Stroke Mortality [Neurosurgery Wiki]

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====== Stroke Mortality ======

{{rss>https://pubmed.ncbi.nlm.nih.gov/rss/search/1z92IKUEytg0p0qV_H3svbT0NwY9TSD4LAaXQVUwZJZwAGYg7d/?limit=15&utm_campaign=pubmed-2&fc=20250619021415}}

[[Stroke]] [[mortality]] refers to the [[incidence]] of [[death]] directly attributable to a [[stroke]], including both [[ischemic stroke]] and [[hemorrhagic stroke]] subtypes. 

It is typically measured as:

A proportion of deaths within a given [[population]] or [[cohort]],

Or as a rate per 100,000 persons per year in epidemiological studies.

🩺 In Clinical and Epidemiological Contexts

Stroke mortality reflects both stroke incidence and case fatality.

It is influenced by:

Age and comorbidities

Stroke type and severity

Access to acute care/intervention

Post-stroke complications

Preventive strategies (e.g., anticoagulation, antihypertensives)

🔍 Measurement in Studies

May be reported as:

Crude mortality rate

Standardized mortality ratio (SMR)

Hazard ratio (HR) for death

In registry-based studies (e.g., SEER), stroke mortality is often derived from death certificate data, which can be imprecise.

⚠️ Limitations

Stroke mortality data can be misclassified, especially in patients with multiple comorbidities (e.g., cancer), where the true cause of death is uncertain or multifactorial.
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In a retrospective [[cohort study]] published in the [[Journal of Clinical Neuroscience]], Ahmed et al. 
((Ahmed YB, Nan Feng AS, Alrawashdeh M, Ellaithy A, Khanduja S, AlBarakat MM, Alshwayyat S, Uchino K, Gusdon AM, Cho SM. Temporal [[trend]]s and [[risk factor]]s associated with [[stroke mortality]] among [[cancer]] [[patient]]s. J Clin Neurosci. 2025 Jun;136:111249. doi: 10.1016/j.jocn.2025.111249. Epub 2025 Apr 18. Erratum in: J Clin Neurosci. 2025 Jun 17:111381. doi: 10.1016/j.jocn.2025.111381. PMID: 40252475.)) 
analyzed [[data]] from over 5.9 million patients diagnosed with a first primary cancer, based on the [[SEER]] [[database]] (2000–2020). The study aimed to quantify the [[risk]] of stroke-related [[death]] (SD) in cancer patients and to identify temporal trends and associated clinical and demographic risk factors.
Stroke-related mortality (SD) among cancer patients has significantly declined over the past two decades across all cancer types and both sexes. However, older [[age]], non-white race, [[male]] sex, and specific cancer types—notably nervous system, respiratory, and head and neck cancers—are associated with a higher risk of stroke [[death]]. Conversely, patients receiving [[chemotherapy]] or [[radiotherapy]] had a lower risk of SD compared to those who received no treatment.
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⚠️ Fatal Methodological Flaws

No Clinical [[Stroke Classification]]

The [[author]]s report on "[[stroke mortality]]" without differentiating ischemic vs. [[hemorrhagic stroke]]s, nor providing [[stroke etiology]] or timing relative to [[cancer diagnosis]] or [[cancer treatment]]—rendering any mechanistic or preventative inference purely [[speculative]].

Reliance on Registry Data Without Validation

The study is built on SEER registry death certificates. These are known to be notoriously unreliable in classifying cause of death in complex patients, particularly in cancer, where the line between terminal illness and stroke is often blurred or misclassified.

Missing Core Clinical Variables

Absolutely no data on cardiovascular comorbidities (e.g., hypertension, atrial fibrillation), medications (e.g., anticoagulants, steroids), or functional status. Without these, attributing causality or understanding modifiable risks is scientifically irresponsible.

“No Treatment” Category is a Black Box

The study repeatedly highlights increased stroke mortality in patients receiving "no treatment", but never interrogates why. Were they terminal? Frail? Untreated by choice? Refusing care? Without this, comparisons to treated groups are invalid.

Statistical Smoke Without Clinical Fire

The use of large numbers and Annual Percentage Change/SMR modeling creates an illusion of depth. But in the absence of clinical granularity, the findings are epidemiologically flashy and clinically empty.

Cancer Type Associations Are Tautological

Finding increased SD risk in patients with nervous system tumors is hardly surprising, given the direct anatomical involvement. Presenting this as a novel association lacks critical insight and borders on [[disingenuous]].

Temporal Trends Mask Structural Changes

Declines in stroke mortality are presented as a success story—but the study fails to account for changes in diagnostic criteria, coding practices, cancer treatments, and palliative care protocols over 20 years. These are not stable baselines.

🧊 Conclusion: Big Data, Small Insight

This [[paper]] is a perfect [[example]] of [[data-driven illusion]]: a [[study]] that rides the wave of big epidemiological numbers without offering a single actionable or mechanistically sound [[conclusion]]. It identifies “[[association]]s” that are either already known, clinically [[irrelevant]], or artefacts of poor [[data]]. The supposed protective effect of [[chemotherapy]]/[[radiotherapy]] is unadjusted for [[prognosis]], [[functional status]], or therapeutic intent—rendering the headline finding [[misleading]] at best.

⚠️ If the purpose of [[research]] is to inform [[practice]], this study falls spectacularly short. It tells us what we already suspect, adds [[confusion]] where [[clarity]] is needed, and fails to bridge [[data]] with clinical [[reality]].