cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5576021
title: Phylogenetic placement of Pseudoneobacillus sp. JJ-79 within Bacillaceae family

description: This repository contains phylogenetic trees (and associated sequence data) inferred to assess the phylogenetic placement of <em>Pseudoneobacillus</em> sp. JJ-79 (tax id: 2880968) within 512 type strains representative of the <em>Bacillaceae</em> family. Three phylogenetic trees were inferred, each from a multi-gene dataset (as described at http://giphy.pasteur.fr/PhyloM/Bacillaceae): <strong>BM1</strong>: 87 conserved genes (Wu et al. 2013, Gupta et al. 2020, Patel and Gupta 2020), <strong>BM2</strong>: major subunits of the DNA Gyrase (<em>GyrA</em> and <em>GyrB</em>) and RNA polymerase (<em>RpoB</em> and <em>RpoC</em>; Patel and Gupta 2020), <strong>BM3</strong>: DNA helicase II and DNA polymerase I (<em>UvrD</em> and <em>PolA</em>; Patel and Gupta 2020). For each dataset <strong>BM<em>i</em></strong> (<em>i</em> = 1, 2, 3), four files are available: <code>BM<em>i</em>.faa </code> the concatenation of the filtered multiple sequence alignments (FASTA format); <code>BM<em>i</em>.nwk </code> a maximum likelihood phylogenetic tree inferred from <code>BM<em>i</em>.faa</code> (NEWICK format); <code>BM<em>i</em>.pdf </code> a graphical representation of the phylogenetic tree (PDF format); <code>BM<em>i</em>.seq.tar.gz </code> for each gene name, three FASTA files are available in this tar.gz archive: initial sequences (*.faa), multiple sequence alignment (*.afa), filtered multiple sequence alignment (*.ffa).
DOI: 10.5281/zenodo.5840367
title: Actinopyga echinites Zanfona pass 1

description: Reference: Stichopus_chloronotus_isolate_Wuzhizhou
DOI: 10.5281/zenodo.5840366
title: Actinopyga echinites Zanfona pass 1

description: Reference: Stichopus_chloronotus_isolate_Wuzhizhou
DOI: 10.5281/zenodo.5840690
title: Broca's Area Light-Sheet Microscopy

description: Example dataset containing light-sheet selective plane illumination microscopy (SPIM) data to illustrate BIDS convention.<br> BIDS version 1.7.0
DOI: 10.5281/zenodo.5517223
title: Broca's Area Light-Sheet Microscopy

description: Example dataset containing light-sheet selective plane illumination microscopy (SPIM) data to illustrate BIDS convention.<br> BIDS version 1.7.0
DOI: 10.5281/zenodo.5840345
title: Generated RGBD Tracking Benchmarks (LaSOT) Part13

description: Fix the broken zip files, including: lion, kangaroo
DOI: 10.5281/zenodo.5840344
title: Generated RGBD Tracking Benchmarks (LaSOT) Part13

description: Fix the broken zip files, including: lion, kangaroo
DOI: 10.5258/soton/d1888
title: Dataset for Mechanically tunable terahertz metamaterial perfect absorber

description: Dataset for article; L. K. Piper et al., Mechanically Tunable Terahertz Metamaterial Perfect Absorber Advanced Photonics Research 2021, DOI: 10.1002/adpr.202100136. Experimental data, simulation results
DOI: 10.6084/m9.figshare.18255668
title: DATA2022.xlsx

description: <br> Insulin overdose is the most common risk factor for hypoglycemia. In pregnant women with type 1 diabetes with elevated fasting C-peptide levels, the dose of basal insulin should be diminished to reduce the risk of hypoglycemia.
DOI: 10.6084/m9.figshare.18255668.v1
title: DATA2022.xlsx

description: <br> Insulin overdose is the most common risk factor for hypoglycemia. In pregnant women with type 1 diabetes with elevated fasting C-peptide levels, the dose of basal insulin should be diminished to reduce the risk of hypoglycemia.
DOI: 10.5281/zenodo.5840333
title: Input data for Differential NicheNet analysis performed in the liver atlas paper Guilliams et al., Cell 2022

description: Input data for Differential NicheNet analysis performed in the liver atlas paper Guilliams et al., Cell 2022 See https://github.com/saeyslab/NicheNet_LiverCellAtlas and https://www.sciencedirect.com/science/article/pii/S0092867421014811
DOI: 10.5281/zenodo.5840332
title: Input data for Differential NicheNet analysis performed in the liver atlas paper Guilliams et al., Cell 2022

description: Input data for Differential NicheNet analysis performed in the liver atlas paper Guilliams et al., Cell 2022 See https://github.com/saeyslab/NicheNet_LiverCellAtlas and https://www.sciencedirect.com/science/article/pii/S0092867421014811
DOI: 10.5281/zenodo.5840831
title: Dataset related to the article "Comparison between PtCO 2 and PaCO 2 and Derived Parameters in Heart Failure Patients during Exercise: A Preliminary Study"

description: Abstract Evaluation of arterial carbon dioxide pressure (PaCO<sub>2</sub>) and dead space to tidal volume ratio (V<sub>D</sub>/V<sub>T</sub>) during exercise is important for the identification of exercise limitation causes in heart failure (HF). However, repeated sampling of arterial or arterialized ear lobe capillary blood may be clumsy. The aim of our study was to estimate PaCO<sub>2</sub> by means of a non-invasive technique, transcutaneous PCO<sub>2</sub> (PtCO<sub>2</sub>), and to verify the correlation between PtCO<sub>2</sub> and PaCO<sub>2</sub> and between their derived parameters, such as V<sub>D</sub>/V<sub>T</sub>, during exercise in HF patients. 29 cardiopulmonary exercise tests (CPET) performed on a bike with a ramp protocol aimed at achieving maximal effort in ≈10 min were analyzed. PaCO<sub>2</sub> and PtCO<sub>2</sub> values were collected at rest and every 2 min during active pedaling. The uncertainty of PCO<sub>2</sub> and V<sub>D</sub>/V<sub>T</sub> measurements were determined by analyzing the error between the two methods. The accuracy of PtCO<sub>2</sub> measurements vs. PaCO<sub>2</sub> decreases towards the end of exercise. Therefore, a correction to PtCO<sub>2</sub> that keeps into account the time of the measurement was implemented with a multiple regression model. PtCO<sub>2</sub> and V<sub>D</sub>/V<sub>T</sub> changes at 6, 8 and 10 min vs. 2 min data were evaluated before and after PtCO<sub>2</sub> correction. PtCO<sub>2</sub> overestimates PaCO<sub>2</sub> for high timestamps (median error 2.45, IQR -0.635-5.405, at 10 min vs. 2 min, <em>p</em>-value = 0.011), while the error is negligible after correction (median error 0.50, IQR = -2.21-3.19, <em>p</em>-value &gt; 0.05). The correction allows removing differences also in PCO<sub>2</sub> and V<sub>D</sub>/V<sub>T</sub> changes. In HF patients PtCO<sub>2</sub> is a reliable PaCO<sub>2</sub> estimation at rest and at low exercise intensity. At high exercise intensity the overall response appears delayed but reproducible and the error can be overcome by mathematical modeling allowing an accurate estimation by PtCO<sub>2</sub> of PaCO<sub>2</sub> and V<sub>D</sub>/V<sub>T</sub>.
DOI: 10.5281/zenodo.5840830
title: Dataset related to the article "Comparison between PtCO 2 and PaCO 2 and Derived Parameters in Heart Failure Patients during Exercise: A Preliminary Study"

description: Abstract Evaluation of arterial carbon dioxide pressure (PaCO<sub>2</sub>) and dead space to tidal volume ratio (V<sub>D</sub>/V<sub>T</sub>) during exercise is important for the identification of exercise limitation causes in heart failure (HF). However, repeated sampling of arterial or arterialized ear lobe capillary blood may be clumsy. The aim of our study was to estimate PaCO<sub>2</sub> by means of a non-invasive technique, transcutaneous PCO<sub>2</sub> (PtCO<sub>2</sub>), and to verify the correlation between PtCO<sub>2</sub> and PaCO<sub>2</sub> and between their derived parameters, such as V<sub>D</sub>/V<sub>T</sub>, during exercise in HF patients. 29 cardiopulmonary exercise tests (CPET) performed on a bike with a ramp protocol aimed at achieving maximal effort in ≈10 min were analyzed. PaCO<sub>2</sub> and PtCO<sub>2</sub> values were collected at rest and every 2 min during active pedaling. The uncertainty of PCO<sub>2</sub> and V<sub>D</sub>/V<sub>T</sub> measurements were determined by analyzing the error between the two methods. The accuracy of PtCO<sub>2</sub> measurements vs. PaCO<sub>2</sub> decreases towards the end of exercise. Therefore, a correction to PtCO<sub>2</sub> that keeps into account the time of the measurement was implemented with a multiple regression model. PtCO<sub>2</sub> and V<sub>D</sub>/V<sub>T</sub> changes at 6, 8 and 10 min vs. 2 min data were evaluated before and after PtCO<sub>2</sub> correction. PtCO<sub>2</sub> overestimates PaCO<sub>2</sub> for high timestamps (median error 2.45, IQR -0.635-5.405, at 10 min vs. 2 min, <em>p</em>-value = 0.011), while the error is negligible after correction (median error 0.50, IQR = -2.21-3.19, <em>p</em>-value &gt; 0.05). The correction allows removing differences also in PCO<sub>2</sub> and V<sub>D</sub>/V<sub>T</sub> changes. In HF patients PtCO<sub>2</sub> is a reliable PaCO<sub>2</sub> estimation at rest and at low exercise intensity. At high exercise intensity the overall response appears delayed but reproducible and the error can be overcome by mathematical modeling allowing an accurate estimation by PtCO<sub>2</sub> of PaCO<sub>2</sub> and V<sub>D</sub>/V<sub>T</sub>.
DOI: 10.5281/zenodo.5840717
title: Electrophorus electricus decontaminated FSCR

description: .
DOI: 10.5281/zenodo.5840716
title: Electrophorus electricus decontaminated FSCR

description: .
DOI: 10.25505/fiz.icsd.cc21fpsz
title: CSD 1890001: Experimental Crystal Structure Determination

description: Related Article: E.S. Zhitova, A.A. Zolotarev, F.C. Hawthorne, S.V. Krivovichev, V.N. Yakovenchuk, A.G. Goncharov|2019|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|75|578|doi:10.1107/S2052520619006024
DOI: 10.25505/fiz.icsd.cc21fpry
title: CSD 1890000: Experimental Crystal Structure Determination

description: Related Article: E.S. Zhitova, A.A. Zolotarev, F.C. Hawthorne, S.V. Krivovichev, V.N. Yakovenchuk, A.G. Goncharov|2019|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|75|578|doi:10.1107/S2052520619006024
DOI: 10.25505/fiz.icsd.cc21fpqx
title: CSD 1889999: Experimental Crystal Structure Determination

description: Related Article: E.S. Zhitova, A.A. Zolotarev, F.C. Hawthorne, S.V. Krivovichev, V.N. Yakovenchuk, A.G. Goncharov|2019|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|75|578|doi:10.1107/S2052520619006024
DOI: 10.25505/fiz.icsd.cc21fppw
title: CSD 1889998: Experimental Crystal Structure Determination

description: Related Article: E.S. Zhitova, A.A. Zolotarev, F.C. Hawthorne, S.V. Krivovichev, V.N. Yakovenchuk, A.G. Goncharov|2019|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|75|578|doi:10.1107/S2052520619006024
DOI: 10.25505/fiz.icsd.cc21fpnv
title: CSD 1889997: Experimental Crystal Structure Determination

description: Related Article: E.S. Zhitova, A.A. Zolotarev, F.C. Hawthorne, S.V. Krivovichev, V.N. Yakovenchuk, A.G. Goncharov|2019|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|75|578|doi:10.1107/S2052520619006024
DOI: 10.25505/fiz.icsd.cc20czgv
title: CSD 1858557: Experimental Crystal Structure Determination

description: Related Article: Rong Wan, Huafeng Li, Xinyi Ma, Zhen Liu, Vikram Singh, Pengtao Ma, Chao Zhang, Jingyang Niu, Jingping Wang|2019|Dalton Trans.|48|10327|doi:10.1039/C9DT01615E
DOI: 10.5517/ccdc.csd.cc22dsz8
title: CCDC 1918930: Experimental Crystal Structure Determination

description: Related Article: Jia-Xiong Chen, Wen-Wen Tao, Wen-Cheng Chen, Ya-Fang Xiao, Kai Wang, Chen Cao, Jia Yu, Shengliang Li, Feng-Xia Geng, Chihaya Adachi, Chun-Sing Lee, Xiao-Hong Zhang|2019|Angew.Chem.,Int.Ed.|58|14660|doi:10.1002/anie.201906575
DOI: 10.5517/ccdc.csd.cc22dt0b
title: CCDC 1918931: Experimental Crystal Structure Determination

description: Related Article: Jia-Xiong Chen, Wen-Wen Tao, Wen-Cheng Chen, Ya-Fang Xiao, Kai Wang, Chen Cao, Jia Yu, Shengliang Li, Feng-Xia Geng, Chihaya Adachi, Chun-Sing Lee, Xiao-Hong Zhang|2019|Angew.Chem.,Int.Ed.|58|14660|doi:10.1002/anie.201906575
DOI: 10.5517/ccdc.csd.cc22f1q9
title: CCDC 1919170: Experimental Crystal Structure Determination

description: Related Article: Zhong Huang, Yohei Ishida, Tetsu Yonezawa|2019|Angew.Chem.,Int.Ed.|58|13411|doi:10.1002/anie.201908905
description: Related Article: Wenyao Zhang, Zhonglei Wei, Zhihua Yang, Shilie Pan|2019|Inorg.Chem.|58|13411|doi:10.1021/acs.inorgchem.9b02307
DOI: 10.5517/ccdc.csd.cc22f1p8
title: CCDC 1919169: Experimental Crystal Structure Determination

description: Related Article: Zhong Huang, Yohei Ishida, Tetsu Yonezawa|2019|Angew.Chem.,Int.Ed.|58|13411|doi:10.1002/anie.201908905
description: Related Article: Wenyao Zhang, Zhonglei Wei, Zhihua Yang, Shilie Pan|2019|Inorg.Chem.|58|13411|doi:10.1021/acs.inorgchem.9b02307
DOI: 10.5517/ccdc.csd.cc22f2xj
title: CCDC 1919207: Experimental Crystal Structure Determination

description: Related Article: Zhong Huang, Yohei Ishida, Tetsu Yonezawa|2019|Angew.Chem.,Int.Ed.|58|13411|doi:10.1002/anie.201908905
description: Related Article: Wenyao Zhang, Zhonglei Wei, Zhihua Yang, Shilie Pan|2019|Inorg.Chem.|58|13411|doi:10.1021/acs.inorgchem.9b02307
DOI: 10.5517/ccdc.csd.cc2261y9
title: CCDC 1912450: Experimental Crystal Structure Determination

description: Related Article: Kanchanok Kodchakorn, Piyarat Nimmanpipug, Suttinun Phongtamrug, Kohji Tashiro|2019|RSC Advances|9|19375|doi:10.1039/C9RA03418H
description: Related Article: Kanchanok Kodchakorn|2019|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2261cq
title: CCDC 1912432: Experimental Crystal Structure Determination

description: Related Article: Kanchanok Kodchakorn, Piyarat Nimmanpipug, Suttinun Phongtamrug, Kohji Tashiro|2019|RSC Advances|9|19375|doi:10.1039/C9RA03418H
description: Related Article: Kanchanok Kodchakorn|2019|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2261bp
title: CCDC 1912431: Experimental Crystal Structure Determination

description: Related Article: Kanchanok Kodchakorn, Piyarat Nimmanpipug, Suttinun Phongtamrug, Kohji Tashiro|2019|RSC Advances|9|19375|doi:10.1039/C9RA03418H
description: Related Article: Kanchanok Kodchakorn|2019|CSD Communication|||
DOI: 10.25505/fiz.icsd.cc22fvt6
title: CSD 1919948: Experimental Crystal Structure Determination

description: Related Article: W. Peng, V. Balédent, M.-B. Lepetit, A. Vaunat, E. Rebolini, M. Greenblatt, P. Foury-Leylekian|2019|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|75|687|doi:10.1107/S2052520619007844
DOI: 10.25505/fiz.icsd.cc22fwt7
title: CSD 1919979: Experimental Crystal Structure Determination

description: Related Article: Xian Zhang, Yi Xiao, Ruiqi Wang, Pengxiang Fu, Chong Zheng, Fuqiang Huang|2019|Dalton Trans.|48|14662|doi:10.1039/C9DT02780G
DOI: 10.25505/fiz.icsd.cc22fwv8
title: CSD 1919980: Experimental Crystal Structure Determination

description: Related Article: Xian Zhang, Yi Xiao, Ruiqi Wang, Pengxiang Fu, Chong Zheng, Fuqiang Huang|2019|Dalton Trans.|48|14662|doi:10.1039/C9DT02780G
DOI: 10.5281/zenodo.5785955
title: PAAL ADL Accelerometry dataset v2.0

description: The PAAL ADL Accelerometry dataset (v2.0) has been acquired with a high-quality wearable multisensor device, the Empatica E4. In this dataset, among the signals collected by the sensors embedded in the Empatica E4, only the acceleration has been extracted to monitor the users performing different activities of daily living (ADLs). To promote the real-life acquisition procedure, subjects acted in their natural environment, with no instructions about how and for how long to perform each activity (other than a minimum time). The device was worn on the dominant hand. The dataset includes <strong>24 different ADLs</strong> performed using real objects. Each activity was repeated between 3 and 5 times (on average) by <strong>52 healthy subjects</strong>, characterized by a gender balance <strong>(26 women and 26 men)</strong>, and a large age range (between 18 and 77 years, mean = 44.08 years and standard deviation = 17.06 years). The PAAL ADL Accelerometry dataset (v2.0) is composed of three files: users.csv: each line contains (participant id, gender, age) of each user performing the ADLs in the dataset. <em>N.B: gender labels are 'man' and 'woman'</em>. ADLs.csv: each line contains (ADL id, ADL name) data.zip: folder with 6,072 files of accelerometer data of users performing ADLs. The name of each file indicates the name of the ADL, the user id and the repetition. Each row in the files represents the continuous gravitational force (g) applied to each of the three spacial dimensions (x, y, and z). The scale is limited to [-2g, +2g]. The sampling frequency is 32 Hz, with a resolution of 0.015 g (8 bit). More information about the format here.
description: This dataset has been recorded as part of the work in the research project PAAL - Privacy-Aware and Acceptable Lifelogging services for older and frail people (https://paal-project.eu/). The support of the More Years Better Lives JPI (JPI MYBL award number: PAAL_JTC2017), the Italian Ministero dell'Istruzione, Università e Ricerca (CUP: I36G17000380001) and the Spanish Agencia Estatal de Investigación (grant no: PCIN-2017-114) is gratefully acknowledged.
DOI: 10.5281/zenodo.4750903
title: PAAL ADL Accelerometry dataset v2.0

description: The PAAL ADL Accelerometry dataset (v2.0) has been acquired with a high-quality wearable multisensor device, the Empatica E4. In this dataset, among the signals collected by the sensors embedded in the Empatica E4, only the acceleration has been extracted to monitor the users performing different activities of daily living (ADLs). To promote the real-life acquisition procedure, subjects acted in their natural environment, with no instructions about how and for how long to perform each activity (other than a minimum time). The device was worn on the dominant hand. The dataset includes <strong>24 different ADLs</strong> performed using real objects. Each activity was repeated between 3 and 5 times (on average) by <strong>52 healthy subjects</strong>, characterized by a gender balance <strong>(26 women and 26 men)</strong>, and a large age range (between 18 and 77 years, mean = 44.08 years and standard deviation = 17.06 years). The PAAL ADL Accelerometry dataset (v2.0) is composed of three files: users.csv: each line contains (participant id, gender, age) of each user performing the ADLs in the dataset. <em>N.B: gender labels are 'man' and 'woman'</em>. ADLs.csv: each line contains (ADL id, ADL name) data.zip: folder with 6,072 files of accelerometer data of users performing ADLs. The name of each file indicates the name of the ADL, the user id and the repetition. Each row in the files represents the continuous gravitational force (g) applied to each of the three spacial dimensions (x, y, and z). The scale is limited to [-2g, +2g]. The sampling frequency is 32 Hz, with a resolution of 0.015 g (8 bit). More information about the format here.
description: This dataset has been recorded as part of the work in the research project PAAL - Privacy-Aware and Acceptable Lifelogging services for older and frail people (https://paal-project.eu/). The support of the More Years Better Lives JPI (JPI MYBL award number: PAAL_JTC2017), the Italian Ministero dell'Istruzione, Università e Ricerca (CUP: I36G17000380001) and the Spanish Agencia Estatal de Investigación (grant no: PCIN-2017-114) is gratefully acknowledged.
DOI: 10.5281/zenodo.5840861
title: Performance of GFN1-xTB for periodic optimization of Metal-Organic Frameworks

description: GFN-xTB optimised structures of CoRE 2014 and CoRE 2019 structures, with and without lattice optimisation.
DOI: 10.5281/zenodo.5840860
title: Performance of GFN1-xTB for periodic optimization of Metal-Organic Frameworks

description: GFN-xTB optimised structures of CoRE 2014 and CoRE 2019 structures, with and without lattice optimisation.
DOI: 10.25403/upresearchdata.18112604
title: Business model framework for education technology entrepreneurs in South Africa

description: Atlas.ti data set with all the transcribed interviews and data coding. File needs to be opened with the Atlas.ti tool.
DOI: 10.25403/upresearchdata.18112604.v1
title: Business model framework for education technology entrepreneurs in South Africa

description: Atlas.ti data set with all the transcribed interviews and data coding. File needs to be opened with the Atlas.ti tool.
DOI: 10.5281/zenodo.5840339
title: Generated RGBD Tracking Benchmarks (LaSOT) Part11

description: Fixed broken zip files, including : pig, rabbit, robot, rubicCube
DOI: 10.5281/zenodo.5840338
title: Generated RGBD Tracking Benchmarks (LaSOT) Part11

description: Fixed broken zip files, including : pig, rabbit, robot, rubicCube
DOI: 10.5281/zenodo.5840343
title: Generated RGBD Tracking Benchmarks (LaSOT) Part12

description: Fix the broken zip files, including: lizard, microphone, monkey, motorcycle, person
DOI: 10.5281/zenodo.5840342
title: Generated RGBD Tracking Benchmarks (LaSOT) Part12

description: Fix the broken zip files, including: lizard, microphone, monkey, motorcycle, person
DOI: 10.5281/zenodo.5840795
title: Gallinago hardwickii decontaminated FSCR

description: .
DOI: 10.5281/zenodo.5840794
title: Gallinago hardwickii decontaminated FSCR

description: .
DOI: 10.20363/gbol-20220112
title: German Barcode of Life Dataset Release
DOI: 10.5281/zenodo.5840874
title: An open-source and easily replicable hardware for Electrical Impedance Tomography

description: Supplementary materials of the paper.
DOI: 10.5281/zenodo.5840858
title: Gnathonemus longibarbis decontaminated FSCR

description: .
DOI: 10.5281/zenodo.5840857
title: Gnathonemus longibarbis decontaminated FSCR

description: .
DOI: 10.6084/m9.figshare.18269075
title: Supplementary Material for: Direct Determination rather than Oscillometric Estimation of Systolic Blood Pressure in Patients with Severe Chronic Kidney Disease

description: <b><i>Introduction:</i></b> Although arterial hypertension is a major concern in patients with chronic kidney disease (CKD), obtaining accurate systolic blood pressure (SBP) measurement is challenging in this population for whom automatic oscillometric devices may yield erroneous results. <b><i>Methods:</i></b> This cross-sectional study was conducted in 89 patients with stages 4, 5, and 5D CKD, for whom we compared SBP values obtained by the recently described systolic foot-to-apex time interval (SFATI) technique which provides direct SBP determination, the standard technique (Korotkoff sounds), and oscillometry. We investigated the effects of age, sex, diabetes, CKD stage, and pulse pressure to explain measurement errors defined as biases or misclassification relative to the SBP thresholds of 110–130-mm Hg. <b><i>Results:</i></b> All 3 techniques showed satisfactory reproducibility for SBP measurement (CCC &gt; 0.84 and &gt;0.91, respectively, in dialyzed and nondialyzed patients). The mean ± SD from SBP as determined via Korotkoff sounds was 1.7 ± 4.6 mm Hg for SFATI (CCC = 0.98) and 5.9 ± 9.3 mm Hg for oscillometry (CCC = 0.88). Referring to the 110–130-mm Hg SBP range outside which treatment prescription or adaptation is recommended for CKD patients, SFATI underestimated SBP in 3 patients and overestimated it in 1, whereas oscillometry underestimated SBP in 12 patients and overestimated it in 3. Higher pulse pressure was the main explanatory factor for measurement and classification errors. <b><i>Discussion/Conclusion:</i></b> SFATI provides accurate SBP measurements in patients with severe CKD and paves the way for the standardization of automated noninvasive blood pressure measurement devices. Before prescribing or adjusting antihypertensive therapy, physicians should be aware of the risk of misclassification when using oscillometry.