Predviđanje stupnja oporavka nakon moždanog udara

master's thesis

• Title (english): Predicting the degree of recovery after stroke
• Author: Marina Čavka
• Mentor: Branko Malojčić (mentor)
• Committee member: Zdravka Poljaković-Skurić (predsjednik povjerenstva)
• Committee member: Mario Habek (član povjerenstva)
• Committee member: Branko Malojčić (član povjerenstva)
• Granter: University of Zagreb; School of Medicine; (Department of Neurology); Zagreb
• Defense date and country: 2022-07-15, Croatia
• Scientific / art field, discipline and subdiscipline: BIOMEDICINE AND HEALTHCARE; Clinical Medical Sciences; Neurology

Abstract

MU je heterogena bolest čiji čimbenici rizika i liječenje ovise o specifičnim etiopatogenetskim mehanizmima. Vodeći je uzrok kratkotrajnog funkcionalnog oštećenja u odraslih koji može dovesti do značajnog dugotrajnog invaliditeta u nedostatku odgovarajućeg liječenja i rehabilitacije. Oporavak od MU je složen proces s obrascima koji se razlikuju među skupinama bolesnika. Ključni izazov u rehabilitaciji i istraživanju novih intervencija nakon MU upravo je varijabilnost stupnja oporavka među klinički sličnim bolesnicima koja otežava procjenu učinka određene rehabilitacijske metode na oporavak. U podlozi procesa oporavka je neuroplastičnost koja čini osnovu spontanog biološkog oporavka i mehanizama oporavka ovisnih o učenju. Bolje razumijevanje ovih mehanizama moglo bi pomoći u predviđanju potencijala oporavka i planiranju personalizirane rehabilitacije. Kako bi se što preciznije predvidio oporavak od MU, na individualnoj razini, razvijaju se modeli predviđanja za različite funkcionalne domene. Modeli uključuju kliničke mjere i biomarkere oštećenja odnosno potencijala oporavka živčanog sustava. U biomarkere spadaju biološke, fiziološke i radiološke mjere koje bi trebale poboljšati točnost predviđanja oporavka utemeljenog na kliničkim mjerama. Alati za predviđanje trebali bi kombinirati manji broj informacija na sustavan i lako pamtljiv način kako bi se lakše implementirali u kliničku praksu. Informiranje bolesnika i njihovih obitelji o očekivanom potencijalu oporavka, kao i mogućem lošem zdravstvenom ishodu, omogućuje bolju prilagodbu novoj životnoj situaciji i planiranje budućnosti.

Abstract (english)

Stroke is a heterogeneous disease with risk factors and treatment that depend on the specific etiopathogenetic mechanisms. Stroke is the leading cause of short-term functional impairment in adults, which can lead to significant long-term disability in the absence of adequate treatment and rehabilitation. Recovery from stroke is a complex process with patterns that differ among patient groups. A key challenge in post-stroke rehabilitation and research of new interventions is precisely the variability of the degree of recovery among clinically similar patients, which makes it difficult to assess the effect of a particular rehabilitation method on recovery. Underlying the recovery process is neuroplasticity which forms the basis of spontaneous biological recovery and learning-dependent recovery mechanisms. A better understanding of these mechanisms could help predict recovery potential and plan personalized rehabilitation. To predict stroke recovery as accurately as possible, at the individual level, prediction models across different functional domains are being developed. The models include clinical measures and biomarkers of damage or recovery potential of the nervous system. Biomarkers, which include biological, physiological, and radiological measures, should improve the accuracy of recovery predictions based on clinical measures. Prediction tools should combine a small amount of information in a systematic and easy-to-remember way for easier implementation in clinical practice. Informing patients and their families about the expected recovery potential, as well as possible poor health outcomes, enables better adaptation to a new life situation and future planning.

• Keywords: moždani udar; neuroplastičnost; neurorehabilitacija; oporavak; predviđanje
• Keywords (english): stroke; neuroplasticity; neurorehabilitation; recovery; prediction
• Language: croatian
• URN:NBN: urn:nbn:hr:105:662952
• Study programme: Title: Medicine; Study programme type: university; Study level: integrated undergraduate and graduate; Academic / professional title: doktor/doktorica medicine (doktor/doktorica medicine)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2023-01-05 07:57:13