Nevin Manimala

J Pak Med Assoc. 2022 Jun;72(6):1250-1254. doi: 10.47391/JPMA.1782.

ABSTRACT

OBJECTIVES: To evaluate YAG capsulotomy rates following implantation of two types of trifocal intraocular lenses (IOLs).

METHODS: In this retrospective cohort study consecutive patients who underwent cataract surgery with a trifocal IOL from 1st May 2017 to 30th October 2019 at Aga Khan University Hospital, Karachi were included. Eyes which either had an AT Lisa Tri or Alcon PanOptix IOL implant were included. The primary outcome measure was Nd: YAG laser. Univariate analysis of all predictor variables was performed followed by a multivariate regression analysis of those which were significant. A p-value of < 0.05 was taken as significant.

RESULTS: A total of 328 eligible eyes were identified. Nine eyes were excluded. Out of the 319 eyes of 177 patients included in this study, 180 received AT Lisa Tri while 139 of them received Alcon PanOptix Trifocal IOLs. The mean (SD) age of the patients was 52.29 years (±11.04). Gender was equally distributed with 91(51.4%). male patients. Median (IQR) time to laser capsulotomy was 8 months (3-16). Clinically posterior capsular opacification (PCO) was present in 75(23.5%) eyes. A total of 39(12.2%) eyes underwent Nd: YAG laser capsulotomy. Among the AT Lisa Tri group 29 (16.1%) eyes underwent laser capsulotomy compared to 10 (7.2%) (n=10) in Alcon PanOptix group (p=0.016). In both univariate and multivariate analyses, gender and IOL type were statistically significant.

CONCLUSIONS: Eyes implanted with AT Lisa Tri showed a significantly increased rate of YAG capsulotomy. A prospective randomized control trial is recommended to confirm these findings.

PMID:35751355 | DOI:10.47391/JPMA.1782

J Pak Med Assoc. 2022 Jun;72(6):1158-1165. doi: 10.47391/JPMA.3885.

ABSTRACT

OBJECTIVE: To determine the effectiveness of digital health technologies in the management of chronic pain.

METHODS: The systematic review comprised search for randomised controlled trials and controlled clinical trials involving patients with chronic pain published between 2010 and 2020. The search was conducted on PubMed, Google Scholar, MEDLINE, National Centre for Biotechnology Information, and National Library of Medicine databases. Risk bias tool was used to evaluate the biasness in the studies and Pedro scale was used to assess the quality of the included articles.

RESULTS: Of the 33 articles fully assessed, 14(42.42%) were analysed. All the studies analysed were randomised controlled trials and scored 6-10 on the Pedro scale which showed high quality of methodology. The studies typically reported statistically significant benefits of digital health technologies in the management of chronic pain. One of the main benefits was enhanced pain coping skills of the patients. Additionally, majority of the studies included increased adherence to exercise as an essential advantage.

CONCLUSIONS: All the studies analysed reported favourable conclusions regarding the use of digital intervention for chronic pain management.

PMID:35751328 | DOI:10.47391/JPMA.3885

J Pak Med Assoc. 2022 Jun;72(6):1123-1127. doi: 10.47391/JPMA.3368.

ABSTRACT

OBJECTIVE: To assess the diagnostic accuracy of haematoxylin-eosin staining in clinically suspected Hirschsprung disease, and to compare the findings with calretinin and S100 immunohistochemistry.

METHODS: The retrospective study was conducted at the AL-Khansaa Teaching Hospital, Nineveh, Iraq, and comprised data from January 2017 to October 2020 of rectal suction biopsies of patients with clinically and radiologically suspected Hirschsprung disease. Histopathology and immunohistochemistry were performed. Data was analysed using SPSS 16.

RESULTS: Of the 114 patients, 74(64.9%) were males and 40(35.1%) were females. Based on histology, 28(24.6%) cases were negative for ganglion cells, and, of them 25(89.2%) revealed nerve bundle hypertrophy. The diagnostic accuracy for the detection of ganglion cell and nerve hypertrophy using haematoxylin-eosin stain was 99.1% and 94.4%, respectively. Correlation of haematoxylin-eosin staining with calretinin and S100 was statistically near perfection (κ= 0.976 and κ = 0.923), respectively.

CONCLUSIONS: The mainstay to confirm or exclude Hirschsprung disease remains an accurate histopathological evaluation of the haematoxylin-eosin-stained sections of an adequate colorectal biopsy.

PMID:35751321 | DOI:10.47391/JPMA.3368

J Pak Med Assoc. 2022 Jun;72(6):1044-1047. doi: 10.47391/JPMA.800.

ABSTRACT

OBJECTIVE: To compare incubator and thermal blanket for thermoregulation in preterm and low birth weight neonates.

METHODS: The pilot study was conducted from January to March 2018 at the emergency department of the National Institute of Child Health, Karachi, and comprised preterm and low birth weight neonates without any co-morbidity who were randomised to control and interventional groups. Data was collected using a proforma about demographics, weight, gestational age and brief clinical history. Temperature, blood pressure and pulse were monitored along with other routine care after every 15 minutes in the incubator, and the same procedure was adopted for thermal blankets. Data was analysed using Statistical Package for Social Sciences (SPSS) Version 23.

RESULTS: Of the 38 subjects, 19(50%) each were cases and controls. The mean gestational age between the groups was not significantly different (p>0.05). Temperature for the first 60 minutes remained similar in the two groups, but at 75 minutes and onwards, the incubator showed a significantly better results (p<0.05).

CONCLUSION: Thermal blankets can sufficiently provide a hyperthermic environment to the neonates, but an incubator is a more reliable option to provide sustained temperature.

PMID:35751306 | DOI:10.47391/JPMA.800

J Pak Med Assoc. 2022 Jun;72(6):1035-1038. doi: 10.47391/JPMA.366.

ABSTRACT

OBJECTIVE: This study aims to evaluate the serological, radiological and epidemiological analysis of suspected cystic echinococcosis patients, and to assess the positivity rate in the region.

METHODS: The retrospective study was conducted at Bursa Uludag University Hospital, Turkey and comprised data from January 2009 to December 2017 related to patients of either gender with suspected cystic echinococcosis who underwent indirect haemagglutination testing. Demographic and clinical data of patients who tested positive were analysed. Statistical analysis was done using SPSS 23.

RESULTS: Of the 3910 patients with a mean age of 41.6±19.35 years (range: 0-93 years) who underwent indirect haemagglutination testing, 692(17.7%) tested positive; 390(56.4%) females, and 302(43.6%) males. The highest seropositivity rate 107(15.5%) was observed in 2011, followed by 104(15%) in 2016. Seropositive cases were predominantly seen in those aged 40-49 years 131 (18.9%), followed by those aged 50-59 years 124 (17.9%).

CONCLUSIONS: Cystic echinococcosis was found to be a public health problem in South Marmara region of Turkey.

PMID:35751304 | DOI:10.47391/JPMA.366

J Environ Manage. 2022 Sep 1;317:115484. doi: 10.1016/j.jenvman.2022.115484. Epub 2022 Jun 9.

ABSTRACT

Water conservation is vital to safeguard future water availability when natural resources like water become extremely scarce. It is fundamental to understand the significant determinants of water conservation activities which can also facilitate the implementation of appropriate policies for water demand management. Thus, the goal of this study was to determine the important social, psychological, and behavioral factors of water conservation behavior. A questionnaire survey was used to collect the data from 625 international students and employees from different universities in Japan. The structural equation modeling demonstrated that the proposed model explained 46% of the variation in water conservation behavior. Awareness of water issues was highly related to attitude, responsibility, and culture. Except for culture, attitude and responsibility were significantly connected with emotion. Finally, emotion, habit, culture and involvement were significantly and positively associated with water conservation behavior. These factors are incorporated for the first time in this study into a single model to better understand individual water conservation behavior. The sequential regression model showed that all determinants including demographic factors raised the variation’s proportion by 53% in water conservation. Female participants had a significantly higher positive attitude, emotion, and water conservation behavior than male participants. Older participants exhibited higher levels of awareness, habit, culture, and water conservation behavior when compared to younger people. Lastly, participants believed that the most dominant component in water conservation behavior was the awareness of water issues. These findings could assist policymakers in raising household awareness, accountability, and involvement towards water conservation efforts.

PMID:35751281 | DOI:10.1016/j.jenvman.2022.115484

J Environ Manage. 2022 Sep 1;317:115464. doi: 10.1016/j.jenvman.2022.115464. Epub 2022 Jun 5.

ABSTRACT

Based on the panel data of 20 countries in EU during the period of 2007-2019, this paper study the effect of energy market integration (EMI) on renewable energy development (RED). We develop a general equilibrium model to explain how EMI affect the RED and the role of different mechanisms. The empirical results reports that the European EMI increased both the consumption and power generation of renewable energy, which proves a significant positive effect of EMI on the RED. In line with our expectations of theoretical model, our estimates show that the increase of renewable energy consumption is mainly due to the fossil energy cost increased, technology advancement and regional environmental regulation strengthening. And the fossil energy cost is the main driven force which plays a completely mediating role between EMI and RED. Furthermore, we also observe a negative effect of FDI and industry structure on RED.

PMID:35751265 | DOI:10.1016/j.jenvman.2022.115464

J Environ Manage. 2022 Sep 1;317:115402. doi: 10.1016/j.jenvman.2022.115402. Epub 2022 Jun 14.

ABSTRACT

The process of extracting information from data generated in environmental monitoring programs is often carried out using statistical tools, with Statistical Process Control (SPC) showing great potential for application in environmental monitoring. In November 2015, millions of cubic metres of tailings were dumped into the basin of the River Doce with the collapse of the Fundão dam. A study of the impact of this incident requires new approaches in data monitoring and processing, so it was sought to evaluate, using SPC tools, changes in water quality in the basin of the River Doce following the collapse of the dam. Using process charts and the process capability index (PCI), water quality parameters in the Doce and Carmo rivers were evaluated between 2009 and 2020. There, turbidity has improved since 2018, and Mn since 2016. Control charts showed that by December 2020 dissolved Fe was still not within normal pre-event fluctuation patterns. The PCI value showed that the situation worsened after the event for each of the parameters, with the lowest values for Mn and E. coli. By using a reference period, SPC makes it possible to infer the permanence of the impact of extreme pollution on the waterbody, which can be used in the routine monitoring of water quality in such events.

PMID:35751244 | DOI:10.1016/j.jenvman.2022.115402

Comput Biol Med. 2022 Jul;146:105623. doi: 10.1016/j.compbiomed.2022.105623. Epub 2022 May 17.

ABSTRACT

The COVID-19 pandemic has changed the way we practice medicine. Cancer patient and obstetric care landscapes have been distorted. Delaying cancer diagnosis or maternal-fetal monitoring increased the number of preventable deaths or pregnancy complications. One solution is using Artificial Intelligence to help the medical personnel establish the diagnosis in a faster and more accurate manner. Deep learning is the state-of-the-art solution for image classification. Researchers manually design the structure of fix deep learning neural networks structures and afterwards verify their performance. The goal of this paper is to propose a potential method for learning deep network architectures automatically. As the number of networks architectures increases exponentially with the number of convolutional layers in the network, we propose a differential evolution algorithm to traverse the search space. At first, we propose a way to encode the network structure as a candidate solution of fixed-length integer array, followed by the initialization of differential evolution method. A set of random individuals is generated, followed by mutation, recombination, and selection. At each generation the individuals with the poorest loss values are eliminated and replaced with more competitive individuals. The model has been tested on three cancer datasets containing MRI scans and histopathological images and two maternal-fetal screening ultrasound images. The novel proposed method has been compared and statistically benchmarked to four state-of-the-art deep learning networks: VGG16, ResNet50, Inception V3, and DenseNet169. The experimental results showed that the model is competitive to other state-of-the-art models, obtaining accuracies between 78.73% and 99.50% depending on the dataset it had been applied on.

PMID:35751202 | DOI:10.1016/j.compbiomed.2022.105623

Comput Biol Med. 2022 Jul;146:105601. doi: 10.1016/j.compbiomed.2022.105601. Epub 2022 May 19.

ABSTRACT

BACKGROUND: The 2019 novel coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is currently a major challenge threatening the global healthcare system. Respiratory virus infection is the most common cause of asthma attacks, and thus COVID-19 may contribute to an increase in asthma exacerbations. However, the mechanisms of COVID-19/asthma comorbidity remain unclear.

METHODS: The “Limma” package or “DESeq2” package was used to screen differentially expressed genes (DEGs). Alveolar lavage fluid datasets of COVID-19 and asthma were obtained from the GEO and GSV database. A series of analyses of common host factors for COVID-19 and asthma were conducted, including PPI network construction, module analysis, enrichment analysis, inference of the upstream pathway activity of host factors, tissue-specific analysis and drug candidate prediction. Finally, the key host factors were verified in the GSE152418 and GSE164805 datasets.

RESULTS: 192 overlapping host factors were obtained by analyzing the intersection of asthma and COVID-19. FN1, UBA52, EEF1A1, ITGB1, XPO1, NPM1, EGR1, EIF4E, SRSF1, CCR5, PXN, IRF8 and DDX5 as host factors were tightly connected in the PPI network. Module analysis identified five modules with different biological functions and pathways. According to the degree values ranking in the PPI network, EEF1A1, EGR1, UBA52, DDX5 and IRF8 were considered as the key cohost factors for COVID-19 and asthma. The H₂O₂, VEGF, IL-1 and Wnt signaling pathways had the strongest activities in the upstream pathways. Tissue-specific enrichment analysis revealed the different expression levels of the five critical host factors. LY294002, wortmannin, PD98059 and heparin might have great potential to evolve into therapeutic drugs for COVID-19 and asthma comorbidity. Finally, the validation dataset confirmed that the expression of five key host factors were statistically significant among COVID-19 groups with different severity and healthy control subjects.

CONCLUSIONS: This study constructed a network of common host factors between asthma and COVID-19 and predicted several drugs with therapeutic potential. Therefore, this study is likely to provide a reference for the management and treatment for COVID-19/asthma comorbidity.

PMID:35751199 | DOI:10.1016/j.compbiomed.2022.105601