16 datasets found
  1. Descriptive statistics of the 2 datasets with mean, standard deviation (SD),...

    • plos.figshare.com
    xls
    Updated Jun 18, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Achim Langenbucher; Nóra Szentmáry; Alan Cayless; Jascha Wendelstein; Peter Hoffmann (2023). Descriptive statistics of the 2 datasets with mean, standard deviation (SD), median, the lower (quantile 2.5%) and upper (quantile 97.5%) boundary of the 95% confidence interval, and the interquartile range IQR (quartile 75%—quartile 25%). [Dataset]. http://doi.org/10.1371/journal.pone.0282213.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 18, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Achim Langenbucher; Nóra Szentmáry; Alan Cayless; Jascha Wendelstein; Peter Hoffmann
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    AL refers to the axial length, CCT to the central corneal thickness, ACD to the external phakic anterior chamber depth measured from the corneal front apex to the front apex of the crystalline lens, LT to the central thickness of the crystalline lens, R1 and R2 to the corneal radii of curvature for the flat and steep meridians, Rmean to the average of R1 and R2, PIOL to the refractive power of the intraocular lens implant, and SEQ to the spherical equivalent power achieved 5 to 12 weeks after cataract surgery.

  2. Z

    360-info/tracker-seaice: Daily sea ice extent: v2024-11-28

    • data.niaid.nih.gov
    Updated Nov 29, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    James Goldie (2024). 360-info/tracker-seaice: Daily sea ice extent: v2024-11-28 [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_10892561
    Explore at:
    Dataset updated
    Nov 29, 2024
    Dataset provided by
    360info
    Authors
    James Goldie
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Tracks the daily sea ice extent for the Arctic Circle and Antarctica using the NSIDC's Sea Ice Index dataset, as well as pre-calculating several useful measures: historical inter-quartile range across the year, the previous lowest year and the previous year.

  3. Performance of bias, precision and accuracy between measured GFR and...

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Xun Liu; Xiaoliang Gan; Jinxia Chen; Linsheng Lv; Ming Li; Tanqi Lou (2023). Performance of bias, precision and accuracy between measured GFR and estimated GFR in the validation data set. [Dataset]. http://doi.org/10.1371/journal.pone.0109743.t005
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Xun Liu; Xiaoliang Gan; Jinxia Chen; Linsheng Lv; Ming Li; Tanqi Lou
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Abbreviations: GFR, glomerular filtration rate; MDRD, Modification of Diet in Renal Disease; CKD-EPI, Chronic Kidney Disease Epidemiology Collaboration; CI, confidence interval; IQR, interquartile range.Performance of bias, precision and accuracy between measured GFR and estimated GFR in the validation data set.

  4. f

    WHO age-standardized and age-specific multimorbidity and dual long-term...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Dec 6, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Alison J. Price; Modou Jobe; Isaac Sekitoleko; Amelia C. Crampin; Andrew M. Prentice; Janet Seeley; Edith F. Chikumbu; Joseph Mugisha; Ronald Makanga; Albert Dube; Frances S. Mair; Bhautesh Dinesh Jani (2023). WHO age-standardized and age-specific multimorbidity and dual long-term conditions combinations prevalence estimates: Malawi, The Gambia and Uganda. [Dataset]. http://doi.org/10.1371/journal.pgph.0002677.t004
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Dec 6, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Alison J. Price; Modou Jobe; Isaac Sekitoleko; Amelia C. Crampin; Andrew M. Prentice; Janet Seeley; Edith F. Chikumbu; Joseph Mugisha; Ronald Makanga; Albert Dube; Frances S. Mair; Bhautesh Dinesh Jani
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    The Gambia, Uganda, Malawi
    Description

    WHO age-standardized and age-specific multimorbidity and dual long-term conditions combinations prevalence estimates: Malawi, The Gambia and Uganda.

  5. Formula prediction error PE (difference of the SEQ measured after cataract...

    • plos.figshare.com
    xls
    Updated Jun 21, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Achim Langenbucher; Nóra Szentmáry; Alan Cayless; Jascha Wendelstein; Peter Hoffmann (2023). Formula prediction error PE (difference of the SEQ measured after cataract surgery minus the formula predicted SEQ) for the Hoffer Q (pACD), the Holladay 1 (SF), Haigis (a0/a1/a2), and Castrop formula (C / H / R). [Dataset]. http://doi.org/10.1371/journal.pone.0282213.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Achim Langenbucher; Nóra Szentmáry; Alan Cayless; Jascha Wendelstein; Peter Hoffmann
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    SD refers to the standard deviation, 2.5% quantile and 97.5% quantile to the lower and upper boundary of the 95% confidence interval, and IQR to the interquartile range as the difference between the 75% and the 25% quantile. Formula constant optimisation was performed to minimise the sum of squared prediction errors PE. Situation A) refers to the ‘classical’ formulae with standard nK/nC values, with situation B) the formula constants and nK/nC in the main part of the formula were varied for optimisation, with situation C) the formula constants and nK/nC in the main part of the formula were varied to minimise for PE and the PE trend error over corneal radius, and with situation D) a standard optimisation was performed using the nK/nC value from situation B) derived from the other dataset in terms of a cross-validation.

  6. f

    Baseline lifestyle factor prevalence estimates: Malawi and Uganda.

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Dec 6, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Alison J. Price; Modou Jobe; Isaac Sekitoleko; Amelia C. Crampin; Andrew M. Prentice; Janet Seeley; Edith F. Chikumbu; Joseph Mugisha; Ronald Makanga; Albert Dube; Frances S. Mair; Bhautesh Dinesh Jani (2023). Baseline lifestyle factor prevalence estimates: Malawi and Uganda. [Dataset]. http://doi.org/10.1371/journal.pgph.0002677.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Dec 6, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Alison J. Price; Modou Jobe; Isaac Sekitoleko; Amelia C. Crampin; Andrew M. Prentice; Janet Seeley; Edith F. Chikumbu; Joseph Mugisha; Ronald Makanga; Albert Dube; Frances S. Mair; Bhautesh Dinesh Jani
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Uganda, Malawi
    Description

    Baseline lifestyle factor prevalence estimates: Malawi and Uganda.

  7. f

    WHO age-standardized prevalence estimates for single long-term conditions:...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Dec 6, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Alison J. Price; Modou Jobe; Isaac Sekitoleko; Amelia C. Crampin; Andrew M. Prentice; Janet Seeley; Edith F. Chikumbu; Joseph Mugisha; Ronald Makanga; Albert Dube; Frances S. Mair; Bhautesh Dinesh Jani (2023). WHO age-standardized prevalence estimates for single long-term conditions: Malawi, The Gambia and Uganda. [Dataset]. http://doi.org/10.1371/journal.pgph.0002677.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Dec 6, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Alison J. Price; Modou Jobe; Isaac Sekitoleko; Amelia C. Crampin; Andrew M. Prentice; Janet Seeley; Edith F. Chikumbu; Joseph Mugisha; Ronald Makanga; Albert Dube; Frances S. Mair; Bhautesh Dinesh Jani
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    The Gambia, Uganda, Malawi
    Description

    WHO age-standardized prevalence estimates for single long-term conditions: Malawi, The Gambia and Uganda.

  8. f

    Nutritional Risk Screening (NRS)-2002 score and measured energy intake,...

    • datasetcatalog.nlm.nih.gov
    • plos.figshare.com
    Updated Apr 29, 2015
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Pichard, Claude; Pittet, Didier; Thibault, Ronan; Makhlouf, Anne-Marie; Chikhi, Marinette; Iavindrasana, Jimison; Kossovsky, Michel P.; Meyer, Rodolphe; Zingg, Walter (2015). Nutritional Risk Screening (NRS)-2002 score and measured energy intake, according to the presence or absence of healthcare-associated infections (HCAI). [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0001871676
    Explore at:
    Dataset updated
    Apr 29, 2015
    Authors
    Pichard, Claude; Pittet, Didier; Thibault, Ronan; Makhlouf, Anne-Marie; Chikhi, Marinette; Iavindrasana, Jimison; Kossovsky, Michel P.; Meyer, Rodolphe; Zingg, Walter
    Description

    Predicted energy needs are calculated as 110% of Harris-Benedict formula.* Nutritional Risk Screening-2002 score is calculated in 1091 patients.† ‘IQR’ is the interquartile range of the median.‡Energy intake is available in 1024 patients.Nutritional Risk Screening (NRS)-2002 score and measured energy intake, according to the presence or absence of healthcare-associated infections (HCAI).

  9. f

    Estimates of the association between sociodemographic and lifestyle factors...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Dec 6, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Alison J. Price; Modou Jobe; Isaac Sekitoleko; Amelia C. Crampin; Andrew M. Prentice; Janet Seeley; Edith F. Chikumbu; Joseph Mugisha; Ronald Makanga; Albert Dube; Frances S. Mair; Bhautesh Dinesh Jani (2023). Estimates of the association between sociodemographic and lifestyle factors and multimorbidity: Malawi, The Gambia and Uganda. [Dataset]. http://doi.org/10.1371/journal.pgph.0002677.t005
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Dec 6, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Alison J. Price; Modou Jobe; Isaac Sekitoleko; Amelia C. Crampin; Andrew M. Prentice; Janet Seeley; Edith F. Chikumbu; Joseph Mugisha; Ronald Makanga; Albert Dube; Frances S. Mair; Bhautesh Dinesh Jani
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    The Gambia, Uganda, Malawi
    Description

    Estimates of the association between sociodemographic and lifestyle factors and multimorbidity: Malawi, The Gambia and Uganda.

  10. Results of current and previous ultrasound studies describing the...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 2, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Kazumasa Oura; Hiroshi Akasaka; Naoki Ishizuka; Yuriko Sato; Masahiro Kudo; Takashi Yamaguchi; Mao Yamaguchi Oura; Ryo Itabashi; Tetsuya Maeda (2023). Results of current and previous ultrasound studies describing the cross-sectional area of the vagus nerve in healthy individuals. [Dataset]. http://doi.org/10.1371/journal.pone.0280661.t005
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Kazumasa Oura; Hiroshi Akasaka; Naoki Ishizuka; Yuriko Sato; Masahiro Kudo; Takashi Yamaguchi; Mao Yamaguchi Oura; Ryo Itabashi; Tetsuya Maeda
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Results of current and previous ultrasound studies describing the cross-sectional area of the vagus nerve in healthy individuals.

  11. f

    Baseline socio-demographic factor prevalence estimates: Malawi, The Gambia...

    • figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Dec 6, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Alison J. Price; Modou Jobe; Isaac Sekitoleko; Amelia C. Crampin; Andrew M. Prentice; Janet Seeley; Edith F. Chikumbu; Joseph Mugisha; Ronald Makanga; Albert Dube; Frances S. Mair; Bhautesh Dinesh Jani (2023). Baseline socio-demographic factor prevalence estimates: Malawi, The Gambia and Uganda. [Dataset]. http://doi.org/10.1371/journal.pgph.0002677.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Dec 6, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Alison J. Price; Modou Jobe; Isaac Sekitoleko; Amelia C. Crampin; Andrew M. Prentice; Janet Seeley; Edith F. Chikumbu; Joseph Mugisha; Ronald Makanga; Albert Dube; Frances S. Mair; Bhautesh Dinesh Jani
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    The Gambia, Uganda, Malawi
    Description

    Baseline socio-demographic factor prevalence estimates: Malawi, The Gambia and Uganda.

  12. f

    Count of individuals estimated glomerular filtration rate (eGFR) category by...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 1, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Jake M. Pry; Michael J. Vinikoor; Carolyn Bolton Moore; Monika Roy; Aaloke Mody; Izukanji Sikazwe; Anjali Sharma; Belinda Chihota; Miquel Duran-Frigola; Harriet Daultrey; Jacob Mutale; Andrew D. Kerkhoff; Elvin H. Geng; Brad H. Pollock; Jaime H. Vera (2023). Count of individuals estimated glomerular filtration rate (eGFR) category by eGFR formula. [Dataset]. http://doi.org/10.1371/journal.pgph.0000124.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Jake M. Pry; Michael J. Vinikoor; Carolyn Bolton Moore; Monika Roy; Aaloke Mody; Izukanji Sikazwe; Anjali Sharma; Belinda Chihota; Miquel Duran-Frigola; Harriet Daultrey; Jacob Mutale; Andrew D. Kerkhoff; Elvin H. Geng; Brad H. Pollock; Jaime H. Vera
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Count of individuals estimated glomerular filtration rate (eGFR) category by eGFR formula.

  13. Characteristics of the study participants.

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 2, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Kazumasa Oura; Hiroshi Akasaka; Naoki Ishizuka; Yuriko Sato; Masahiro Kudo; Takashi Yamaguchi; Mao Yamaguchi Oura; Ryo Itabashi; Tetsuya Maeda (2023). Characteristics of the study participants. [Dataset]. http://doi.org/10.1371/journal.pone.0280661.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Kazumasa Oura; Hiroshi Akasaka; Naoki Ishizuka; Yuriko Sato; Masahiro Kudo; Takashi Yamaguchi; Mao Yamaguchi Oura; Ryo Itabashi; Tetsuya Maeda
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    ObjectivesAlthough the vagus nerve (VN) is easily observed by ultrasonography, few studies have evaluated the cross-sectional area (CSA) of the VN in healthy older individuals from East Asia. In this study, we aimed to report reference values for the CSA of the VN in community-dwelling elderly Japanese individuals and to identify any associated medical history and/or lifestyle factors.MethodsThe present study included 336 participants aged ≥ 70 years from a prospective cohort study conducted in Yahaba, Japan from October 2021 to February 2022. The CSA of the VN was measured bilaterally at the level of the thyroid gland by ultrasonography. Simple linear regression analysis and generalized estimating equation were conducted to identify the associations between clinical and background factors and the CSA of the VN.ResultsIn our cohort, the median CSA of the VN was 1.3 mm2 (interquartile range [IQR] 1.1–1.6) on the right side and 1.2 mm2 (IQR 1.0–1.4) on the left side. Generalized estimating equation showed that history of head injury (β = 0.19, p < .01), current smoking habit (β = -0.09, p = .03), and BMI (β = 0.02, p < .01) were independently associated with the CSA of the VN.ConclusionWe have reported reference VN CSA values for community-dwelling elderly Japanese individuals. In addition, we showed that the CSA of the VN was positively associated with a history of head injury and BMI and inversely associated with current smoking habit.

  14. Multivariable linear regression analysis of variables associated with vagus...

    • figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 2, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Kazumasa Oura; Hiroshi Akasaka; Naoki Ishizuka; Yuriko Sato; Masahiro Kudo; Takashi Yamaguchi; Mao Yamaguchi Oura; Ryo Itabashi; Tetsuya Maeda (2023). Multivariable linear regression analysis of variables associated with vagus nerve cross-sectional area. [Dataset]. http://doi.org/10.1371/journal.pone.0280661.t004
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Kazumasa Oura; Hiroshi Akasaka; Naoki Ishizuka; Yuriko Sato; Masahiro Kudo; Takashi Yamaguchi; Mao Yamaguchi Oura; Ryo Itabashi; Tetsuya Maeda
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Multivariable linear regression analysis of variables associated with vagus nerve cross-sectional area.

  15. Demographic and clinical data: Proportion/median and...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Oct 8, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Mathias Mlewa; Helmut A. Nyawale; Shimba Henerico; Ivon Mangowi; Aminiel Robert Shangali; Anselmo Mathias Manisha; Felix Kisanga; Benson R. Kidenya; Hyasinta Jaka; Semvua B. Kilonzo; Mariam M. Mirambo; Stephen E. Mshana (2024). Demographic and clinical data: Proportion/median and percentage/interquartile range [IQIR]. [Dataset]. http://doi.org/10.1371/journal.pone.0309314.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Oct 8, 2024
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Mathias Mlewa; Helmut A. Nyawale; Shimba Henerico; Ivon Mangowi; Aminiel Robert Shangali; Anselmo Mathias Manisha; Felix Kisanga; Benson R. Kidenya; Hyasinta Jaka; Semvua B. Kilonzo; Mariam M. Mirambo; Stephen E. Mshana
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Demographic and clinical data: Proportion/median and percentage/interquartile range [IQIR].

  16. Baseline and clinical characteristics of the Parkinson’s disease patients (n...

    • plos.figshare.com
    • figshare.com
    xls
    Updated Jun 1, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Seyed-Mohammad Fereshtehnejad; Mahdiyeh Shafieesabet; Farzaneh Farhadi; Hasti Hadizadeh; Arash Rahmani; Nader Naderi; Dena Khaefpanah; Gholam Ali Shahidi; Ahmad Delbari; Johan Lökk (2023). Baseline and clinical characteristics of the Parkinson’s disease patients (n = 157). [Dataset]. http://doi.org/10.1371/journal.pone.0137081.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Seyed-Mohammad Fereshtehnejad; Mahdiyeh Shafieesabet; Farzaneh Farhadi; Hasti Hadizadeh; Arash Rahmani; Nader Naderi; Dena Khaefpanah; Gholam Ali Shahidi; Ahmad Delbari; Johan Lökk
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    SD: standard deviation; IQR: interquartile range; PIGD: postural-instability-gait-difficulty; FOSS: freezing-speech-swallowing1 Score A is the sum of UPDRS-Part III items concerning facial expression, tremor, rigidity, and Bradykinesia which are considered relatively L-dopa responsive2 Score B is the sum of UPDRS-Part III items concerning speech and axial impairment (arising from chair, posture, postural stability, gait) which are considered relatively L-dopa non-responsive.Baseline and clinical characteristics of the Parkinson’s disease patients (n = 157).

  17. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Achim Langenbucher; Nóra Szentmáry; Alan Cayless; Jascha Wendelstein; Peter Hoffmann (2023). Descriptive statistics of the 2 datasets with mean, standard deviation (SD), median, the lower (quantile 2.5%) and upper (quantile 97.5%) boundary of the 95% confidence interval, and the interquartile range IQR (quartile 75%—quartile 25%). [Dataset]. http://doi.org/10.1371/journal.pone.0282213.t001
Organization logo

Descriptive statistics of the 2 datasets with mean, standard deviation (SD), median, the lower (quantile 2.5%) and upper (quantile 97.5%) boundary of the 95% confidence interval, and the interquartile range IQR (quartile 75%—quartile 25%).

Related Article
Explore at:
xlsAvailable download formats
Dataset updated
Jun 18, 2023
Dataset provided by
PLOShttp://plos.org/
Authors
Achim Langenbucher; Nóra Szentmáry; Alan Cayless; Jascha Wendelstein; Peter Hoffmann
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

AL refers to the axial length, CCT to the central corneal thickness, ACD to the external phakic anterior chamber depth measured from the corneal front apex to the front apex of the crystalline lens, LT to the central thickness of the crystalline lens, R1 and R2 to the corneal radii of curvature for the flat and steep meridians, Rmean to the average of R1 and R2, PIOL to the refractive power of the intraocular lens implant, and SEQ to the spherical equivalent power achieved 5 to 12 weeks after cataract surgery.

Search
Clear search
Close search
Google apps
Main menu