Journal of Gandhara Medical and Dental Science

Frequency of Maternal Morbidities in Patients with Placenta Previa - A Prospective Single-Centered Study in Hazara Division.

2024-08-09T00:28:57-05:00

OBJECTIVES

The study aimed to determine the maternal morbidities in patients with placenta previa in a tertiary care hospital. Moreover, patients’ risk factors and outcomes will also be accessed as secondary outcomes.

METHODOLOGY

This prospective cross-sectional study was undertaken at Ayub Teaching Hospital Abbottabad from January 2022 to July 2024. Any pregnant patients carrying the ultrasound diagnosis of placenta previa in an emergency or the ward were included in the study. A non-randomized convenience technique was applied for sample collection. Patients with other placental anomalies, such as placenta accreta, were excluded from the current study. The data was analyzed in SPSS version 21, and significance was kept below 0.005.
RESULTS
In the present study, 104 cases of placenta previa were recruited, among which 76(73%) patients fall in the age range between 24 and 34 years. The incidence of major placenta previa was observed in 76/104 cases. In 86% of cases, obstetric trauma was observed, and in 54 (52%) cases, purpureal sepsis was recorded. The purpureal sepsis was 10/36(28%) in patients with tamponade placement and 8/36(22%) in APH patients with a significance of 0.001. Presentation with antepartum hemorrhage was seen in 67% of cases (8/12) in the age group < 20 years. The maternal mortality was 2%.

CONCLUSION

The complication rate was relatively higher than reported in previous studies. The rate of morbidity can be minimized by following a multi-disciplinary approach. The cases should be managed in settings with ICU care and blood bank facilities.

Concordance and Discordance Between Radiology Residents and Consultant Radiologist Interpretation Of CT Brain

2024-05-26T23:54:46-05:00

OBJECTIVES

The primary objective of this study is to assess the degree of concordance and discordance between the interpretations of computed tomography (CT) brain images by resident and consultant radiologists while emphasizing the critical significance of accurate image interpretation for informed clinical decision-making.

METHODOLOGY

The evaluation of radiology reports for CT Brain interpretation through a prospective analysis at the Radiology Department of Rehman Medical Institute over two years, from 1st October 2020 to 31st October 2022. A total of 198 patients who underwent cranial CT scans were interpreted by residents (R1, R2, R3, R4). Following this, the consultant radiologists reviewed the images and completed their reports. The reports of the residents and the consultant radiologists were then compared, and concordance was achieved when the residents’ reports were consistent with the final radiologist’s reports. The data collected were recorded in Microsoft Excel. The statistical analysis was performed using SPSS version 22 (IBM Corp., Armonk, NY), and the kappa coefficient was used to determine the level of agreement between residents and consultants.
RESULTS
Among the 198 CT Head reports evaluated, 186 of them were in agreement with the final report of the consultant radiologist. Of the correctly diagnosed cases, R1 correctly diagnosed 46 cases, R2 correctly diagnosed 80 cases, R3 correctly diagnosed 54 cases, and R4 correctly diagnosed 6 cases. Our study achieved a percentage agreement of 93.93, with a Cohen's kappa coefficient of 0.8.
CONCLUSION
The overall concordance rate between residents and consultant radiologists was 93.93%, with a kappa coefficient 0.8. This high kappa coefficient indicates strong agreement between the two groups.

Midterm Follow-Up Of Tlif In Single-Level Lumbar Disc Degeneration

2024-08-22T02:29:03-05:00

OBJECTIVES

This study aims to evaluate the midterm clinical and radiological outcomes of TLIF in patients with single-level lumbar disc degeneration. The focus is on assessing the procedure's effectiveness in terms of pain relief, functional improvement, and any potential complications.

METHODOLOGY

A retrospective cohort study was conducted at Hayatabad Medical Complex, Peshawar involving 120 patients who underwent single-level TLIF for lumbar disc degeneration between 2018-2023. The patients with a diagnosis of single-level lumbar disc degeneration confirmed by MRI, failure of conservative treatment for at least 6 months, and who underwent TLIF during the study period were included in the study. Data were collected on preoperative and postoperative pain scores, Oswestry Disability Index (ODI), and radiological parameters. SPSS version 24 was used.

RESULTS
The mean follow-up period was 36 months (range 24-48 months). There was a statistically significant improvement in both pain scores (p < 0.001) and ODI scores (p < 0.001). Fusion rates were high, with 92% of patients achieving solid fusion by the final follow-up. Complications were observed in 15% of the cases, with adjacent segment disease being the most common.

CONCLUSION

TLIF provides significant pain relief and functional improvement in patients with single-level lumbar disc degeneration at midterm follow-up. The procedure demonstrates a high fusion rate with an acceptable complication profile, making it a reliable option for this patient population

Outcomes of Retro Colic Retro Pyloric Roux En Y Hepaticojejunostomy In Biliary Reconstruction

2024-08-16T23:32:12-05:00

OBJECTIVES

To assess the effectiveness of retro pyloric Roux-En-Y Hepaticojejunostomy in cases of choledochal cysts and bile duct injuries to reduce complications, such as delayed gastric emptying and acute cholangitis.

METHODOLOGY

This retrospective cohort study was conducted in the surgical C unit of Hayatabad Medical Complex, Peshawar (January 2019 - December 2022). This study included 37 patients treated for bile duct injuries and choledochal cysts. All patients had an ASA III or above, aged 5 to 36 years. Amongst the 35 patients, 21 patients underwent surgery for choledochal cysts, while 14 patients were treated for bile duct injuries. Patients with type 1choledochal cysts were admitted through OPD after getting diagnosed by ultrasound abdomen and, in some cases, MRCP.

RESULTS
Out of 36 patients, 23 (63.71%) presented with type I choledochal cysts, while 14 (40%) exhibited bile duct injuries (BDI). Among the 14 BDI cases, 57.14% underwent open cholecystectomy, 42.85% underwent laparoscopic cholecystectomy, and 5.71% received immediate repair during the primary surgery. Conversely, 8.57% of patients with CBD ligation underwent exploration on the 3rd postoperative day upon early detection of the injury. Among the patients diagnosed with BDI after the 7th postoperative day, 25.71% underwent delayed repair at three months. Postoperatively, patients were authorized for fluid consumption within 24-48 hours. Moreover, 4 (11.42%) patients developed a fever of approximately 100°F, managed with intravenous Paracetamol in 2 (5.71%) cases. Patients also presented with subsequent wound infections, which were treated on an outpatient basis through oral antibiotics and wound dressing.

CONCLUSION

The Retropyloric Roux-en-Y hepaticojejunostomy is a modified biliary reconstruction procedure with minimal morbidity and better outcomes than traditional methods. It reduces complications like delayed gastric emptying and acute cholangitis. We recommend its frequent use for biliary reconstruction when appropriate.

Frequency of Dyslipidemia in Patients Having Subclinical Hypothyroidism

2024-08-15T01:53:19-05:00

OBJECTIVES

To determine the lipid abnormalities in subclinical hypothyroidism.

METHODOLOGY

A case-control study was conducted on euthyroid and subclinical hypothyroid patients presenting to OPD and medical wards of Hayatabad Medical Complex from January to December 2023. The euthyroid control arm had no history of thyroid disease in the past. These hundred control patients were compared to a hundred cases who had subclinical hypothyroidism. All the patients underwent laboratory tests for thyroid hormones and lipid levels. Overt hypothyroidism was excluded. All the results were compared using SPSS statistical analysis version 23.

RESULTS
We found that in subclinical hypothyroidism, high triglycerides (TG) were the only abnormal findings, while total cholesterol (TC) and high-density lipoproteins (HDL) were not affected. The risk of hyper triglyceridemia with thyroid stimulating hormone (TSH) levels ≥10mIU/L was 2-fold higher compared to that in the average population (P<0.05)..

CONCLUSION

Disorders of TG metabolism with subclinical hypothyroidism show a direct correlation with the level of TSH, and the risk of hypertriglyceridemia is moderately increased when the level of TSH ≥10mIU/L. SCH does not affect the level of TC and HDL.

Efficacy of B-Lynch Compression Suture for Control of Primary Post-Partum Hemorrhage

2024-08-21T23:42:34-05:00

OBJECTIVES

This study aimed to evaluate the efficiency of the B-Lynch compression suture for primary post-partum hemorrhage control.

METHODOLOGY

It is a prospective cross-sectional study performed for two years, i.e., 1 November 2021 to 31 October 2023, at the Department of Obstetrics and Gynaecology in a tertiary care hospital. This study included 65 study cases out of 23,964 with primary post-partum hemorrhage (PPH) due to uterine atony during cesarean delivery not responding to pharmacological treatment and was managed by applying B-Lynch compression sutures. The amount of blood loss, demographic characteristics, birth weight of babies, causative factors, and other related complications were studied in such selected cases.

RESULTS
B-Lynch compression suture presented a success rate of 97% in the present study. 52% had blood loss of 1000-1500ml, 29% had loss between 1501-2000ml and 18% had 2001-2500ml blood loss. 6% had wound gaping, 10.7% had a fever, and 8% had more than seven days stay in hospital, and wound infections were noted.

CONCLUSION

Our study concluded that the B-Lynch compression suture had a success rate of 97% in the management of primary post-partum hemorrhage, with few post-operative complications. The current research demonstrates the efficacy of B-Lynch as a lifesaving, easy, effectual technique that avoids hysterectomy and thus avoids heavy blood loss.

Diagnostic Accuracy of X-Ray PNS for Paranasal Sinuses (X-Ray PNS) Sinus Pathologies with Computed Tomography Paranasal Sinuses (CT PNS) A The Gold Standard

2024-02-01T00:40:37-06:00

OBJECTIVES

To determine the diagnostic accuracy of X-ray PNS in different pathologies of paranasal sinuses, using CT PNS as the gold standard, and establishing X-ray PNS as a potential first-line screening tool.

METHODOLOGY

This cross-sectional study was conducted over two years in the Department of Radiology, Rehman Medical Institute Peshawar. 100 patients in the sample with suspected PNS pathologies were selected through the purposive sampling technique, aged 18-70. All patients underwent X-ray PNS initially, followed by CT scans. CT PNS was performed even in cases with normal X-ray findings to check for false negatives or positives.

RESULTS
Out of 100 patients, 56% were male. Most PNS pathologies (55%) were in the 15-35 age group (mean age 24 years, SD ±3.89). The most common symptoms were nasal obstruction (40%) and headache (39%). X-ray PNS showed 67% sensitivity, 60% specificity, 85% PPV, and 64% NPV. The overall diagnostic accuracy of X-ray PNS was 66% compared to CT PNS.

CONCLUSION

X-ray PNS demonstrates a diagnostic accuracy of 66% in diagnosing PNS pathologies. While not as comprehensive as CBCT, X-ray PNS shows potential as a first-line screening tool, particularly for larger sinuses, potentially reducing unnecessary radiation exposure from CT scans.

The Fetomaternal Outcome of Pregnancy in Women with Thyroid Disease

2024-08-15T01:45:01-05:00

OBJECTIVES

To determine the frequency of fetomaternal outcomes in women with pregnancy with thyroid disease presented to Khyber Teaching Hospital Peshawar.

METHODOLOGY

A descriptive observational study was conducted in Khyber’s Obstetrics and Gynecology Department Teaching Hospital Peshawar from February to July 2022. A total of 160 pregnant patients with thyroid disease were included in the study. All patients were followed till delivery, and fetomaternal outcomes (gestational hypertension, pre-eclampsia, postpartum hemorrhage, mode of delivery, Oligohydramnios, birth weight, neonatal hyperbilirubinemia) were noted.

RESULTS
The age range in this study was from 18 to 40 years with a mean age of 29.787 +2.23 years, mean gestational age of 25.331+4.14 weeks, mean parity of 1.818+1.23 and mean weight of 68.462+3.30 kg. Hypothyroidism was seen in 76.9% of patients, and hyperthyroidism was seen in 23.1%. Gestational hypertension was observed in 11.9%, pre-eclampsia in 5%, postpartum haemorrhage in 47.5%, the cesarean section in 27.5%, Oligohydramnios in 11.3%, low birth weight in 21.3% and neonatal hyperbilirubinemia in 10.6%.

CONCLUSION

The most frequent complication observed in pregnancy with thyroid disease was postpartum haemorrhage, followed by cesarean section and low birth weight.

Transforming Medical and Dental Curriculum in the era of Artificial Intelligence (AI)

2024-09-14T01:18:57-05:00

The dawn of artificial intelligence (AI) signifies a pivotal shift in medical and dental education. Integrating AI into the curriculum modernizes learning and equips future healthcare professionals with crucial tools for the 21st century. The COVID-19 pandemic revealed the limitations of conventional educational models, necessitating rapid adaptation to remote and online learning environments. This disruption expedited the transition to digital platforms, laying the foundation for further integration of technology, including AI, into medical education. What began as an emergency response has now become a permanent feature of the educational landscape, evolving from static textbooks to dynamic digital platforms that offer greater accessibility, inclusivity, and personalization of learning experiences.¹ In the AI era, it is insufficient to merely digitize the curriculum; a comprehensive transformation is essential. The digital curriculum opens new avenues for interactive learning environments, simulation-based practices, and adaptive learning algorithms that respond to the individual needs of students. AI-driven tools such as virtual patient simulations, diagnostic decision-making platforms, and predictive analytics have the potential to revolutionize how medical students learn, practice, and apply their knowledge in clinical settings.² These innovations allow for an enhanced learning experience where students can interact with realistic patient cases and make informed decisions, fostering a deeper understanding of clinical practice.

One of the most promising applications of AI in medical education is its role as an educational partner. AI-powered platforms can function as personalized tutors, providing real-time feedback, adjusting learning modules based on student performance, and even predicting areas where additional support may be required.³ Adaptive learning systems can analyze the learner’s pace and comprehension, offering tailored resources to bridge knowledge gaps. This personalized approach to education ensures that no student is left behind, addressing one of the longstanding challenges of traditional, one-size-fits-all curricula. Additionally, AI can enhance clinical reasoning through simulation and data-driven case scenarios. By analyzing patterns in patient data, AI algorithms can help medical students gain deeper insights into complex clinical decision-making processes. This data-driven approach can significantly improve learners’ ability to diagnose and plan treatments, thereby improving clinical outcomes. While AI and digital tools offer substantial benefits, the role of educators remains essential in this new educational paradigm. Rather than replacing teachers, AI will augment their roles, allowing them to focus on mentorship, critical thinking, and the ethical dimensions of healthcare.⁴ Educators will need to reimagine their roles, becoming facilitators of learning who guide students in interpreting and applying AI-generated data in clinical settings. As AI takes on administrative tasks such as grading, educators can dedicate more time to meaningful interactions with students.⁵ However, this shift toward AI-driven curricula also requires significant investment in faculty development. Educators must be trained in the use of AI tools and possess a thorough understanding of their applications to ensure that AI is used responsibly and effectively in shaping future healthcare professionals.

As AI becomes more integrated into medical education, addressing the ethical challenges associated with this technology becomes crucial. While AI-driven tools hold great promise, they must be designed and deployed with an acute awareness of biases, data privacy concerns, and the risk of over-reliance on algorithms in clinical decision-making.⁶ The digital curriculum must provide students with technical skills and a strong ethical foundation for AI use in healthcare. Students must be trained to critically evaluate AI outputs, understand their limitations, and ensure that human judgment remains central to patient care. Transforming medical curricula in the AI era is not without challenges. Digital divides, access to technology, and the initial cost of AI-driven platforms may pose barriers to widespread adoption. Institutions must ensure equitable access to resources for all students, regardless of their geographic or socioeconomic backgrounds. Moreover, regulatory bodies such as the Higher Education Commission (HEC) and the Pakistan Medical and Dental Council (PMDC) must revise standards to accommodate these technological advancements. In conclusion, the transformation of medical and dental curricula into a digital, AI-enhanced model represents not only a modernization of education but also a fundamental shift in preparing future healthcare professionals. By embracing AI as an educational partner, medical institutions can create personalized, data-driven learning environments that equip students with the skills and knowledge needed to thrive in an increasingly complex healthcare landscape. The integration of AI into the curriculum offers an opportunity to empower the next generation of doctors, enabling them to navigate future challenges with confidence and competence. Now is the time for this transformation, and it is a journey that we must embark on collectively to ensure the future of education, healthcare, and patient care.