Tag: nevin manimala

BMC Musculoskelet Disord. 2023 May 31;24(1):439. doi: 10.1186/s12891-023-06556-x.

ABSTRACT

BACKGROUND: Musculoskeletal (MSK) disorders are one of the main causes of disability among adults globally. The burden of MSK disorders varies greatly between different regions and is the highest in low- and middle income- countries. This study sought to investigate trends in the burden of MSK disorders across the MENA region, utilizing the GBD 2019 dataset.

METHODS: This ecological study utilized data from the Global Burden of Disease (GBD) to report on the burden of musculoskeletal (MSK) disorders in The Middle East and North Africa (MENA) region between 1990 and 2019. Our analysis involved descriptive statistics and sociodemographic trends and did not employ any specific statistical analyses. Using age-standardized rates of prevalence and disability-adjusted life-years (DALYs), we reported trends in the burden of MSK disorders, as well as national variation between different countries. Furthermore, we analyzed trends in risk factors contributing to MSK disorders by age and gender.

RESULTS: The longitudinal analysis from 1990 to 2019 showed an increase in the age-standardized rate for prevalence and DALYs of MSK disorders by 5% and 4.80%, respectively. Low back pain continued to be the most prevalent MSK condition, while RA and other MSK disorders had the largest percentage increase for DALYs between 1990 and 2019. The study found that Afghanistan had the lowest age standardized DALYs rate attributed to MSK disorders, while Iran, Turkey, and Jordan had the highest. Further, Syria showed the most dramatic decrease while Saudi Arabia had the most notable increase in age standardized DALY rates from 1990 to 2019. In 2019, occupational risks, high body mass index, and tobacco smoking were the main risk factors for MSK disorders, with occupational risks being the largest contributor, and between 1990 and 2019, there was a decrease in the contribution of occupational risks but an increase in the contribution of high body mass index as a risk factor.

CONCLUSION: This study highlights the significant burden of MSK disorders in the MENA region, with various risk factors contributing to its increasing prevalence in recent decades. Further research is needed to better understand the underlying factors and potential interventions that could improve health outcomes. Addressing MSK disorders should be a public health priority in the region, and efforts should be made to develop effective strategies to prevent and manage this debilitating condition.

PMID:37259119 | DOI:10.1186/s12891-023-06556-x

Thyroid Res. 2023 Jun 1;16(1):15. doi: 10.1186/s13044-023-00156-6.

ABSTRACT

BACKGROUND: One of the common causes of suboptimal control of thyroid stimulating hormone (TSH) in levothyroxine-treated hypothyroidism is coadministration of proton pump inhibitors (PPIs). Morning administration of pantoprazole has been shown to suppress intragastric pH to a greater extent. We therefore aimed to determine the effect of pantoprazole at different time points of the day on thyroid function test (TFT) in levothyroxine-treated overt primary hypothyroidism.

METHODS: In this single centre, hospital based, prospective, two arm cross-over study (AB, BA), participants were randomized into 2 groups based on morning (6:00 am – 7:00 am simultaneously with the scheduled levothyroxine tablet) (group M) and evening (30 min before dinner) intake of 40 mg pantoprazole tablet (group N). After the initial 6 weeks (period 1), a washout period of 1 week for pantoprazole was given, and then both the groups crossed over for another 6 weeks (period 2). Patients were instructed to continue the same brand of levothyroxine tablet at empty stomach 1-hour before breakfast. Serum TSH was measured at baseline, week 6, and week 13.

RESULTS: Data from 30 patients, who completed the study with 100% compliance, were analysed. Mean TSH values of the study participants were significantly higher both at week 6 and week 13 compared to the baseline. Mean baseline serum TSH concentrations for groups M and N were 2.70 (± 1.36), and 2.20 (± 1.06) µlU/mL, respectively. Mean serum TSH concentrations at the end periods 1 and 2 for group M were 3.78 (± 4.29), and 3.76 (± 2.77) while the levels in group N were 3.30 (± 1.90), and 4.53 (± 4.590) µlU/mL, respectively. There was a significant rise in serum TSH concentration across periods 1 and 2 in both the groups (F_{2, 58} = 3.87, p = 0.03). Within group changes in TSH across periods 1 and 2 were not statistically significant. Similarly difference in TSH between the groups, either at 6 weeks or at 13 weeks, were also not statistically significant.

CONCLUSIONS: Concomitant use of pantoprazole, even for 6 weeks, leads to significant elevation in serum TSH in levothyroxine-treated patients who are biochemically euthyroid, irrespective of timing of pantoprazole intake. Early morning and night-time administration of pantoprazole have similar effect on TFT in these patients.

PMID:37259094 | DOI:10.1186/s13044-023-00156-6

Pediatr Rheumatol Online J. 2023 May 31;21(1):50. doi: 10.1186/s12969-023-00836-5.

ABSTRACT

OBJECTIVES: To determine the clinical and laboratory differences between leukemic arthritis (LA) and juvenile idiopathic arthritis (JIA) at the onset of the disease.

MATERIAL AND METHODS: Patients under 16 years of age, both genders, who presented for the first time to the pediatric rheumatology service with a diagnosis of probable JIA, with arthritis and without peripheral blood blasts, in which the final diagnosis was acute lymphoblastic leukemia (ALL) or JIA. The clinical and laboratory characteristics of the patients were compared, chi-square and relative risk were used for categorical variables, and the Mann-Whitney U and T-test for the comparison of means between groups. A binary logistic regression model was developed to differentiate leukemic arthritis from JIA.

RESULTS: A total of 76 patients, 14 with LA and 62 with JIA, were analyzed. The mean age at diagnosis was lower in the leukemic arthritis group, the female gender prevailed in the JIA group, and the time to onset of symptoms was lower in the leukemic arthritis group. Patients with leukemic arthritis showed increased pain intensity, fever, weight loss, nocturnal diaphoresis, lymph node enlargement, hepatosplenomegaly, and pain that did not improve with analgesic administration. Laboratory parameters with statistical significance were the presence of anemia, leukopenia, and neutropenia. The platelet count was significant but in a low normal value, compared to the JIA. A binary logistic regression model was developed to differentiate leukemic arthritis from JIA. The probability associated with the statistic (Chi-square) was 0.000, and the Cox and Snell R2 and Nagelkerke R2 values were 0.615 and 1, respectively. The developed model correctly classified 100% of the cases.

CONCLUSIONS: The diagnosis of acute lymphoblastic leukemia should be ruled out in patients who present with arthritis and hematological alterations, mainly leukopenia and neutropenia, with joint pain disproportionate to the degree of arthritis, predominantly at night and that does not improve with the use of analgesics, fever, lymph nodes, and hepatosplenomegaly. Criteria are suggested to differentiate both diseases.

PMID:37259088 | DOI:10.1186/s12969-023-00836-5

BMC Nurs. 2023 May 31;22(1):186. doi: 10.1186/s12912-023-01348-z.

ABSTRACT

BACKGROUND: Nurses’ effective handover communication is vital for patient safety and quality of care. Few studies have empirically tested how certain factors influence the quality of handover in the Saudi context.

METHODS: A descriptive correlational design was used with a convenience sample of all nurses (N = 201) working in Saudi hospital CCUs in 2022. Demographics and handover quality instruments were used to collect the necessary data in addition to two open-ended questions that asked about perceived barriers and facilitators to handover. The analysis was conducted using descriptive statistics and regression analysis.

RESULTS: The majority of nurses reported good-quality handover. The regression analysis showed that staffing, cognitive capacity, the focus of attention, relationships, and safety climate factors contributed positively to the variance of handover quality. In contrast, intrusions, distractions, anxiety, time stress, and acute and chronic fatigue factors negatively affected the prediction of handover quality (p < 0.05). Nurses added types of shifts and languages as barriers to handover while emphasizing training and the use of standardized tools for handover as facilitators.

CONCLUSION AND RECOMMENDATIONS: Nursing handover is a multidimensional phenomenon. By understanding the determinants that contribute to or hinder handover quality, it is possible to develop targeted interventions aimed at improving communication and the quality of shift handover in CCUs. The current study’s findings highlight the need for nurses to work in a more supportive environment, receive better training, and follow a standardized handover protocol. Additionally, nurse managers should pay more attention to nurses’ well-being to control or mitigate the effect of psychological precursors on the quality of nurses’ handover. Future research should investigate handover practices and outcomes on units that have both good and bad practice environments.

PMID:37259086 | DOI:10.1186/s12912-023-01348-z

BMC Public Health. 2023 May 31;23(1):1031. doi: 10.1186/s12889-023-15856-9.

ABSTRACT

BACKGROUND: According to the minority stress theory, stigma affects the health of marginalized populations. Previous stigma research has focused on the health effects of individual and interpersonal stigma, paying less attention to structural factors. Laws on legal gender recognition affect the lives of transgender individuals in unique ways. The fact that these laws and population attitudes vary greatly between European countries, offer a unique opportunity to study the role of structural stigma in the lives of transgender individuals. Little is known about how transgender specific structural stigma relates to individual health determinants. Consequently, the aim of this study was to explore the association between structural stigma and access to gender affirming care, gender identity disclosure in health care, and experiences of discrimination in health care across 28 European countries.

METHODS: By using multilevel regression, we combined data on health seeking behavior, transgender identity disclosure to health care providers, and experiences of discrimination in health care from 6,771 transgender individuals participating in the 2012 European Union Lesbian, Gay, Bisexual and Transgender survey with a structural stigma measure, consisting of population attitudes towards transgender individuals as well as national legislation on gender recognition. Reasons to refrain from seeking care and discrimination in health care were assessed by categorizing countries as low or high in structural stigma and using Chi-square statistics.

RESULTS: Country-level structural stigma was negatively associated experiences of seeking gender affirming care and positively associated with concealment of being transgender to health care providers. Identity concealment was associated with a lower likelihood of exposure to discrimination in the health care setting across countries regardless of their level of structural stigma. The most prevalent reasons to forgo gender affirming care were shared between low and high structural stigma country groups and centered around fear.

CONCLUSION: The results highlight the importance of changing stigmatizing legislation and population attitudes to promote access to gender affirming care as well as openness of being transgender towards providers. Measures to decrease discrimination in the health care setting are warranted in high as well as in low structural stigma countries.

PMID:37259082 | DOI:10.1186/s12889-023-15856-9

BMC Geriatr. 2023 May 31;23(1):341. doi: 10.1186/s12877-023-04077-9.

ABSTRACT

BACKGROUND: Under the state of emergency, it has been reported that the amount of physical activity among community-dwelling older adults has decreased significantly due to refraining from going out, and there are strong concerns about the Geriatric Locomotive Function Scale and deterioration of mental health. Therefore, this study aimed to investigate whether the depressive state before the coronavirus disease 2019 (COVID-19) pandemic affected the 25-Geriatric Locomotive (GLFS) score during the COVID-19 pandemic among community-dwelling older adults.

METHODS: The participants were 194 community-dwelling older adults (45 men, 149 women) with an average age of 75.5 ± 5.5 years who responded to a self-administered survey conducted three times (preliminary, second, and third) from before the 2018 COVID-19 pandemic to March 2021. Individuals with a score of ≥ 10 on the Geriatric Depression Scale 15 (GDS 15) were excluded. The survey items included the 25-question Geriatric Locomotive Function Scale (GLFS25), GDS 15, and other basic attributes. Those with scores of 5 to 9 on the GDS 15 and those with scores of 0 to 4 were assigned to the depressive symptoms (DS) group and the non-DS group, respectively. Statistical analysis was performed using two-way analysis of variance. The Mann-Whitney U test was used for comparisons between the groups.

RESULTS: In total, 187 patients were included in the analysis, excluding 7 patients. GLFS 25 showed a significant increase in scores at the second and third time points compared with baseline, and a main effect was confirmed in both groups, with no interaction effect. The second time, the score was 10.0 ± 8.5 and 13.7 ± 10.5 in the non-DS and DS groups, respectively. The third time, the non-DS and DS groups scored 10.8 ± 10.5 and 14.9 ± 10.1 points, respectively, indicating a significant difference.

CONCLUSIONS: Our results revealed that the increase in the GLFS 25 score in community-dwelling older adults during the COVID-19 pandemic was related to their DS during normal times before the pandemic. Evaluating such individuals and providing social support may effectively reduce the deterioration of the GLFS 25 score.

PMID:37259068 | DOI:10.1186/s12877-023-04077-9

BMC Infect Dis. 2023 May 31;23(1):366. doi: 10.1186/s12879-023-08343-4.

ABSTRACT

BACKGROUND: Hepatitis B (HB) is a virus which causes a potentially fatal liver infection. It is a DNA virus belonging to the Hepadnaviridae virus family. Africa, after Asia, has the second highest number of chronic HBV carriers and is considered a high-endemic region. Ethiopia is classified as a country with a high prevalence of viral hepatitis and with nations that lack a systematic strategy for viral hepatitis surveillance.

METHODS: S-I-C-R deterministic model was developed and the numerical simulations were done in “R” statistical and programming software. Fixed population assumption was considered so as to develop a simple model which could predict the HBV vertical transmission for the next 5 decades.

RESULTS: The model revealed that significant number of populations will be infected and become carrier till the end the next 49 years even though it has decreasing trend. It was predicted that 271,719 people will die of HBV complications if no intervention will be made on its vertical transmission. The sensitivity analysis result showed that the force of infection has the most important parameter in the vertical transmission dynamics of hepatitis B. Provision of hepatitis B immunoglobulin (HBVIG) and vaccines at the time of delivery could decrease the force of infection by more than half and 51,892 lives will be saved if the intervention is offered for 50% of deliveries in Ethiopia.

CONCLUSION: Despite the fact that the incidence of HBV vertical transmission is substantial, it is expected to decline during the next five decades. However, the situation necessitates immediate attention, since it results in thousands of deaths if no action is taken. Offering HBVIG and vaccinations to the 50% of infants can save many lives and reduces the force of infection by more than a half.

PMID:37259048 | DOI:10.1186/s12879-023-08343-4

BMC Public Health. 2023 Jun 1;23(1):1039. doi: 10.1186/s12889-023-15835-0.

ABSTRACT

BACKGROUND: Mathematical models to forecast the risk trend of the COVID-19 pandemic timely are of great significance to control the pandemic, but the requirement of manual operation and many parameters hinders their efficiency and value for application. This study aimed to establish a convenient and prompt one for monitoring emerging infectious diseases online and achieving risk assessment in real time.

METHODS: The Optimized Moving Average Prediction Limit (Op-MAPL) algorithm model analysed real-time COVID-19 data online and was validated using the data of the Delta variant in India and the Omicron in the United States. Then, the model was utilized to determine the infection risk level of the Omicron in Shanghai and Beijing.

RESULTS: The Op-MAPL model can predict the epidemic peak accurately. The daily risk ranking was stable and predictive, with an average accuracy of 87.85% within next 7 days. Early warning signals were issued for Shanghai and Beijing on February 28 and April 23, 2022, respectively. The two cities were rated as medium-high risk or above from March 27 to April 20 and from April 24 to May 5, indicating that the pandemic had entered a period of rapid increase. After April 21 and May 26, the risk level was downgraded to medium and became stable by the algorithm, indicating that the pandemic had been controlled well and mitigated gradually.

CONCLUSIONS: The Op-MAPL relies on nothing but an indicator to assess the risk level of the COVID-19 pandemic with different data sources and granularities. This forward-looking method realizes real-time monitoring and early warning effectively to provide a valuable reference to prevent and control infectious diseases.

PMID:37259046 | DOI:10.1186/s12889-023-15835-0

BMC Med Res Methodol. 2023 May 31;23(1):133. doi: 10.1186/s12874-023-01955-z.

ABSTRACT

OBJECTIVE: PONV reduces patient satisfaction and increases hospital costs as patients remain in the hospital for longer durations. In this study, we build a preliminary artificial intelligence algorithm model to predict early PONV in patients.

METHODS: We use R for statistical analysis and Python for the machine learning prediction model.

RESULTS: Average characteristic engineering results showed that haloperidol, sex, age, history of smoking, and history of PONV were the first 5 contributing factors in the occurrence of early PONV. Test group results for artificial intelligence prediction of early PONV: in terms of accuracy, the four best algorithms were CNNRNN (0.872), Decision Tree (0.868), SVC (0.866) and adab (0.865); in terms of precision, the three best algorithms were CNNRNN (1.000), adab (0.400) and adab (0.868); in terms of AUC, the top three algorithms were Logistic Regression (0.732), SVC (0.731) and adab (0.722). Finally, we built a website to predict early PONV online using the Streamlit app on the following website: ( https://zhouchengmao-streamlit-app-lsvc-ad-st-app-lsvc-adab-ponv-m9ynsb.streamlit.app/ ).

CONCLUSION: Artificial intelligence algorithms can predict early PONV, whereas logistic regression, SVC and adab were the top three artificial intelligence algorithms in overall performance. Haloperidol, sex, age, smoking history, and PONV history were the first 5 contributing factors associated with early PONV.

PMID:37259031 | DOI:10.1186/s12874-023-01955-z

BMC Emerg Med. 2023 Jun 1;23(1):61. doi: 10.1186/s12873-023-00831-9.

ABSTRACT

BACKGROUND: Injury data play a pivotal role in monitoring public health issues and Injury Surveillance Information Systems (ISIS) are useful for continuous data collection and analysis purposes. Since emergency department (ED) is usually the first place of referral for the injured people, the aim of this study was to develop a conceptual model for an ED-based ISIS.

METHODS: This study was completed in 2020 and the Delphi technique (three rounds) was used to determine the main components of an ED-based ISIS. The participants were selected using the purposive sampling method. A 5-point Likert scale questionnaire was used for data collection and data were analyzed using descriptive statistics.

RESULTS: In the first, second, and third rounds of the Delphi study, 60, 44, and 28 experts participated, respectively. In the first and second rounds, most of the items including the personal data, clinical data, data sources, and system functions were found important. In the third round of the Delphi study, 13 items which did not reach a consensus in the previous rounds were questioned again and five items were removed from the final model.

CONCLUSION: According to the findings, various data elements and functions could be considered for designing an ED-based ISIS and a number of data sources should be taken into count to be integrated with this system. Although the conceptual model presented in the present study can facilitate designing the actual system, the final system needs to be implemented and used in practice to determine how it can meet users’ requirements.

PMID:37259025 | DOI:10.1186/s12873-023-00831-9