KEY POINTS
- Question: What is the diagnostic accuracy of the currently available noninvasive methods for intracranial hypertension (ICH) monitoring?
- Finding: Several noninvasive intracranial pressure (ICP) monitors show promise as tools for diagnosing ICH.
- Meaning: Using multiple, readily available, noninvasive methods is better than reliance on a single sign such as physical examination or computed tomography (CT) alone.
Elevated intracranial pressure (ICP) is a common cause of secondary brain injury1 and can lead to decreased cerebral perfusion pressure. Untreated intracranial hypertension (ICH) can lead to brain herniation, ischemia, and death. Invasive ICP evaluation is the reference tool to monitor ICP.2,3 Persistent ICP of ≥20 mm Hg has been associated with poor outcomes after traumatic brain injury (TBI), subarachnoid hemorrhage, intracerebral hemorrhage, hydrocephalus, benign ICH, meningitis, stroke, and acute liver failure.4,5 Many guidelines indicate the invasive ICP monitoring for patients in whom there is a suspicion for ICH or impaired cerebral perfusion.6,7 However, invasive ICP monitoring is not available in all settings. This is especially true in emergency departments where immediate intervention for ICH can be necessary,8 and in centers with limited or no access to on-site neurosurgical input because only neurosurgeons have the skills to insert an ICP monitor in most hospitals.9 Even in circumstances where invasive ICP monitoring is available, patient factors can make it difficult or even contraindicated in some situations, for example, cases with hemostasis abnormalities, and instances where severe brain swelling has caused compressed ventricles.5 Furthermore, invasive monitoring can lead to several significant complications, including hemorrhage, infection, malfunction, and obstruction.10,11
The accessibility of precise tools to noninvasively estimate the ICP may improve the management of these patients. Current techniques rely on changes associated with increased ICP such as either physical examination signs; brain imaging and morphological findings from magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound (US); or indirectly transmitted ICP and physiological-based methods such as transcranial Doppler (TCD) including the pulsatility index (PI),12,13 fundoscopy, tympanometry, near-infrared spectroscopy, electroencephalography, visual-evoked potentials, and otoacoustic emissions assessment. The presence of such findings may help identify patients who may need invasive monitoring.6,7 Although these signs and methods are widely used, their diagnostic accuracy for the detection of ICH is unknown. With this in mind, this systematic review and meta-analysis aimed to investigate the diagnostic accuracy of the currently available noninvasive methods for ICP estimation.
METHODS
Search Strategy
This systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement14 (Supplemental Digital Content 1, Document, https://links.lww.com/AA/D192). The study protocol was registered on the International Prospective Register of Systematic Reviews (CRD 42019151818). In August 2019, we performed searches to identify pertinent studies on the following databases; PubMed, Institute of Science Index, Scopus, Cochrane Central Register of Controlled Trials (CENTRAL), and Embase. Prespecified search terms were utilized and adapted to each database to yield the most accurate results (Supplemental Digital Content 2, Document, https://links.lww.com/AA/D192). A manual search, using references of the included randomized controlled trials and the previous reviews, was conducted to retrieve relevant articles.15,16 Three reviewers independently screened titles and abstracts according to our inclusion and exclusion criteria and any disagreements were resolved through discussion.
Selection Criteria
The inclusion criteria were studies comparing reference versus noninvasive methods for ICP monitoring. Any original studies including clinical trials and observational studies with no restrictions regarding language, race, sex, country, year, and age were included. Our exclusion criteria were overlapped data sets and duplicated studies. Articles such as animal studies, case reports, previous reviews, conference, books, or thesis or author responses which do not have enough information to be extracted were excluded. Included studies were required to have a 2 × 2 table for the analysis constructed from the reported information, raw data, or sensitivity, and specificity of these methods. We contacted the authors if these values were not reported. All full texts were reviewed carefully by 3 independent reviewers, and, where there was any disagreement, it was resolved through discussion to reach a final decision.
Outcomes and Extracted Data
Table. -
A Description for the Included Diagnostic Techniques
| Test |
Description |
| US ONSD |
Distension or expansion of the sheath of the optic nerve measured by the US. |
| CT ONSD |
Distension or expansion of the sheath of the optic nerve measured by the CT. |
| MRI ONSD |
Distension or expansion of the sheath of the optic nerve measured by the MRI. |
| IOP |
The fluid pressure inside the eye. |
| PI |
It is a calculated flow parameter in US, derived from the maximum, minimum, and mean Doppler frequency shifts during a defined cardiac cycle and is used to assess the resistance in a pulsatile vascular system. |
| TCD |
It measures the velocity of blood flow through the brain’s vessels by measuring the echoes of US moving transcranially. |
| Papilledema |
Optic disk swelling that is caused by increased intracranial pressure. |
| Compression or absence of basal cisterns |
Compression or absence of basal cisterns which are one of the subarachnoid cisterns. It is a wide cerebrospinal fluid-filled cavity between the 2 temporal lobes anteriorly and encloses the cerebral peduncles as well as structures contained within the interpeduncular fossa. |
| Midline shift |
It happens when the pressure exerted by the build-up of blood and swelling around the brain is powerful enough to push the entire brain off-center. |
| Marshall score |
As classification of TBI, it is a CT scan to predict outcome in patients with TBI using some features such as swelling degree, determined by midline shift and/or compression of basal cisterns presence and size of contusions/hemorrhages. It places patients into 1 of 6 categories. Higher categories have worse prognosis and survival. |
| Pupillary dilation |
Dilation of the pupil size. |
| Decreased level of consciousness |
A Glasgow Coma Scale/Score of ≤8. |
| Motor posturing |
A Glasgow Coma Scale/Score of ≤3. |
| Tight subarachnoid spaces |
Tightness or narrowing of the subarachnoid space which caused by the high intracranial pressure. |
| Slit-like ventricles |
Tightness or narrowing of the ventricle which caused by the high intracranial pressure. |
| Sinus stenosis |
Stenosis of the sinuses such as the transverse sinus. |
| Pituitary deformity |
Deformity, distortion, or malformation of the pituitary gland caused by the high intracranial pressure. |
| ON tortuosity |
Tortuous optic nerves are abnormally curvatured optic nerves by intracranial hypertension. |
| ON enhancement |
Optic nerve enhancement is the increase in contrast on MRI. |
| Meckel caves abnormality |
Abnormality, malformation, or distortion of the Meckel cave which is a dural recess in the posteromedial portion of the middle cranial fossa that acts as a conduit for the trigeminal nerve between the prepontine cistern and the cavernous sinus. |
| ON protrusion |
Optic nerve protrusion |
| Posterior globe flattening |
Flattening of the posterior aspect of the optic globe—defined as straightening of the normal outward convexity of the sclera at the area of attachment to the optic nerve. |
| Inferior position of cerebellar tonsils |
Downward displacement of cerebellar tonsils as compared to normal anatomical location. |
| Empty sella |
When the pituitary fossa was filled with cerebrospinal fluid. |
| Cephaloceles/meningoceles |
Bulging or herniation of brain, dura mater, arachnoid, or cerebrospinal fluid. |
Abbreviations: CT, computed tomography; IOP, intraocular pressure; MRI, magnetic resonance imaging; ON, optic nerve; ONSD, optic nerve sheath distension; PI, pulsatility index; TBI, traumatic brain injury; TCD, transcranial Doppler; US, ultrasound.
A standardized data extraction sheet was produced in Microsoft Excel for data extraction by 3 independent authors. The extracted information included the authors’ names, study design, year, number of patients, country, and type of standard/noninvasive methods. Moreover, patients’ demographics (such as age and sex), pathology, delay, or timing between both methods and definition of the ICH were extracted. A discussion was held where any disagreements existed. In these instances, a conclusion was made with consensus agreement between the 3 authors and, if needed, a fourth author. Articles published by the same research group and/or studying the same variables were examined for potential duplicate information based on the year of patients’ recruitment and hospital where the patients were recruited and confirmation from authors of the study. The Table contains descriptions for the included noninvasive diagnostic tests.
Quality Assessment
We used the quality assessment of diagnostic accuracy studies (QUADAS-2) method. The QUADAS-2 evaluates 4 items for bias and applicability of the research question including patients’ selection, index test, reference standard, and flow and timing.17 The quality of the included studies was evaluated by 3 authors independently and if any disagreement occurred, it was resolved through discussion.
Statistical Analysis
The quantitative analysis was conducted if there were at least 2 studies evaluating a specific test in diagnosing ICH. The accuracy measures included the sensitivity, specificity, likelihood ratios, and diagnostic odds ratio (DOR) with their associated 95% confidence intervals (CIs). A higher DOR indicates a higher diagnostic accuracy. AUC values of ≥0.5, 0.75, 0.93, or 0.97 were considered to represent fair, good, very good, or excellent accuracy, respectively.18 Moreover, we also constructed a hierarchical summary receiver operator curve (SROC) for the ICP assessment methods. A fixed-effect method19 was applied when there was no evidence of heterogeneity between studies, otherwise, a random-effects method was chosen.20 The heterogeneity between studies was evaluated using Q statistic and I2 test,20–23 where P = .1 and/or I2 >50% indicating a significant heterogeneity.24–26 The heterogeneity was explored using metaregression, and sensitivity as well as subgroup analysis according to the potential covariates such as study design, risk of bias, ICH prevalence, pathology, patients’ age, females’ percent, the ICH, and the cutoff value of the optic nerve sheath diameter (ONSD) and the time between the reference and noninvasive assessment. The metaregression has been used to explore between-study heterogeneity in meta-analysis studies aiming to incorporate the effect of the aforementioned covariates on summary measures of performance. Indeed, the heterogeneity in the diagnostic accuracy could originate from several causes related to definitions of the test and reference standards, characteristics of the test, methods of data collection, and patients’ characteristics. Thus, covarying factors were introduced into a regression with any test performance measure as the dependent variable. Since the publication bias analysis is a concern for meta-analysis, it was conducted using a funnel plot and Egger test.27 We used the Midas command in Stata Statistical Software Release 12 (StataCorp LP, College Station, TX) for the analysis.28 A P value <.05 was considered significant.
RESULTS
Search Results
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Figure 1.: The PRISMA chart showing the flow of publications via the review process. ICH indicates intracranial hypertension; ICP, intracranial pressure; ISI, Institute for Scientific Information; PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-analyses.
Our search retrieved 1447 articles, among which 565 duplicates were removed. The rest underwent abstract screening to yield 276 articles for full-text screening. Ultimately, a total of 134 articles with 14,799 individuals were included in our study (Figure 1).
Studies and Patients’ Characteristics
There were 91 prospective studies with predominantly males (59.75%). Moreover, there were more studies that included mainly adult patients (109) than children (19 studies). The primary diagnosis was TBI in 36 studies and idiopathic intracranial hypertension (IIH) in 27 studies (Supplemental Digital Content 2, Table S1, https://links.lww.com/AA/D192). The reference test varied and included lumbar puncture, intraventricular or intraparenchymal monitor, CT, MRI, modified Dandy criteria, and Friedmann 2002 or 2013 criteria. The timing or delay between the reference and the noninvasive method was simultaneous in 26 studies and within an hour in 16 studies. The most frequently evaluated method was the US ONSD (50 studies), followed by papilledema (24 studies), empty sella (17 studies), and MRI ONSD (15 studies) (Supplemental Digital Content 2–3, Table S2, Document, https://links.lww.com/AA/D192).
Quality Assessment
Of the studies, 45 were considered to be at low risk of bias, while the remaining were at high risk of bias (Supplemental Digital Content 2, Table S3, Figure S1, https://links.lww.com/AA/D192).
Quantitative Synthesis
Optic Nerve Sheath Diameter.
Figure 2.: The diagnostic accuracy of US ONSD for diagnosis of ICH. A, Forest plot showing the sensitivity and specificity with its 95% CI. B, Forest plot showing the positive and negative LR with its 95% CI. C, Forest plot showing the diagnostic score and DOR with its 95% CI. D, The SROC and the AUC with each circle indicate an individual study in the meta-analysis. The curve is the regression that summarizes the overall diagnostic accuracy. AUC indicates area under the curve; CI, confidence interval; DLR, diagnostic likelihood ratio; DOR, diagnostic odds ratio; ICH, intracranial hypertension; LR, likelihood ratio; SENS, sensitivity; SPEC, specificity; SROC, summary receiver operator curve; US ONSD, ultrasonographic optic nerve sheath diameter.
The US ONSD had a high diagnostic accuracy (number of studies = 50, estimated sensitivity of 90% [87–92], estimated specificity of 88% [84–91], DOR of 63 [43–94]) while the MRI had estimated sensitivity of 77% (64–87), estimated specificity of 89% (84–93), DOR of 29 (13–64), and the CT ONSD had estimated sensitivity of 93% (90–96), estimated specificity of 79% (56–92), DOR of 53 (18–156; Figure 2).
MRI Signs.
All MRI signs had a very high estimated specificity ranging from 90% to 99% but a low estimated sensitivity with the exception of sinus stenosis (SS), which was found to have an excellent diagnostic accuracy (number of studies = 13, estimated specificity and sensitivity of 96% [91–99] and 90% [75–96], respectively).
Physical Examination Signs.
Among the physical examination signs, pupillary dilation had a high estimated specificity (86% [76–93]).
Other good diagnostic tests included PI (number of studies = 6, estimated sensitivity and specificity of 84% [55–96] and 94% [89–97], respectively), papilledema (number of studies = 24, estimated specificity of 95% [92–97]), TCD (number of studies = 7, estimated sensitivity of 87% [80–92]), compression or absence of basal cisterns (number of studies = 6, estimated sensitivity of 96% [55–100]), while ≥10 mm midline shift had a good estimated specificity (91% [75–97]).
In addition, we did not find any significant publication bias except for the optic nerve (ON) tortuosity analysis (P = .024). However, there was significant heterogeneity in most analyses (Supplemental Digital Content 3, Document, https://links.lww.com/AA/D192).
Subgroup Analysis and Metaregression
We used subgroup analysis and metaregression to see the effect of covariates and heterogeneity on the diagnostic accuracy of the included methods. Of note, little heterogeneity was found. However, setting the cutoff value of ICH to ≥20 mm Hg instead of values <20 mm Hg was associated with higher sensitivity. Moreover, if the delay between both methods was <1 hour, the MRI ONSD had a significantly higher sensitivity and specificity while papilledema had higher specificity compared to the >1 hour subgroup (Supplemental Digital Content 4, Document, https://links.lww.com/AA/D192).
DISCUSSION
Our comprehensive systematic review and meta-analysis summarized the currently available noninvasive methods for measuring ICP. We have found several tools with good diagnostic accuracy for ICP estimation. We documented that US ONSD, all analyzed MRI signs, especially SS, PI, pupillary dilation, papilledema, compression or absence of basal cisterns, ≥10 mm midline shift, and TCD had good sensitivity and/or specificity.
US ONSD is a simple bedside tool, widely used in emergency departments.29 The sheath enveloping the ON is in continuity with the dura mater and the cerebrospinal fluid (CSF)–containing subarachnoid space of the brain,30 and because the ON sheath (ONS) is distensible, when ICP increases, the pressure in the ONS increases linearly31 as early as 4 hours following trauma,32 particularly in the anterior, retro-bulbar compartment.33 A previous report showed that using the intrathecal infusion method varies the ONSD with alteration of lumbar CSF pressure.34 In contrast, Tamburrelli et al35 demonstrated that the ONS expands when the diastolic ICP is ≥13–14 mm Hg. Additionally, a simultaneous linear correlation was seen between ONSD and ICP increase. Of note, these changes in the ONS happen before the nerve alterations, such as papilledema, become visible on the fundoscopic examination which takes hours to days to develop.36 Several studies have examined covariates influencing the US ONSD accuracy. Romagnuolo et al37 showed that the ONSD does not change with patients’ position. Indeed, US ONSD appears to be superior to some CT- or magnetic resonance (MR)-morphological changes such as the size of ventricle, sulci, basilar cistern, gray/white matter differentiation, and degree of transfalcine herniation.38 Compared with CT and MR, US is of low cost, readily available, does not need long acquisition times or require harmful patient transport, and some reports documented a small intra-/interobserver variation for the US ONSD.39 The measurements are highly repeatable compared to CT or MRI,33 even for novice operators taught in a single training session.40 Moreover, US ONSD findings can indicate when more complex imaging, such as CT or MRI, is required. Yet, US is liable to artifacts,41 and assessing the ONSD in off-axis may lead to an erroneous value.
CT signs such as basal cisterns abnormality (with very high sensitivity) and ≥10 mm midline shift (with high specificity) were found to be promising clinical tools for accurately and quickly predicting and diagnosing patients having clinical signs or symptoms of ICH. It was suggested that CT findings may have greater accuracy for diagnosing ICH compared to physical examination,42 and several studies used CT as the standard technique for pressure monitoring. Compression or effacement of the basal cisterns may happen because of increased parenchymal edema and was suggested as a sensitive predictor of ICH.43 It is noteworthy that worsening shift was suggested to be associated with higher ICP,42 yet an important reminder to physicians is that severe edema can lead to ICH, without evidence of shift on the CT scan. As of today, some recommendations support invasive monitoring only in TBI individuals with physical examination and CT signs of ICH.7,44,45 We did not find any of those physical examination signs alone as independently sensitive or specific enough to diagnose ICH. Physicians without access to other tools of monitoring should not rely only on these signs in patient’s management; however, a more comprehensive view should be taken, with special attention on patient’s characteristics, characteristics associated with the brain injury, and clinical signs.45 Indeed, CT imaging is readily available and not operator dependent. Furthermore, CT aids in determining which management strategy to begin. The CT scan does not, however, allow for continuous monitoring. The fact that CT is based on x-rays and ionizing radiation is an additional disadvantage. This is an especially significant disadvantage in younger patients requiring several measurements owing to their higher susceptibility to radiation and longer premorbid life expectancy.46
MRI signs with their high diagnostic accuracy, especially SS, were found to be reliable with high accuracy, as well as reproducibility. Transverse sinus diameter was shown to correlate to invasive venous pressure gradients in patients with IIH47 and was reported to increase after lumbar puncture.48 Precise monitoring of transverse sinus diameter could not only be important to diagnose IIH but also to evaluate the treatment effect. Indeed, MRI was used in ICP monitoring in hydrocephalus49 and cerebral arteriovenous malformations with the monitoring of CSF as well as blood dynamics.50 Notwithstanding, this technique could not be used for continuous monitoring or repeated ICP monitoring and it needs a good choice of accurate imaging slices and the selection of the candidate blood vessels.51 Further, its restricted availability and imaging time constraints limit its widespread use as a real-time monitor of the pressure. It is also important to note that MRI signs predicting ICH, specifically pituitary height and globe configuration, may persist after papilledema and ICH have settled.52
TCD is a safe, reproducible method with no major complications to monitor ICP and to detect specific changes in cerebral blood flow velocity (FV). It is noteworthy that TCD has been used for the detection of cerebral embolization, vasospasm, arterial stenoocclusive disease, cerebral circulatory arrest, vasospasm in subarachnoid hemorrhage, and the evaluation of TBI, collateral circulation, recanalization, cerebrovascular autoregulation, and for measuring ICP.53 TCD creates a velocity-time waveform of cerebral blood flow from which the peak systolic velocity (PSV) and end diastolic velocity (EDV) flow rates can be calculated. The mean flow velocity (MFV), resistance index (RI), an indicator of resistance of an organ to perfusion, and the PI, a reflection of resistance encountered with the cardiac cycle, are commonly reported derivations from the waveform display with the PI as the most widely evaluated method.54 Klingelhöfer et al55 showed that ICP influenced TCD flow patterns. With ICH, there was a further decline in the MFV and EDV with an increased RI. The indices are based on the change that occurs in the TCD-derived pulse curve when the intracranial hemodynamic changes. As ICP increases, the diastolic FV is more reduced compared with the systolic FV, resulting in an increased pulse peak between the diastole and the systole and hence in the PI and RI. However, TCD practice needs training, and there are also intra- and interobserver variations.56 Further, it sometimes is not applicable due to the absence of a proper bone window for the US. Despite high pooled SROC, the variation in the cutoffs urges that clinicians should pay attention while using the PI and US ONSD. Additionally, US ONSD could be challenging to perform in patients with facial trauma and is contraindicated in suspected globe injury.57
In respect to ICP accuracy, it is known that even the standard invasive techniques might not show the specified limits for error, especially with intraparenchymal microtransducers.58,59 Thus, it is questionable if these accuracy requirements are realistic for all sorts of ICP monitoring. An important thought that should be borne in mind is that ICP is not solely a number; dynamic features of this parameter, such as its waveform and relative changes in time, are essential for proper monitoring of the clinical state of the patient.60 We evaluated these findings independently because only a few included articles investigated the diagnostic accuracy of combined criteria, which almost yielded a higher accuracy.61–64 Yet, clinicians use a combination of signs to have a diagnosis in clinical practice. A prospective data collection and a multivariable prediction model is required to derive a robust score for ICH diagnosis, which ideally should also incorporate clinical parameters according to multiple potential signs in combination. Indeed, continuous ICP evaluation makes timely detection and tracking changes of ICP more feasible. Undoubtedly, the ideal noninvasive monitoring method has to monitor ICP bilaterally, be of low cost, readily available (in particular, in emergency departments), risk-free, operator-independent, as well as of high diagnostic accuracy.
Our findings agree with previous systematic reviews,57,65–67 although we included more studies. Moreover, we included missing data given by included article’s authors, conducted risk of bias evaluation, and provided sensitivity analysis through removing articles with a high risk of bias. However, we have some limitations. We acknowledge that all of the available noninvasive techniques described for measuring the ICP have not been systematically reviewed nor meta-analyzed. Although the included diagnostic tests were investigated near to the reference method, several studies did not mention the timing between both methods, yet we did a sensitivity analysis through removing these studies and that has not changed our findings for most methods. Furthermore, some techniques have been only demonstrated in a small number of studies; consequently, the diagnostic accuracy of these techniques needs further validation by future studies. Although the ONSD had high diagnostic accuracy, no unified cutoff is present, and its accuracy can be influenced by clinician experience. With this in mind, due diligence should be made while interpreting ONSD findings. Finally, we could not compare the noninvasive diagnostic tests with each other because there were different reference tests across the studies. Thus, future clinical studies need to compare them within the same study cohort to investigate their diagnostic accuracy against each other.
CONCLUSIONS
Our study showed several promising tools for diagnosing ICH noninvasively. Moreover, we demonstrated that using multiple readily available noninvasive methods is better than depending on a single sign such as physical examination or CT alone and the absence of physical signs is not sufficient to exclude ICH. In cases where there is any suspicion for ICH, physicians should always undertake a comprehensive review of patients, with empirical management considered if necessary.
ACKNOWLEDGMENTS
We thank all authors of the included studies who helped us in this study by providing us with the missing raw data that allowed us to complete the analysis and make the study more rigorous.
DISCLOSURES
Name: Amr Sallam, MD, FCAI.
Contribution: This author helped create the idea of the research, database search, data extraction, revision, editing and approval of the final manuscript.
Name: Ahmed Abdelaal Ahmed Mahmoud M. Alkhatip, MD, EDAIC, FCAI.
Contribution: This author helped create the idea of the research, database search, data extraction, writing the primary draft, revision, editing, and approval of the final manuscript.
Name: Mohamed Gomaa Kamel, MBBCh.
Contribution: This author helped perform a systematic literature search, data extraction, and tabulation, statistical analysis, writing the initial draft of the methods and results, revision, editing, and approval of the final manuscript.
Name: Mohamed Khaled Hamza, MD.
Contribution: This author helped in data extraction, revision, editing, and approval of the final manuscript.
Name: Hany Mahmoud Yassin, MD.
Contribution: This author helped in the literature search, data extraction, writing the primary draft, revision, editing, and approval of the final manuscript.
Name: Hisham Hosny, MD.
Contribution: This author helped in the literature search, data extraction, revision, editing, and approval of the final manuscript.
Name: Mohamed I. Younis, FCAI.
Contribution: This author helped in the literature search, data extraction, revision, editing, and approval of the final manuscript.
Name: Eslam Ramadan, MD, FCAI.
Contribution: This author helped in the literature search, data extraction, revision, editing, and approval of the final manuscript.
Name: Haytham Zien Algameel, MD.
Contribution: This author helped in the literature search, data extraction, revision, editing, and approval of the final manuscript.
Name: Mohamed Abdelhaq, MD.
Contribution: This author helped in the literature search, data extraction, revision, editing, and approval of the final manuscript.
Name: Mohamed Abdelkader, MD, EDAIC.
Contribution: This author helped in the literature search, data extraction, revision, editing, and approval of the final manuscript.
Name: Kerry E. Mills, PhD.
Contribution: This author helped in the statistical analysis, revision, editing, and approval of the final manuscript.
Name: Hassan Mohamed, MD, FCAI.
Contribution: This author helped in the literature search, data extraction, revision, editing, and approval of the final manuscript.
This manuscript was handled by: Thomas M. Hemmerling, MSc, MD, DEAA.
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