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6 results for “time-to-event”

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zenodo36/100

Plant diversity darkspots for global collection priorities: time-to-event datasets per botanical country as defined by the World Geographical Scheme for Recording Plant Distributions (WGSRPD).

<p>Datasets used to predict the number of plant species remaining to be described and/or geolocated within a botanical country, which represents the third level of subdivision (generally equating to a political country) used by WGSRPD for recording plant distributions. The folder is composed of two subfolders <em>has_coords</em> and <em>has_no_coords</em> containing the time-to-event data for species with valid and no (invalidated) occurrence records within a given botanical country respectively<em>.</em></p> <ul> <li>Each folder contains a<strong> </strong>list of 361 botanical countries with the following 16 fields:</li> </ul> <pre><strong>species:</strong> species name<br><strong>time_ofdescription:</strong> year of the (first) description<br><strong>time_ofcollection:</strong> year of the collection of the earliest record<br><strong>family:</strong> species family name<br><strong>lifeform_description: </strong>the life form categorised into 4 classes <br><strong>CHELSA_bio_1: </strong>annual mean temperature (&deg;C)<br><strong>CHELSA_bio_12:</strong> annual precipiation (mm)<br><strong>CHELSA_bio_15</strong>: temperature seasonality (-)<br><strong>CHELSA_bio_4</strong>: precipitation seasonality (-)<br><strong>elevation</strong>: elevation (m)<br><strong>range_size_area:</strong> total area of the botanical countries encompassing the species' native range <br>according to the World Checklist of Vascular Plants (WCVP) (km^2) <br><strong>taxo_activity</strong>: taxonomic activity calculated as the number of named authors in the World Checklist of Vascular Plants<br>describing species from the same family during the year of description of the species,<br>divided by the number of species described within the given family that year. <br><strong>num_records_per_year:</strong> geographic activity calculated as the number of occurrence records<br>collected within the native range of the species, divided by the number of years between <br>the earliest and the lastest (first) record collected within this range.<br><strong>num_uses</strong>: number of human uses<br><strong>time_todescription:</strong> number of years between the (first) description and 1753<br><strong>time_tocollection:</strong> number of years between the (first) description and the collection of the first record of the species<br><br></pre> <p>&nbsp;</p>

opencc-by-4.0Jul 2024View details →
zenodo36/100

Time-to-Event analysis of factors influencing delay in discharge from a subacute Complex Discharge Unit during the first year of the pandemic (2020) in an Irish tertiary centre hospital

<p><strong>Figure S1:</strong> Forest plots 1 and 2 depicting Age and Gender strata associated Hazard ratio (Markers) estimates (95% Confidence Interval demonstrated by horizontal line) exhibited statistically significant results for individuals &lt;65 years of age who had a delay in discharge due to complications from comorbidities; those in 65-75 years of age category, had prolonged LOS due to admission with frailty, falls and/or integrated rehabilitation needs; and 75-85 years of age category showed an association of at least 4 out of the 5 common delaying factors. Strata Gender exhibited a significant delay in discharge due to complications from comorbidities and patient-centred needs; in comparison to the female gender who also experienced a delay in discharge as a result of both factors alongside frailty, falls and/or integrated rehabilitation needs.<strong>[A. </strong>Complications/comorbidities prolonging discharge, <strong>B.</strong> Healthcare-associated infection, <strong>C</strong>. Frailty, falls and/or integrated&nbsp;rehabilitation needs, <strong>D</strong>. Patient-centred needs, <strong>E</strong>. Community services].&nbsp;</p> <p><strong>Figure S2:</strong> Forest plot 3 depicting Multimorbidity (MM) strata-associated Hazard ratio (Markers) estimates (95% Confidence Interval demonstrated by horizontal line) exhibited a significant delay in discharge due to complications from comorbidities, frailty, falls, and/or integrated rehabilitation and patient-centred needs in patients with &le;4 MM. In contrast patients with &gt;4 MM experienced significant delays in discharge due to complications from comorbidities and patient-centred needs.&nbsp;<strong>[A. </strong>Complications/comorbidities prolonging discharge, <strong>B.</strong> Healthcare-associated infection, <strong>C</strong>. Frailty, falls and/or integrated rehabilitation needs, <strong>D</strong>. Patient-centred needs, <strong>E</strong>. Community Services].</p>

opencc-by-4.0Jan 2023View details →
ClinicalTrials.gov36/100

Definition for the Assessment of Time-to-event Endpoints in CANcer Trials (DATECAN-1)

ClinicalTrials.gov study NCT03676010. IPD Sharing: NO. Countries: 1. Publications: 7.

closedIPD-NOFeb 2026View details →
dryad36/100

BayesW time-to-event analysis posterior outputs and summary statistics

Open the record for dataset details and reuse information.

publicMar 2021View details →
ClinicalTrials.gov32/100

Sample Size for Multivariate Time-to-event Data

ClinicalTrials.gov study NCT03964402. IPD Sharing: NO. Countries: 1. Publications: 3.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

Predictive Time-to-Event Model for Major Medical Complications After Colectomy

ClinicalTrials.gov study NCT05150548. IPD Sharing: NO. Countries: 1. Publications: 6.

closedIPD-NOFeb 2026View details →

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International Brain Laboratory public data

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