Log In Sign up
The largest database of trusted experimental protocols
> Procedures > Health Care Activity > Patient Discharge

Patient Discharge

Patient Discharge: The process of discharging a patient from a healthcare facility after the completion of treatment or care.
This involves coordinating the transfer of the patient's care to the next setting, whether it's home, a rehabilitation facility, or another healthcare institution.
Effective patient discharge optimization using AI-driven protocol comparison can help identify the most appropriate discharge plans, enhance reproducibility, and improve research accuracy for better patient outcomes.

Most cited protocols related to «Patient Discharge»

1
Propensity Score Matching for Statin Exposure
The propensity score was estimated using logistic regression to regress receipt of a statin prescription at discharge on the 24 baseline covariates described in Table I. The estimated propensity score was the predicted probability of statin exposure derived from the fitted logistic regression model. In the propensity-score model we assumed a linear relationship between continuous covariates and the log-odds of receiving a statin prescription. Furthermore, the propensity-score model did not include any interactions.
We created a matched sample by matching treated and untreated subjects on the logit of the propensity score using calipers of width equal to 0.2 of the standard deviation of the logit of the propensity score [3 (link), 17 (link), 18 (link)]. A greedy, nearest-neighbour matching algorithm was employed to form pairs of treated and untreated subjects.
, & Austin P.C. (2009). Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Statistics in Medicine, 28(25), 3083-3107.
Full text: Click here
Publication 2009
Hydroxymethylglutaryl-CoA Reductase Inhibitors Patient Discharge
2
VEP Cache Generation and Utilization
The VEP’s caches are built for each of Ensembl’s primary species (70 species as of Ensembl version 84); the files are updated in concert with Ensembl’s release cycle, ensuring access to the latest annotation data. Cache files for all previous releases remain available on Ensembl’s FTP archive site [91 ] to facilitate reproducibility. For 15 of these species there are three types of cache files: one with the Ensembl transcripts, a “refseq” one with the RefSeq transcripts, and a “merged” one that contains both. Caches for both the latest GRCh38 and previous GRCh37 (hg19) human genome builds are maintained. The human GRCh38 cache file is around 5 gigabytes in size, including transcript, regulatory, and variant annotations as well as pathogenicity algorithm predictions. Performance using the cache is substantially faster than using the database; analyzing a small VCF file of 175 variants takes 5 seconds using the cache versus 40 seconds using the public Ensembl variation database over a local network (performance can be expected to be slower when using a remote database connection).
The VEP can use FASTA format files of genomic sequence for sequence retrieval. This functionality is needed to generate HGVS notations and to quality check input variants against the reference genome. The VEP uses either an htslib-based indexer [92 ] or BioPerl’s FASTA DB interface to provide fast random access to a whole genome FASTA file. Sequence may alternatively be retrieved from an Ensembl core database, with corresponding performance penalties.
Cache and FASTA files are automatically downloaded and set up using the VEP package’s installer script, which utilizes checksums to ensure the integrity of downloaded files. The installer script can also download plugins by consulting a registry. The VEP package also includes a script, gtf2vep.pl, to build custom cache files. This requires a local GFF or general transfer format (GTF) file that describes transcript structures and a FASTA file of the genomic sequence.
McLaren W., Gil L., Hunt S.E., Riat H.S., Ritchie G.R., Thormann A., Flicek P, & Cunningham F. (2016). The Ensembl Variant Effect Predictor. Genome Biology, 17, 122.
Full text: Click here
Publication 2016
GB virus C Genome Genome, Human Homo sapiens Neoplasm Metastasis Pathogenicity Patient Discharge
3
UniRef Database Production and Updates
The UniRef databases have been produced as a component of UniProt (2013) (link) since its first release in January 5, 2004 and updated with each release of UniProtKB. Production details were previously described (Suzek et al., 2007 (link)). Briefly, the databases are generated in a hierarchical fashion; UniRef100 clusters are generated first using sequences from UniProtKB and UniParc, UniRef90 clusters are then generated using UniRef100 clusters and UniRef50 clusters are generated using UniRef90 clusters. The clusters are computed using a parallelized version of the CD-HIT algorithm (Li et al., 2001 (link); Li and Godzik, 2006) (link). Using a full update procedure, the clusters are computed ab initio at the end of year and are updated for the remaining year using an incremental procedure that favors clustering of new sequences under existing clusters. The representatives of clusters are selected based on the level of curation (reviewed versus unreviewed), protein name (e.g. names do not contain hypothetical or putative preferred), source organism (e.g. proteins from model organisms preferred) and length of protein. The UniRef identifiers are derived from the cluster ‘representatives’ identifiers and are preserved for approximately 98% of the clusters between releases. UniRef production has been continuously enhanced to improve the quality and information content of the databases, as well as the efficiency of cluster computation to cope with explosive growth in sequences being reported.
Starting in January, 2013 an 80% sequence length overlap threshold was introduced for the computation of UniRef90 and UniRef50 databases, that is each member of a given UniRef90 and UniRef50 cluster will have a minimum length overlap of 80% with the longest (seed) sequence. Computed in this manner UniRef is conceptually similar to the PIRSF ‘homeomorphic’ family classification (Wu et al., 2004 (link)). This overlap threshold prevents proteins sharing only partial sequences from being clustered together. For example, polyproteins and their component proteins, or clusters of domain families partially sharing domain architecture. The threshold also improves intra-cluster molecular function consistency. UniRef100 is computed without the overlap threshold in order to remove sequence redundancy resulting from subfragments. The parallel cluster computation algorithm (Suzek et al., 2007 (link)) has been revised to accommodate the new overlap threshold.
Suzek B.E., Wang Y., Huang H., McGarvey P.B, & Wu C.H. (2014). UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches. Bioinformatics, 31(6), 926-932.
Full text: Click here
Publication 2014
Explosive Agents GTP-Binding Proteins Patient Discharge Polyproteins Proteins
4
Accessing SILVA Sequence Databases
The SILVA databases are available via a web-based interface at http://www.arb-silva.de. The web interface is divided into six sections: the browser, search, list, download, background, and FAQs pages. Download of the complete Parc and Ref datasets in ARB format is available in the download section. It is also possible to download files that gain additional sequences from new releases. Subsets of aligned sequences from the Parc dataset can be retrieved from the website. This is currently possible via two entry points: a taxonomic browser and advanced search functions. After selecting a database and the desired taxonomy in the browser, the user can navigate through the taxonomy by clicking on the respective nodes. A cart system is used to easily select subsets of single sequences, complete groups or even phyla. The cart system keeps the selections for the SSU and LSU databases distinct. This allows the user to select sequences from both databases simultaneously without mixing the two sequence types. However, it must be noted that any misclassification or erroneous information provided by INSDC is currently propagated on the SILVA webpage.
Additionally, the advanced search functions of the SILVA website can be used to build custom subsets of sequences. In addition to simple searches e.g. for accession numbers, organism names, taxonomic entities, or publication DOI/PubMed IDs, complex queries over several database fields using constraints such as sequence length or quality values are possible. The results can be sorted according to accession numbers, organism names, sequence length, sequence and alignment quality and Pintail values. Before download, the search results must be added to the ‘List’. This can be done by either manually selecting the sequences by mouse click or by clicking on ‘Add complete result to List’ to mark and transfer all results.
The coloured bars on the search page and in the short and detailed sequence views of the browser given a fast overview of the different quality aspects assigned to every sequence. The length of the bars is a graphical representation of the respective quality value. The colours classify the information into four categories: A green bar represents a value equal to or greater than 75. Yellow bars stand for values equal to or greater than 50 but less than 75. Values less than 50 are expressed by an orange bar. Red bars are only used for scores of 0. Since ‘problematic’ sequences, sequences of inadequate quality, as well as insufficiently aligned sequences were discarded from the databases only the Pintail scores can have 0.
In the ‘List’ section of the website, the entries can be inspected, items can be deleted, and the download files can be created. By clicking on the ‘generate download’ button the user will be asked whether he would like to download the sequences as a multi-FASTA or ARB file from the download section of the web page. All generated files will be available for download on the download page for up to 24 h. The background section of the website provides additional information about the current status of the databases, and the FAQ section describes the main steps necessary to download subsets of sequences and how to merge the retrieved ARB databases with the user's personal ARB database.
Pruesse E., Quast C., Knittel K., Fuchs B.M., Ludwig W., Peplies J, & Glöckner F.O. (2007). SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Research, 35(21), 7188-7196.
Publication 2007
ADRB2 protein, human CART protein, human Mice, House Patient Discharge
5
Comprehensive Database of CircRNA Identification
Our web server user interface is implemented using HTML, CSS, and JavaScript. Data are stored in a MySQL database, which is interfaced to the front end by a series of server-side Perl CGI scripts. A web browser fully compatible with HTML5 and CSS3 is required for optimal performance. We have thoroughly tested the web server in Google Chrome 31.0, Mozilla Firefox 25.0, and Internet Explorer 10.0.
To the best of our knowledge, circBase contains data from all studies of large-scale circRNA identification published to date (Table 1; Jeck et al. 2013 (link); Memczak et al. 2013 (link); Nitsche et al. 2013 (link); Salzman et al. 2013 (link); Zhang et al. 2013 (link)). In addition to the information made available by the investigators, we have annotated all circRNA transcripts, predicted their putative spliced forms, and, where applicable, provided alignments of reads spanning head-to-tail junctions. Transcript reannotation was necessary to standardize the content and level the amount of information contained across some publications (Jeck et al. 2013 (link); Salzman et al. 2013 (link)). Unique identifiers are assigned to circRNAs and will provide fixed references for future circBase releases.
Glažar P., Papavasileiou P, & Rajewsky N. (2014). circBase: a database for circular RNAs. RNA, 20(11), 1666-1670.
Publication 2014
Head Patient Discharge RNA, Circular Tail

Most recents protocols related to «Patient Discharge»

1
Hafnium Metal Production from Hafnium Chloride
Not available on PMC !

Example 5

113 g of sodium metal was melted and brought to 250° C. in an Inconel reactor vessel. The sodium was then stirred using a Cowles blade mixer rotating at 2000-2500 rpm. Powdered hafnium chloride (from Areva) was pulse-fed over approximately 1 hour into the stirred sodium, until 82 g of hafnium chloride had been added, at which point the reaction was halted. At the end of the reaction, the vortex in the sodium had substantially disappeared and the reactor temperature had increased to 301° C.

Once the reaction was completed, the reactor vessel was sealed, transferred to a furnace, and heated to 825° C. for four hours to reduce the surface area of the hafnium metal produced in the reaction. During this process step, unreacted sodium was removed from the hafnium metal to leave a hafnium-sodium chloride composite.

The hafnium and sodium chloride mixture was then transferred to a vacuum furnace and heated under vacuum to 2300° C., held at that temperature for one hour, and then cooled. This removed the sodium chloride and produced a button of solid hafnium.

The hafnium button was analyzed via glow discharge mass spectrometry (GDMS) and found to have 26 ppm oxygen content, 1690 ppm zirconium, and less than 150 ppm total transition metals. The results demonstrate the production of a low oxygen hafnium metal produced directly from hafnium powder consolidation.

US11858046B2. Methods for producing metal powders (2024-01-02). Nanoscale Powders LLC [US]. Inventors: David Henderson [US], Andrew Matheson [US], Richard Van Lieshout [US], Donald Finnerty [US], John W. Koenitzer [US].
Full text: Click here
Patent 2024
ARID1A protein, human Blood Vessel Hafnium hafnium chloride Mass Spectrometry Metals Oxygen Patient Discharge Powder Pulse Rate Sodium Sodium Chloride Transition Elements Vacuum Zirconium
2
Activated Carbon Production from Coal Pitch
Not available on PMC !

Example 2

A mixture obtained by mixing 100 parts by mass of granular coal pitch having a softening point of 280° C. as an organic material with 0.9 part by mass of tris(2,4-pentanedionato)iron(III) (metal species: Fe) was fed into a melt extruder, where it was melted and mixed at a melting temperature of 320° C., and spun at a discharge rate of 16 g/min to obtain a pitch fiber. The pitch fiber was subjected to an infusibilization treatment by heating for 54 minutes, to 354° C. from ambient temperature in the air at a rate of 1 to 30° C./minute, to obtain an infusibilized pitch fiber as an activated carbon precursor. The iron (Fe) content in the activated carbon precursor was 0.11% by mass.

The activated carbon precursor was activated by conducting a heat treatment at an atmospheric temperature of 950° C. for 40 minutes, while continuously introducing a gas having a CO2 concentration of 100% by volume into an activation furnace, to obtain an activated carbon of Example 2. In the activated carbon, the pore volume A of pores with a size of 1.0 nm or less was 0.396 cc/g, the pore volume B of pores with a size of 3.0 nm or more and 3.5 nm or less was 0.016 cc/g, the iron content was 0.251% by mass, and the average fiber diameter was 13.6 μm.

Granular coal pitch having a softening point of 280° C. as an organic material was fed into a melt extruder, where it was melted and mixed at a melting temperature of 320° C., and spun at a discharge rate of 20 g/min, to obtain a pitch fiber. The pitch fiber was subjected to an infusibilization treatment by heating for 54 minutes, to 354° C. from ambient temperature in the air at a rate of 1 to 30° C./minute, to obtain an infusibilized pitch fiber as an activated carbon precursor. The iron content in the activated carbon precursor was 0% by mass.

The activated carbon precursor was activated by conducting a heat treatment at an atmospheric temperature of 875° C. for 40 minutes, while continuously introducing a gas having an H2O concentration of 100% by volume into an activation furnace, to obtain an activated carbon of Comparative Example 2. In the activated carbon, the pore volume A of pores with a size of 1.0 nm or less was 0.401 cc/g, the pore volume B of pores with a size of 3.0 nm or more and 3.5 nm or less was 0.000 cc/g, the iron content was 0% by mass, and the average fiber diameter was 16.7 μm.

US11873235B2. Activated carbon (2024-01-16). AD'ALL CO., LTD. [JP], UNITIKA LTD. [JP], OSAKA GAS CHEMICALS CO., LTD. [JP]. Inventors: Tomoyasu Nakano [JP], Hirokazu Shimizu [JP], Akinori Kawachi [JP], Keiji Sakai [JP].
Full text: Click here
Patent 2024
Carbon Fiber Charcoal, Activated Coal Fibrosis Iron Metals Patient Discharge Tromethamine
3
Activated Carbon Precursor from Coal Pitch
Not available on PMC !

Example 6

A mixture obtained by mixing 100 parts by mass of granular coal pitch having a softening point of 280° C. as an organic material with 0.3 part by mass of tris(acetylacetonato)yttrium was fed into a melt extruder, where it was melted and mixed at a melting temperature of 320° C., and spun at a discharge rate of 20 g/min to obtain a pitch fiber. The pitch fiber was subjected to an infusibilization treatment by heating for 54 minutes, to 354° C. from ambient temperature in the air at a rate of 1 to 30° C./minute, to obtain an infusibilized pitch fiber as an activated carbon precursor. The yttrium content in the activated carbon precursor was 0.06% by mass.

The activated carbon precursor was activated by conducting a heat treatment at an atmospheric temperature of 950° C. for 60 minutes, while continuously introducing a gas having a CO2 concentration of 100% by volume into an activation furnace, to obtain an activated carbon of Comparative Example 6. In the activated carbon, the pore volume A of pores with a size of 1.0 nm or less was 0.429 cc/g, the pore volume B of pores with a size of 3.0 nm or more and 3.5 nm or less was 0.000 cc/g, the yttrium content was 0.15% by mass, and the fiber diameter was 18.2 μm.

US11873235B2. Activated carbon (2024-01-16). AD'ALL CO., LTD. [JP], UNITIKA LTD. [JP], OSAKA GAS CHEMICALS CO., LTD. [JP]. Inventors: Tomoyasu Nakano [JP], Hirokazu Shimizu [JP], Akinori Kawachi [JP], Keiji Sakai [JP].
Full text: Click here
Patent 2024
Carbon Fiber Charcoal, Activated Coal Fibrosis Patient Discharge Tromethamine Yttrium
4
Capacitor Discharge Duration Control
Not available on PMC !

Example 14

The apparatus of any one or more of Examples 10 through 13, wherein the predetermined discharge rate for the capacitor is selected to result in the capacitor charge falling below the activation threshold after the capacitor is coupled with the discharge load feature for between about 4 hours and about 24 hours.

US11864786B2. System and method to track usage of surgical instrument (2024-01-09). Cilag GmbH International [CH]. Inventors: Craig N. Faller [US], Benjamin D. Dickerson [US], Jeffrey L. Aldridge [US], Jeffrey A. Bullock [US], Richard W. Timm [US], Ryan M. Asher [US], Timothy S. Holland [US], Craig T. Davis [US], Christina M. Hough [US], Cory G. Kimball [US], Ashvani K. Madan [US], David C. Yates [US], Shan Wan [US], Jacob S. Gee [US], Joseph E. Hollo [US], Chad P. Boudreaux [US], John B. Schulte [US], Tylor C. Muhlenkamp [US], Brian D. Black [US].
Full text: Click here
Patent 2024
Patient Discharge Surgical Instruments
5
Chlamydia: Diagnosis, Transmission, and Impacts
Not available on PMC !

Example 2

Chlamydia is a common STI that is caused by the bacterium Chlamydia trachomatis. Transmission occurs during vaginal, anal, or oral sex, but the bacterium can also be passed from an infected mother to her baby during vaginal childbirth. It is estimated that about 1 million individuals in the United States are infected with this bacterium, making chlamydia one of the most common STIs worldwide. Like gonorrhea, chlamydial infection is asymptomatic for a majority of women. If symptoms are present, they include unusual vaginal bleeding or discharge, pain in the abdomen, painful sexual intercourse, fever, painful urination or the urge to urinate more frequently than usual. Of those who develop asymptomatic infection, approximately half may develop PID. Infants born to mothers with chlamydia may suffer from pneumonia and conjunctivitis, which may lead to blindness. They may also be subject to spontaneous abortion or premature birth.

Diagnosis of chlamydial infection is usually done by nucleic acid amplification techniques, such as PCR, using samples collected from cervical swabs or urine specimens (Gaydos et al., J. Clin. Microbio., 42:3041-3045; 2004). Treatment involves various antibiotic regimens.

In some embodiments, the disclosed device can be used to detect chlamydial infections from menstrual blood or cervicovaginal fluids.

US11864740B2. Sample collection and preservation devices, systems and methods (2024-01-09). NextGen Jane, Inc. [US]. Inventors: Ridhi Tariyal [US], Stephen K. Gire [US].
Full text: Click here
Patent 2024
Abdominal Pain Antibiotics Anus Asymptomatic Infections Bacteria Blindness Blood Childbirth Chlamydia Chlamydia Infections Chlamydia trachomatis Coitus Conjunctivitis Diagnosis Dysuria Fever Gonorrhea Infant Medical Devices Menstruation Mothers Neck Nucleic Acid Amplification Techniques Pain Patient Discharge Pneumonia Premature Birth Sexually Transmitted Diseases Spontaneous Abortion Transmission, Communicable Disease Treatment Protocols Urine Vagina Woman

Top products related to «Patient Discharge»

1
Sas version 9 by SAS Institute
Sourced in United States, Austria, Japan, Cameroon, Germany, United Kingdom, Canada, Belgium, Israel, Denmark, Australia, New Caledonia, France, Argentina, Sweden, Ireland, India
SAS version 9.4 is a statistical software package. It provides tools for data management, analysis, and reporting. The software is designed to help users extract insights from data and make informed decisions.
2
Sas 9 by SAS Institute
Sourced in United States, Austria, Japan, Belgium, United Kingdom, Cameroon, China, Denmark, Canada, Israel, New Caledonia, Germany, Poland, India, France, Ireland, Australia
SAS 9.4 is an integrated software suite for advanced analytics, data management, and business intelligence. It provides a comprehensive platform for data analysis, modeling, and reporting. SAS 9.4 offers a wide range of capabilities, including data manipulation, statistical analysis, predictive modeling, and visual data exploration.
3
Vitrobot mark 4 by Thermo Fisher Scientific
Sourced in United States, Germany, Netherlands, United Kingdom, Czechia, Israel
The Vitrobot Mark IV is a cryo-electron microscopy sample preparation instrument designed to produce high-quality vitrified specimens for analysis. It automates the process of blotting and plunge-freezing samples in liquid ethane, ensuring consistent and reproducible sample preparation.
4
Stata 15 by StataCorp
Sourced in United States, United Kingdom, Austria, Denmark
Stata 15 is a comprehensive, integrated statistical software package that provides a wide range of tools for data analysis, management, and visualization. It is designed to facilitate efficient and effective statistical analysis, catering to the needs of researchers, analysts, and professionals across various fields.
5
Sas v9 by SAS Institute
Sourced in United States, Austria, United Kingdom, Cameroon, Belgium, Israel, Japan, Australia, France, Germany
SAS v9.4 is a software product developed by SAS Institute. It is a comprehensive data analysis and statistical software suite. The core function of SAS v9.4 is to provide users with tools for data management, analysis, and reporting.
6
R version 3 by R Project for Statistical Computing
Sourced in United States, Austria, Japan, Belgium, New Zealand, United Kingdom, Germany, Denmark, Australia, France
R version 3.6.1 is a statistical computing and graphics software package. It is an open-source implementation of the S programming language and environment. R version 3.6.1 provides a wide range of statistical and graphical techniques, including linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, and more.
7
Stata version 14 by StataCorp
Sourced in United States, Denmark, Austria, United Kingdom, Japan, Canada
Stata version 14 is a software package for data analysis, statistical modeling, and graphics. It provides a comprehensive set of tools for data management, analysis, and reporting. Stata version 14 includes a wide range of statistical techniques, including linear regression, logistic regression, time series analysis, and more. The software is designed to be user-friendly and offers a variety of data visualization options.
8
Matlab by MathWorks
Sourced in United States, United Kingdom, Germany, Canada, Japan, Sweden, Austria, Morocco, Switzerland, Australia, Belgium, Italy, Netherlands, China, France, Denmark, Norway, Hungary, Malaysia, Israel, Finland, Spain
MATLAB is a high-performance programming language and numerical computing environment used for scientific and engineering calculations, data analysis, and visualization. It provides a comprehensive set of tools for solving complex mathematical and computational problems.
9
Spss version 22 by IBM
Sourced in United States, Japan, United Kingdom, Austria, Germany, Czechia, Belgium, Denmark, Canada
SPSS version 22.0 is a statistical software package developed by IBM. It is designed to analyze and manipulate data for research and business purposes. The software provides a range of statistical analysis tools and techniques, including regression analysis, hypothesis testing, and data visualization.

More about "Patient Discharge"

Patient Discharge, Patient Transfer, Healthcare Transition, Discharge Planning, Discharge Optimization, AI-Driven Protocol Comparison, Discharge Process, Patient Outcomes, Discharge Coordination, Discharge Reproducibility, Discharge Research Accuracy, SAS 9.4, Vitrobot Mark IV, Stata 15, SAS v9.4, R 3.6.1, Stata 14, MATLAB, SPSS 22.0.
Effective patient discharge is a critical component of healthcare delivery, ensuring a smooth transition of care for patients as they leave a healthcare facility.
The discharge process involves coordinating the transfer of the patient's care to the next appropriate setting, whether that's home, a rehabilitation facility, or another healthcare institution.
Optimizing this process can have a significant impact on patient outcomes.
One innovative approach to enhancing patient discharge is the use of AI-driven protocol comparison.
By leveraging advanced analytical tools like SAS 9.4, Stata 15, R 3.6.1, and MATLAB, healthcare providers can identify the most appropriate discharge plans for their patients.
This can improve reproducibility and enhance the accuracy of research, ultimately leading to better patient outcomes.
For example, the Vitrobot Mark IV is a tool used in the preparation of samples for electron microscopy, which can be relevant in the context of healthcare research.
Similarly, SPSS version 22.0 is a statistical software package that can be utilized in the analysis of patient discharge data.
By incorporating these insights and technologies, healthcare organizations can streamline the discharge process, reduce the risk of complications, and ensure that patients receive the most effective and personalized care as they transition out of the healthcare facility.
This holistic approach to patient discharge optimization can have far-reaching benefits for both patients and healthcare providers.