Table Info

Table 8.

Multivariable regression analysis for the prediction of cognitive impairment

Variable	Coefficient	SE	t	p value
Age (years)	0.005	0.005	0.985	0.328
Sex	–0.183	0.141	–1.296	0.199
Residence	0.018	0.14	0.13	0.897
Education	–0.179	0.125	–1.428	0.157
Smoking	–0.1	0.119	–0.836	0.406
Hypertension	0.056	0.129	0.432	0.667
Diabetes mellitus	–0.381	0.177	–2.156	0.034^*
Dyslipidaemia	–0.113	0.14	–0.811	0.42
IHD	0.451	0.235	1.921	0.059
Atrial fibrillation	–0.123	0.181	–0.679	0.499
Arrhythmia	0.213	0.266	0.798	0.427
Duration of illness (years)	0.024	0.01	2.344	0.022^*
Hb (g/dL)	0.075	0.062	1.217	0.228
Platelets (× 10⁹/L)	0	0.002	–0.172	0.864
WBCs (× 10⁹/L)	–0.052	0.05	–1.039	0.303
FBS (mg/dL)	0	0.003	–0.158	0.875
HbA1C (%)	0.098	0.135	0.726	0.47
Serum creatinine (mg/dL)	–0.217	0.313	–0.692	0.492
Urea (mg/dL)	–0.019	0.005	–3.698	< 0.001^*
ALT (U/L)	0.005	0.005	1.117	0.268
AST (U/L)	0.004	0.005	0.714	0.478
TSH (mIU/L)	0.046	0.116	0.4	0.691
Free T4 (ng/dL)	0.806	0.644	1.251	0.215
Free T3 (ng/dL)	0.325	0.272	1.193	0.237
Total cholesterol (mg/dL)	0	0.002	–0.008	0.993
Triglycerides (mg/dL)	–0.003	0.003	–0.911	0.365
HDL (mg/dL)	0.001	0.012	0.119	0.905
LDL (mg/dL)	0.012	0.005	2.168	0.033
Hoehn and Yahr (H-Y)	0.271	0.029	9.313	< 0.001^*
UPDRS-III	0.003	0.001	3.478	0.001^*
BDI	0.006	0.002	2.858	0.006^*
SDMT	–0.012	0.003	–3.33	0.001^*
BVMT-R	–0.016	0.008	–2.073	0.042^*
CVLT-II	–0.006	0.003	–2.48	0.015^*
CVLT-II delayed recall	–0.025	0.012	–2.13	0.036^*
MoCA score	–0.018	0.006	–3.056	0.003^*
HAM-A	0.006	0.003	2.048	0.044^*

^* Data is significant, p value < 0.05. SE: Standard Error; IBD: Ischemic heart disease; Hb: hemoglobin; WBCs: white blood cells; FBS: fasting blood glucose; HbA1C: hemoglobin A1c; ALT: alanine aminotransferase; AST: aspartate aminotransferase; TSH: thyroid-stimulating hormone; HDL: high-density lipoprotein; LDL: low-density lipoprotein; UPDRS-III: Unified Parkinson’s Disease Rating Scale, Part III; BDI: Beck Depression Inventory; SDMT: Symbol Digit Modalities Test; BVMT-R: Brief Visuospatial Memory Test-Revised; CVLT-II: California Verbal Learning Test-II; MoCA: Montreal Cognitive Assessment; HAM-A: Hamilton Anxiety Rating Scale

Declarations

Author contributions

AAG: Conceptualization, Investigation, Writing—original draft, Writing—review & editing. NHE: Investigation, Writing—review & editing. AES: Validation, Writing—review & editing, Supervision. AE: Validation, Writing—review & editing, Supervision. All authors read and approved the submitted version.

Conflicts of interest

The authors declare that they have no conflicts of interest regarding the publication of this article.

Ethical approval

This study was approved by the Institutional Review Board (IRB) of the Faculty of Medicine, Al-Azhar University, Cairo, Egypt (Approval number: Near-Med._78 Predictors Of Cognitive Impairment In Egyptian Patients With Parkinson’s Disease._000078), and was conducted in accordance with the Declaration of Helsinki.

Consent to participate

Informed consent to participate in the study was obtained from all participants.

Consent to publication

Informed consent to publication was obtained from relevant participants.

Availability of data and materials

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

Funding

Not applicable.

Copyright

Publisher’s note

Open Exploration maintains a neutral stance on jurisdictional claims in published institutional affiliations and maps. All opinions expressed in this article are the personal views of the author(s) and do not represent the stance of the editorial team or the publisher.

References

Olanow CW, Tatton WG. Etiology and pathogenesis of Parkinson’s disease. Annual Review of Neuroscience. 1999;22:123–44. [DOI]

Leite Silva ABR, Gonçalves de Oliveira RW, Diógenes GP, de Castro Aguiar MF, Sallem CC, Lima MPP, et al. Premotor, nonmotor and motor symptoms of Parkinson’s Disease: A new clinical state of the art. Ageing Res Rev. 2023;84:101834. [DOI] [PubMed]

Bernal-Pacheco O, Limotai N, Go CL, Fernandez HH. Nonmotor Manifestations in Parkinson Disease. Neurologist. 2012;18:1–16. [DOI] [PubMed]

Marino BLB, de Souza LR, Sousa KPA, Ferreira JV, Padilha EC, da Silva CHTP, et al. Parkinson’s Disease: A Review from Pathophysiology to Treatment. Mini Rev Med Chem. 2020;20:754–67. [DOI] [PubMed]

McGregor MM, Nelson AB. Circuit Mechanisms of Parkinson’s Disease. Neuron. 2019;101:1042–56. [DOI] [PubMed]

Meireles J, Massano J. Cognitive impairment and dementia in Parkinson’s disease: clinical features, diagnosis, and management. Front Neurol. 2012;3:88. [DOI] [PubMed] [PMC]

Hely MA, Reid WG, Adena MA, Halliday GM, Morris JG. The Sydney multicenter study of Parkinson’s disease: the inevitability of dementia at 20 years. Mov Disord. 2008;23:837–44. [DOI] [PubMed]

Emre M, Aarsland D, Albanese A, Byrne EJ, Deuschl G, De Deyn PP, et al. Rivastigmine for Dementia Associated with Parkinson’s Disease. N Engl J Med. 2004;351:2509–18. [DOI] [PubMed]

Locascio JJ, Corkin S, Growdon JH. Relation between clinical characteristics of Parkinson’s disease and cognitive decline. J Clin Exp Neuropsychol. 2003;25:94–109. [DOI] [PubMed]

10.

Ibarretxe-Bilbao N, Junque C, Marti MJ, Tolosa E. Brain structural MRI correlates of cognitive dysfunctions in Parkinson’s disease. J Neurol Sci. 2011;310:70–4. [DOI] [PubMed]

11.

McKinlay A, Grace RC. Characteristic of cognitive decline in Parkinson’s disease: a 1-year follow-up. Appl Neuropsychol. 2011;18:269–77. [DOI] [PubMed]

12.

Pagonabarraga J, Kulisevsky J. Cognitive impairment and dementia in Parkinson’s disease. Neurobiol Dis. 2012;46:590–6. [DOI] [PubMed]

13.

Shi M, Huber BR, Zhang J. Biomarkers for cognitive impairment in Parkinson disease. Brain Pathol. 2010;20:660–71. [DOI] [PubMed] [PMC]

14.

Hou Y, Shang H. Magnetic Resonance Imaging Markers for Cognitive Impairment in Parkinson’s Disease: Current View. Front Aging Neurosci. 2022;14:788846. [DOI] [PubMed] [PMC]

15.

Kalia LV. Biomarkers for cognitive dysfunction in Parkinson’s disease. Parkinsonism Relat Disord. 2018;46:S19–23. [DOI] [PubMed]

16.

Chen J, Zhao D, Wang Q, Chen J, Bai C, Li Y, et al. Predictors of cognitive impairment in newly diagnosed Parkinson’s disease with normal cognition at baseline: A 5-year cohort study. Front Aging Neurosci. 2023;15:1142558. [DOI] [PubMed] [PMC]

17.

Kim HM, Nazor C, Zabetian CP, Quinn JF, Chung KA, Hiller AL, et al. Prediction of cognitive progression in Parkinson’s disease using three cognitive screening measures. Clin Park Relat Disord. 2019;1:91–7. [DOI] [PubMed] [PMC]

18.

Aarsland D, Andersen K, Larsen JP, Lolk A, Nielsen H, Kragh-Sørensen P. Risk of dementia in Parkinson’s disease: a community-based, prospective study. Neurology. 2001;56:730–6. [DOI] [PubMed]

19.

Mohammadi R, Ng SYE, Tan JY, Ng ASL, Deng X, Choi X, et al. Machine Learning for Early Detection of Cognitive Decline in Parkinson’s Disease Using Multimodal Biomarker and Clinical Data. Biomedicines. 2024;12:2758. [DOI] [PubMed] [PMC]

20.

Almgren H, Camacho M, Hanganu A, Kibreab M, Camicioli R, Ismail Z, et al. Machine learning-based prediction of longitudinal cognitive decline in early Parkinson’s disease using multimodal features. Sci Rep. 2023;13:13193. [DOI] [PubMed] [PMC]

21.

Dennis AP, Strafella AP. The identification of cognitive impairment in Parkinson’s disease using biofluids, neuroimaging, and artificial intelligence. Front Neurosci. 2024;18:1446878. [DOI] [PubMed] [PMC]

22.

World Medical Association. World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA. 2013;310:2191–4. [DOI] [PubMed]

23.

IBM SPSS Statistics. Version 28.0. NY: IBM Corp.; 2021.

24.

Helmy A, Hamid E, Salama M, Gaber A, El-Belkimy M, Shalash A. Baseline predictors of progression of Parkinson’s disease in a sample of Egyptian patients: clinical and biochemical. Egypt J Neurol Psychiatr Neurosurg. 2022;58:9. [DOI] [PubMed] [PMC]

25.

Badr MY, Amer RA, Kotait MA, Shoeib SM, Reda AM. Role of multimodal advanced biomarkers as potential predictors of cognitive and psychiatric aspects of Parkinson’s disease. Egypt J Neurol Psychiatry Neurosurg. 2023;59:58. [DOI]

26.

Shalash AS, Hamid E, Elrassas HH, Bedair AS, Abushouk AI, Khamis M, et al. Non-Motor Symptoms as Predictors of Quality of Life in Egyptian Patients With Parkinson’s Disease: A Cross-Sectional Study Using a Culturally Adapted 39-Item Parkinson’s Disease Questionnaire. Front Neurol. 2018;9:357. [DOI] [PubMed] [PMC]

27.

Ahmed H, Abushouk AI, Gabr M, Negida A, Abdel-Daim MM. Parkinson’s disease and pesticides: A meta-analysis of disease connection and genetic alterations. Biomed Pharmacother. 2017;90:638–49. [DOI] [PubMed]

28.

Martínez-Horta S, Bejr-Kasem H, Horta-Barba A, Pascual-Sedano B, Santos-García D, de Deus-Fonticoba T, et al.; COPPADIS Study Group. Identifying comorbidities and lifestyle factors contributing to the cognitive profile of early Parkinson’s disease. BMC Neurol. 2021;21:477. [DOI] [PubMed] [PMC]

29.

Burton EJ, McKeith IG, Burn DJ, Williams ED, O’Brien JT. Cerebral atrophy in Parkinson’s disease with and without dementia: a comparison with Alzheimer’s disease, dementia with Lewy bodies and controls. Brain. 2004;127:791–800. [DOI] [PubMed]