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      A Male Patient with Hydrocephalus via Multimodality Diagnostic Approaches: A Case Report

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      1 , 2 , * , , 1 , 1 , 3 , 3 , 4 , 3 , 3 , * , , 1 , 2 , * ,
      Cyborg and Bionic Systems
      AAAS

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          Abstract

          Introduction: Idiopathic normal pressure hydrocephalus (iNPH) is a kind of hydrocephalus that is easily to be misdiagnosed with brain atrophy due to the similarity of ventricular dilation and cognitive impairment. In this case, we present an old male patient who was diagnosed with iNPH by multimodality approaches. Outcomes: A 68-year-old male patient, with deteriorated gait, declined cognitive function for at least 3 years and urinary incontinence for 3 months. The doctors suspected him a patient with hydrocephalus or Alzheimer's disease based on his symptoms. We used multimodality diagnostic approaches including brain imaging, cerebrospinal fluid tap test, continuous intracranial pressure monitoring, and infusion study to make the final diagnosis of iNPH. He underwent ventriculoperitoneal shunt surgery and was well recovered. Conclusion: This case demonstrates the efficacy of using multimodality approaches for iNPH diagnosis, which saves patient time and clinical cost, worthy of further promotion.

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          Most cited references17

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          SYMPTOMATIC OCCULT HYDROCEPHALUS WITH "NORMAL" CEREBROSPINAL-FLUID PRESSURE.A TREATABLE SYNDROME.

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            Dutch normal-pressure hydrocephalus study: prediction of outcome after shunting by resistance to outflow of cerebrospinal fluid.

            The authors examined whether measurement of resistance to outflow of cerebrospinal fluid (Rcsf) predicts outcome after shunting for patients with normal-pressure hydrocephalus (NPH). In four centers 101 patients (most of whom had idiopathic NPH) who fulfilled strict entry criteria underwent shunt placement irrespective of their level of Rcsf obtained by lumbar constant flow infusion. Gait disturbance and dementia were quantified by using an NPH scale and the patient's level of disability was assessed by using the modified Rankin scale (mRS). In addition the Modified Mini-Mental State Examination was performed. Patients were assessed prior to and 1, 3, 6, 9, and 12 months after surgery. Primary outcome measures were based on differences between the preoperative and last NPH scale scores and mRS grades. Improvement was defined as a change measuring at least 15% in the NPH scale score and at least one mRS grade. Intention-to-treat analysis of all patients at 1 year yielded improvement for 57% in NPH scale score and 59% in mRS grade. Efficacy analysis, excluding serious events and deaths that were unrelated to NPH, was performed for 95 patients. Improvement rose to 76% in NPH scale score and 69% in mRS grade. Six cut-off levels of Rcsf were related to improvement in NPH scale score using two-by-two tables. Positive predictive values were approximately 80% for an Rcsf of 10, 12, or 15 mm Hg/ml/minute, 92% for an Rcsf of 18 mm Hg/ml/minute, and 100% for an Rcsf of 24 mm Hg/ml/minute. Negative predictive values were low. More important was the highest likelihood ratio of 3.5 for an Rcsf of 18 mm Hg/ml/minute. Extensive comorbidity was a major prognostic factor. Measurement of Rcsf reliably predicts outcome if the limit for shunting is raised to 18 mm Hg/ml/minute. At lower Rcsf values the decision depends mainly on the extent to which clinical and computerized tomography findings are typical of NPH.
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              Epidemiology of Idiopathic Normal Pressure Hydrocephalus: A Systematic Review of the Literature.

              Idiopathic normal pressure hydrocephalus (iNPH) is an important cause of gait disturbance and cognitive impairment in elderly adults. However, the epidemiology of iNPH is relatively unknown, largely as a result of the paucity of specifically designed population studies. This systematic review aims to assess the prevalence and incidence of iNPH.
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                Author and article information

                Journal
                Cyborg Bionic Syst
                Cyborg Bionic Syst
                CBSYSTEMS
                Cyborg and Bionic Systems
                AAAS
                2097-1087
                2692-7632
                01 July 2024
                2024
                : 5
                : 0135
                Affiliations
                [ 1 ]State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University , Tianjin 300072, China.
                [ 2 ] Haihe Laboratory of Brain Computer Interaction and Human-Machine Integration , Tianjin 300380, China.
                [ 3 ]Department of Neurosurgery, Tianjin Medical University General Hospital , Tianjin 300070, China.
                [ 4 ]Department of Neurosurgery, Tianjin Huanhu Hospital , Tianjin 300060, China.
                Author notes
                [*] [* ]Address correspondence to: xiuyun_liu@ 123456tju.edu.cn (X.L.); huijiewei@ 123456126.com (H.Y.); richardming@ 123456tju.edu.cn (D.M.)
                [†]

                These authors contributed equally to the work.

                Article
                0135
                10.34133/cbsystems.0135
                11321655
                39139629
                f7410b05-989c-434e-bf4d-3231215d481d
                Copyright © 2024 Xiuyun Liu et al.

                Exclusive licensee Beijing Institute of Technology Press. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY 4.0).

                History
                : 05 March 2024
                : 09 May 2024
                : 01 July 2024
                Page count
                Figures: 2, Tables: 0, References: 17, Pages: 0
                Funding
                Funded by: National Key Technologies Research and Development Program;
                Award ID: 2021YFF1200602
                Award Recipient : Xiuyun Liu
                Funded by: National Defense Science and Technology Innovation Fund of Chinese Academy of Sciences;
                Award ID: c02022088
                Award Recipient : Xiuyun Liu
                Funded by: Tianjin Science and Technology Program;
                Award ID: 20JCZDJC00810
                Award Recipient : Meijun Pang
                Funded by: Tianjin University Innovation Fund;
                Award ID: 020/0903065111
                Award Recipient : Xiuyun Liu
                Categories
                Rapid Report

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