Coronary artery calcification (CAC) is commonly encountered by interventional cardiologists. Severe CAC may impair
stent delivery or result in stent underexpansion, stent thrombosis and/orin-stent restenosis (ISR).Adequate preparation of
heavily calcified coronary lesions (e.g. using non-compliant balloons, cutting/scoring balloons, rotational/orbital atherecto
my or intravascular lithotripsy) prior to stent implantation is essential in preventing stent underexpansion.However, in cer
tain cases the deployed stent may remain underexpanded despite extensive lesion preparation.Recent reports have suggest
ed that IVL could be used with success in patients with acute stent failure.We present a case of Acute IWMI with stent un
Keywords: CAC(Coronary artery calcium),PCI(Percutaneous coronary intervention),IWMI(Inferior wall MI),IVL(Intravs
cular lithotripsy),RA(rotational atherectomy),NCB(non compliant balloon)
derexpansion during primary PCI due to focal dense calcification managed with IVL with good final result. Shockwave In
travascular Lithotripsy (IVL) is the only technology that cracks both medial and intimal calcium while minimizing trauma
to the vessel wall.In the recent past it has been indicated for denovo calcified coronary lesions and calcified Instent resteno
sis.For IVL use in acute stent failure it is a off label indication.
Author Name: Punish Sadana |
|
Journal of Case Reports and Studies
Artificial Intelligence and Machine Learning (ML) are increasingly being used in the Neurocritical Care and healthcare in
general. The ML model algorithms have many existing and potential uses in triage, diagnosis, clinical decision support, mon
itoring, and prevention of clinical syndromes. Combining and appropriately analyzing the vast number of neurocritical care
data parameters, ranging from clinical (including electronic medical record), laboratory, imaging, multimodal monitoring,
and many others is beyond human capability. ML algorithms can help the providers and patients in analyzing these data pa
rameters to address certain defined problems. Machine learning does have limitations in several aspects (technical, medi
co-legal, financial, clinical, ethical, social, etc.), which can prevent realization of its full potential. Addressing these pitfalls
with appropriate solutions in a timely manner is important to get the maximum benefit out of this valuable technological ad
vancement
Author Name: Alok Dabi |
|
Journal of Neurology and Neurological Disorders
Objective: This study was explored the impact of Nihavent theme on decreasing of adaptation difficulty in patients with
Alzheimer’s disease.
Materials and methods: The study was conducted with a total of 30 patients, 15 patients in the intervention group and 15
patients in the control group. Before the application, The Descriptive Characteristics Data Form and Assessment Scale of
Adaptation Difficulty for the Elderly were administered to both groups. The patients in intervention group had music ses
sions for 12 weeks. Patients in the control group received standard care but did not participate in the specific intervention.
One week after the music session completed, the Assessment Scale of Adaptation Difficulty for the Elderly was re-adminis
tered to both groups.
Author Name: Münevver KIYAK |
|
Journal of Nursing and Patient Health Care
This study examined the effectiveness of Solution-Focused Therapy (SFT) in reducing tobacco smoking dependency be
haviour among incarcerated individuals within correctional settings in Oyo State. Anchored on social cognitive theory,
which highlights the role of self-efficacy in behaviour change, the research was designed to address the pressing public
health concern of tobacco smoking among the inmates.
Author Name: Omopo Oluwaseun Emmanuel |
|
Journal of Addiction Research & Treatment
Empowering Incarcerated Individuals: Solution-Focused Therapy for Reducing Tobacco Smoking Dependency Behaviour among Correctional Inmates in Oyo State, Nigeria
Coronary artery calcification (CAC) is commonly encountered by interventional cardiologists. Severe CAC may impair
stent delivery or result in stent underexpansion, stent thrombosis and/orin-stent restenosis (ISR).Adequate preparation of
heavily calcified coronary lesions (e.g. using non-compliant balloons, cutting/scoring balloons, rotational/orbital atherecto
my or intravascular lithotripsy) prior to stent implantation is essential in preventing stent underexpansion.However, in cer
tain cases the deployed stent may remain underexpanded despite extensive lesion preparation.Recent reports have suggest
ed that IVL could be used with success in patients with acute stent failure.We present a case of Acute IWMI with stent un
Keywords: CAC(Coronary artery calcium),PCI(Percutaneous coronary intervention),IWMI(Inferior wall MI),IVL(Intravs
cular lithotripsy),RA(rotational atherectomy),NCB(non compliant balloon)
derexpansion during primary PCI due to focal dense calcification managed with IVL with good final result. Shockwave In
travascular Lithotripsy (IVL) is the only technology that cracks both medial and intimal calcium while minimizing trauma
to the vessel wall.In the recent past it has been indicated for denovo calcified coronary lesions and calcified Instent resteno
sis.For IVL use in acute stent failure it is a off label indication.
Author Name: Punish Sadana |
|
Empowering Incarcerated Individuals: Solution-Focused Therapy for Reducing Tobacco Smoking Dependency Behaviour among Correctional Inmates in Oyo State, Nigeria
Artificial Intelligence and Machine Learning (ML) are increasingly being used in the Neurocritical Care and healthcare in
general. The ML model algorithms have many existing and potential uses in triage, diagnosis, clinical decision support, mon
itoring, and prevention of clinical syndromes. Combining and appropriately analyzing the vast number of neurocritical care
data parameters, ranging from clinical (including electronic medical record), laboratory, imaging, multimodal monitoring,
and many others is beyond human capability. ML algorithms can help the providers and patients in analyzing these data pa
rameters to address certain defined problems. Machine learning does have limitations in several aspects (technical, medi
co-legal, financial, clinical, ethical, social, etc.), which can prevent realization of its full potential. Addressing these pitfalls
with appropriate solutions in a timely manner is important to get the maximum benefit out of this valuable technological ad
vancement
Author Name: Alok Dabi |
|
Empowering Incarcerated Individuals: Solution-Focused Therapy for Reducing Tobacco Smoking Dependency Behaviour among Correctional Inmates in Oyo State, Nigeria
Objective: This study was explored the impact of Nihavent theme on decreasing of adaptation difficulty in patients with
Alzheimer’s disease.
Materials and methods: The study was conducted with a total of 30 patients, 15 patients in the intervention group and 15
patients in the control group. Before the application, The Descriptive Characteristics Data Form and Assessment Scale of
Adaptation Difficulty for the Elderly were administered to both groups. The patients in intervention group had music ses
sions for 12 weeks. Patients in the control group received standard care but did not participate in the specific intervention.
One week after the music session completed, the Assessment Scale of Adaptation Difficulty for the Elderly was re-adminis
tered to both groups.
Author Name: Münevver KIYAK |
|
Empowering Incarcerated Individuals: Solution-Focused Therapy for Reducing Tobacco Smoking Dependency Behaviour among Correctional Inmates in Oyo State, Nigeria
This study examined the effectiveness of Solution-Focused Therapy (SFT) in reducing tobacco smoking dependency be
haviour among incarcerated individuals within correctional settings in Oyo State. Anchored on social cognitive theory,
which highlights the role of self-efficacy in behaviour change, the research was designed to address the pressing public
health concern of tobacco smoking among the inmates.
Author Name: Omopo Oluwaseun Emmanuel |
|