Obesity in aneurysmal subarachnoid hemorrhage

Obesity in aneurysmal subarachnoid hemorrhage

As the number of obese people is globally increasing, reports about the putative protective effect of obesity in life-threatening diseases, such as subarachnoid hemorrhage (SAH), are gaining more interest. This theory-the obesity paradox-is challenging to study, and the impact of obesity has remained unclear in the survival of several critical illnesses, including SAH. Thus, we performed a systematic review to clarify the relation between obesity and SAH mortality. Our study protocol included systematic literature search in PubMed, Scopus, and Cochrane library databases, whereas risk-of-bias estimation and quality of each selected study were evaluated by the Critical Appraisal Skills Program and Cochrane Collaboration guidelines. A directional power analysis was performed to estimate a sufficient sample size for significant results. From 176 reviewed studies, six fulfilled our eligibility criteria for qualitative analysis. One study found paradoxical effect (odds ratio, OR = 0.83 (0.74-0.92)) between morbid obesity (body mass index (BMI) > 40) and in-hospital SAH mortality, and another study found the effect between continuously increasing BMI and both short-term (OR = 0.90 (0.82-0.99)) and long-term SAH mortalities (OR = 0.92 (0.85-0.98)). However, according to our quality assessment, methodological shortcomings expose all reviewed studies to a high-risk-of-bias. Even though two studies suggest that obesity may protect SAH patients from death in the acute phase, all reviewed studies suffered from methodological shortcomings that have been typical in the research field of obesity paradox. Therefore, no definite conclusions could be drawn 1).

263 SAH patients were included of which leptin levels were assessed in 24 cases. BMI was recorded along disease severity documented by the Hunt and Hess and modified Fisher scales. The occurrence of clinical or functional DCI (neuromonitoringCT Perfusion) was assessed. Long-term clinical outcome was documented after 12 months (extended Glasgow outcome scale). A total of 136 (51.7%) patients developed DCI of which 72 (27.4%) developed DCI-related cerebral infarctions. No association between BMI and DCI occurrence (P = .410) or better clinical outcome (P = .643) was identified. Early leptin concentration in serum (P = .258) and CSF (P = .159) showed no predictive value in identifying patients at risk of unfavorable outcomes. However, a significant increase of leptin levels in CSF occurred from 326.0 pg/ml IQR 171.9 prior to DCI development to 579.2 pg/ml IQR 211.9 during ongoing DCI (P = .049). No association between obesity and clinical outcome was detected. After DCI development, leptin levels in CSF increased either by an upsurge of active transport or disruption of the blood-CSF barrier. This trial has been registered at ClinicalTrials.gov (NCT02142166) as part of a larger-scale prospective data collection. BioSAB: https://clinicaltrials.gov/ct2/show/NCT02142166 2).


In a study involving a nationwide administrative database, milder obesity was not significantly associated with increased mortality rates, neurological complications, or poor outcomes after SAH. Morbid obesity, however, was associated with increased odds of venous thromboembolic, renal, and infectious complications, as well as of a nonroutine hospital discharge. Notably, milder obesity was associated with decreased odds of some medical complications, primarily in patients treated with coiling 3).


A total of 305 consecutive SAH patients (2002 to 2011) were retrospectively reviewed to collect demographics, BMI (kg/m(2)), comorbidities, Glascow Coma Scale, World Federation of Neurologic Surgeons Scale, aneurysm treatment, delayed cerebral ischemia, radiographic infarction, and short-term and long-term (> 24 months) morbidity, and mortality. Patients were stratified by BMI into category 1, < 25 kg/m(2); category 2, 25 -< 30 kg/m(2); and category 3, ≥ 30 kg/m(2).

Results: Categories 1, 2, and 3 had 93, 100, and 87 patients with mean BMIs of 22.4 ± 1.8, 27.6 ± 1.4, and 35.7 ± 4.6 (P < 0.05), respectively. By category, 24-month follow-up was available in 92%, 85%, and 85%. Category 3 had more hypertension, diabetes mellitus, and clipping than category 1. Short-term mortality rates were 17%, 12%, and 8%; long-term mortality rates were 34%, 26%, and 19% (P > 0.05 at all points between categories 1 vs. 3, but not 1 vs. 2 or 2 vs. 3). On univariate analysis, BMI was inversely associated with short-term (odds ratio, 0.91; 95% confidence interval 0.84-0.98; P = 0.009) and long-term (odds ratio, 0.92; 95% confidence interval 0.87-0.97; P = 0.001) mortality. On multivariate analysis including age, World Federation of Neurologic Surgeons Scale, delayed cerebral ischemia, and radiographic infarction, BMI remained significant for short-term (odds ratio, 0.91; 95% confidence interval 0.81-0.99; P = 0.047) and long-term (odds ratio, 0.92; 95% confidence interval 0.85-0.98; P = 0.021) mortality. On Kaplan-Meier survival analysis, P > 0.05 for categories 1 versus 2 and 2 versus 3, but P = 0.005 for categories 1 versus 3.

Conclusions: In our SAH population, higher BMI resulted in less short-term and long-term mortality, but no difference in functional outcome 4).


data for 741 SAH patients. A BMI greater than 25 kg/m(2) was considered overweight and greater than 30 kg/m(2) obese. The outcome according to the Glasgow Outcome Scale at discharge and after 6 months was assessed using logistic regression analysis.

Results: According to the BMI, 268 patients (36.2%) were overweight and 113 (15.2%) were obese. A favorable outcome (Glasgow Outcome Scale score >3) was achieved in 53.0% of overweight patients. In contrast, 61.4% of the 360 patients with a normal BMI had a favorable outcome (P = .021). However, in the multivariate analysis, only age (odds ratio [OR]: 1.051, 95% confidence interval [CI]: 1.04-1.07, P < .001), World Federation of Neurological Surgeons grade (OR: 2.095, 95% CI: 1.87-2.35, P < .001), occurrence of vasospasm (OR: 2.90, 95% CI: 1.94-4.34, P < .001), and aneurysm size larger than 12 mm (OR: 2.215, 95% CI: 1.20-4.10, P = .011) were independent predictors of outcome after 6 months. Of the 321 poor grade patients (World Federation of Neurological Surgeons score >3), 171 (53.3%) were overweight. Of these, 21.6% attained a favorable outcome compared with 35.3% of normal-weight patients (P = .006).

Conclusion: Although many physicians anticipate a worse outcome for obese patients, in our study, the BMI was not an independent predictor of outcome. Based on the BMI, obesity seems to be negligible for outcome after SAH compared with the impact of SAH itself, the patient’s age, occurrence of vasospasm, or aneurysm size 5).


Systolic and diastolic blood pressure were strong predictors of aneurysmal SAH, and there was a substantially increased risk associated with smoking. However, high body mass was associated with reduced risk of aneurysmal SAH 6).


1)

Rautalin I, Kaprio J, Korja M. Obesity paradox in subarachnoid hemorrhage: a systematic review. Neurosurg Rev. 2020 Dec;43(6):1555-1563. doi: 10.1007/s10143-019-01182-5. Epub 2019 Oct 29. PMID: 31664582; PMCID: PMC7680302.
2)

Veldeman M, Weiss M, Simon TP, Hoellig A, Clusmann H, Albanna W. Body mass index and leptin levels in serum and cerebrospinal fluid in relation to delayed cerebral ischemia and outcome after aneurysmal subarachnoid hemorrhage. Neurosurg Rev. 2021 Apr 17. doi: 10.1007/s10143-021-01541-1. Epub ahead of print. PMID: 33866464.
3)

Dasenbrock HH, Nguyen MO, Frerichs KU, Guttieres D, Gormley WB, Ali Aziz-Sultan M, Du R. The impact of body habitus on outcomes after aneurysmal subarachnoid hemorrhage: a Nationwide Inpatient Sample analysis. J Neurosurg. 2016 Jul 15:1-11. [Epub ahead of print] PubMed PMID: 27419827.
4)

Hughes JD, Samarage M, Burrows AM, Lanzino G, Rabinstein AA. Body Mass Index and Aneurysmal Subarachnoid Hemorrhage: Decreasing Mortality with Increasing Body Mass Index. World Neurosurg. 2015 Dec;84(6):1598-604. doi: 10.1016/j.wneu.2015.07.019. Epub 2015 Jul 15. PMID: 26187112.
5)

Platz J, Güresir E, Schuss P, Konczalla J, Seifert V, Vatter H. The impact of the body mass index on outcome after subarachnoid hemorrhage: is there an obesity paradox in SAH? A retrospective analysis. Neurosurgery. 2013 Aug;73(2):201-8. doi: 10.1227/01.neu.0000430322.17000.82. PMID: 23632760.
6)

Sandvei MS, Romundstad PR, Müller TB, Vatten L, Vik A. Risk factors for aneurysmal subarachnoid hemorrhage in a prospective population study: the HUNT study in Norway. Stroke. 2009 Jun;40(6):1958-62. doi: 10.1161/STROKEAHA.108.539544. Epub 2009 Feb 19. PMID: 19228833.

Obesity in neurosurgery

Obesity in neurosurgery

Concern exists for increased complications due to surgical challenges posed by obese patients and their often-prevalent comorbidities.

In a study involving a nationwide administrative database, milder obesity was not significantly associated with increased mortality rates, neurological complications, or poor outcomes after SAH. Morbid obesity, however, was associated with increased odds of venous thromboembolic, renal, and infectious complications, as well as of a nonroutine hospital discharge. Notably, milder obesity was associated with decreased odds of some medical complications, primarily in patients treated with coiling 1).

Obesity is a major risk factor globally and it is associated with an increased risk of severe vision loss due to idiopathic intracranial hypertension(IIH). There has been an increase in obesity prevalence in the Middle East countries mainly affecting the Gulf Council Countries (GCC), which parallels increased industrial development. This rise may be contributing to the increasing incidence of IIH in these countries. Other risk factors may also be contributing to IIH in Middle East countries and the differences and similarities to Western IIH merit further study 2).


Li et al., from Beijing aimed to examine the relationship between metabolically healthy obese (MHO) and risk of cardiovascular diseases (CVD) among the Chinese population.

The China Health and Retirement Longitudinal Study is a prospective cohort study of 7849 participants aged ≥45 years without CVD at baseline. Metabolic health status was assessed based on blood pressuretriglycerides, high-density lipoprotein cholesterol, glycated hemoglobin, fasting glucose, and C reactive protein. A cutoff point of body mass index of 24.0 kg/m2 was used to define over-weight/obesity (≥24.0 kg/m2) or normal weight (<24.0 kg/m2). CVD was based on self-reported doctor’s diagnosis of heart problems and stroke. Incidence rate ratio (IRR) with 95% confidence interval (CI) was deduced from modified Poisson regression.

During a mean 3.6 years of follow-up, 880 incident CVD events were recorded. 789 (10.05%) were identified MHO among 3321 (42.3%) obese individuals. Compared with metabolically healthy normal weight individuals, the multivariable adjusted IRR of CVD was 1.33 (95%CI: 1.19-1.49) for MHO, 1.29 (95%CI: 1.22-1.38) for metabolically unhealthy normal weight, and 1.61 (95%CI: 1.51-1.75) for metabolically unhealthy obese in the full adjusted model.

MHO individuals are associated with the increased risk of cardiovascular diseases among the Chinese population 3).

Types

see Hypothalamic obesity.

Severe obesity: body mass index (BMI ≥ 35).

Obesity in spinal surgery

Deep brain stimulation for obesity

Sixteen Sprague-Dawley rats were maintained on a high-fat diet. Daily food intake and weight gain were measured for 7 days, at which time the animals underwent stereotactic placement of 0.25-mm-diameter bipolar stimulating electrodes bilaterally in the LH. On postoperative Day 7, eight animals began to receive continuous stimulation of the LH. The remaining eight animals were left unstimulated as the control group. Individual animal weight, food intake, and water intake were monitored daily and continuously throughout the experiment until postoperative Day 24.

There was a decreased rate of weight gain after surgery in all animals, but the unstimulated group recovered and resumed a linear weight gain curve. The stimulated group, however, failed to show weight gain and remained below the mean baseline for body mass. There was a significant weight loss between the stimulated and unstimulated groups. On postoperative Day 24, compared with the day of surgery (Day 0), the unstimulated group had a mean weight gain of 13.8%, whereas the stimulated group had a 2.3% weight loss on average (p = 0.001), yielding a 16.1% weight difference between the two groups 4).


The lateral hypothalamus and ventromedial hypothalamus are the appetite and satiety centers in the brain, respectively. Substantial data support targeting these regions with DBS for the purpose of appetite suppression and weight loss. However, reward sensation associated with highly caloric food has been implicated in overconsumption as well as obesity, and may in part explain the failure rates of conservative management and bariatric surgery. Thus, regions of the brain’s reward circuitry, such as the nucleus accumbens, are promising alternatives for DBS in obesity control5).


Several studies have shown involvement of the nucleus accumbens in these and other addictive behaviors. In a case report, a patient who quit smoking and lost weight without any effort.

A 47-year-old woman presented with chronic treatment-refractory obsessive-compulsive disorder, nicotine dependence, and obesity.

The patient was treated with deep brain stimulation of the nucleus accumbens for obsessive-compulsive disorder. Unintended, effortless, and simultaneous smoking cessation and weight loss were observed.

This study supports the idea of compulsivity with common circuitry in the processing of diverse rewards and suggests that deep brain stimulation of the nucleus accumbens could be a possible treatment of patients with a dependency not responding to currently available treatments 6).


Deep brain stimulation must achieve a success rate of 83% to be equivalent to bariatric surgery. This high-threshold success rate is probably due to the reported success rate of LRYGB, despite its higher complication rate (33.4%) compared with DBS (19.4%). The results support further research into the role of DBS for the treatment of obesity 7).


Appetite modulation in conjunction with enhancing metabolic rate with hypothalamic lesions has been widely documented in animal and even in humans. It appears these effects can be reproduced by DBS, and the titratability and reversibility of this procedure, in addition to well established safety profile, make DBS an appealing option for obesity treatment. Targeting the hypothalamus with DBS has already been shown to be feasible and potentially effective in managing patients with intractable chronic cluster headache. The surgical risk however must be cautiously taken into account when targeting the hypothalamus, where some mortality cases have been reported when targeting the posterior part. The development of new surgical approach will probably reduce this surgical risk. Moreover, the role of functional neurosurgery in obesity is not a new idea. In fact, LH was targeted in obese humans with electrocoagulation more than 30 years ago, resulting in significant yet transient appetite suppression and slight weight reduction. All those elements have made possible the recent regain of interest in DBS for morbid obesity and open an exciting new area of research in neurosurgery and endocrinology 8).


Ho et al. present a review of the evidence of the neuroanatomical basis for obesity, the potential neural targets for deep brain stimulation (DBS), as well as a rationale for DBS and future trial design. Identification of an appropriate patient population that would most likely benefit from this type of therapy is essential. There are also significant cost and ethical considerations for such a neuromodulatory intervention designed to alter maladaptive behavior. Finally, the authors present a consolidated set of inclusion criteria and study end points that should serve as the basis for any trial of DBS for obesity 9).

Dupré et al. review the history of deep brain stimulation (DBS) in patients for treating obesity, describe current DBS targets in the brain, and discuss potential DBS targets and nontraditional stimulation parameters that may improve the effectiveness of DBS for ameliorating obesity. Deep brain stimulation for treating obesity has been performed both in animals and in humans with intriguing preliminary results. The brain is an attractive target for addressing obesity because modulating brain activity may permit influencing both sides of the energy equation-caloric intake and energy expenditure 10).

Tumor

Findings highlight obesity as a risk factor for overall brain/CNS tumors, meningiomas and gliomas among females, as well as for meningiomas among males 11).

For Niedermaier et al adiposity is related to enhanced risk for meningioma but is unassociated with risk for glioma. Based on a limited body of evidence, physical activity is related to decreased risk of meningioma but shows little association with risk of glioma 12).

References

1)

Dasenbrock HH, Nguyen MO, Frerichs KU, Guttieres D, Gormley WB, Ali Aziz-Sultan M, Du R. The impact of body habitus on outcomes after aneurysmal subarachnoid hemorrhage: a Nationwide Inpatient Sample analysis. J Neurosurg. 2016 Jul 15:1-11. [Epub ahead of print] PubMed PMID: 27419827.
2)

Almarzouqi SJ, Morgan ML, Lee AG. Idiopathic intracranial hypertension in the Middle East: A growing concern. Saudi J Ophthalmol. 2015 Jan-Mar;29(1):26-31. doi: 10.1016/j.sjopt.2014.09.013. Epub 2014 Sep 28. Review. PubMed PMID: 25859136; PubMed Central PMCID: PMC4314590.
3)

Li H, He D, Zheng D, Amsalu E, Wang A, Tao L, Guo J, Li X, Wang W, Guo X. Metabolically healthy obese phenotype and risk of cardiovascular disease: Results from the China Health and Retirement Longitudinal Study. Arch Gerontol Geriatr. 2019 Jan 25;82:1-7. doi: 10.1016/j.archger.2019.01.004. [Epub ahead of print] PubMed PMID: 30710843.
4)

Sani S, Jobe K, Smith A, Kordower JH, Bakay RA. Deep brain stimulation for treatment of obesity in rats. J Neurosurg. 2007 Oct;107(4):809-13. PubMed PMID: 17937228.
5)

Halpern CH, Wolf JA, Bale TL, Stunkard AJ, Danish SF, Grossman M, Jaggi JL, Grady MS, Baltuch GH. Deep brain stimulation in the treatment of obesity. J Neurosurg. 2008 Oct;109(4):625-34. doi: 10.3171/JNS/2008/109/10/0625. Review. PubMed PMID: 18826348.
6)

Mantione M, van de Brink W, Schuurman PR, Denys D. Smoking cessation and weight loss after chronic deep brain stimulation of the nucleus accumbens: therapeutic and research implications: case report. Neurosurgery. 2010 Jan;66(1):E218; discussion E218. doi: 10.1227/01.NEU.0000360570.40339.64. PubMed PMID: 20023526.
7)

Pisapia JM, Halpern CH, Williams NN, Wadden TA, Baltuch GH, Stein SC. Deep brain stimulation compared with bariatric surgery for the treatment of morbid obesity: a decision analysis study. Neurosurg Focus. 2010 Aug;29(2):E15. doi: 10.3171/2010.5.FOCUS10109. Review. PubMed PMID: 20672917.
8)

Torres N, Chabardès S, Benabid AL. Rationale for hypothalamus-deep brain stimulation in food intake disorders and obesity. Adv Tech Stand Neurosurg. 2011;36:17-30. doi: 10.1007/978-3-7091-0179-7_2. Review. PubMed PMID: 21197606.
9)

Ho AL, Sussman ES, Pendharkar AV, Azagury DE, Bohon C, Halpern CH. Deep brain stimulation for obesity: rationale and approach to trial design. Neurosurg Focus. 2015 Jun;38(6):E8. PubMed PMID: 26030708.
10)

Dupré DA, Tomycz N, Oh MY, Whiting D. Deep brain stimulation for obesity: past, present, and future targets. Neurosurg Focus. 2015 Jun;38(6):E7. PubMed PMID: 26030707.
11)

Sergentanis TN, Tsivgoulis G, Perlepe C, Ntanasis-Stathopoulos I, Tzanninis IG, Sergentanis IN, Psaltopoulou T. Obesity and Risk for Brain/CNS Tumors, Gliomas and Meningiomas: A Meta-Analysis. PLoS One. 2015 Sep 2;10(9):e0136974. doi: 10.1371/journal.pone.0136974. eCollection 2015. PubMed PMID: 26332834; PubMed Central PMCID: PMC4558052.
12)

Niedermaier T, Behrens G, Schmid D, Schlecht I, Fischer B, Leitzmann MF. Body mass index, physical activity, and risk of adult meningioma and glioma: A meta-analysis. Neurology. 2015 Sep 16. pii: 10.1212/WNL.0000000000002020. [Epub ahead of print] Review. PubMed PMID: 26377253.