P375 The mathematical approach for diagnosis early stage of Parkinson’s disease
Parkinson’s disease (PD) is a neurodegenerative disorder characterized by a different motor and non-motor signs. Since there is no diagnostic biological marker for Parkinson disease, the diagnosis is based on the results of clinical assessment. From that reason early cases of PD present a diagnostic...
Saved in:
Published in | Clinical neurophysiology Vol. 128; no. 9; pp. e299 - e300 |
---|---|
Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Elsevier B.V
01.09.2017
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | Parkinson’s disease (PD) is a neurodegenerative disorder characterized by a different motor and non-motor signs. Since there is no diagnostic biological marker for Parkinson disease, the diagnosis is based on the results of clinical assessment. From that reason early cases of PD present a diagnostic challenge.
We analyzed possibilityof diagnosis of Parkinson’s disease in an early stage, based on characteristics of the input-output curve. Input-output (IO) curve was analyzed in two ways: gain of the curve for low-level transcranial stimulation (110% of motor threshold-MT) and calculation M of the IO curve “quality“, based on the quantum Tsallis entropy E(q):
M=∑k=1Kp(xk)q=1-(q-1)E(q)
where K is the number of selected points of IO curve, xk are selected points of IO curve and p stands for probability.
Healthy subjects with MT<100μV, have significant gain for stimulation at the level of 110% of MT, which is not the case for the unhealthy subjects (100% cases). Healthy subjects with MT >100μV have gain in a limited interval (70% cases), while all unhealthy subjects have gain that is out of that interval. IO curve quality of the healthy subjects is in the limited interval, while 80% of the unhealthy subjects have quality outside of the interval.
A thorough understanding of the broad spectrum of clinical manifestations of PD is essential to the proper diagnosis of the disease. It seems that unhealthy subjects on the lower level of stimulation (110% of MT) have bigger increase of the MEP, which means that in the early stage of illness they have compromised inhibitive regulatory mechanisms. |
---|---|
AbstractList | Parkinson’s disease (PD) is a neurodegenerative disorder characterized by a different motor and non-motor signs. Since there is no diagnostic biological marker for Parkinson disease, the diagnosis is based on the results of clinical assessment. From that reason early cases of PD present a diagnostic challenge.
We analyzed possibilityof diagnosis of Parkinson’s disease in an early stage, based on characteristics of the input-output curve. Input-output (IO) curve was analyzed in two ways: gain of the curve for low-level transcranial stimulation (110% of motor threshold-MT) and calculation M of the IO curve “quality“, based on the quantum Tsallis entropy E(q):
M=∑k=1Kp(xk)q=1-(q-1)E(q)
where K is the number of selected points of IO curve, xk are selected points of IO curve and p stands for probability.
Healthy subjects with MT<100μV, have significant gain for stimulation at the level of 110% of MT, which is not the case for the unhealthy subjects (100% cases). Healthy subjects with MT >100μV have gain in a limited interval (70% cases), while all unhealthy subjects have gain that is out of that interval. IO curve quality of the healthy subjects is in the limited interval, while 80% of the unhealthy subjects have quality outside of the interval.
A thorough understanding of the broad spectrum of clinical manifestations of PD is essential to the proper diagnosis of the disease. It seems that unhealthy subjects on the lower level of stimulation (110% of MT) have bigger increase of the MEP, which means that in the early stage of illness they have compromised inhibitive regulatory mechanisms. |
Author | Janković, Marko Kačar, Aleksandra |
Author_xml | – sequence: 1 givenname: Aleksandra surname: Kačar fullname: Kačar, Aleksandra organization: Nuerology Clinic, Clinical Centre of Serbia, Belgrade, EMG and EP department, Belgrade, Serbia – sequence: 2 givenname: Marko surname: Janković fullname: Janković, Marko organization: Electrical Engineering ”Nikola Tesla”, Center for Control and Regulation, Belgrade, Serbia |
BookMark | eNqFkMtKw0AUhgdRsK2-gYt5gcS5JTMBEaR4g4IV6no4nZw006ZJmSlCd76Gr-eTmFBXbro55yz-7-fwjcl527VIyA1nKWc8v12nrvHtrk4F4zplOpVGnpERN1okpsjEeX9LYxKhMn1JxjGuGWOaKTEi73OpM7qokW5hX2M_vIOGwm4XOnA1rbpASw-rtos-UoTQHGjcwwppV9E5hI1vY9f-fH3HPhYRIl6RiwqaiNd_e0I-nh4X05dk9vb8On2YJY5nUia6BOVyKDiUulgCGuVMxZa5NopplIxxIyqucpWbTLtcKFm6pSwQZKlEKUBOiDr2utDFGLCyu-C3EA6WMztosWt71GIHLZZp22vpsfsjhv1vnx6Djc5j67D0Ad3elp0_VXD3r2AIDdY2eDiN_wIziIRt |
ContentType | Journal Article |
Copyright | 2017 |
Copyright_xml | – notice: 2017 |
DBID | AAYXX CITATION |
DOI | 10.1016/j.clinph.2017.07.383 |
DatabaseName | CrossRef |
DatabaseTitle | CrossRef |
DatabaseTitleList | |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Medicine |
EISSN | 1872-8952 |
EndPage | e300 |
ExternalDocumentID | 10_1016_j_clinph_2017_07_383 S1388245717308702 |
GroupedDBID | --- --K --M -~X .1- .55 .FO .GJ .~1 0R~ 1B1 1P~ 1RT 1~. 1~5 29B 4.4 457 4G. 53G 5GY 5RE 5VS 6J9 7-5 71M 8P~ AABNK AAEDT AAEDW AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AATTM AAXKI AAXLA AAXUO AAYWO ABBQC ABCQJ ABFNM ABFRF ABIVO ABJNI ABLJU ABMAC ABMZM ABTEW ABWVN ABXDB ACDAQ ACGFO ACIEU ACIUM ACRLP ACRPL ACVFH ADBBV ADCNI ADEZE ADMUD ADNMO ADVLN AEBSH AEFWE AEIPS AEKER AENEX AEUPX AEVXI AFJKZ AFPUW AFRHN AFTJW AFXIZ AGCQF AGHFR AGQPQ AGUBO AGWIK AGYEJ AI. AIEXJ AIGII AIIUN AIKHN AITUG AJRQY AJUYK AKBMS AKRWK AKYEP ALMA_UNASSIGNED_HOLDINGS AMRAJ ANKPU ANZVX APXCP ASPBG AVWKF AXJTR AZFZN BKOJK BLXMC BNPGV CS3 DU5 EBS EFJIC EFKBS EJD EO8 EO9 EP2 EP3 F5P FDB FEDTE FGOYB FIRID FNPLU FYGXN G-Q GBLVA HVGLF HX~ HZ~ IHE J1W K-O KOM L7B M41 MO0 MOBAO MVM N9A O-L O9- OAUVE OHT OP~ OZT P-8 P-9 P2P PC. Q38 R2- ROL RPZ SCC SDF SDG SDP SEL SES SEW SPCBC SSH SSN SSZ T5K UAP UNMZH UV1 VH1 X7M XOL XPP Z5R ZGI ~G- AACTN AADPK AAIAV ABLVK ABYKQ AFCTW AFKWA AFMIJ AHPSJ AJBFU AJOXV AMFUW EFLBG LCYCR RIG VQA ZA5 AAYXX AGRNS CITATION |
ID | FETCH-LOGICAL-c1533-7da4c6a91ad79bae84c8f0b678407e300182f14646857c6243dcb39ea3d42d2a3 |
IEDL.DBID | .~1 |
ISSN | 1388-2457 |
IngestDate | Tue Jul 01 02:54:41 EDT 2025 Fri Feb 23 02:12:23 EST 2024 Tue Aug 26 16:32:22 EDT 2025 |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 9 |
Keywords | Tsallis entropy PB IO curve |
Language | English |
License | https://www.elsevier.com/tdm/userlicense/1.0 |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c1533-7da4c6a91ad79bae84c8f0b678407e300182f14646857c6243dcb39ea3d42d2a3 |
ParticipantIDs | crossref_primary_10_1016_j_clinph_2017_07_383 elsevier_sciencedirect_doi_10_1016_j_clinph_2017_07_383 elsevier_clinicalkey_doi_10_1016_j_clinph_2017_07_383 |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | September 2017 2017-09-00 |
PublicationDateYYYYMMDD | 2017-09-01 |
PublicationDate_xml | – month: 09 year: 2017 text: September 2017 |
PublicationDecade | 2010 |
PublicationTitle | Clinical neurophysiology |
PublicationYear | 2017 |
Publisher | Elsevier B.V |
Publisher_xml | – name: Elsevier B.V |
SSID | ssj0007042 |
Score | 2.2159982 |
Snippet | Parkinson’s disease (PD) is a neurodegenerative disorder characterized by a different motor and non-motor signs. Since there is no diagnostic biological marker... |
SourceID | crossref elsevier |
SourceType | Index Database Publisher |
StartPage | e299 |
SubjectTerms | IO curve Tsallis entropy |
Title | P375 The mathematical approach for diagnosis early stage of Parkinson’s disease |
URI | https://www.clinicalkey.com/#!/content/1-s2.0-S1388245717308702 https://dx.doi.org/10.1016/j.clinph.2017.07.383 |
Volume | 128 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LS8NAEB5KBfEiPrE-yh68rk2ym2xyLMVSlRZFC70t2c1GKliL1qv4N_x7_hJn8qgKQsFjws4SZodvvjDfzAKcuojUX57k0vghlzb1eZKHjvuZkYHCjJAUFd3hKBqM5eUknDSgV_fCkKyywv4S0wu0rt50Km925tNp59YXyA5lSGVkD6OOcFhKRVF-9vYt81BecYEOLea0um6fKzRe1H04p5KEr2iEp4jF3-npR8rpb8FmxRVZt_ycbWi42Q6sD6tq-C7cXAsVMjxo9rgcvorr6zHhDPkoy0op3fSFORplzJAM3jv2lDNqdy46vz7fP15YVafZg3H__K434NUVCdwSUeMqS6WN0sRPM5WY1MXSxrlnMAPhj5oTdOVekCMYyigOlY0CKTJrROJSkckgC1KxD83Z08wdAMOzEdbLnTEWd7HSoOOMcEgBYyECZ1vAa8_oeTkJQ9cSsQddelKTJ7WnNHqyBWHtPl13eSIuaYTqFXZqafcrElZaHv7b8gg26KnUjh1Dc_H86k6QbCxMu4imNqx1L64Goy_OQdRN |
linkProvider | Elsevier |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1bS8MwFA5jA_VFvOK85sHXsLZJmvZxDEfnLihusLfQpKlMcBtuvvs3_Hv-Ek_adCgIA1_bnFC-HL7zlXMJQrcmtNVfHiNM-ZwwnfokzrkhfqZYICAixEVGdzgKkwm7n_JpDXWqXhhbVum4v-T0gq3dk5ZDs7WczVpPPgV1yLhNI3vgdcDDDTuditdRo93rJ6MNIQuvuEPHrifWoOqgK8q8bAPi0mYlfGGneNKI_h2hfkSd7gHad3IRt8svOkQ1Mz9CO0OXED9Gjw9UcAxnjV8381dhfTUpHIMkxVlZTTdbYWOnGWPQg88GL3JsO56L5q-vj88VdqmaEzTp3o07CXG3JBBttRoRWcp0mMZ-molYpSZiOso9BUEI_tUMtbfuBTnwIQsjLnQYMJppRWOT0owFWZDSU1SfL-bmDGE4Hqq93CilYRfNFACnqAEVGFEaGN1EpEJGLsthGLKqEnuRJZLSIik9IQHJJuIVfLJq9ARqksDWW-zExu6XM2y1PP-35Q3aTcbDgRz0Rv0LtGfflKVkl6i-fns3V6A91ura-dY3IebW_g |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=P375+The+mathematical+approach+for+diagnosis+early+stage+of+Parkinson%E2%80%99s+disease&rft.jtitle=Clinical+neurophysiology&rft.au=Ka%C4%8Dar%2C+Aleksandra&rft.au=Jankovi%C4%87%2C+Marko&rft.date=2017-09-01&rft.pub=Elsevier+B.V&rft.issn=1388-2457&rft.eissn=1872-8952&rft.volume=128&rft.issue=9&rft.spage=e299&rft.epage=e300&rft_id=info:doi/10.1016%2Fj.clinph.2017.07.383&rft.externalDocID=S1388245717308702 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1388-2457&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1388-2457&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1388-2457&client=summon |