scholarly journals Condensed trajectory of the temporal correlation of diseases and mortality extracted from over 300,000 patients in hospitals

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0257894
Author(s):  
Hyojung Paik ◽  
Jimin Kim
Keyword(s):  
Temporal Correlation ◽  
Hospital Death ◽  
Mortality Data ◽  
Strong Correlations ◽  
Short Term ◽  
Temporal Correlations ◽  
Systematic Fashion ◽  
Dead End ◽  
End Stage ◽  
Substantial Heterogeneity

Understanding mortality, derived from debilitations consisting of multiple diseases, is crucial for patient stratification. Here, in systematic fashion, we report comprehensive mortality data that map the temporal correlation of diseases that tend toward deaths in hospitals. We used a mortality trajectory model that represents the temporal ordering of disease appearance, with strong correlations, that terminated in fatal outcomes from one initial diagnosis in a set of patients throughout multiple admissions. Based on longitudinal healthcare records of 10.4 million patients from over 350 hospitals, we profiled 300 mortality trajectories, starting from 118 diseases, in 311,309 patients. Three-quarters (75%) of 59,794 end-stage patients and their deaths accrued throughout 160,360 multiple disease appearances in a short-term period (<4 years, 3.5 diseases per patient). This overlooked and substantial heterogeneity of disease patients and outcomes in the real world is unraveled in our trajectory map at the disease-wide level. For example, the converged dead-end in our trajectory map presents an extreme diversity of sepsis patients based on 43 prior diseases, including lymphoma and cardiac diseases. The trajectories involving the largest number of deaths for each age group highlight the essential predisposing diseases, such as acute myocardial infarction and liver cirrhosis, which lead to over 14,000 deaths. In conclusion, the deciphering of the debilitation processes of patients, consisting of the temporal correlations of diseases that tend towards hospital death at a population-wide level is feasible.

Principles of pediatric lupus nephritis in a prospective contemporary multi-center cohort

Lupus ◽  
2021 ◽  
pp. 096120332110286
Author(s):  
Kathleen M Vazzana ◽  
Ankana Daga ◽  
Beatrice Goilav ◽  
Ekemini A Ogbu ◽  
Daryl M Okamura ◽  
...  
Keyword(s):  
Lupus Nephritis ◽  
Kidney Function ◽  
Lupus Erythematosus ◽  
Extensive Literature ◽  
Short Term ◽  
Renal Outcomes ◽  
Childhood Arthritis ◽  
Black Patients ◽  
End Stage

Lupus nephritis (LN) is a life-threatening manifestation of systemic lupus erythematosus (SLE) and is more common in children than adults. The epidemiology and management of childhood-onset SLE (cSLE) have changed over time, prompting the need to reassess expected outcomes. The purpose of this study is to use the Childhood Arthritis and Rheumatology Research Alliance (CARRA) prospective registry to validate historical principles of LN in a contemporary, real-world cohort. After an extensive literature review, six principles of LN in cSLE were identified. The CARRA registry was queried to evaluate these principles in determining the rate of LN in cSLE, median time from cSLE diagnosis to LN, short-term renal outcomes, and frequency of rituximab as an induction therapy. Of the 677 cSLE patients in the CARRA registry, 32% had documented LN. Decline in kidney function was more common in Black cSLE patients than non-Black patients ( p = 0.04). Black race was associated with worse short-term renal outcomes. In short-term follow up, most children with LN had unchanged or improved kidney function, and end stage kidney disease (ESKD) was rare. Ongoing follow-up of cSLE patients in the CARRA registry will be necessary to evaluate long-term outcomes to inform risk, management, and prognosis of LN in cSLE.

Short-Term Clinical Outcome of Hemiarthroplasty Versus Arthrodesis for End-Stage Hallux Rigidus

2015 ◽  
Vol 54 (5) ◽  
pp. 848-851 ◽  
Author(s):  
Karin H. Simons ◽  
Pieter van der Woude ◽  
Frank W.M. Faber ◽  
Paulien M. van Kampen ◽  
Bregje J.W. Thomassen
Keyword(s):  
Clinical Outcome ◽  
Hallux Rigidus ◽  
Short Term ◽  
End Stage

scholarly journals Assessing the effects of air temperature and rainfall on malaria incidence: an epidemiological study across Rwanda and Uganda

2016 ◽  
Vol 11 (1s) ◽  
Author(s):  
Felipe J. Colón-González ◽  
Adrian M. Tompkins ◽  
Riccardo Biondi ◽  
Jean Pierre Bizimana ◽  
Didacus Bambaiha Namanya
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
Malaria Incidence ◽  
Temporal Correlation ◽  
Early Warning Systems ◽  
Socioeconomic Indicators ◽  
Malaria Surveillance ◽  
Short Term ◽  
Climatic Information ◽  
Short Term Effects

We investigate the short-term effects of air temperature, rainfall, and socioeconomic indicators on malaria incidence across Rwanda and Uganda from 2002 to 2011. Delayed and nonlinear effects of temperature and rainfall data are estimated using generalised additive mixed models with a distributed lag nonlinear specification. A time series cross-validation algorithm is implemented to select the best subset of socioeconomic predictors and to define the degree of smoothing of the weather variables. Our findings show that trends in malaria incidence agree well with variations in both temperature and rainfall in both countries, although factors other than climate seem to play an important role too. The estimated short-term effects of air temperature and precipitation are nonlinear, in agreement with previous research and the ecology of the disease. These effects are robust to the effects of temporal correlation. The effects of socioeconomic data are difficult to ascertain and require further evaluation with longer time series. Climate-informed models had lower error estimates compared to models with no climatic information in 77 and 60% of the districts in Rwanda and Uganda, respectively. Our results highlight the importance of using climatic information in the analysis of malaria surveillance data, and show potential for the development of climateinformed malaria early warning systems.

scholarly journals An Evaluation of Precipitation Forecasts from Operational Models and Reanalyses Including Precipitation Variations Associated with MJO Activity

2010 ◽  
Vol 138 (12) ◽  
pp. 4542-4560 ◽  
Author(s):  
John E. Janowiak ◽  
Peter Bauer ◽  
Wanqiu Wang ◽  
Phillip A. Arkin ◽  
Jon Gottschalck
Keyword(s):  
Prediction Models ◽  
Coupled Model ◽  
Warm Season ◽  
Temporal Correlation ◽  
Operational Model ◽  
Temporal Correlations ◽  
Operational Models ◽  
Environmental Prediction ◽  
The Tropics ◽  
Model Precipitation

Abstract In this paper, the results of an examination of precipitation forecasts for 1–30-day leads from global models run at the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) during November 2007–February 2008 are presented. The performance of the model precipitation forecasts are examined in global and regional contexts, and results of a case study of precipitation variations that are associated with a moderate to strong Madden–Julian oscillation (MJO) event are presented. The precipitation forecasts from the ECMWF and NCEP operational prediction models have nearly identical temporal correlation with observed precipitation at forecast leads from 2 to 9 days over the Northern Hemisphere during the cool season, despite the higher resolution of the ECMWF operational model, while the ECMWF operational model forecasts are slightly better in the tropics and the Southern Hemisphere during the warm season. The ECMWF Re-Analysis Interim (ERA-Interim) precipitation forecasts perform only slightly worse than the NCEP operational model, while NCEP’s Climate Forecast System low-resolution coupled model forecasts perform the worst among the four models. In terms of bias, the ECMWF operational model performs the best among the four model forecasts that were examined, particularly with respect to the ITCZ regions in both the Atlantic and Pacific. Local temporal correlations that were computed on daily precipitation totals for day-2 forecasts against observations indicate that the operational models at ECMWF and NCEP perform the best during the 4-month study period, and that all of the models have low to insignificant correlations over land and over much of the tropics. They perform the best in subtropical and extratropical oceanic regions. Also presented are results that show that striking improvements have been made over the past two decades in the ability of the models to represent precipitation variations that are associated with MJO. The model precipitation forecasts exhibit the ability to characterize the evolution of precipitation variations during a moderate–strong period of MJO conditions for forecast leads as long as 10 days.

scholarly journals Korelasi antara Letak Ujung Kateter Lumen Ganda Femoralis Jangka Pendek Non-tunneling dengan Laju Aliran darah pada Saat Hemodialisis di RSUP Prof Dr. R. D. Kandou

2018 ◽  
Vol 10 (2) ◽  
Author(s):  
Fery Purba ◽  
Richard Sumangkut ◽  
Djoni E. Tjandra
Keyword(s):  
Renal Failure ◽  
Positive Relationship ◽  
Scatter Plot ◽  
Short Term ◽  
Double Lumen ◽  
End Stage Renal Failure ◽  
Double Lumen Catheter ◽  
Lumen Catheter ◽  
Tip Position ◽  
End Stage

Abstract: Patients with end-stage renal failure are unable to survive without dialysis or renal transplantation. To achieve effective dialysis using a double lumen catheter, placement of the catheter tip plays an important role because it may affect blood flow/Quick of Blood (QB). The selection of femoral vein access is more favorable in critical patients. This study was aimed to obtain the correlation between the tip position of the non-tunneling short-term femoral double lumen catheter (DLC) and QB at the time of hemodialysis. This was an analytical correlative and prospective study with a cross-sectional design in patients with end-stage renal failure undergoing hemodialysis using a non-tunneling short-term femoral DLC. This study was conducted at the Hemodialysis Installation of Prof. Dr. R. D. Kandou Hospital Manado. Data were analyzed by using the Pearson's r test. The results showed that there were 31 patients enrolled in this study. The Pearson’s r test obtained an r of 0.147 (statistically weak) and Sig (2-tailed) of 0.430 which showed no correlation but the scatter plot showed a tendency of a weak positive relationship. Conclusion: There was no significant correlation between Qb and the tip position of DLC, albeit, there was a tendency of a weak positive relationship. Increasing the number of samples will more accurately predict the presence or absence of the correlation between Qb and the tip position of the DLC.Keywords: DLC, QB, hemodialysisAbstrak: Pasien dengan penyakit ginjal stadium akhir tidak dapat mempertahankan hidup tanpa dukungan terapi pengganti ginjal yaitu dialisis atau transplantasi ginjal. Untuk mencapai dialisis yang efektif dengan menggunakan kateter lumen ganda, penempatan kateter berperan penting karena dapat memengaruhi aliran darah/Quick of Blood (QB). Pemilihan akses vena femoralis lebih menguntungkan pada pasien kritis. Penelitian ini bertujuan untuk mengetahui korelasi letak ujung kateter lumen ganda femoralis jangka pendek (DLC) dengan QB pada saat hemodialisis. Jenis penelitian ialah analitik korelatif dan prospektif dengan desain potong lintang. Subyek penelitian ialah pasien dengan gagal ginjal tahap akhir yang menjalani hemodialisis menggunakan kateter lumen ganda femoralis jangka pendek non-tunneling. Penelitian dilakukan di Instalasi Hemodialisis RSUP Prof. Dr. R. D. Kandou, Manado. Data dianalisis menggunakan koefisien korelasi Pearson. Hasil penelitian mendapatkan 31 pasien sebagai subyek. Hasil analisis koefisien Pearson terhadap korelasi antara letak ujung DLC dan QB memperlihatkan hubungan statistik lemah (r = 0,147) dengan Sig (2-tailed) 0,430 yang menunjukkan tidak terdapat hubungan bermakna tetapi pada scatter plot terlihat adanya kecenderungan hubungan positif lemah. Simpulan: Tidak terdapat korelasi bermakna antara Qb dan letak ujung DLC tetapi terdapat kecenderungan hubungan positif lemah. Menambah jumlah sampel akan lebih akurat untuk memrediksi ada tidaknya hubungan antara Qb dan letak ujung DLC. Kata kunci: DLC, laju aliran dara (QB), hemodialisis

scholarly journals Functional Connectivity within Brain Networks of Long Term and Short term Meditators

2019 ◽  
Vol 9 (2S) ◽  
pp. 29-34
Keyword(s):  
Functional Connectivity ◽  
Temporal Correlation ◽  
Brain Regions ◽  
Invasive Technique ◽  
Long Term Effects ◽  
Short Term ◽  
Statistical Concept ◽  
The Brain ◽  
Meditative Practices

Meditation refers to a state of mind of relaxation and concentration, where generally the mind and body is at rest. The process of meditation reflects the state of the brain which is distinct from sleep or typical wakeful states of consciousness. Meditative practices usually involve regulation of emotions and monitoring of attention. Over the past decade there has been a tremendous increase in an interest to study the neural mechanisms involved in meditative practices. It could also be beneficial to explore if the effect of meditation is altered by the number of years of meditation practice. Functional Magnetic Resonance Imaging (fMRI) is a very useful imaging technique which can be used to perform this analysis due to its inherent benefits, mainly it being a non-invasive technique. Functional activation and connectivity analysis can be performed on the fMRI data to find the active regions and the connectivity in the brain regions. Functional connectivity is defined as a simple temporal correlation between anatomically separate, active neural regions. Functional connectivity gives the statistical dependencies between regional time series. It is a statistical concept and is quantified using metrics like Correlation. In this study, a comparison is made between functional connectivity in the brain regions of long term meditation practitioners (LTP) and short-term meditation practitioners (STP) to see the differences and similarities in the connectivity patterns. From the analysis, it is evident that in fact there is a difference in connectivity between long term and short term practitioners and hence continuous practice of meditation can have long term effects.

scholarly journals Connectionist Temporal Modeling of Video and Language: a Joint Model for Translation and Sign Labeling

2019 ◽  
Author(s):  
Dan Guo ◽  
Shengeng Tang ◽  
Meng Wang
Keyword(s):  
Dynamic Programming ◽  
Objective Function ◽  
Visual Representations ◽  
Sequential Learning ◽  
Short Term ◽  
Temporal Modeling ◽  
Temporal Correlations ◽  
Feature Correlation ◽  
3D Cnn

Online sign interpretation suffers from challenges presented by hybrid semantics learning among sequential variations of visual representations, sign linguistics, and textual grammars. This paper proposes a Connectionist Temporal Modeling (CTM) network for sentence translation and sign labeling. To acquire short-term temporal correlations, a Temporal Convolution Pyramid (TCP) module is performed on 2D CNN features to realize (2D+1D)=pseudo 3D' CNN features. CTM aligns the pseudo 3D' with the original 3D CNN clip features and fuses them. Next, we implement a connectionist decoding scheme for long-term sequential learning. Here, we embed dynamic programming into the decoding scheme, which learns temporal mapping among features, sign labels, and the generated sentence directly. The solution using dynamic programming to sign labeling is considered as pseudo labels. Finally, we utilize the pseudo supervision cues in an end-to-end framework. A joint objective function is designed to measure feature correlation, entropy regularization on sign labeling, and probability maximization on sentence decoding. The experimental results using the RWTH-PHOENIX-Weather and USTC-CSL datasets demonstrate the effectiveness of the proposed approach.

Production Forecasting with the Interwell Interference by Integrating Graph Convolutional and Long Short-Term Memory Neural Network

2021 ◽  
pp. 1-17
Author(s):  
Enda Du ◽  
Yuetian Liu ◽  
Ziyan Cheng ◽  
Liang Xue ◽  
Jing Ma ◽  
...  
Keyword(s):  
Neural Network ◽  
Short Term Memory ◽  
Short Term ◽  
Term Memory ◽  
Production Forecasting ◽  
Temporal Correlations ◽  
Proposed Model ◽  
The Mean ◽  
Long Short Term Memory ◽  
The Impact

Summary Accurate production forecasting is an essential task and accompanies the entire process of reservoir development. With the limitation of prediction principles and processes, the traditional approaches are difficult to make rapid predictions. With the development of artificial intelligence, the data-driven model provides an alternative approach for production forecasting. To fully take the impact of interwell interference on production into account, this paper proposes a deep learning-based hybrid model (GCN-LSTM), where graph convolutional network (GCN) is used to capture complicated spatial patterns between each well, and long short-term memory (LSTM) neural network is adopted to extract intricate temporal correlations from historical production data. To implement the proposed model more efficiently, two data preprocessing procedures are performed: Outliers in the data set are removed by using a box plot visualization, and measurement noise is reduced by a wavelet transform. The robustness and applicability of the proposed model are evaluated in two scenarios of different data types with the root mean square error (RMSE), the mean absolute error (MAE), and the mean absolute percentage error (MAPE). The results show that the proposed model can effectively capture spatial and temporal correlations to make a rapid and accurate oil production forecast.

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