60 resultados para CAVAN-MONAGHAN
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Monaghan General Hospital – Proposals for further and future development The Independent Review Panel recommended a review of the existing protocol for emergency obstetric cases presenting at Hospitals such as Monaghan which have no on-site obstetric expertise, and the implementation of a revised protocol. They also recommended that each maternity incident should be reviewed by a multidisciplinary team from the Cavan Monaghan Group. Click here to download PDF 49kb Appendix PDF 2.5mb
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Background: Duration of untreated psychosis (DUP) depends on several factors, including socio-demographic, socioeconomic, clinical and contextual circumstances, such as availability of mental health services. Living arrangements may also play a role, especially in low- and middle-income countries, where most people who develop psychosis live with their relatives. Methods: Population-based study of first-episode psychosis in Sao Paulo, Brazil. Participants were aged 18-64 years, lived in a defined geographic area of the city and had a first contact in life with mental health services due to a psychotic episode. Duration of untreated psychosis was defined as the period between onset of first psychotic symptom and first contact with health service due to psychosis. The median DUP was used to classify participants into short and long DUP. Psychopathology, social adjustment and psychiatric diagnoses were made with standardized assessments. Type of service sought and living arrangements were examined. Results: Two hundred participants were included (52% women, 61% non-affective psychoses). The median DUP was 4.1 weeks (inter-quartile range: 1.9-11.4), and was shorter for affective psychoses. Most participants had their first contact with psychiatric emergency services. Those who did not live with a relative (children older than 18 years, parents, partner) were more likely to present long DUP (OR: 2.63; 95%Cl: 0.98-7.04); p = 0.05). Conclusion: The DUP in Sao Paulo was shorter than expected. Living arrangements may play an important role in shortening the DUP in urban centres of low- and middle income countries that have a network of mental health services. (C) 2009 Elsevier B.V. All rights reserved.
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The Minister for Health and Children convened a Panel and requested an independent evaluation be carried out of the report of the North Eastern Health Board into the handling of an obstetrical emergency at the Cavan Monaghan Hospital Group on 11 December 2002. Â Report of the Independent Review Panel North Eastern Health Board Report
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 Click here to download PDF 222KB Please scroll down for related documents  Related Documents: HSE National and Regional Progress Reports HSE – Key Deliverables 2009 – Report PDF 55KB HSE – National Report PDF 363KB HSE – Regional Report – Dublin Mid Leinster PDF 82KB HSE – Regional Report – Dublin North East PDF 89KB HSE – Regional Report – West PDF 91KB HSE – Regional Report -South PDF 152KB HSE Local Area Progress Reports HSE – Tipperay South PDF 395KB HSE – Tipperary North PDF 367KB HSE Sligo/Leitrim and West Cavan PDF 359KB HSE – Roscommon PDF 352KB HSE – Mayo PDF 338KB HSE – Louth/Meath PDF 525KB HSE – Limerick PDF 395KB HSE – Laois/Offaly PDF 366KB HSE – Kildare/West Wicklow PDF 317KB HSE – Galway West PDF 297KB HSE – Galway/Mayo and Roscommon Child and Adolescent PDF 59KB HSE – Galway East PDF 400KB HSE – Dun Laoghaire PDF 262KB HSE – Dublin West South West PDF 346KB HSE – Dublin South City PDF 361KB HSE – Dublin North PDF 371KB HSE – Dublin North West PDF 432KB HSE – Dublin North – Dublin Central & part of NW Dublin – Child and Adolescent PDF 53KB HSE – Dublin North Central PDF 341KB HSE – Donegal PDF 485KB HSE – Cork West PDF 424KB HSE – Cork South Lee PDF 469KB HSE – Cork North PDF 423KB HSE – Cavan/Monaghan PDF 371KB HSE – Carlow/Kilkenny PDF 451KB Progress Reports from Government Departments Department of Community Rural and Gaeltacht Affairs PDF 20KB Department of Education and Science PDF 121KB Department of Enterprise Trade and Employment PDF 25KB Department of Environment Heritage and Local Government PDF 47KB Department of Health and Children PDF 50KB Department of Justice Equality and Law Reform PDF 19KB Department of Social and Family Affairs PDF 27KB Submissions Received by the IMG Amnesty International Ireland submission PDF 87KB Association of Occupational Therapists submission PDF 81KB College of Psychiatry of Ireland submission PDF 21KB Disability Federation of Ireland submission PDF 81KB Health Research Board submission PDF 24KB Inclusion Ireland submission PDF 18KB Independent Mental Health Sevice Providers submission PDF 82KB Irish Association of Consultants in Psychiatry of Old Age submission PDF 37KB Irish College of General Practitioners submission PDF 25KB Irish Hospital Consultancts Association submission PDF 155KB Irish Medical Organisation submission PDF 63KB Irish Mental Health Coalition submission PDF 90KB Mental Health Commission submission PDF 64KB Mental Health Nurse Managers submission PDF 206KB National Council for the Professional Development of Nursing and Midwifery submission PDF 67KB National Disability Authority submission PDF 49KB National Service Users Executive submission PDF 28KB Neurobehaviour Clinic – National Rehabilitation Hospital submission PDF 24KB Neurological Alliance of Ireland submission PDF 20KB
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[1] Union: Clogher/Counties: Monaghan & Tyrone -- [2] Union: Castlerea/Counties: Roscommon & Mayo -- [3] Union: Castletowndelvin/Counties: Meath & Westmeath -- [4] Union: Cootehill/County: Cavan -- [5] Union: Clifton/County: Galway, in which is included the Island of Inishbofin in the County of Mayo -- [6] Union: Claremorris/County: Mayo -- [7] Union: Cootehill/County: Managhan -- [8] Union: Clones/(Part of) County: Monaghan -- [9] Union: Ardee/Counties: Louth & Meath -- [10] Union: Bailieborough/County: Cavan -- [11] Union: Ballina/Counties: Mayo & Sligo -- [12] Union: Ballinasloe/County: Roscommon -- [13] Union: Ballinrobe/County: Mayo -- [14] Union: Ballymahon/Counties: Longford & Westmeath -- [15] Union: Ballymahon/County: Westmeath -- [16] Union: Ballyshannon/County: Donegal -- [17] Union: Ballyshannon/County: Leitrim -- [18] Union: Ballyvaghan/County: Clare -- [19] Union: Baltinglass/County: Wicklow -- [20] Unions: Bandon & Kinsale/County: Cork -- [21] Union: Bawnboy/County: Cavan -- [22] Union: Bawnboy/County: Leitrim -- [23] Union: Belmullet/County: Mayo -- [24] Union: Carrick-on-Shannon/County: Roscommon -- [25] Union: Carrickmacross/County: Monaghan -- [26] Union: Castlebar/County: Mayo -- [27] Union: Castleblayney (part of)/County: Monaghan -- [28] Union: Corrofin/County: Clare -- [29] Barony: Upper Deece/County: Meath -- [30] Barony: Cork/County: Cork -- [31] Barony: Coshmore & Coshbride/County: Waterford -- [32] Barony: Trough/County: Monaghan -- [33] Union: Donegal/County: Donegal -- [34] Union: Drogheda/Counties: Louth & Meath -- [35] Union: Dromore, West/County: Sligo -- [36] Union: Dunfanaghy/County: Donegal -- [37] Unions: Cahersiveen, Kenmare, and Killarney/County: Kerry -- [38] Barony: Dunkerron South/County: Kerry -- [39] Union: Dunshaughlin/County: Meath -- [40] Union: Edenderry/County: Meath -- [41] Union: Edenderry/County: Kildare -- [42] Union: Edenderry/King's County -- [43] Union: Enniskillen/County: Cavan -- [44] Union: Ennistimon/County: Clare -- [45] Barony: Glenahiry/County: Waterford -- [46] Union: Gort/Counties: Galway & Clare -- [47] Union: Granard/County: Longford -- [48] Union: Granard/County: Westmeath -- [49] Barony: Iffa & Offa West/County: Tipperary -- [50] Barony: Imokilly/County: Cork -- [51] Union: Kells/County: Meath -- [52] Barony: Kenry/County: Limerick -- [53] Barony: Kerrycurrihy/County: Cork -- [54] Barony: Kilculliheen/County: Waterford -- [55] Union: Killadysert/County: Clare -- [56] Union: Killala/County: Mayo -- [57] Union: Letterkenny/County: Donegal -- [58] Union: Limerick/County: Limerick -- [59] Union: Longford/County: Longford -- [60] Barony: Magunihy/County: Kerry -- [61] Unions: Mallow & Cork/County: Cork -- [62] Union: Manorhamilton/County: Leitrim -- [63] Union: Millford/County: Donegal -- [64] Union: Mountbellew/County: Galway -- [65] Union: Naas/County: Wicklow -- [66] Union: Navan/County: Meath -- [67] Union: Newport/County: Mayo -- [68] Union: Oldcastle/County: Meath -- [69] Barony: Upper Ormond/County: Tipperary, North Riding -- [70] Barony: Orrery & Kilmore/County: Cork -- [71] Union: Oughterard/ Counties: Galway & Mayo together with that portion of the Union of Ballinrobe in the County of Galway -- [72] Union: Portumna/County: Galway -- [73] Barony: Rathdown/County: Wicklow -- [74] Barony: Salt/County: Kildare -- [75] Barony: South Salt/County: Kildare -- [76] Union: Scarriff/Counties: Clare & Galway -- [77] Union: Shillelagh/County: Wicklow -- [78] Union: Stranorlar/County: Donegal -- [79] Union: Tobercurry/County: Sligo -- [80] Union: Trim/County: Meath -- [81] Barony: Trughanacmy/County: Kerry -- [82] Barony: Upperthird/County: Waterford -- [83] Union: Wexford/County: Wexford -- [84] Barony: Castleknock/County: Dublin -- [85] Barony: Balrothery, East/County: Dublin -- [86] Barony: Newcastle/County: Dublin -- [87] City of Dublin, North Dublin Union, Arran Quay Ward -- [88] City of Dublin, South Dublin Union, Fitzwilliam Ward -- [89] City of Dublin, North Dublin Union, Inns Quay Ward -- [90] City of Dublin, South Dublin Union, Mansion House Ward -- [91] City of Dublin, South Dublin Union, Merchants' Quay Ward -- [92] City of Dublin, North Dublin Union, Mountjoy Ward -- [93] City of Dublin, North Dublin Union, North Dock Ward -- [94] City of Dublin, North Dublin Union, North City Ward -- [95] City of Dublin, North Dublin Union, Rotundo Ward -- [96] City of Dublin, South Dublin Union, Royal Exchange Ward -- [97] City of Dublin, South Dublin Union, South City Ward -- [98] City of Dublin, South Dublin Union, South Dock Ward -- [99] City of Dublin, South Dublin Union, Trinity Ward -- [100] City of Dublin, South Dublin Union, Usher's Quay Ward -- [101] City of Dublin, South Dublin Union, Wood Quay Ward.
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Tyrosine hydroxylase deficiency is an autosomal recessive disorder resulting from cerebral catecholamine deficiency. Tyrosine hydroxylase deficiency has been reported in fewer than 40 patients worldwide. To recapitulate all available evidence on clinical phenotypes and rational diagnostic and therapeutic approaches for this devastating, but treatable, neurometabolic disorder, we studied 36 patients with tyrosine hydroxylase deficiency and reviewed the literature. Based on the presenting neurological features, tyrosine hydroxylase deficiency can be divided in two phenotypes: an infantile onset, progressive, hypokinetic-rigid syndrome with dystonia (type A), and a complex encephalopathy with neonatal onset (type B). Decreased cerebrospinal fluid concentrations of homovanillic acid and 3-methoxy-4-hydroxyphenylethylene glycol, with normal 5-hydroxyindoleacetic acid cerebrospinal fluid concentrations, are the biochemical hallmark of tyrosine hydroxylase deficiency. The homovanillic acid concentrations and homovanillic acid/5-hydroxyindoleacetic acid ratio in cerebrospinal fluid correlate with the severity of the phenotype. Tyrosine hydroxylase deficiency is almost exclusively caused by missense mutations in the TH gene and its promoter region, suggesting that mutations with more deleterious effects on the protein are incompatible with life. Genotype-phenotype correlations do not exist for the common c.698G > A and c.707T > C mutations. Carriership of at least one promotor mutation, however, apparently predicts type A tyrosine hydroxylase deficiency. Most patients with tyrosine hydroxylase deficiency can be successfully treated with l-dopa.
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Given the dynamic nature of cardiac function, correct temporal alignment of pre-operative models and intraoperative images is crucial for augmented reality in cardiac image-guided interventions. As such, the current study focuses on the development of an image-based strategy for temporal alignment of multimodal cardiac imaging sequences, such as cine Magnetic Resonance Imaging (MRI) or 3D Ultrasound (US). First, we derive a robust, modality-independent signal from the image sequences, estimated by computing the normalized crosscorrelation between each frame in the temporal sequence and the end-diastolic frame. This signal is a resembler for the left-ventricle (LV) volume curve over time, whose variation indicates di erent temporal landmarks of the cardiac cycle. We then perform the temporal alignment of these surrogate signals derived from MRI and US sequences of the same patient through Dynamic Time Warping (DTW), allowing to synchronize both sequences. The proposed framework was evaluated in 98 patients, which have undergone both 3D+t MRI and US scans. The end-systolic frame could be accurately estimated as the minimum of the image-derived surrogate signal, presenting a relative error of 1:6 1:9% and 4:0 4:2% for the MRI and US sequences, respectively, thus supporting its association with key temporal instants of the cardiac cycle. The use of DTW reduces the desynchronization of the cardiac events in MRI and US sequences, allowing to temporally align multimodal cardiac imaging sequences. Overall, a generic, fast and accurate method for temporal synchronization of MRI and US sequences of the same patient was introduced. This approach could be straightforwardly used for the correct temporal alignment of pre-operative MRI information and intra-operative US images.
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While fluoroscopy is still the most widely used imaging modality to guide cardiac interventions, the fusion of pre-operative Magnetic Resonance Imaging (MRI) with real-time intra-operative ultrasound (US) is rapidly gaining clinical acceptance as a viable, radiation-free alternative. In order to improve the detection of the left ventricular (LV) surface in 4D ultrasound, we propose to take advantage of the pre-operative MRI scans to extract a realistic geometrical model representing the patients cardiac anatomy. This could serve as prior information in the interventional setting, allowing to increase the accuracy of the anatomy extraction step in US data. We have made use of a real-time 3D segmentation framework used in the recent past to solve the LV segmentation problem in MR and US data independently and we take advantage of this common link to introduce the prior information as a soft penalty term in the ultrasound segmentation algorithm. We tested the proposed algorithm in a clinical dataset of 38 patients undergoing both MR and US scans. The introduction of the personalized shape prior improves the accuracy and robustness of the LV segmentation, as supported by the error reduction when compared to core lab manual segmentation of the same US sequences.