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Hippocampal atrophy in untreated de novo Parkinson's disease with obstructive sleep apnea.

Code ↔ Paper

12 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 12 matches · 5 of them tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted
  1. [1] § Methods › Participants ↔ R/describe_data.R, the whole file · a weak match · score 0.90 · MDS UPDRS III, uric acid, epilepsy, diabetes, hypertension, cholesterol
  2. [2] § Methods › Statistical analysis ↔ R/describe_data.R, the whole file · a weak match · score 0.84 · disease duration, MDS UPDRS, PD MCI, continuous variables, Fazekas, RBD
  3. [3] § Methods › Statistical analysis ↔ R/lm_funs.R, lines 65–92 · score 0.80 · Breusch Pagan, Shapiro Wilk, linear regression models, residuals, homoscedasticity, lm
  4. [4] § Methods › Statistical analysis ↔ R/data_funs.R, lines 111–170 · score 0.73 · disease duration, MDS UPDRS, PD MCI, III, symptom, motor
  5. [5] § Methods › Participants ↔ R/data_funs.R, lines 111–170 · score 0.69 · MDS UPDRS III, duration, axial, rigidity, tremor, symptom
  6. [6] § Methods › Statistical analysis ↔ R/compute_marginal_rates.R, the whole file · a weak match · score 0.66 · pairwise comparison, logistic regression, emmeans, probabilities, model
  7. [7] § Methods › Statistical analysis ↔ R/extract_funs.R, lines 67–83 · score 0.64 · pairwise comparison, logistic regression, emmeans, probabilities, model
  8. [8] § Methods › Statistical analysis ↔ R/fit_funs.R, lines 108–150 · score 0.58 · brms, linear regression, variance, homoscedasticity, heteroscedasticity, Bayesian
  9. [9] § Methods › Neuropsychological assessment ↔ R/extract_funs.R, lines 25–44 · score 0.56 · processing speed, executive function, neuropsychological
  10. [10] § Methods › Statistical analysis ↔ R/model_check.R, the whole file · a weak match · score 0.56 · brms, regression models, log, heteroscedasticity, Bayesian, fitted
  11. [11] § Methods › Statistical analysis ↔ R/table_funs.R, lines 79–156 · score 0.56 · Subcortical volumes, subcortical structures, hemispheres, OSA interaction, covariates, FDR
  12. [12] § Results › Subcortical volume segmentation ↔ R/targets_sensitivity.R, the whole file · a weak match · score 0.56 · uric acid, MoCA, sensitivity, glucose, covariates, volumes

Paper

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The authors' code

R · 150 lines · 4 KB · other · 2 matches

  1. #' Describes the Sample
  2. #'
  3. #' Takes in data and computes descriptive statistics with
  4. #' associated statistical tests for variables deemed
  5. #' descriptive for the paper.
  6. #'
  7. #' @param data A data.frame generated by \code{import_data}.
  8. #'
  9. #' @returns A data.frame containing per group descriptive
  10. #' statistics.
  11. #'
  12. #' @export
  13. describe_data <- function(data) {
  14. # List variables to be described:
  15. cont <- c(
  16. "AGE",
  17. "EDU.Y",
  18. "BMI",
  19. "AHI",
  20. "age_first_symptom",
  21. "disease_duration",
  22. "moca",
  23. "mds_updrs_i",
  24. "mds_updrs_ii",
  25. "mds_updrs_iii_total",
  26. "mds_updrs_iii_axial",
  27. "mds_updrs_iii_rigidityakineasia",
  28. "mds_updrs_iii_tremor",
  29. "UPSIT",
  30. "uric_acid",
  31. "urea",
  32. "creatinine",
  33. "cholesterol",
  34. "TAG",
  35. "TSH",
  36. "fT4",
  37. "glucose",
  38. "Fazekas",
  39. "orto_tk_leh_sys",
  40. "orto_tk_leh_dia",
  41. "orto_tk_0_sys",
  42. "orto_tk_0_dia",
  43. "orto_tk_1_sys",
  44. "orto_tk_1_dia",
  45. "orto_tk_3_sys",
  46. "orto_tk_3_dia",
  47. "orto_pulz_leh",
  48. "orto_pulz_0",
  49. "orto_pulz_1",
  50. "orto_pulz_3"
  51. )
  52. nomin <- c(
  53. "GENDER",
  54. "RBD",
  55. "Path_MTA_A",
  56. "Path_MTA_H",
  57. "PDMCI_I",
  58. "PDMCI_II",
  59. "orto_hypo",
  60. "an_rodina",
  61. "demence_rodina",
  62. "pn_rodina",
  63. "tres_rodina",
  64. "rbd_rodina",
  65. "uraz_opakovane",
  66. "uzkost_opak_kont",
  67. "deprese_opak_kont",
  68. "psychatricka_onemocneni",
  69. "hypercholesterolemie",
  70. "ichs",
  71. "arytmie",
  72. "hypertenze",
  73. "diabetes_mellitus",
  74. "thyreopatie",
  75. "icmp",
  76. "epilepsie",
  77. "polyneuropatie",
  78. "migreny",
  79. "encefalitis",
  80. "hcmp",
  81. "glaukom",
  82. "rls"
  83. )
  84. # Pre-process data:
  85. d0 <- data |>
  86. dplyr::mutate(dplyr::across(tidyselect::all_of(c(nomin, "SUBJ", "AHI.F")), as.factor)) |>
  87. within({
  88. contrasts(SUBJ) <- -contr.sum(2) / 2 # CON = -0.5, PD = 0.5
  89. contrasts(AHI.F) <- -contr.sum(2) / 2 # High = -0.5, Low = 0.5
  90. })
  91. # Prepare a table with descriptions
  92. tab1 <- d0 |>
  93. dplyr::group_by(GROUP) |>
  94. dplyr::summarise(
  95. dplyr::across(tidyselect::all_of(nomin), freqprop),
  96. dplyr::across(tidyselect::all_of(cont), msd)
  97. ) |>
  98. dplyr::ungroup() |>
  99. tibble::column_to_rownames("GROUP") |>
  100. t() |>
  101. as.data.frame() |>
  102. dplyr::mutate(dplyr::across(tidyselect::everything(), \(x) dplyr::if_else(grepl("NaN", x), "-", x))) |>
  103. tibble::rownames_to_column("y")
  104. # Add statistical analysis results of variables present in both PD and HC:
  105. tab1 <- dplyr::left_join(
  106. tab1, purrr::map_dfr(cont[c(1:4, 7, 14:length(cont))], function(y) {
  107. summary(lm(as.formula( paste0(y," ~ SUBJ * AHI.F")), data = d0))$coefficients[ , c("t value", "Pr(>|t|)")] |>
  108. statextract(y = y, stat = "t")
  109. }),
  110. by = "y"
  111. )
  112. # Add logistic regression for common variables:
  113. nomintest <- sapply(nomin, function(x) {
  114. if (stringr::str_detect(x, "MCI") || x == "RBD") {
  115. FALSE
  116. } else {
  117. ncol(table(d0[ , c("GROUP", x)])) == 2
  118. }
  119. })
  120. nomintest <- nomin[nomintest]
  121. for (i in nomintest) {
  122. tab1[tab1$y == i, c("SUBJ1", "AHI.F1", "SUBJ1:AHI.F1")] <-
  123. summary(glm(as.formula(paste0(i, " ~ SUBJ * AHI.F")), family = binomial(), data = d0))$coefficients[ , c("z value","Pr(>|z|)")] |>
  124. statextract(y = i, stat = "z") |>
  125. dplyr::select(-y)
  126. }
  127. # Add logistic regression for iRBD and PD-MCI level I
  128. for (i in c("RBD", "PDMCI_I", "PDMCI_II")) {
  129. tab1[tab1$y == i, "AHI.F1"] <- summary(
  130. glm(
  131. as.formula(paste0(i," ~ AHI.F")),
  132. family = binomial(),
  133. data = subset(d0, SUBJ == "PD")
  134. )
  135. )$coefficients[ , c("z value","Pr(>|z|)")] |>
  136. statextract(y = i, stat = "z") |>
  137. dplyr::select(-y)
  138. }
  139. # Add results of continuous variables for PD only:
  140. for (i in with(tab1, y[CONH == "-"] )[-1:-3]) {
  141. tab1[ tab1$y == i, "AHI.F1"] <-
  142. summary(lm(as.formula(paste0(i," ~ AHI.F")), data = d0))$coefficients[ , c("t value", "Pr(>|t|)")] |>
  143. statextract(y = i, stat = "t") |>
  144. dplyr::select(-y)
  145. }
  146. # Return the table:
  147. tab1 |>
  148. dplyr::relocate(PDH, .before = CONH) |>
  149. dplyr::relocate(PDL, .after = PDH)
  150. }

describe_data.R at commit aca7b17, under other · at the source

Overview

Authors: Kristína Burdová1, Filip Růžička1, Josef Mana1,2, Pavel Filip1,3, Jiří Nepožitek1, Simona Dostálová1, Pavla Peřinová1, Ondrej Bezdicek1, Petr Gregorovič1, Filip Havlík1, Evžen Růžička1, Petr Dušek1, Karel Šonka1, Robert Jech1
ORCID iDs: Jiří Nepožitek, Petr Dušek
  1. Department of Neurology, Charles University, First Faculty of Medicine and General University Hospital in Prague, Prague, Czech Republic
  2. Institute of Psychology, Czech Academy of Sciences, Prague, Czech Republic
  3. Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN USA
Institutions: Charles University (Czechia); General University Hospital in Prague (Czechia); Czech Academy of Sciences (Czechia); Czech Academy of Sciences, Institute of Psychology (Czechia); University of Minnesota (United States)
Journal: NPJ Parkinson's disease, volume 12, issue 1, article 169
Dates: received 23 January 2025; accepted 8 April 2026; published online 5 May 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1038/s41531-026-01360-5 · PMID 42086584 · PMCID PMC13346879 · OpenAlex W7160268551
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: structural MRI / diffusion (modality), Parkinson's (population), sleep disorders (population), clinical / translational (subfield)
Methods: Statistics, Machine learning, fMRI & imaging, Preprocessing
Keywords: Parkinson's disease, Neurodegeneration
Topic: Obstructive Sleep Apnea Research (Physiology, Medicine), according to OpenAlex
Funding: The Ministry of Health of the Czech Republic (AZV) (Grant No. NU21-04-00443); General University Hospital in Prague project (MH CZ-DRO-VFN64165); National Institute for Neurological Research - EXCELES (ID Project No. LX22NPO5107); Charles University: Cooperatio Program in Neuroscience
Citations: not cited yet (Europe PMC); 110 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Repository

Its files are read in the Code ↔ Paper reader above, with 12 matches between paragraphs and lines of code.

josefmana/pdosa

License: other
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Commit: aca7b175d26dd615f3715a9a09d79104beeab53d, 22 February 2026
Languages: R (25)
Size: 71 files, 25 scripts
Software Heritage: not archived
Found in: “Code availability”
Holds: README, license file, environment (DESCRIPTION), documentation
Not found: CITATION.cff, tests, continuous integration
Tools: tidyverse (19 files), brms (5 files), ggplot2 (5 files), emmeans (4 files), ggpubr (3 files), easystats (2 files), patchwork (2 files), psych (2 files)
Availability: 1 check, the latest on 28 September 2026: the link answers
  • 28 September 2026: the link answers
28 files
At the source: github.com/josefmana/pdosa

Code availability statement

The paper has a code availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

  • it points to the authors' code: josefmana/pdosa
  • it says that the code is available on request

Read it in the paper: doi.org/10.1038/s41531-026-01360-5.

Tracing map

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What the map holds:

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  • 25 scripts, each with its path and the digest of its content;
  • 12 matches between paragraphs of the paper and lines of the code (method lexical-v1);
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Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Data availability statement

The paper has a data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

  • it says that the data are available on request

Read it in the paper: doi.org/10.1038/s41531-026-01360-5.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 14 authors, 2 keywords, 4 funders, 103 references.

Cite

This paper

Burdová, K., Růžička, F., Mana, J., Filip, P., Nepožitek, J., Dostálová, S., Peřinová, P., Bezdicek, O., Gregorovič, P., Havlík, F., Růžička, E., Dušek, P., Šonka, K., & Jech, R. (2026). Hippocampal atrophy in untreated de novo Parkinson's disease with obstructive sleep apnea. NPJ Parkinson's disease, 12(1), 169. https://doi.org/10.1038/s41531-026-01360-5

BibTeX

@article{burdova2026hippocampal,
author = {Burdová, Kristína and Růžička, Filip and Mana, Josef and Filip, Pavel and Nepožitek, Jiří and Dostálová, Simona and Peřinová, Pavla and Bezdicek, Ondrej and Gregorovič, Petr and Havlík, Filip and Růžička, Evžen and Dušek, Petr and Šonka, Karel and Jech, Robert},
title = {{Hippocampal atrophy in untreated de novo Parkinson's disease with obstructive sleep apnea}},
journal = {NPJ Parkinson's disease},
year = {2026},
month = may,
volume = {12},
number = {1},
pages = {169},
publisher = {Nature Publishing Group},
issn = {2373-8057},
doi = {10.1038/s41531-026-01360-5},
url = {https://doi.org/10.1038/s41531-026-01360-5},
pmid = {42086584},
pmcid = {PMC13346879}
}

RIS

TY - JOUR
AU - Burdová, Kristína
AU - Růžička, Filip
AU - Mana, Josef
AU - Filip, Pavel
AU - Nepožitek, Jiří
AU - Dostálová, Simona
AU - Peřinová, Pavla
AU - Bezdicek, Ondrej
AU - Gregorovič, Petr
AU - Havlík, Filip
AU - Růžička, Evžen
AU - Dušek, Petr
AU - Šonka, Karel
AU - Jech, Robert
TI - Hippocampal atrophy in untreated de novo Parkinson's disease with obstructive sleep apnea
T2 - NPJ Parkinson's disease
J2 - NPJ Parkinsons Dis
PY - 2026
DA - 2026/05/05
VL - 12
IS - 1
SP - 169
SN - 2373-8057
PB - Nature Publishing Group
DO - 10.1038/s41531-026-01360-5
UR - https://doi.org/10.1038/s41531-026-01360-5
LA - en
ER -

CSL-JSON

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"id": "10.1038/s41531-026-01360-5",
"type": "article-journal",
"title": "Hippocampal atrophy in untreated de novo Parkinson's disease with obstructive sleep apnea",
"container-title": "NPJ Parkinson's disease",
"author": [
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"family": "Burdová",
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"date-parts": [
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}
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