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Article ; Online: Is minimally invasive orthopedic surgery safer than open? A systematic review of systematic reviews.

Rafaqat, Wardah / Ahmad, Tashfeen / Ibrahim, Muhammad Talal / Kumar, Sudhesh / Bluman, Eric M / Khan, Khalid S

International journal of surgery (London, England)

2022 Volume 101, Page(s) 106616

Abstract: Background: To assess the safety of minimally invasive surgery (MIS) for orthopedic spinal, upper limb and lower limb procedures, this systematic review of systematic reviews compared their complications with open procedures.: Materials and methods: ... ...

Abstract	Background: To assess the safety of minimally invasive surgery (MIS) for orthopedic spinal, upper limb and lower limb procedures, this systematic review of systematic reviews compared their complications with open procedures. Materials and methods: A literature search was conducted electronically (PubMed, Cochrane library and Web of Science; May 8, 2021) without language restriction in the past five years. Reviews that consulted at least two databases, compared MIS with open orthopedic surgery, and reported the following: intraoperative, post-operative or total complications, function, ambulation, pain, hospital stay, reoperation rate and operation time were included. Article selection, quality assessment using AMSTAR-2, and data extraction were conducted in duplicate on predesigned forms. In each review, a subset analysis focusing on prospective cohort and randomized studies was additionally performed. Prospero: CRD42020178171. Results: The search yielded 531 articles from which 76 reviews consisting of 1104 primary studies were included. All reviews were assessed as being low quality. Compared to open surgery, MIS had fewer total, postoperative and intraoperative complications in 2/10, 2/11 and 2/5 reviews of spinal procedures respectively, 1/3, 1/4 and 1/2 reviews of upper limb procedures respectively, and 4/6, 2/7 and 0/2 reviews of lower limb procedures respectively. Conclusions: MIS had greater overall safety compared to open surgery in spinal procedures. In upper limb and lower limb procedures, MIS was not outright superior to open procedures in terms of safety hence a general preference of MIS is not justified on the premise of a better safety profile compared to open procedures.
MeSH term(s)	Humans ; Minimally Invasive Surgical Procedures/adverse effects ; Minimally Invasive Surgical Procedures/methods ; Operative Time ; Prospective Studies ; Spinal Fusion/methods ; Systematic Reviews as Topic ; Treatment Outcome
Language	English
Publishing date	2022-04-12
Publishing country	United States
Document type	Journal Article ; Systematic Review
ZDB-ID	2212038-5
ISSN	1743-9159 ; 1743-9191
ISSN (online)	1743-9159
ISSN	1743-9191
DOI	10.1016/j.ijsu.2022.106616
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Article ; Online: A Review of the Molecular Mechanisms of Traumatic Brain Injury.

Ladak, Asma Akbar / Enam, Syed Ather / Ibrahim, Muhammad Talal

World neurosurgery

2019 Volume 131, Page(s) 126–132

Abstract: Traumatic brain injury (TBI) refers to any insult to the brain resulting in primary (direct) and secondary (indirect) damage to the brain parenchyma. Secondary damage is often linked to the molecular mechanisms that occur post TBI and result in ... ...

Abstract	Traumatic brain injury (TBI) refers to any insult to the brain resulting in primary (direct) and secondary (indirect) damage to the brain parenchyma. Secondary damage is often linked to the molecular mechanisms that occur post TBI and result in excitotoxicity, neuroinflammation and cytokine damage, oxidative damage, and eventual cell death as prominent mechanisms of cell damage. We present a review highlighting the relation of each of these mechanisms with TBI, their mode of damaging brain tissue, and therapeutic correlation. We also mention the long-term sequelae and their pathophysiology in relation to TBI focusing on Parkinson disease, Alzheimer disease, epilepsy, and chronic traumatic encephalopathy. Understanding of the molecular mechanisms is important in order to realize the secondary and long-term sequelae that follow primary TBI and to devise targeted therapy for quick recovery accordingly.
MeSH term(s)	Animals ; Brain Injuries, Traumatic/metabolism ; Brain Injuries, Traumatic/therapy ; Humans
Language	English
Publishing date	2019-07-10
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	2534351-8
ISSN	1878-8769 ; 1878-8750
ISSN (online)	1878-8769
ISSN	1878-8750
DOI	10.1016/j.wneu.2019.07.039
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Article ; Online: Exploring the Potential of Artificial Intelligence and Machine Learning to Combat COVID-19 and Existing Opportunities for LMIC: A Scoping Review.

Naseem, Maleeha / Akhund, Ramsha / Arshad, Hajra / Ibrahim, Muhammad Talal

Journal of primary care & community health

2020 Volume 11, Page(s) 2150132720963634

Abstract: Background: In the face of the current time-sensitive COVID-19 pandemic, the limited capacity of healthcare systems resulted in an emerging need to develop newer methods to control the spread of the pandemic. Artificial Intelligence (AI), and Machine ... ...

Abstract	Background: In the face of the current time-sensitive COVID-19 pandemic, the limited capacity of healthcare systems resulted in an emerging need to develop newer methods to control the spread of the pandemic. Artificial Intelligence (AI), and Machine Learning (ML) have a vast potential to exponentially optimize health care research. The use of AI-driven tools in LMIC can help in eradicating health inequalities and decrease the burden on health systems. Methods: The literature search for this Scoping review was conducted through the PubMed database using keywords: COVID-19, Artificial Intelligence (AI), Machine Learning (ML), and Low Middle-Income Countries (LMIC). Forty-three articles were identified and screened for eligibility and 13 were included in the final review. All the items of this Scoping review are reported using guidelines for PRISMA extension for scoping reviews (PRISMA-ScR). Results: Results were synthesized and reported under 4 themes. (a) Conclusion: AI-based tools can be a game-changer for diagnosis, treatment, and management of COVID-19 patients with the potential to reshape the future of healthcare in LMIC.
MeSH term(s)	Artificial Intelligence ; Betacoronavirus ; COVID-19 ; Contact Tracing ; Coronavirus Infections/diagnosis ; Coronavirus Infections/epidemiology ; Coronavirus Infections/therapy ; Coronavirus Infections/virology ; Data Mining ; Delivery of Health Care ; Developing Countries ; Drug Development ; Humans ; Machine Learning ; Mass Screening ; Pandemics ; Pneumonia, Viral/diagnosis ; Pneumonia, Viral/epidemiology ; Pneumonia, Viral/therapy ; Pneumonia, Viral/virology ; Poverty ; Research ; SARS-CoV-2 ; Vaccines
Chemical Substances	Vaccines
Keywords	covid19
Language	English
Publishing date	2020-09-30
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	2550221-9
ISSN	2150-1327 ; 2150-1319
ISSN (online)	2150-1327
ISSN	2150-1319
DOI	10.1177/2150132720963634
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Article: Clinical spectrum of sarcoidosis in patients at a tertiary care hospital, Pakistan: Ten-year follow-up study.

Arshad, Ainan / Riaz, Mehmood / Naseem, Zehra / Qadri, Fatima / Baqir, Syed Mujtaba / Ibrahim, Muhammad Talal / Ayaz, Ahmed

JPMA. The Journal of the Pakistan Medical Association

2022 Volume 72, Issue 8, Page(s) 1491–1496

Abstract: Objective: To identify the local patterns of manifestations, organ involvement other than lungs, diagnostic tools and treatment regimens related to patients of sarcoidosis.: Methods: The retrospective study was conducted from November 1, 2019, to ... ...

Abstract	Objective: To identify the local patterns of manifestations, organ involvement other than lungs, diagnostic tools and treatment regimens related to patients of sarcoidosis. Methods: The retrospective study was conducted from November 1, 2019, to February 28, 2020, at the Aga Khan University Hospital, Karachi, and comprised data of sarcoidosis patients who needed hospitalisation between 2009 and 2019. The entire clinical spectrum was noted based on organ involvement. Data was analysed using SPSS 21. Results: Of the 80 patients, 53(66.3%) were women. The overall mean age at diagnosis was 52.0±13.5 years. Pulmonary sarcoidosis was found in 60(75%) patients, while 13(16.3%) had extrapulmonary manifestations, and 6(8.8%) had both pulmonary and extrapulmonary involvement. None of the patients had hypercalcaemia, while antinuclear antibodies were positive in 2 (18.2%) patients. In terms of treatment, 75(93.8%) patients received corticosteroids. Acute exacerbation of interstitial lung disease was the most common reason of hospitalisation 16(20%). Mortality was the outcome in 11(14.7%) cases. Conclusions: Sarcoidosis was found to be more prevalent in women aged 50 years and above. A quarter of patients had extrapulmonary manifestation, while interstitial lung disease was the most common complication.
MeSH term(s)	Humans ; Female ; Adult ; Middle Aged ; Aged ; Male ; Follow-Up Studies ; Retrospective Studies ; Tertiary Care Centers ; Antibodies, Antinuclear ; Pakistan/epidemiology ; Sarcoidosis/diagnosis ; Sarcoidosis/epidemiology ; Sarcoidosis/therapy ; Lung Diseases, Interstitial
Chemical Substances	Antibodies, Antinuclear
Language	English
Publishing date	2022-10-24
Publishing country	Pakistan
Document type	Journal Article
ZDB-ID	603873-6
ISSN	0030-9982
ISSN	0030-9982
DOI	10.47391/JPMA.2382
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Article: Peer-Assisted Learning (PAL): An innovation aimed at engaged learning for undergraduate medical students.

Siddiqi, Hasan Salman / Rehman, Rehana / Syed, Farzeen Fatma / Martins, Russell Seth / Ibrahim, Muhammad Talal / Alam, Faiza

JPMA. The Journal of the Pakistan Medical Association

2020 Volume 70, Issue 11, Page(s) 1996–2000

Abstract: Objective: To evaluate the effectiveness of Peer Assisted Learning in teaching at undergraduate level and to assess its effects on Peer Leaders and Peer Learners.: Methods: The cross-sectional study was conducted at the Aga Khan University, Karachi, ... ...

Abstract	Objective: To evaluate the effectiveness of Peer Assisted Learning in teaching at undergraduate level and to assess its effects on Peer Leaders and Peer Learners. Methods: The cross-sectional study was conducted at the Aga Khan University, Karachi, from May to October 2017, and comprised Peer Learners who were trained by faculty members in workshops and pre-run of experiments. Students were divided into two groups; Group A had Peer Learners taught by Peer Leaders, and Group B had those taught by trained lab technologists. Knowledge of the groups was assessed by a quiz using Kahoot. Post-session feedback questionnaires were also filled by the participants. Data was analysed using SPSS 23. Results: There were 10 Peer Leaders with a mean age of 19.5±0.85 years, and 62 Peer Learners with a mean age of 19.08±0.81 years. Among the learners, there were 35(56.5%) males and 27(43.5%) females. Post-session assessment showed a significant difference in the test performance by the two groups (p<0.05). Feedback indicated that the learners found Peer Leaders more accessible than lab staff, leading to enhanced understanding of the subject. Conclusions: Peer-Assisted Learning was found to promote learning by creating an informal student-friendly learning environment.
MeSH term(s)	Adolescent ; Adult ; Cross-Sectional Studies ; Education, Medical, Undergraduate ; Female ; Humans ; Learning ; Male ; Peer Group ; Students, Medical ; Teaching ; Young Adult
Language	English
Publishing date	2020-12-20
Publishing country	Pakistan
Document type	Journal Article
ZDB-ID	603873-6
ISSN	0030-9982
ISSN	0030-9982
DOI	10.5455/JPMA.29714
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Article ; Online: Clinical characteristics and outcomes of patients presenting with hip fractures at a tertiary care hospital in Pakistan.

Arshad, Ainan / Ibrahim, Muhammad Talal / Arshad, Hajra / Hammad, Muhammad Bin / Sheikh, Sijal Akhtar / Khan, Aysha Habib / Jafri, Lena / Nadeem, Sarah

Archives of osteoporosis

2021 Volume 16, Issue 1, Page(s) 25

Abstract: Osteoporosis remains under-recognized and sub-optimally managed in Pakistan, with a lack of awareness that minimal impact hip fracture is a manifestation of low bone mineral density (BMD).: Purpose: Hip fracture is often the first clinical ... ...

Abstract	Osteoporosis remains under-recognized and sub-optimally managed in Pakistan, with a lack of awareness that minimal impact hip fracture is a manifestation of low bone mineral density (BMD). Purpose: Hip fracture is often the first clinical presentation of osteoporosis and an opportunity to intervene and reduce future fracture risk. Our aim was to understand the current practices in Pakistan related to bone health in patients presenting with a hip fracture. Methods: This is a retrospective study at a tertiary care center in Pakistan of patients admitted with a hip fracture. Data collected includes previous fracture history, known preceding diagnosis of low BMD medication details, comorbidities, and DXA results. Results: Two hundred ten patients were studied. The mean age of patients was 73.1 years, with 112 (53.3%) women. Most (195 (92.9%)) had presented with a low-impact hip fracture, with 17 (8.1%) reporting previous history of fracture. None had been treated with osteoporosis medications prior to fracture. Nineteen (9%) were on calcium and vitamin D supplements prior to fracture; of the minority who were screened, all were vitamin D deficient and subsequently discharged on vitamin D supplements. No one was prescribed medications to reduce fracture risk at discharge. Conclusion: This study reveals that patients admitted with minimal impact hip fractures in Pakistan are rarely evaluated for low BMD and not started on osteoporosis medications even after presenting with a typical osteoporosis-related fracture. This underscores the need for health provider education about osteoporosis as a major cause for hip fractures and the need to intervene for future fracture risk reduction.
MeSH term(s)	Aged ; Bone Density ; Female ; Hip Fractures/epidemiology ; Humans ; Osteoporosis/drug therapy ; Osteoporosis/epidemiology ; Pakistan/epidemiology ; Retrospective Studies ; Tertiary Care Centers
Language	English
Publishing date	2021-02-08
Publishing country	England
Document type	Journal Article
ZDB-ID	2253231-6
ISSN	1862-3514 ; 1862-3522
ISSN (online)	1862-3514
ISSN	1862-3522
DOI	10.1007/s11657-021-00895-9
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Article ; Online: Exploring the Potential of Artificial Intelligence and Machine Learning to Combat COVID-19 and Existing Opportunities for LMIC

Naseem, Maleeha / Akhund, Ramsha / Arshad, Hajra / Ibrahim, Muhammad Talal

Journal of Primary Care & Community Health

A Scoping Review

2020 Volume 11, Page(s) 215013272096363

Abstract	Background: In the face of the current time-sensitive COVID-19 pandemic, the limited capacity of healthcare systems resulted in an emerging need to develop newer methods to control the spread of the pandemic. Artificial Intelligence (AI), and Machine Learning (ML) have a vast potential to exponentially optimize health care research. The use of AI-driven tools in LMIC can help in eradicating health inequalities and decrease the burden on health systems. Methods: The literature search for this Scoping review was conducted through the PubMed database using keywords: COVID-19, Artificial Intelligence (AI), Machine Learning (ML), and Low Middle-Income Countries (LMIC). Forty-three articles were identified and screened for eligibility and 13 were included in the final review. All the items of this Scoping review are reported using guidelines for PRISMA extension for scoping reviews (PRISMA-ScR). Results: Results were synthesized and reported under 4 themes. (a) The need of AI during this pandemic: AI can assist to increase the speed and accuracy of identification of cases and through data mining to deal with the health crisis efficiently, (b) Utility of AI in COVID-19 screening, contact tracing, and diagnosis: Efficacy for virus detection can a be increased by deploying the smart city data network using terminal tracking system along-with prediction of future outbreaks, (c) Use of AI in COVID-19 patient monitoring and drug development: A Deep learning system provides valuable information regarding protein structures associated with COVID-19 which could be utilized for vaccine formulation, and (d) AI beyond COVID-19 and opportunities for Low-Middle Income Countries (LMIC): There is a lack of financial, material, and human resources in LMIC, AI can minimize the workload on human labor and help in analyzing vast medical data, potentiating predictive and preventive healthcare. Conclusion: AI-based tools can be a game-changer for diagnosis, treatment, and management of COVID-19 patients with the potential to reshape the future of healthcare in LMIC.
Keywords	Public Health, Environmental and Occupational Health ; Community and Home Care ; covid19
Language	English
Publisher	SAGE Publications
Publishing country	us
Document type	Article ; Online
ZDB-ID	2550221-9
ISSN	2150-1327 ; 2150-1319
ISSN (online)	2150-1327
ISSN	2150-1319
DOI	10.1177/2150132720963634
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Article: Exploring the Potential of Artificial Intelligence and Machine Learning to Combat COVID-19 and Existing Opportunities for LMIC: A Scoping Review

Naseem, Maleeha / Akhund, Ramsha / Arshad, Hajra / Ibrahim, Muhammad Talal

J Prim Care Community Health

Abstract: BACKGROUND: In the face of the current time-sensitive COVID-19 pandemic, the limited capacity of healthcare systems resulted in an emerging need to develop newer methods to control the spread of the pandemic. Artificial Intelligence (AI), and Machine ... ...

Abstract	BACKGROUND: In the face of the current time-sensitive COVID-19 pandemic, the limited capacity of healthcare systems resulted in an emerging need to develop newer methods to control the spread of the pandemic. Artificial Intelligence (AI), and Machine Learning (ML) have a vast potential to exponentially optimize health care research. The use of AI-driven tools in LMIC can help in eradicating health inequalities and decrease the burden on health systems. METHODS: The literature search for this Scoping review was conducted through the PubMed database using keywords: COVID-19, Artificial Intelligence (AI), Machine Learning (ML), and Low Middle-Income Countries (LMIC). Forty-three articles were identified and screened for eligibility and 13 were included in the final review. All the items of this Scoping review are reported using guidelines for PRISMA extension for scoping reviews (PRISMA-ScR). RESULTS: Results were synthesized and reported under 4 themes. (a) The need of AI during this pandemic: AI can assist to increase the speed and accuracy of identification of cases and through data mining to deal with the health crisis efficiently, (b) Utility of AI in COVID-19 screening, contact tracing, and diagnosis: Efficacy for virus detection can a be increased by deploying the smart city data network using terminal tracking system along-with prediction of future outbreaks, (c) Use of AI in COVID-19 patient monitoring and drug development: A Deep learning system provides valuable information regarding protein structures associated with COVID-19 which could be utilized for vaccine formulation, and (d) AI beyond COVID-19 and opportunities for Low-Middle Income Countries (LMIC): There is a lack of financial, material, and human resources in LMIC, AI can minimize the workload on human labor and help in analyzing vast medical data, potentiating predictive and preventive healthcare. CONCLUSION: AI-based tools can be a game-changer for diagnosis, treatment, and management of COVID-19 patients with the potential to reshape the future of healthcare in LMIC.
Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #807898
Database	COVID19

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Book ; Online: Exploring the potential of artificial intelligence and machine learning to combat COVID-19 and existing opportunities for LMIC

Naseem, Maleeha / Akhund, Ramsha / Arshad, Hajra / Ibrahim, Muhammad Talal

Community Health Sciences

A scoping review

2020

Abstract	Background: In the face of the current time-sensitive COVID-19 pandemic, the limited capacity of healthcare systems resulted in an emerging need to develop newer methods to control the spread of the pandemic. Artificial Intelligence (AI), and Machine Learning (ML) have a vast potential to exponentially optimize health care research. The use of AI-driven tools in LMIC can help in eradicating health inequalities and decrease the burden on health systems.Methods: The literature search for this Scoping review was conducted through the PubMed database using keywords: COVID-19, Artificial Intelligence (AI), Machine Learning (ML), and Low Middle-Income Countries (LMIC). Forty-three articles were identified and screened for eligibility and 13 were included in the final review. All the items of this Scoping review are reported using guidelines for PRISMA extension for scoping reviews (PRISMA-ScR).Results: Results were synthesized and reported under 4 themes. (a) The need of AI during this pandemic: AI can assist to increase the speed and accuracy of identification of cases and through data mining to deal with the health crisis efficiently, (b) Utility of AI in COVID-19 screening, contact tracing, and diagnosis: Efficacy for virus detection can a be increased by deploying the smart city data network using terminal tracking system along-with prediction of future outbreaks, (c) Use of AI in COVID-19 patient monitoring and drug development: A Deep learning system provides valuable information regarding protein structures associated with COVID-19 which could be utilized for vaccine formulation, and (d) AI beyond COVID-19 and opportunities for Low-Middle Income Countries (LMIC): There is a lack of financial, material, and human resources in LMIC, AI can minimize the workload on human labor and help in analyzing vast medical data, potentiating predictive and preventive healthcare.Conclusion: AI-based tools can be a game-changer for diagnosis, treatment, and management of COVID-19 patients with the potential to reshape the future of healthcare in LMIC.
Keywords	COVID-19 ; Artificial intelligence ; Low middle-income countries ; Machine learning ; Pandemic ; Community Health and Preventive Medicine ; Public Health ; Virus Diseases ; covid19
Subject code	006
Publishing date	2020-01-01T08:00:00Z
Publisher	eCommons@AKU
Publishing country	pk
Document type	Book ; Online
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Article: Impact of Perfectionism and Resilience on Empathy in Medical Students: A Cross-Sectional Study.

Rafaqat, Wardah / Sami, Ashmal / Ibrahim, Muhammad Talal / Ibad, Hamza / Awais, Sheharbano / Memon, Ayesha / Shahbaz, Fatima Farrukh / Ahmed, Daniyaal / Zindani, Shahzaib / Leghari, Abdul Lateef / Saleem, Sarah

Journal of patient experience

2022 Volume 9, Page(s) 23743735221106603

Abstract: Empathy is a cognitive attribute that forms the cornerstone for good doctor-patient encounters. The formative period for the development of empathy toward patients begins with clinical encounters within medical school. An individual medical student's ... ...

Abstract	Empathy is a cognitive attribute that forms the cornerstone for good doctor-patient encounters. The formative period for the development of empathy toward patients begins with clinical encounters within medical school. An individual medical student's empathy levels may in part be a product of their resilience and perfectionist attitudes. A cross-sectional study with 320 medical students across all years of study was conducted to determine the correlation of perfectionism and resilience with clinical empathy in medical students. The JSE-S, CD-RISC 10, and APS-R scales were used to assess levels of empathy, resilience, and perfectionism, respectively. The study found that a positive correlation exists between resilience (
Language	English
Publishing date	2022-06-07
Publishing country	United States
Document type	Journal Article
ZDB-ID	2857285-3
ISSN	2374-3743 ; 2374-3735
ISSN (online)	2374-3743
ISSN	2374-3735
DOI	10.1177/23743735221106603
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