Prognostic Biomarkers for Delayed Cerebral Ischemia Post-Aneurysmal Subarachnoid Hemorrhage: Evaluating CSF 8-iso-Prostaglandin F2α and Erythrocyte Anisocytosis

doi:10.21203/rs.3.rs-3899387/v1

Background

Delayed cerebral ischemia (DCI) is a serious, life-threatening, complication affecting patients who have survived the initial bleeding from a ruptured intracranial aneurysm. Due to the challenging diagnosis, potential DCI prognostic markers should be of value in clinical practice. According to recent reports isoprostanes and red blood cell distribution (RDW) showed to be promising in this respect.

Methods

We conducted a prospective study with a control group (n=8), recruiting aSAH patients (n=27), who underwent surgery within the first day of the initial bleeding. We collected data regarding clinical status and results of biochemical, and radiological examinations. We measured cerebrospinal fluid (CSF) concentration of 8-iso-prostaglandin F2α (F2-IsoP) and RDW on day 1, 3, and 5.

Results

Both CSF F2-IsoP level and RDW measured on day 1 were significant predictors of DCI. The receiver operating characteristics curve for DCI prediction based on the multivariate model yielded an area under the curve (AUC) of 0.924 (95%CI: 0.824-0.1, p<0.01).

Conclusions

In our study, the model based on the combination of RDW and the level of isoprostanes in CSF on the first day after the initial bleeding showed a prognostic value for DCI prediction. Further studies are required to validate this observation.

Biological sciences/Neuroscience/Neuro vascular interactions

Health sciences/Biomarkers

Health sciences/Neurology

Aneurysmal subarachnoid haemorrhage (aSAH) is a serious, life-threatening medical condition. Roughly 10% of patients with aSAH die before receiving medical assistance and nearly 40% of them do not survive the first 30 days of hospitalization [1, 2]. Furthermore, one-third of the patients experience severe complications that can result in functional impairment [3]. One of the adverse events present in 20–30% of the SAH patients is delayed cerebral ischemia (DCI) [4, 5]. The diagnosis of DCI is based on clinical evaluation, radiological imaging and laboratory tests. DCI is defined as the occurrence of new neurological deficit (e.g., apraxia, aphasia, hemi-inattention, hemiparesis) and/or deterioration in level of consciousness shown as a drop in Glasgow Coma Scale (GCS) of 2 or more points. These symptoms must last for at least one hour and should not occur following the exclusion of aneurysm from circulation. The diagnosis of DCI is only possible after ruling out other potential causes of the deterioration, such as hypotension, electrolyte imbalance, infection or re-bleeding [6, 7, 8]. Although the specific pathomechanism of DCI remains unclear, many authors emphasize that its cause is complex and comprises microcirculatory disturbances, microthrombosis, inflammation, blood-barrier disruption, electrolyte imbalances and cerebral autoregulation disorders. According to one of the most likely theories, metabolic changes associated with extravasated blood lead to an inflammation in the arterial walls and oxidative stress (OS) [9, 10, 11]. OS is a condition marked by increased levels of toxic oxygen species (TOS), reactive oxygen species (ROS) and endogenous antioxidants. The elevated concentration of ROS, leads to predominance of oxidation reaction and finally, to disruption of redox signalling (RS) [12]. RS regulates “redox switches” which are diverse mechanisms which influence endothelium and vasoconstriction [13–18]. As a result, there are local perfusion disruptions which may be responsible for clinical picture of DCI. Since ROS levels has been associated with F2-isorpostanes (F2-IsoPs), the both have been postulated as oxidative stress markers. Another factor that has been associated with inflammation and thus with OS, confirmed in various diseases, is red blood cell anisocytosis [19, 20, 21]. Defined as heterogeneity in shape and volume of erythrocytes, anisocytosis can be presented as red cell distribution width (RDW) which is the result of a mathematical equation calculated based on the mean corpuscular value (MCV). RDW can be expressed as a standard deviation (RDW-SD) or as a coefficient of variation (RDW-CV) [22]. Analysis conducted in 2022, showed that SAH patients with poor outcome, had had significantly greater RDW-CV on admission (13.9% vs 12.8%, p = 0.016) [23].

In the current paper, we decided to look at erythrocyte anisocytosis and cerebrospinal-fluid (CSF) concentration of F2-IsoPs in aSAH patients. Bearing in mind the relevance of anisocytosis and F2-IsoPs in inflammation and oxidative stress, we assumed that they might serve as predictors of DCI.

Ethical statement

The local Ethical Committee of Medical University of Lodz gave positive opinion on the research protocol (number RNN/280/13/KE). Written informed consents were acquired from patients prior to enrolment. The study was performed in accordance to Good Clinical Practice and the Declaration of Helsinki.

Patients

We performed a prospective analysis of 27 consecutive aSAH patients. The patients were operated on for a ruptured cerebral aneurysm within 24 hours after the bleeding between May 2013 and January 2018. The patient information were collected as a part of an ongoing prospective database of clinical, biochemical, and radiological data from patients with confirmed aSAH. Moreover, we included a control group consisting of 8 volunteers (4 (50%) females). The inclusion and exclusion criteria for both groups are collected in Figure 1.

Clinical assessment

After patient inclusion routine radiological (chest x-ray, resting electrocardiogram) and laboratory test were performed. In each case the amount of subarachnoid blood was confirmed on computed tomography (CT) according to Modified Fisher scale (mFisher) scale. Computed tomography angiography (CTA) or digital subtraction angiography (DSA) were performed to confirm the presence of the aneurysm. The patients’ clinical state was assessed according to the Hunt and Hess scale. A decision about the treatment strategy (microsurgery and endovascular intervention) was made by a multidisciplinary team. In each case we performed, routine, neuroimaging examination at 12h after aneurysm surgery.

When clinical deterioration was observed the suspicion of DCI was taken into account. DCI was diagnosed in every case of otherwise unexplainable new symptoms of confusion or drop in the level of consciousness (by ≥2 point in GCS), with or without accompanying focal neurologic deficits. In those cases, both, transcranial Doppler and DSA were performed to look for radiological signs of cerebral vasospasm (CV). In most severe cases, in unconscious patients, intracranial pressure and cerebral perfusion pressure monitoring were used first.

The neurological examination was performed at discharge and after 1 and 12 months (in a routine out-patient clinic follow-up), by a neurosurgeon who did not have access to the study data. Glasgow Outcome Scale (GOS) and the modified Rankin Scale (mRS) were used [26,27].

Specimen Collection

Cerebrospinal fluid (CSF) samples (2ml) were collected through a lumbar puncture on the 1^st, 3^rd and 5^th day after surgery. The samples were aliquoted then centrifuged for 10 minutes at 7000g to remove particulates and snap frozen in liquid nitrogen, and stored at -80ºC until further analysis. Blood samples were collected on the 1^st, 3^rd and 5^th day after surgery, and directly passed along to the laboratory for analysis. Regarding the control group, single CSF samples and blood samples were collected and processed in the exactly the same way.

Detection of Free Form of F2-IsoPs (8-iso Prostaglandin F_2α)

We performed the analysis of 27 samples in the study group and in 8 samples in the control group. Free form of F2-IsoPs in CSF was quantified using STAT-8- Isoprostane ELISA Kit (Cayman Chemical, Ann Arbor, Michigan, USA). The analysis was conducted according to the manufacturer’s protocol. All samples were measured in duplicates. Synergy 2 Multi-Mode Reader (BioTek Instruments, Inc., Winooski, VT, USA) and the dedicated software were used for plate readings.

Detection of erythrocytes anisocytosis (RDW-CV; RDW-SD)

RDW-CV and RDW-SD were analysed in routine morphology test performed after the operation. Plasma samples (5-10 mL of morning sample taken following ≥8h of fasting) were collected from each patient into commercially available ethylenediaminetetraacetic acid (EDTA) treated tubes as a part of a routine examination.

Analytical recovery studies for 8-iso Prostaglandin F_2α, RDW-CV and RDW-SD

Analytical recovery studies were carried out using CSF samples from 3 different time points assessing the F2-IsoPs level from 3 different time points assessing the RDW-CV and RDW-SD, revealing that the recovery rate ranged from 95.9%-97.8%.

Statistical Analysis

The Shapiro–Wilk test was used to evaluate the normal distribution. Continuous variables with normal distribution were expressed as means ± SD and using parametric tests; otherwise data were shown as median with interquartile range (1. – 3. quartile) and were tested with nonparametric tests. Nominal variables were analysed using the chi-square test, chi-square test with Yates’ correction or exact Fisher test based on the size of the smallest subgroup (n≥15, 15>n≥5, and 5>n, respectively).

The predictive potential of single factors and more complex models were assessed using receiver operating characteristic (ROC) curves with calculation of the area under the curve (AUC) [29]. The optimal thresholds were identified according to Youden’s index. Finally, we performed multivariable analysis using the stepwise logistic regression. For all analyses, the p values < 0.05 were considered as statistically significant. Statistical analyses were performed using the Statistica 13.3PL software (StatSoft, Tulsa, OK, USA).

Sample Size Calculation: The minimal sample size required for this study was determined using initial data from a cohort of the first 5 aSAH patients, who developed DCI and first 5 who did not. This calculation was based on RDW-CV, RDW-SD, and CSF ISOP measured on the first day post-surgery. An additional contingency of 10%, rounded up, was incorporated to account for potential data loss or variability. Consequently, the largest derived sample size, n=27, was established as the minimum number required to ensure statistical robustness and validity of the study outcomes (see Tab. 1).

Table 1. Sample size calculation.

	RDW-CV	RDW-SD	ISOP CSF
DCI mean	13.42	35.08	36.55
nonDCI mean	15.20	48.90	91.40
SD	1.26	6.30	35.95
Minimal sample size (total)	27	14	25

The Patients’ Clinical Condition

As it was shown on Fig. 1., 45 patients were screened for eligibility and 27 were included in further investigations. Their clinical and laboratory data are summarized in Table 2.

Table 2. Complete clinical data.

Patient number	Age (y.o.)	Gender (M-1; W-0)	H/H grade	mFisher grade	DCI	ICH	HCP	GOS at discharge	GOS after 12 months	mRS after 12 months	RDW-CV (%CV) day 1	RDW-SD (fl) day 1	RDW-CV (%CV) day 3	RDW-SD (fl) day 3	RDW-CV (%CV) day 5	RDW-SD (fl) day 5	ISOP CSF 1 (pg/ml)	ISOP CSF 3 (pg/ml)	ISOP CSF 5 (pg/ml)
1	73	0	2	4	1	0	1	4	2	5	17.7	58.1	12.3	32.4	12.9	43.2	76.2	104.2	76.7
2	62	1	3	4	1	1	0	2	1	6	12.6	35.6	13.4	33.5	12.6	40.1	100.7	143.7	52.8
3	61	0	3	3	0	0	0	3	1	6	12.5	26.1	12.8	38.1	11.9	44.8	70.8	49.4	67.4
4	72	0	3	4	1	0	1	2	1	6	15.9	49.1	14.2	39.2	13.9	47.8	175.6	105.6	154.3
5	63	0	2	4	1	0	1	3	2	5	14.9	49.6	11.3	40.4	14.1	38.5	21.1	97.3	98.2
6	46	1	3	1	0	1	1	3	1	6	13.7	40.9	12.6	42.4	12.5	36.8	29.4	16.9	34.9
7	31	1	3	4	1	0	1	3	3	4	14.9	52.1	11.6	43.2	15	33.8	83.2	86.5	71.2
8	64	0	3	3	1	0	1	3	2	5	15.9	52.2	11.8	39.8	11.9	40.6	67.6	73.5	43.2
9	58	0	4	1	0	1	0	2	3	3	14.8	35.2	13.5	45.7	12.1	39.7	25.5	94.3	44.3
10	52	1	3	1	0	0	0	3	1	6	12.5	39.5	12.4	43.2	13.5	35.9	50.4	19.1	44.8
11	64	1	3	4	1	1	1	2	2	5	14.5	53.6	13.5	44.8	13.1	40.8	31.8	76.3	45.5
12	56	0	2	4	0	0	1	3	4	3	13.6	33.7	11.2	44.9	14.1	45.8	6.6	7.2	7.7
13	70	0	3	3	1	0	0	4	1	6	15.2	58.1	11.7	49.1	11.9	48.5	30.5	91.4	51.9
14	42	1	3	4	0	1	1	4	4	3	13	40.7	13	41.8	12.5	43.9	5.7	73.8	36.1
15	56	0	3	4	1	0	1	2	1	6	15.2	57.4	14	55.2	11.6	49.1	23.5	19.7	10.3
16	62	1	3	4	1	0	0	2	1	6	13.8	44.5	12.5	38.7	12.8	42.9	12.8	15.9	17.9
17	73	0	2	2	0	0	1	3	1	6	13.1	41.3	11.8	39.6	13.1	44.7	6.6	5.3	19.4
18	82	0	1	2	0	0	0	3	3	3	15.1	50.6	11.4	44.8	14.2	45.9	23.9	23.5	39.7
19	61	0	2	4	0	0	1	4	4	2	12.9	42.3	12.1	43.9	11.3	47.1	5.6	80.7	8.0
20	60	1	3	4	1	0	0	3	2	5	11.2	28.4	12.9	41.2	11.5	38.6	67.2	14.1	36.7
21	61	0	3	4	1	0	0	3	4	2	11.5	28.8	13.1	38.5	12.7	37.1	140.7	120.6	89.6
22	35	0	3	4	0	0	0	3	4	3	13.1	48.9	14	44.9	13.1	39.5	8.8	0.8	12.3
23	68	1	3	4	0	0	0	3	2	5	13	44.6	12.6	43.9	14.1	39.4	15.8	22.1	15.1
24	90	1	2	3	1	0	1	4	1	6	15.5	47.3	11.8	45.1	12.9	38.7	23.6	23.4	54.8
25	48	1	3	4	0	0	0	3	3	4	12.1	39.9	13.2	38.1	13.1	40.1	17.7	43.5	34.6
26	42	0	2	2	0	0	0	4	5	0	11.9	38.5	11.4	40.3	12.9	39.4	25.6	10.7	24.9
27	38	0	2	2	0	0	1	4	4	2	14	40	11.7	44.5	13.3	44.4	39.5	63.3	51.7

The study group comprised 16 (59.26%) males, while the control group had 4 (50%) males. The aneurysms were located most often in the anterior part of the circle of Willis (n=23, 85.2%). DCI was diagnosed in 13 (48.15%) patients and the median day of DCI onset was day 5. The DCI diagnosis was made by a multidisciplinary team, consisting of neurosurgeons and a radiologist.

First, we assessed the dependencies between DCI, nonDCI and the control group in the terms of: RDW-SD, RDW-CV and F2-IsoP levels. Analysis indicated a statistically significant difference in RDW-between the tested groups (see Fig. 2). Moreover, we noted that CSF F2-IsoP levels on day 1 and day 5 were associated with DCI occurrence, comparing to non-DCI patients and the controls (see Fig. 3A&C). Interestingly, on day 3 its concentration differs only between DCI and control group (see Fig. 3B).

Next, we performed a univariate analysis and assessed the relation between clinical, radiological, laboratory features and F2-IsoP levels regarding DCI occurrence. The results are presented in Table 2. In the next step, we performed a multivariate analysis (backward stepwise logistic regression). To the analysis we included only those variables that had shown to be significant in the univariate analysis. The results are presented in Table 3.

Table 3. The univariate and multivariative analyses assessing the relation between clinical, radiological, laboratory features and F2-IsoP levels regarding DCI occurrence.

	Total n=27	DCI n=13 (48.1%)	Without DCI n=14 (51.9%)	Univariate OR (95% CI)	P value	Multivariate OR (95% CI)	P value
*Age [years]*	61 (50-66)	63 (61-70)	54 (43-61)	1.05 (0.99-1.12)	0.09
*Gander* [male]	11	6 (54.5%)	5 (45.5%)	1.53 (0.32-7.22)	0.582
*Intracerebral haemorrhage (ICH)*	5 (18.5%)	2 (15.4%)	3 (21.4%)	0.66 (0.09-4.8)	0.687
*Hydrocephalus (HCP)*	14 (51.8%)	8 (61.5%)	6 (42.8%)	2.13 (0.45-9.94)	0.334
*RDW-CV (%CV) – day 1*	13.8±1.5 13(12-15)	14.5±1.8 14(13-15)	13.2±0.9 13(12-13)	1.92 (1.02-3.61)	0.04	1.28 (1.04-1.59)	0.02
*RDW-SD (fl) – day 1*	43.5±8.9 42(39-50)	47.2±10 49(44-53)	40.1±6 40(38-42)	1.11 (1-1.23)	0.04
*RDW-CV (%CV) – day 3*	12.5±0.8 12(11-13)	12.6±0.9 12(11-13)	12.4±0.8 12(11-12)	1.32 (0.55-3.16)	0.525
*RDW-SD (fl) – day 3*	42.1±4.5 42(39-44)	41.6±6 40(38-44)	42.5±2.5 43(40-44)	0.95 (0.8-1.13)	0.581
*RDW-CV (%CV) – day 5*	12.9±0.9 12(12-13)	12.8±1 12 (11-13)	12.9±0.8 13(12-13)	0.84 (0.36-1.94)	0.690
*RDW-SD (fl) – day 5*	41.7±4 40(39-44)	41.5±4 40(38-43)	41.9±3.6 42(39-44)	0.97 (0.8-1.17)	0.774
*ISOP CSF day 1 (pg/ml)*	43.9±42 25(16-67)	65.7±50 67(23-83)	23.7±19 20(7-28)	1.04 (1-1.08)	0.02	1.09 (1.005-1.19)	0.03
*ISOP CSF day 3 (pg/ml)*	49.3±37 43(16-80)	65.8±39 76(21-94)	36.4±30 22(12-59)	1 (0.98-1)	0.878
*ISOP CSF day 5 (pg/ml)*	46±32 43(22-53)	61.7±52(43-76)	31.4±17 34(16-43)	1.05 (1.004-1.097)	0.03
*GOS at discharge* I II III IV V		0 (0%) 5 (38.5%) 5 (38.5%) 3 (23%) 0 (0%)	0 (0%) 1 (7.1%) 9 (64.3%) 4 (28.6%) 0 (0%)	0.44 (0.13-1.45)	0.179
*GOS after 12 months* I II III IV V		6 (46.1%) 5 (38.5%) 1 (7.7%) 1 (7.7%) 0 (0%)	4 (28.6%) 1 (7.1%) 3 (21.5%) 5 (35.7%) 1 (7.1%)	0.46 (0.22-0.95)	0.03
*mRS after 12 months* 0 I II III IV V VI		0 (0%) 0 (0%) 1 (7.7%) 0 (0%) 1 (7.7%) 5 (38.5%) 6 (46.1%)	1 (7.1%) 0 (0%) 2 (14.3%) 5 (35.8%) 1 (7.1%) 1 (7.1%) 4 (28.6%)	1.8 (1.03-3.46)	0.03

We noted that day 1 CSF F2-IsoP concentration and day 1 RDW-SD value were the most important predictors for DCI. The receive operating characteristic curve for DCI prediction based on multivariate model had the area under the curve (AUC: 0.924, 95% CI: 0.824–0.1, p<0.01; see Fig. 4A).

In the second step we investigated in the backward stepwise logistic regression models, which with a combination with the clinical features provided the highest prognostic value regarding the occurrence of DCI. ROC curves based on backward stepwise logistic regression showed that the best model for DCI prediction on the basis of the clinical markers incorporated only mFisher grade (AUC: 0.726, 95% CI: 0.532–0.924, p=0.02; see Fig. 4B).

When we built a model with F2-IsoP concentration on day 1 and RDW-SD value we received even better results. Thus, the combination of CSF F2-IsoP concentration on day 1 and RDW-SD value on day 1 turned out to be a very good DCI predictor (AUC: 0.924, 95% CI: 0.824–0.1, p<0.01; see Fig. 4C).

Furthermore, we investigated which variables had been associated with poor long-term outcomes. To reach this purpose, we dichotomized the quality-of-life scales according to the need for assistance in everyday life (i.e., GOS scores 4–5 vs. 1–3 and mRS scores 0–3 vs. 4–6). The backward stepwise logistic regression showed that age (OR 1.1 (95% CI: 1.01-1.2), p=0.02) with a cut-off point 62years (figure 4D), DCI (OR 23.41 (95% CI: 1.8-303.7), p=0.01) and male gender (OR 15,68 (95% CI:1.15-213.68), p=0.03) were the most important predictors for poor outcomes according to GOS and mRS.

Moreover, we decided to investigate the correlation between the patients’ age and DCI, as according to the literature older individuals are prone to DCI [30]. Hence, we dichotomized the patients into two age groups (i.e., ≥60 y. o. vs. <60 y. o.) according to the ROC curve and the best cut-off point (see Fig. 4E). We showed a correlation between DCI and age (p<0.01).

Using the same dichotomization, we also checked the correlation between the patients’ age and IsoP levels on day 5, noting a statistical trend between them. The U Mann-Whitney test result was borderline, yet non-significant one (p=0.07).

The main finding of our work is the exploration of clinical significance of CSF IsoP concentration and RDW-CV on day 1 in the context of DCI risk. Notably, we showed the potential role of oxidative stress in the DCI and predictive potential of IsoPs (as an oxidative stress biomarker) and erythrocytes anisocytosis (expressed by RDW-CV value) as an independent risk factor for DCI following aSAH.

In previous studies, it was shown that most important clinical predictors for DCI are: age (40-59 y. o.), thick SAH (high Fisher grade) and aneurysm located in the anterior circulation [30], but no objective laboratory predictor was proposed. The amount of blood after SAH directly correlates with the severity of oxidative stress and DCI. It should be also mentioned that the blood in the subarachnoid space not only plays a role in the development of DCI, but also has an impact on early brain injury being the cause of neural damage in the first 72h after the aneurysm rupture [31,32]. The extravasated blood increases intracranial pressure (ICP), leads to a decrease in the cerebral perfusion pressure (CPP) and impairs autoregulation causing cell death and brain oedema [33]. Further consequences might bemicrothrombosis, altered ionic homeostasis, excitotoxicity, oxidative stress and energy dysfunction secondary to cortical spreading depolarization (SDs) [34,35,36]. All those events would add up to the DCI pathophysiology. There is no doubt that having an easily accessible biomarker of high prognostic value for DCI prediction would be of great assistance in the DCI prediction and diagnosis, on the other hand indicating a group of aSAH patients without the risk of DCI and thus reducing the cost of their hospitalization. As it seems, providing our observation are confirmed in the further studies, we could hope that our model will be useful as a biomarker for an early DCI detection.

The increase in oxidative stress is mostly a result of the lysis of red blood cells (RBCs) released into the subarachnoid space. Physiologically, the extravasated erythrocytes derived haemoglobin (Hb) and free heme are bound to haptoglobin (Hp) that neutralizes the strong oxidative capacity of heme-iron and prepares it for phagocytosis. In aSAH those mechanisms become rapidly exhausted and only some of the Hb and free heme originating from erythrocytes is neutralized by Hp. They collapse even faster in older patients due to insufficient antioxidant mechanisms in this age group [37]. Thus, free heme and iron in the extracellular space are the principal source of oxidative stress and reactive oxygen species (ROS).

The isoprostanes are prostaglandin-like compounds are formed in vivo from the free radical-catalysed peroxidation of cell membrane arachidonic acid without the direct action of cyclooxygenase (COX) enzymes. Their concentration directly correlates with ROS production; thus, they were classified as oxidative stress biomarkers with potent biological activity [38]. In our research, we found that CSF IsoPs concentration on day 1 after surgery was elevated in the DCI group. From one side the level of IsoPs informs us about the severity of neuronal damage caused by oxidative stress as the concentration was higher in the DCI group vs. non-DCI and control and from the other, their biological potential to affect the DNA synthesis in the smooth muscle cells, as well as mitogenesis and stimulation of platelets aggregation, fibroblast proliferation and vasoconstriction, all of which may also play a role in DCI pathophysiology [39]. In our work, we also showed that poor outcome and DCI occurrence were more frequently observed in older patients with the cut-off point at 60years, as it already had been suggested in the literature [42]. The ROS formation increase, is well-known to be age-related, whereas the age-dependent functional decline of antioxidant mechanisms in the population is also observed [40,41]. We would also draw attention to the trend between age and IsoPs level on day 5 as it suggests that on day 5, which was the median day of DCI onset in our cohort, there is an increase of ROS. In our opinion it is related to the insufficient antioxidant reaction that is observed in older patients. The dynamic balance between the production and elimination of ROS in patients with DCI might be shifted towards the ROS formation. This issue needs more investigation.

The pathophysiological mechanisms leading to DCI include microcirculatory disturbances and microthromboembolism. Some studies propose that anisocytosis may be associated with both of these mechanisms. According to the study by Pato et al., patients with RDW above 14% had significantly decreased RBC deformability [43]. In an animal model study, lower blood flow was associated with reduced plasticity of RBC [44]. Although the exact mechanism remains unclear, one hypothesis proposes that erythrocytes with reduced deformability, may be recognized by macrophages, which secret the agents causing vasoconstriction and accumulation of platelets and leukocytes. Aarts et al. suggest that erythrocytes with reduced deformability were also responsible for increased platelet adhesion [45] which could be a potential cause of aggravated microthromboembolism. However, association of RCB deformability and RDW is not fully understood as there is only one study confirming existence of this relationship.

Many authors indicated that RDW-CV and RDW-SD show an upward trend with advanced age, however, exact mechanism of how aging influences anisocytosis is not known [46,47,48,49]. This may potentially explain the association of RDW with poor outcome in various diseases. In our multivariate analysis, the combination of isoprostanes and RDW turned out to be the very good predictor of DCI (AUC: 0.924, 95% CI: 0.824–0.1, p<0.01). Additionally, RDW-SD values were also greater in patients over 59 years of age.

Anisocytosis has been identified as a risk factor of poor outcome in many diseases, also being associated with age [50]. In 2023r. Lukito et al. performed meta-analysis in which they found that high RDW value was significantly correlated with poor functional outcome, mortality and DCI [51]. Importantly enough, our study findings are consistent with analyses involving other possible biomarkers and RDW. Researchers looking at factors such as neutrophil-to-lymphocyte ratio (NLR) or systemic inflammatory response index (SIRI) also found a correlation between RDW and DCI [52,53]. Interestingly, an analysis performed by Ingacio et al. demonstrated that RDW holds greater significance in predicting the DCI than NLR does [54].

A certain drawback of our work is that in the study protocol we employed the Hunt-Hess scale while WFNS scale is usually preferred in clinical analyses, albeit the Hunt-Hess scale, is still widely. We would like to draw attention to a fact that it is difficult to collect CFS samples at strict time points in aSAH patients. This may render incorporating suggested CSF biomarkers into the routine clinical practice somewhat difficult. Nonetheless, we believe that our efforts are sensible from a clinical point of view. Establishing a biochemical marker or screening test detecting DCI should facilitate minimally invasive DCI monitoring and prompt implementation of the treatment as well as reduce the costs of hospitalization. Finally, this could kindle a future search for a specific treatment directly preventing DCI.

According to the results of our analysis, the combination of RDW-CV value and the concentration of IsoPs in CSF on the first day after surgery for a ruptured intracranial aneurysm, can serve as prognostic factors in DCI.

Data Availability

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

Authors Contributions

Conceptualization – Wiśniewski K.

Methodology – Wiśniewski K.; Bieńkowski M.

Analysis – Wiśniewski K.; Zaczkowski K.; Popęda M.; Bieńkowski M.; Szmyd B.

Investigation – Wiśniewski K.; Zaczkowski K.; Popęda M.; Bieńkowski M.; Posmyk B.; Bobeff E.J.

Writing original draft preparation – Wiśniewski K.; Zaczkowski K.; Szmyd B.

Writing—review and editing – Wiśniewski K.; Zaczkowski K.; Szmyd B.; Jaskólski D.J.

Project administration – Wiśniewski K.

Supervision – Wiśniewski K.; Jaskólski D.J.

All authors reviewed and accepted the manuscript.

Competing interests

The author(s) declare no competing interests.

National Science Center and Ministry of Science and Higher Education provided financial support in the form of PRELUDIUM VI; Project ID 507/1-121-03/507-10-075/UMO-2013/11/N/NZ4/00273.

Rinkel, G. J., & Algra, A. (2011). Long-term outcomes of patients with aneurysmal subarachnoid haemorrhage. The Lancet Neurology, 10(4), 349–356. doi:10.1016/s1474-4422(11)70017-5
Hijdra A, Braakman R. Aneurysmal subarachnoid hemorrhage. Complications and outcome in a hospital population. Stroke. 1987; 18:1061–1067.
. Al-Khindi T, Macdonald RL, Schweizer TA. Cognitive and functional outcome after aneurysmal subarachnoid hemorrhage. Stroke. 2010;41(8): e519‐e536
Vergouwen, M. D., Vermeulen, M., Coert, B. A., Stroes, E. S., & Roos, Y. B. (2008). "Microthrombosis after Aneurysmal Subarachnoid Hemorrhage: An Additional Explanation for Delayed Cerebral Ischemia." Journal of Cerebral Blood Flow & Metabolism, 28(11), 1761–1770.
Frontera, J. A., Claassen, J., Schmidt, J. M., et al. (2006). "Prediction of Symptomatic Vasospasm after Subarachnoid Hemorrhage: The Modified Fisher Scale." Neurosurgery, 59(1), 21–27
Dankbaar, J. W. et al. (2009). Relationship between vasospasm, cerebral perfusion, and delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage. Neuroradiology, 51(12), 813–819. doi:10.1007/s00234-009-0575-y
Vergouwen, M. D. I., et al. (2010). Definition of Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage as an Outcome Event in Clinical Trials and Observational Studies: Proposal of a Multidisciplinary Research Group. Stroke, 41(10), 2391–2395. doi:10.1161/strokeaha.110.589275
Claassen J, Bernardini GL, Kreiter K, Bates J, Du Y, Copeland D, et al. Effect of cisternal and ventricular blood on risk of delayed cerebral ischemia after subarachnoid hemorrhage. The Fisher scale revisited. Stroke. 2001; 32:2012–2020
Pradilla G, Garzon-Muvdi T, Ruzevick JJ, Bender M, Edwards L, Momin EN. Systemic L-citrulline prevents cerebral vasospasm in haptoglobin 2–2 transgenic mice after subarachnoid hemorrhage. Neurosurgery 2012; 70:747–57.
Lin C-L, Kwan A-L, Dumont AS, Su YF, Kassell NF, Wang CJ, et al. Attenuation of experimental subarachnoid hemorrhage-induced increases in circulating intercellular adhesion molecule-1 and cerebral vasospasm by the endothelin-converting enzyme inhibitor CGS 26303. J Neurosurg 2007; 106:442–8.
Reuter S, Gupta SC, Chaturvedi MM, Aggarwal BB. Oxidative stress, inflammation, and cancer: how are they linked? Free Radic Biol Med 2010; 49:603–16.
Sies H. Oxidative stress: a concept in redox biology and medicine. Redox Biol 2015; 4:180–3.
Forstermann U, Munzel T. Endothelial nitric oxide synthase in vascular disease: from marvel to menace. Circulation 2006; 113:1708–14.
Brune B, Schmidt KU, Ullrich V. Activation of soluble guanylate cyclase by carbon monoxide and inhibition by superoxide anion. Eur J Biochem/FEBS 1990; 192:683–8.
Sayed N, Baskaran P, Ma X, van den Akker F, Beuve A. Desensitization of soluble guanylyl cyclase, the NO receptor, by S-nitrosylation. Proc Natl Acad Sci U S A 2007; 104:12312–7.
Li L, Watts SW, Banes AK, Galligan JJ, Fink GD, Chen AF. NADPH oxidase-derived superoxide augments endothelin- 1-induced venoconstriction in mineralocorticoid hypertension. Hypertension 2003; 42:316–21.
Li L, Fink GD, Watts SW, Northcott CA, Galligan JJ, Pagano PJ, et al. Endothelin-1 increases vascular superoxide via endothelin (A)-NADPH oxidase pathway in low-renin hypertension. Circulation 2003; 107:1053–8.
Hernanz R, Briones AM, Salaices M, Alonso MJ. New roles for old pathways? A circuitous relationship between reactive oxygen species and cyclooxygenase in hypertension. Clin Sci (Lond) 2014; 126:111–21.
Pantelis Oustamanolakis, et al. Measurement of reticulocyte and red blood cell indices in the evaluation of anemia in inflammatory bowel disease, Journal of Crohn's and Colitis, Volume 5, Issue 4, August 2011, Pages 295–300, https://doi.org/10.1016/j.crohns.2011.02.002
Horta-Baas, G., & Romero-Figueroa, M. del S. (2018). Clinical utility of red blood cell distribution width in inflammatory and non-inflammatory joint diseases. International Journal of Rheumatic Diseases. doi:10.1111/1756-185x.13332
Lippi G, Pavesi F, Bardi M, Pipitone S. Lack of harmonization of red blood cell distribution width (RDW). Evaluation of four hematological analyzers. Clin Biochem. 2014; 47:1100–1103.
Lucijanic, et al. (2016). The Degree of Anisocytosis Predicts Survival in Patients with Primary Myelofibrosis. Acta Haematologica, 136(2), 98–100. doi:10.1159/000445247
Bobeff EJ, et al. Plasma Amino Acids May Improve Prediction Accuracy of Cerebral Vasospasm after Aneurysmal Subarachnoid Haemorrhage. J Clin Med. 2022;11(2):380. doi: 10.3390/jcm11020380. PMID: 35054073; PMCID: PMC8779950.
Mallat, Z, et al Elevated levels of 8-iso-prostaglandin F2alpha in pericardial fluid of patients with heart failure: A potential role for in vivo oxidant stress in ventricular dilatation and progression to heart failure. Circulation 1998, 28, 1536–1539.
Yan, Z.; Mas, E.; Mori, T.A.; Croft, K.D.; Barden, A.E. A significant proportion of F2-isoprostanes in human urine are excreted as glucuronide conjugates. Anal. Biochem. 2010, 403, 126–128.
Jennett B, Bond M. Assessment of outcome after severe brain damage. Lancet. 1975; 1: 480–484.
Teasdale G, Jennett B. Assessment of coma and impaired consciousness. A practical scale. Lancet. 1974; 2: 81–84.
Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007; 39: 175–191.
Robin X, et al. (2011) pROC: an open-source package for R and S + to analyze and compare ROC curves. BMC Bioinformatics 12:77.
Lee H, Perry JJ et al. Clinical prediction of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage. J Neurosurg. 2018 Jun 1:1–8.
Sehba, F. A., Hou, J., Pluta, R. M. & Zhang, J. H. The importance of early brain injury after subarachnoid hemorrhage. Prog. Neurobiol. 97, 14–37 (2012).
Kusaka G, Ishikawa M, Nanda A, Granger DN, Zhang JH. Signaling pathways for early brain injury after subarachnoid hemorrhage. J Cereb Blood Flow Metab: official journal of the International Society of Cerebral Blood Flow and Metabolism. 2004;24(8):916–25. https://doi.org/10.1097/01.WCB. 0000125886.48838.7E.
Gaasch M, et al. Cerebral autoregulation in the prediction of delayed cerebral ischemia and clinical outcome in poor-grade aneurysmal subarachnoid hemorrhage patients. Crit Care Med. 2018;46(5):774–80. https://doi.org/10.1097/CCM.0000000000003016 I
de Oliveira Manoel AL, et al. The critical care management of poor-grade subarachnoid haemorrhage. Crit Care. 2016;20:21. https://doi.org/10.1186/s13054-016-1193-
Chou SH, et al. Elevated peripheral neutrophils and matrix metalloproteinase 9 as biomarkers of functional outcome following subarachnoid hemorrhage. Transl Stroke Res. 2011;2(4):600–7. https://doi.org/10.1007/s12975-011-0117-x. 16.
Sakowitz OW, et al. Clusters of spreading depolarizations are associated with disturbed cerebral metabolism in patients with aneurysmal subarachnoid hemorrhage. Stroke. 2013;44(1):220–3. https://doi.org/10.1161/STROKEAHA.112.672352.
Gorni D, Finco A. Oxidative stress in elderly population: A prevention screening study. Aging Med (Milton). 2020;3(3):205–213. doi: 10.1002/agm2.12121. PMID: 33103041; PMCID: PMC7574639.
Montuschi P, Barnes PJ, Roberts LJ 2nd. Isoprostanes: markers and mediators of oxidative stress. FASEB J. 2004;18(15):1791 – 800. doi: 10.1096/fj.04-2330rev. PMID: 15576482.
Wiśniewski K. et al. Isoprostanes as potential cerebral vasospasm biomarkers. Neurol Neurochir Pol. 2018 Nov-Dec;52(6):643–651. doi: 10.1016/j.pjnns.2018.09.009. Epub 2018 Oct 4. PMID: 30314904.
Meydani SN, Wu D, Santos MS, Hayek MG. Antioxidants and immune response in aged persons: overview of present evidence. Am J Clin Nutr. 1995;62(6 Suppl):1462S-1476S. doi: 10.1093/ajcn/62.6.1462S. PMID: 7495247.
De la Fuente M. Effects of antioxidants on immune system ageing. Eur J Clin Nutr. 2002;56 Suppl 3:S5-8. doi: 10.1038/sj.ejcn.1601476. PMID: 12142953.
Rautalin I, Juvela S, Martini ML, Macdonald RL, Korja M. Risk Factors for Delayed Cerebral Ischemia in Good-Grade Patients With Aneurysmal Subarachnoid Hemorrhage. J Am Heart Assoc. 2022;11(23):e027453. doi: 10.1161/JAHA.122.027453. Epub 2022 Nov 29. PMID: 36444866; PMCID: PMC9851459.
Patel, K. et al. (2012). Association of the Red Cell Distribution Width with Red Blood Cell Deformability. Oxygen Transport to Tissue XXXIV, 211–216. doi:10.1007/978-1-4614-4989-8_29 10.1007/978-1-4614-4989-8_29
. Simchon S, Jan KM, Chien S (1987) In fl uence of reduced red cell deformability on regional blood fl ow. Am J Physiol 253:H898–H903
PA Aarts, PA Bolhuis, KS Sakariassen, RM Heethaar, JJ Sixma; Red blood cell size is important for adherence of blood platelets to artery subendothelium. Blood 1983; 62 (1): 214–217. doi: https://doi.org/10.1182/blood.V62.1.214.214
Lippi G. et al. between red blood cell distribution width and inflammatory biomarkers in a large cohort of unselected outpatients. Arch Pathol Lab Med. 2009;133(4):628–632.
Qiao R, Yang S, Yao B, Wang H, Zhang J, Shang H. Complete blood count reference intervals and age- and sex-related trends of North China Han population. Clin Chem Lab Med 2014;52:1025–32.
Lippi, G., Salvagno, G. L., & Guidi, G. C. (2014). Red blood cell distribution width is significantly associated with aging and gender. Clinical Chemistry and Laboratory Medicine (CCLM), 0(0). doi:10.1515/cclm-2014-0353
Patel KV et al. Red cell distribution width and mortality in older adults: a meta-analysis. J Gerontol A Biol Sci Med Sci. 2010;65(3):258–65. doi: 10.1093/gerona/glp163. Epub 2009 Oct 30. PMID: 19880817; PMCID: PMC2822283.
Danese E., Lippi G., Montagnana M. Red blood cell distribution width and cardiovascular diseases. J Thorac Dis. 2015;7(10):E402–E411. doi: 10.3978/j.issn.2072-1439.2015.10.04.
Lukito PP, Lie H, Angelica V, Wijovi F, Nathania R, July J. Red-cell distribution width as a prognostic marker for aneurysmal subarachnoid hemorrhage: A systematic review and meta-analysis. World Neurosurg X. 2023;19:100202. doi: 10.1016/j.wnsx.2023.100202. PMID: 37181583; PMCID: PMC10172754.
Shi M., Yang C., Tang Q.W., Xiao L.F., Chen Z.H., Zhao W.Y. The prognostic value of neutrophil-to-lymphocyte ratio in patients with aneurysmal subarachnoid hemorrhage: a systematic review and meta-analysis of observational studies. Front Neurol. 2021;12 doi: 10.3389/fneur.2021.745560
Systemic inflammation response index and systemic immune-inflammation index for predicting the prognosis of patients with aneurysmal subarachnoid hemorrhage. J Stroke Cerebrovasc Dis. 2021;30(8) doi: 10.1016/j.jstrokecerebrovasdis.2021.105861.
Ignacio K.H.D., Diestro J.D.B., Enriquez C.A.G., et al. Predictive value of hematologic inflammatory markers in delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage. World Neurosurg. 2022;160:e296–e306.

No competing interests reported.

Prognostic Biomarkers for Delayed Cerebral Ischemia Post-Aneurysmal Subarachnoid Hemorrhage: Evaluating CSF 8-iso-Prostaglandin F2α and Erythrocyte Anisocytosis

Status:

Version 1

Abstract

Figures

Introduction

Material and methods

Results

Discussion

Conclusion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1