counseled on the small increased risk for genitourinary abnormalities after ART, particularly after ICSI, which should be avoided in couples without problems of male infertility. PRIMARY FUNDING SOURCE: Australian National Health and Medical Research Council.


Asunto(s)
Infertilidad Masculina , Anomalías Urogenitales , Femenino , Humanos , Lactante , Masculino , Embarazo , Australia , Estudios de Cohortes , Resultado del Embarazo , Semen , Recién Nacido , Preescolar
12.
Int J Equity Health ; 22(1): 226, 2023 10 23.
Artículo en Inglés | MEDLINE | ID: mdl-37872627

RESUMEN

BACKGROUND: International evidence suggests patients receiving cardiac interventions experience differential outcomes by their insurance status. We investigated outcomes of in-hospital care according to insurance status among patients admitted in public hospitals with acute myocardial infarction (AMI) undergoing percutaneous coronary intervention (PCI). METHODS: We conducted a cohort study within the Australian universal health care system with supplemental private insurance. Using linked hospital and mortality data, we included patients aged 18 + years admitted to New South Wales public hospitals with AMI and undergoing their first PCI from 2017-2020. We measured hospital-acquired complications (HACs), length of stay (LOS) and in-hospital mortality among propensity score-matched private and publicly funded patients. Matching was based on socio-demographic, clinical, admission and hospital-related factors. RESULTS: Of 18,237 inpatients, 30.0% were privately funded. In the propensity-matched cohort (n = 10,630), private patients had lower rates of in-hospital mortality than public patients (odds ratio: 0.59, 95% CI: 0.45-0.77; approximately 11 deaths avoided per 1,000 people undergoing PCI procedures). Mortality differences were mostly driven by STEMI patients and those from major cities. There were no significant differences in rates of HACs or average LOS in private, compared to public, patients. CONCLUSION: Our findings suggest patients undergoing PCI in Australian public hospitals with private health insurance experience lower in-hospital mortality compared with their publicly insured counterparts, but in-hospital complications are not related to patient health insurance status. Our findings are likely due to unmeasured confounding of broader patient selection, socioeconomic differences and pathways of care (e.g. access to emergency and ambulatory care; delays in treatment) that should be investigated to improve equity in health outcomes.


Asunto(s)
Infarto del Miocardio , Intervención Coronaria Percutánea , Humanos , Intervención Coronaria Percutánea/efectos adversos , Estudios de Cohortes , Nueva Gales del Sur/epidemiología , Australia , Infarto del Miocardio/cirugía , Seguro de Salud , Hospitales Públicos , Resultado del Tratamiento , Mortalidad Hospitalaria
13.
Artif Intell Med ; 144: 102662, 2023 10.
Artículo en Inglés | MEDLINE | ID: mdl-37783551

RESUMEN

Encouraged by the success of pretrained Transformer models in many natural language processing tasks, their use for International Classification of Diseases (ICD) coding tasks is now actively being explored. In this study, we investigated two existing Transformer-based models (PLM-ICD and XR-Transformer) and proposed a novel Transformer-based model (XR-LAT), aiming to address the extreme label set and long text classification challenges that are posed by automated ICD coding tasks. The Transformer-based model PLM-ICD, which currently holds the state-of-the-art (SOTA) performance on the ICD coding benchmark datasets MIMIC-III and MIMIC-II, was selected as our baseline model for further optimisation on both datasets. In addition, we extended the capabilities of the leading model in the general extreme multi-label text classification domain, XR-Transformer, to support longer sequences and trained it on both datasets. Moreover, we proposed a novel model, XR-LAT, which was also trained on both datasets. XR-LAT is a recursively trained model chain on a predefined hierarchical code tree with label-wise attention, knowledge transferring and dynamic negative sampling mechanisms. Our optimised PLM-ICD models, which were trained with longer total and chunk sequence lengths, significantly outperformed the current SOTA PLM-ICD models, and achieved the highest micro-F1 scores of 60.8 % and 50.9 % on MIMIC-III and MIMIC-II, respectively. The XR-Transformer model, although SOTA in the general domain, did not perform well across all metrics. The best XR-LAT based models obtained results that were competitive with the current SOTA PLM-ICD models, including improving the macro-AUC by 2.1 % and 5.1 % on MIMIC-III and MIMIC-II, respectively. Our optimised PLM-ICD models are the new SOTA models for automated ICD coding on both datasets, while our novel XR-LAT models perform competitively with the previous SOTA PLM-ICD models.


Asunto(s)
Clasificación Internacional de Enfermedades , Memoria , Procesamiento de Lenguaje Natural
14.
BMJ Open ; 13(9): e076860, 2023 09 22.
Artículo en Inglés | MEDLINE | ID: mdl-37739460

RESUMEN

INTRODUCTION: Current efforts to reduce dementia focus on prevention and risk reduction by targeting modifiable risk factors. As dementia and cardiometabolic non-communicable diseases (NCDs) share risk factors, a single risk-estimating tool for dementia and multiple NCDs could be cost-effective and facilitate concurrent assessments as compared with a conventional single approach. The aim of this study is to develop and validate a new risk tool that estimates an individual's risk of developing dementia and other NCDs including diabetes mellitus, stroke and myocardial infarction. Once validated, it could be used by the public and general practitioners. METHODS AND ANALYSIS: Ten high-quality cohort studies from multiple countries were identified, which met eligibility criteria, including large representative samples, long-term follow-up, data on clinical diagnoses of dementia and NCDs, recognised modifiable risk factors for the four NCDs and mortality data. Pooled harmonised data from the cohorts will be used, with 65% randomly allocated for development of the predictive model and 35% for testing. Predictors include sociodemographic characteristics, general health risk factors and lifestyle/behavioural risk factors. A subdistribution hazard model will assess the risk factors' contribution to the outcome, adjusting for competing mortality risks. Point-based scoring algorithms will be built using predictor weights, internally validated and the discriminative ability and calibration of the model will be assessed for the outcomes. Sensitivity analyses will include recalculating risk scores using logistic regression. ETHICS AND DISSEMINATION: Ethics approval is provided by the University of New South Wales Human Research Ethics Committee (UNSW HREC; protocol numbers HC200515, HC3413). All data are deidentified and securely stored on servers at Neuroscience Research Australia. Study findings will be presented at conferences and published in peer-reviewed journals. The tool will be accessible as a public health resource. Knowledge translation and implementation work will explore strategies to apply the tool in clinical practice.


Asunto(s)
Demencia , Diabetes Mellitus , Infarto del Miocardio , Enfermedades no Transmisibles , Accidente Cerebrovascular , Humanos , Diabetes Mellitus/diagnóstico , Diabetes Mellitus/epidemiología , Factores de Riesgo , Infarto del Miocardio/diagnóstico , Infarto del Miocardio/epidemiología , Infarto del Miocardio/etiología , Accidente Cerebrovascular/diagnóstico , Accidente Cerebrovascular/epidemiología , Accidente Cerebrovascular/etiología , Demencia/diagnóstico , Demencia/epidemiología
15.
Europace ; 25(9)2023 08 02.
Artículo en Inglés | MEDLINE | ID: mdl-37703326

RESUMEN

AIMS: An infection following cardiac implantable electronic device (CIED) procedure is a serious complication, but its association with all-cause mortality is inconsistent across observational studies. To quantify the association between CIED infection and all-cause mortality in a large, contemporary cohort from New South Wales, Australia. METHODS AND RESULTS: This retrospective cohort study used linked hospital and mortality data and included all patients aged >18 years who underwent a CIED procedure between July 2017 and September 2022. Cardiac implantable electronic device infection was defined by the presence of relevant diagnosis codes. Cox regression to estimate adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs) for the association of CIED infection with mortality, at 1-year, and at the end of follow-up, with CIED infection included as a time-dependent variable, and other potential risk factors for mortality included as fixed covariates. We followed 37,750 patients with CIED procedures {36% female, mean age [standard deviation (SD)] 75.8 [12.7] years}, and 487 (1.3%) CIED infections were identified. We observed 5771 (15.3%) deaths during an average follow-up of 25.2 (SD 16.8) months. Compared with no infection group, patients with CIED infection had a higher Kaplan-Meier mortality rate (19.4 vs. 6.8%) and adjusted hazard of mortality (aHR 2.73, 95% CI 2.10-3.54) at 12 months post-procedure. These differences were attenuated but still remained significant at the end of follow-up (aHR 1.83, 95% CI 1.52-2.19). CONCLUSION: In a complete, state-wide cohort of CIED patients, infection was associated with higher risks of both short-term and long-term mortality.


Asunto(s)
Electrónica , Cardiopatías , Femenino , Humanos , Masculino , Australia , Hospitales , Estudios Retrospectivos , Persona de Mediana Edad , Anciano , Anciano de 80 o más Años
16.
Sci Rep ; 13(1): 15692, 2023 09 21.
Artículo en Inglés | MEDLINE | ID: mdl-37735615

RESUMEN

Both blood glucose and lactate are well-known predictors of organ dysfunction and mortality in critically ill patients. Previous research has shown that concurrent adjustment for glucose and lactate modifies the relationship between these variables and patient outcomes, including blunting of the association between blood glucose and patient outcome. We aim to investigate the relationship between ICU admission blood glucose and hospital mortality while accounting for lactate and diabetic status. Across 43,250 ICU admissions, weighted to account for missing data, we assessed the predictive ability of several logistic regression and generalised additive models that included blood glucose, blood lactate and diabetic status. We found that inclusion of blood glucose marginally improved predictive performance in all patients: AUC-ROC 0.665 versus 0.659 (p = 0.005), with a greater degree of improvement seen in non-diabetics: AUC-ROC 0.675 versus 0.663 (p < 0.001). Inspection of the estimated risk profiles revealed the standard U-shaped risk profile for blood glucose was only present in non-diabetic patients after controlling for blood lactate levels. Future research should aim to utilise observational data to estimate whether interventions such as insulin further modify this effect, with the goal of informing future RCTs of interventions targeting glycaemic control in the ICU.


Asunto(s)
Diabetes Mellitus , Hiperglucemia , Hiperlactatemia , Humanos , Hiperglucemia/complicaciones , Glucemia , Estudios Retrospectivos , Ácido Láctico , Diabetes Mellitus/epidemiología
17.
J Biomed Inform ; 146: 104498, 2023 10.
Artículo en Inglés | MEDLINE | ID: mdl-37699466

RESUMEN

OBJECTIVE: Blood glucose measurements in the intensive care unit (ICU) are typically made at irregular intervals. This presents a challenge in choice of forecasting model. This article gives an overview of continuous time autoregressive recurrent neural networks (CTRNNs) and evaluates how they compare to autoregressive gradient boosted trees (GBT) in forecasting blood glucose in the ICU. METHODS: Continuous time autoregressive recurrent neural networks (CTRNNs) are a deep learning model that account for irregular observations through incorporating continuous evolution of the hidden states between observations. This is achieved using a neural ordinary differential equation (ODE) or neural flow layer. In this manuscript, we give an overview of these models, including the varying architectures that have been proposed to account for issues such as ongoing medical interventions. Further, we demonstrate the application of these models to probabilistic forecasting of blood glucose in a critical care setting using electronic medical record and simulated data and compare with GBT and linear models. RESULTS: The experiments confirm that addition of a neural ODE or neural flow layer generally improves the performance of autoregressive recurrent neural networks in the irregular measurement setting. However, several CTRNN architecture are outperformed by a GBT model (Catboost), with only a long short-term memory (LSTM) and neural ODE based architecture (ODE-LSTM) achieving comparable performance on probabilistic forecasting metrics such as the continuous ranked probability score (ODE-LSTM: 0.118 ± 0.001; Catboost: 0.118 ± 0.001), ignorance score (0.152 ± 0.008; 0.149 ± 0.002) and interval score (175 ± 1; 176 ± 1). CONCLUSION: The application of deep learning methods for forecasting in situations with irregularly measured time series such as blood glucose shows promise. However, appropriate benchmarking by methods such as GBT approaches (plus feature transformation) are key in highlighting whether novel methodologies are truly state of the art in tabular data settings.


Asunto(s)
Benchmarking , Glucemia , Unidades de Cuidados Intensivos , Redes Neurales de la Computación , Factores de Tiempo , Registros Electrónicos de Salud , Predicción
18.
Interact J Med Res ; 12: e46322, 2023 Aug 25.
Artículo en Inglés | MEDLINE | ID: mdl-37624624

RESUMEN

BACKGROUND: The narrative free-text data in electronic medical records (EMRs) contain valuable clinical information for analysis and research to inform better patient care. However, the release of free text for secondary use is hindered by concerns surrounding personally identifiable information (PII), as protecting individuals' privacy is paramount. Therefore, it is necessary to deidentify free text to remove PII. Manual deidentification is a time-consuming and labor-intensive process. Numerous automated deidentification approaches and systems have been attempted to overcome this challenge over the past decade. OBJECTIVE: We sought to develop an accurate, web-based system deidentifying free text (DEFT), which can be readily and easily adopted in real-world settings for deidentification of free text in EMRs. The system has several key features including a simple and task-focused web user interface, customized PII types, use of a state-of-the-art deep learning model for tagging PII from free text, preannotation by an interactive learning loop, rapid manual annotation with autosave, support for project management and team collaboration, user access control, and central data storage. METHODS: DEFT comprises frontend and backend modules and communicates with central data storage through a filesystem path access. The frontend web user interface provides end users with a user-friendly workspace for managing and annotating free text. The backend module processes the requests from the frontend and performs relevant persistence operations. DEFT manages the deidentification workflow as a project, which can contain one or more data sets. Customized PII types and user access control can also be configured. The deep learning model is based on a Bidirectional Long Short-Term Memory-Conditional Random Field (BiLSTM-CRF) with RoBERTa as the word embedding layer. The interactive learning loop is further integrated into DEFT to speed up the deidentification process and increase its performance over time. RESULTS: DEFT has many advantages over existing deidentification systems in terms of its support for project management, user access control, data management, and an interactive learning process. Experimental results from DEFT on the 2014 i2b2 data set obtained the highest performance compared to 5 benchmark models in terms of microaverage strict entity-level recall and F1-scores of 0.9563 and 0.9627, respectively. In a real-world use case of deidentifying clinical notes, extracted from 1 referral hospital in Sydney, New South Wales, Australia, DEFT achieved a high microaverage strict entity-level F1-score of 0.9507 on a corpus of 600 annotated clinical notes. Moreover, the manual annotation process with preannotation demonstrated a 43% increase in work efficiency compared to the process without preannotation. CONCLUSIONS: DEFT is designed for health domain researchers and data custodians to easily deidentify free text in EMRs. DEFT supports an interactive learning loop and end users with minimal technical knowledge can perform the deidentification work with only a shallow learning curve.

19.
J Biomed Inform ; 144: 104436, 2023 08.
Artículo en Inglés | MEDLINE | ID: mdl-37451495

RESUMEN

OBJECTIVE: Clinical data's confidential nature often limits the development of machine learning models in healthcare. Generative adversarial networks (GANs) can synthesise realistic datasets, but suffer from mode collapse, resulting in low diversity and bias towards majority demographics and common clinical practices. This work proposes an extension to the classic GAN framework that includes a variational autoencoder (VAE) and an external memory mechanism to overcome these limitations and generate synthetic data accurately describing imbalanced class distributions commonly found in clinical variables. METHODS: The proposed method generated a synthetic dataset related to antiretroviral therapy for human immunodeficiency virus (ART for HIV). We evaluated it based on five metrics: (1) accurately representing imbalanced class distribution; (2) the realism of the individual variables; (3) the realism among variables; (4) patient disclosure risk; and (5) the utility of the generated dataset for developing downstream machine learning models. RESULTS: The proposed method overcomes the issue of mode collapse and generates a synthetic dataset that accurately describes imbalanced class distributions commonly found in clinical variables. The generated data has a patient disclosure risk of 0.095%, lower than the 9% threshold stated by Health Canada and the European Medicines Agency, making it suitable for distribution to the research community with high security. The generated data also has high utility, indicating the potential of the proposed method to enable the development of downstream machine learning algorithms for healthcare applications using synthetic data. CONCLUSION: Our proposed extension to the classic GAN framework, which includes a VAE and an external memory mechanism, represents a promising approach towards generating synthetic data that accurately describe imbalanced class distributions commonly found in clinical variables. This method overcomes the limitations of GANs and creates more realistic datasets with higher patient cohort diversity, facilitating the development of downstream machine learning algorithms for healthcare applications.


Asunto(s)
Infecciones por VIH , VIH , Humanos , Algoritmos , Benchmarking , Revelación , Infecciones por VIH/tratamiento farmacológico
20.
Med J Aust ; 219(7): 303-309, 2023 10 02.
Artículo en Inglés | MEDLINE | ID: mdl-37476970

RESUMEN

OBJECTIVE: To investigate elective rates of spinal fusion, decompression, and disc replacement procedures for people with degenerative conditions, by funding type (public, private, workers' compensation). DESIGN, SETTING: Cross-sectional study; analysis of hospitals admissions data extracted from the New South Wales Admitted Patient Data Collection. PARTICIPANTS: All adults who underwent elective spinal surgery (spinal fusion, decompression, disc replacement) in NSW, 1 July 2001 - 30 June 2020. MAIN OUTCOME MEASURES: Crude and age- and sex-adjusted procedure rates, by procedure, funding type, and year; annual change in rates, 2001-20, expressed as incidence rate ratios (IRRs). RESULTS: During 2001-20, 155 088 procedures in 129 525 adults were eligible for our analysis: 53 606 fusion, 100 225 decompression, and 1257 disc replacement procedures. The privately funded fusion procedure rate increased from 26.6 to 109.5 per 100 000 insured adults (per year: IRR, 1.06; 95% confidence interval [CI], 1.05-1.07); the workers' compensation procedure rate increased from 6.1 to 15.8 per 100 000 covered adults (IRR, 1.04; 95% CI, 1.01-1.06); the publicly funded procedure rate increased from 5.6 to 12.4 per 100 000 adults (IRR, 1.03; 95% CI, 1.01-1.06), and from 10.5 to 22.1 per 100 000 adults without hospital cover private health insurance (IRR, 1.03; 95% CI, 1.01-1.05). The privately funded decompression procedure rate increased from 93.4 to 153.6 per 100 000 people (IRR, 1.02; 95% CI, 1.01-1.03); the workers' compensation procedure rate declined from 19.7 to 16.7 per 100 000 people (IRR, 0.98; 95% CI, 0.96-0.99), and the publicly funded procedure rate did not change significantly. The privately funded disc replacement procedure rate increased from 6.2 per million in 2010-11 to 38.4 per million people in 2019-20, but did not significantly change for the other two funding groups. The age- and sex-adjusted rates for privately and publicly funded fusion and decompression procedures were similar to the crude rates. CONCLUSIONS: Privately funded spinal surgery rates continue to be larger than for publicly funded procedures, and they have also increased more rapidly. These differences may indicate that some privately funded procedures are unnecessary, or that the number of publicly funded procedures does not reflect clinical need.


Asunto(s)
Seguro de Salud , Indemnización para Trabajadores , Humanos , Adulto , Estudios Transversales , Nueva Gales del Sur/epidemiología , Hospitalización
SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA
...