Predictive potential of platelet mass index for 30-day mortality in acute ischemic stroke

İzzet Ustaalioğlu

Article Details

Predictive potential of platelet mass index for 30-day mortality in acute ischemic stroke

Authors:

İzzet Ustaalioğlu

Publisher:

Gumushane University

Main Topics:

Acil Tıp

Journal:

Gümüşhane Üniversitesi Sağlık Bilimleri Dergisi Vol.14 Issue 1, pp.25-31

Document Type:

Article

Publication Date:

3/2025

Document Language:

English

Document ID (Org No.):

2001342977

pISSN:

2146-9954

Keywords:

Abstract:

 Acute ischemic stroke AIS is a leading cause of morbidity and mortality worldwide, with early mortality risk prediction essential for guiding treatment decisions. Platelet Mass Index PMI, a composite measure derived from platelet count and mean platelet volume MPV, has shown promise as a biomarker in cardiovascular conditions. This study aimed to assess the predictive value of PMI for 30-day mortality in AIS patients. This retrospective cohort study included patients diagnosed with AIS who presented to the emergency department of a tertiary hospital between January 1, 2019, and January 1, 2024. The primary outcome was 30-day mortality. To determine the optimal PMI cutoff for predicting mortality, we calculated sensitivity, specificity, and likelihood ratios and the area under the curve AUC was obtained for overall diagnostic accuracy. A total of 117 AIS patients were analyzed, with a mean age of 68,214,6 years, and 58,1 were female. The 30-day mortality rate was 27,4, with deceased patients being significantly older than survivors. PMI values were notably lower in deceased patients, and the ROC analysis yielded an AUC of 0,775. The optimal PMI cutoff provided a sensitivity of 71,8 and a specificity of 75, with higher values associated with decreased survival. PMI may serve as a valuable prognostic tool for predicting 30-day mortality in AIS patients. These findings support the potential utility of PMI in early risk stratification, though further prospective studies are needed to validate its use in diverse clinical settings.

 Acute ischemic stroke AIS is a leading cause of morbidity and mortality worldwide, with early mortality risk prediction essential for guiding treatment decisions. Platelet Mass Index PMI, a composite measure derived from platelet count and mean platelet volume MPV, has shown promise as a biomarker in cardiovascular conditions. This study aimed to assess the predictive value of PMI for 30-day mortality in AIS patients. This retrospective cohort study included patients diagnosed with AIS who presented to the emergency department of a tertiary hospital between January 1, 2019, and January 1, 2024. The primary outcome was 30-day mortality. To determine the optimal PMI cutoff for predicting mortality, we calculated sensitivity, specificity, and likelihood ratios and the area under the curve AUC was obtained for overall diagnostic accuracy. A total of 117 AIS patients were analyzed, with a mean age of 68,214,6 years, and 58,1 were female. The 30-day mortality rate was 27,4, with deceased patients being significantly older than survivors. PMI values were notably lower in deceased patients, and the ROC analysis yielded an AUC of 0,775. The optimal PMI cutoff provided a sensitivity of 71,8 and a specificity of 75, with higher values associated with decreased survival. PMI may serve as a valuable prognostic tool for predicting 30-day mortality in AIS patients. These findings support the potential utility of PMI in early risk stratification, though further prospective studies are needed to validate its use in diverse clinical settings.

 Acute ischemic stroke AIS is a leading cause of morbidity and mortality worldwide, with early mortality risk prediction essential for guiding treatment decisions. Platelet Mass Index PMI, a composite measure derived from platelet count and mean platelet volume MPV, has shown promise as a biomarker in cardiovascular conditions. This study aimed to assess the predictive value of PMI for 30-day mortality in AIS patients. This retrospective cohort study included patients diagnosed with AIS who presented to the emergency department of a tertiary hospital between January 1, 2019, and January 1, 2024. The primary outcome was 30-day mortality. To determine the optimal PMI cutoff for predicting mortality, we calculated sensitivity, specificity, and likelihood ratios and the area under the curve AUC was obtained for overall diagnostic accuracy. A total of 117 AIS patients were analyzed, with a mean age of 68,214,6 years, and 58,1 were female. The 30-day mortality rate was 27,4, with deceased patients being significantly older than survivors. PMI values were notably lower in deceased patients, and the ROC analysis yielded an AUC of 0,775. The optimal PMI cutoff provided a sensitivity of 71,8 and a specificity of 75, with higher values associated with decreased survival. PMI may serve as a valuable prognostic tool for predicting 30-day mortality in AIS patients. These findings support the potential utility of PMI in early risk stratification, though further prospective studies are needed to validate its use in diverse clinical settings.

 Akut iskemik inme Aİİ, dünya çapında morbidite ve mortalitenin önde gelen nedenlerinden biri olup, erken mortalite risk tahmini tedavi kararlarını yönlendirmek için önemlidir. Platelet Mass İndeksi PMİ, platelet sayısı ve mean platelet volume MPV kullanılarak hesaplanan bileşik bir ölçüdür ve kardiyovasküler hastalıklar gibi durumlarda biyomarker olarak umut verici sonuçlar göstermiştir. Bu çalışma, Aİİ hastalarında PMİnin 30 günlük mortaliteyi öngörücü değerini değerlendirmeyi amaçlamıştır. Bu retrospektif kohort çalışmasına, 1 Ocak 2019 ile 1 Ocak 2024 tarihleri arasında bir üçüncü basamak hastanenin acil servisine başvuran Aİİ tanısı almış hastalar dahil edilmiştir. Birincil sonlanım noktası 30 günlük mortalite olarak belirlendi. Mortalitenin tahmin edilmesinde optimal PMİ kesiş noktasını belirlemek için duyarlılık, özgüllük ve olasılık oranları hesaplanmış ve genel tanısal doğruluğun ölçülmesi için eğri altındaki alan hesaplanmıştır. Toplamda 117 Aİİ hastası analiz edilmiştir, ortalama yaş 68,214,6 yıl olup, hastaların 58,1i kadındı. 30 günlük mortalite oranı 27,4 olup, ölen hastalar hayatta kalanlardan belirgin şekilde yüksek yaştaydı. Ölen hastalarda PKİ değerleri anlamlı şekilde düşüktü ve EAA 0,775 olarak bulunmuştur. Optimal PMİ kesiş noktası, 71,8 duyarlılık ve 75 özgüllük sağlamakta olup, yüksek değerlerin daha düşük sağkalımla ilişkilendirildiği görülmüştür. PMİ, Aİİ hastalarında 30 günlük mortaliteyi öngörebilecek değerli bir prognostik araç olabilir. Bu bulgular, PKİnin erken risk sınıflandırmasındaki potansiyel faydasını desteklemekte olup, farklı klinik ortamlarda kullanımının doğrulanması için ileriye dönük çalışmalar gerekmektedir.

Article Details

Predictive potential of platelet mass index for 30-day mortality in acute ischemic stroke

Authors:

İzzet Ustaalioğlu

Publisher:

Gumushane University

Main Topics:

Acil Tıp

Journal:

Gümüşhane Üniversitesi Sağlık Bilimleri Dergisi Vol.14 Issue 1, pp.25-31

Document Type:

Article

Publication Date:

3/2025

Document Language:

English

Document ID (Org No.):

2001342977

pISSN:

2146-9954

Acute ischemic stroke

Mortality

Platelet mass indexAkut iskemik inme

Mortalite

Platelet kütlesi indeksi

Issues

Article Details

Predictive potential of platelet mass index for 30-day mortality in acute ischemic stroke

Authors: İzzet Ustaalioğlu

Publisher: Gumushane University

Main Topics: Acil Tıp

Journal: Gümüşhane Üniversitesi Sağlık Bilimleri Dergisi Vol.14 Issue 1, pp.25-31

Document Type: Article

Publication Date: 3/2025

Document Language: English

Document ID (Org No.): 2001342977

pISSN: 2146-9954

Acute ischemic stroke

Mortality

Platelet mass indexAkut iskemik inme

Mortalite

Platelet kütlesi indeksi

Issues

Authors:

İzzet Ustaalioğlu

Publisher:

Gumushane University

Main Topics:

Acil Tıp

Journal:

Gümüşhane Üniversitesi Sağlık Bilimleri Dergisi Vol.14 Issue 1, pp.25-31

Document Type:

Article

Publication Date:

3/2025

Document Language:

English

Document ID (Org No.):

2001342977

pISSN:

2146-9954