Drugs use during pregnancy at Medani Maternity Hospital, Sudan

Background: There is a limited knowledge on use of drugs during pregnancy including beneficial and possible adverse effects of drugs on both the mother and the fetus.Objective: To investigate epidemiology of use of drugs during pregnancy.Methods: A cross sectional hospital based study at Medani Hospital during the period December 2011. After signing an informed consent, a pre-tested questionnaire was used to gather data from each parturient mother on her age, parity, level of education, antenatal care visits and use of drug during the index pregnancy.Results: The vast majority (334; 98.2%) of the interviewed women used drugs during the index pregnancy. Around ten percent (35; 10.5%) of these women used the drugs in the first trimester of pregnancy. The majority (266; 78.2%) used the drugs in third trimester and the rest used it in the second trimester. The most common drugs used were antibiotics, tonics, antimalarials and antiemetic.Conclusion: There is a very high rate of drug use in this setting. Antibiotics and antimalarials drugs were the most used drugs.Keywords: drugs, pregnancy, antibiotics, antimalarials, Sudan

ATR based infrared spectroscopy for the diagnosis of neonatal respiratory distress syndrome

Optical spectroscopy offers a potential non-invasive, label free and rapid method to assist clinicians to diagnose diseases for which biomarkers are known. Neonatal respiratory distress syndrome (nRDS) diagnosis in preterm infants is known to be correlated with the lecithin/sphingomyelin ratio (LS ratio) in gastric aspirates, with a ratio less than 2.2 indicating that surfactant replacement therapy is needed. Currently no widespread method exists that can give clinically relevant answers in less than 2 hours from the point of sample collection as it is difficult to identify those who could benefit from prompt surfactant treatment. Various LS ratios were generated using pure dipalmitoylphosphatidylcholine (DPPC) and sphingomyelin (SM) dissolved in dichloromethane and infrared spectra generated using Attenuated Total Reflection (ATR) assisted Fourier Transform InfraRed spectrometry (FTIR). Subsequent analysis obtained the LS ratio using the spectra alone. Further, we demonstrate the application of principal component regression (PCR) and partial least squares (PLS) fits to measured spectra to assist in the determination of the LS ratio using a model trained with multiple runs of the different batches of the same concentration

How to prioritize patients and redesign care to safely resume planned surgery during the COVID-19 pandemic.

AIMS: Restarting planned surgery during the COVID-19 pandemic is a clinical and societal priority, but it is unknown whether it can be done safely and include high-risk or complex cases. We developed a Surgical Prioritization and Allocation Guide (SPAG). Here, we validate its effectiveness and safety in COVID-free sites. METHODS: A multidisciplinary surgical prioritization committee developed the SPAG, incorporating procedural urgency, shared decision-making, patient safety, and biopsychosocial factors; and applied it to 1,142 adult patients awaiting orthopaedic surgery. Patients were stratified into four priority groups and underwent surgery at three COVID-free sites, including one with access to a high dependency unit (HDU) or intensive care unit (ICU) and specialist resources. Safety was assessed by the number of patients requiring inpatient postoperative HDU/ICU admission, contracting COVID-19 within 14 days postoperatively, and mortality within 30 days postoperatively. RESULTS: A total of 1,142 patients were included, 47 declined surgery, and 110 were deemed high-risk or requiring specialist resources. In the ten-week study period, 28 high-risk patients underwent surgery, during which 68% (13/19) of Priority 2 (P2, surgery within one month) patients underwent surgery, and 15% (3/20) of P3 ( three months) groups. Of the 1,032 low-risk patients, 322 patients underwent surgery. Overall, 21 P3 and P4 patients were expedited to 'Urgent' based on biopsychosocial factors identified by the SPAG. During the study period, 91% (19/21) of the Urgent group, 52% (49/95) of P2, 36% (70/196) of P3, and 26% (184/720) of P4 underwent surgery. No patients died or were admitted to HDU/ICU, or contracted COVID-19. CONCLUSION: Our widely generalizable model enabled the restart of planned surgery during the COVID-19 pandemic, without compromising patient safety or excluding high-risk or complex cases. Patients classified as Urgent or P2 were most likely to undergo surgery, including those deemed high-risk. This model, which includes assessment of biopsychosocial factors alongside disease severity, can assist in equitably prioritizing the substantial list of patients now awaiting planned orthopaedic surgery worldwide. Cite this article: Bone Jt Open 2021;2(2):134-140

Remnant cholesterol predicts progression of diabetic nephropathy and retinopathy in type 1 diabetes

Background We aimed to assess whether remnant cholesterol concentration and variability predict the progression of diabetic nephropathy (DN) and severe diabetic retinopathy (SDR) in type 1 diabetes. Methods This observational prospective study covered 5150 FinnDiane Study participants. Remnant cholesterol was calculated as total cholesterol - LDL cholesterol - HDL cholesterol and variability as the coefficient of variation. DN category was based on consensus albuminuria reference limits and the progression status was confirmed from medical files. SDR was defined as retinal laser treatment. For 1338 individuals, the severity of diabetic retinopathy (DR) was graded using the ETDRS classification protocol. Median (IQR) follow-up time was 8.0 (4.9-13.7) years for DN and 14.3 (10.4-16.3) for SDR. Results Remnant cholesterol (mmol L-1) was higher with increasing baseline DN category (P < 0.001). A difference was also seen comparing non-progressors (0.41 [0.32-0.55]) with progressors (0.55 [0.40-0.85]), P < 0.001. In a Cox regression analysis, remnant cholesterol predicted DN progression, independently of diabetes duration, sex, HbA(1c), systolic blood pressure, smoking, BMI, estimated glucose disposal rate and estimated glomerular filtration rate (HR: 1.51 [1.27-1.79]). Remnant cholesterol was also higher in those who developed SDR (0.47 [0.36-0.66]) than those who did not (0.40 [0.32-0.53]), P < 0.001, and the concentration increased stepwise with increasing DR severity (P < 0.001). Regarding SDR, the HR for remnant cholesterol was 1.52 (1.26-1.83) with the most stringent adjustment. However, remnant cholesterol variability was not independently associated with the outcomes. Conclusions Remnant cholesterol concentration, but not variability, predicts DN progression and development of SDR. However, it remains to be elucidated whether the associations are causal or not.Peer reviewe

Prediction of Neonatal Respiratory Distress Biomarker Concentration by Application of Machine Learning to Mid-Infrared Spectra

The authors of this study developed the use of attenuated total reflectance Fourier transform infrared spectroscopy (ATR–FTIR) combined with machine learning as a point-of-care (POC) diagnostic platform, considering neonatal respiratory distress syndrome (nRDS), for which no POC currently exists, as an example. nRDS can be diagnosed by a ratio of less than 2.2 of two nRDS biomarkers, lecithin and sphingomyelin (L/S ratio), and in this study, ATR–FTIR spectra were recorded from L/S ratios of between 1.0 and 3.4, which were generated using purified reagents. The calibration of principal component (PCR) and partial least squares (PLSR) regression models was performed using 155 raw baselined and second derivative spectra prior to predicting the concentration of a further 104 spectra. A three-factor PLSR model of second derivative spectra best predicted L/S ratios across the full range (R2: 0.967; MSE: 0.014). The L/S ratios from 1.0 to 3.4 were predicted with a prediction interval of +0.29, −0.37 when using a second derivative spectra PLSR model and had a mean prediction interval of +0.26, −0.34 around the L/S 2.2 region. These results support the validity of combining ATR–FTIR with machine learning to develop a point-of-care device for detecting and quantifying any biomarker with an interpretable mid-infrared spectrum

Trypanosoma cruzi screening in people living with HIV in the UK

People living with HIV (PLWH) are at higher risk of reactivation of Chagas disease, a neglected tropical disease, caused by Trypanosoma cruzi. There are no data from UK HIV clinics on the prevalence of T. cruzi. We implemented T. cruzi screening at our clinic as part of routine care for PLWH with epidemiological risk factors. Among 86 patients screened, none had positive serology: one seropositive patient was identified due to increased clinician awareness. Implementing T. cruzi screening as part of routine clinical care was feasible, though labour intensive and identified at-risk individuals

Effectiveness of an integrated diabetes care package at primary healthcare facilities: a cluster randomised trial in Pakistan

Background: There were an estimated 7 million people living with diabetes in Pakistan in 2014, and this is predicted to reach 11.4 million by 2030. Aim: To assess if an integrated care package can achieve better control of diabetes. Design & setting: The pragmatic cluster randomised controlled trial (cRCT) was conducted from December 2014–June 2016 at 14 primary healthcare facilities in Sargodha district. Opportunistic screening, diagnostic testing, and patient recording processes were introduced in both the control 'testing, treating, and recording' (TTR) arm, and the intervention 'additional case management' (ACM) arm, which also included a clinical care guide and pictorial flipbook for lifestyle education, associated clinician training, and mobile phone follow-up. Method: Clinics were randomised on a 1:1 basis (sealed envelope lottery method) and 250 patients recruited in the ACM arm and 245 in the TTR-only arm (age ≥25 years and HbA1c >7%). The primary outcome was mean change in HbA1c (%) from baseline to 9-month follow-up. Patients and staff were not blinded. Results: The primary outcome was available for n = 238/250 (95.2%) participants in the ACM arm and n = 219/245 (89.4%) participants in the TTR-only arm (all clusters). Cluster level mean outcome was -2.26 pp (95% confidence intervals [CI] = -2.99 to -1.53) for the ACM arm, and -1.44 pp (95% CI = -2.34 to -0.54) for the TTR-only arm. Cluster level mean ACM–TTR difference (covariate-unadjusted) was -0.82 pp (95% CI = -1.86 to 0.21; P = 0.11). Conclusion: The ACM intervention in public healthcare facilities did not show a statistically significant effect on HbA1c reduction compared to the control (TTR-only) arm. Future evaluation should assess changes after a longer follow-up period, and minimal care enhancement in the comparator (control) arm

Hybrid Focal Stereo Networks for Pattern Analysis in Homogeneous Scenes

In this paper we address the problem of multiple camera calibration in the presence of a homogeneous scene, and without the possibility of employing calibration object based methods. The proposed solution exploits salient features present in a larger field of view, but instead of employing active vision we replace the cameras with stereo rigs featuring a long focal analysis camera, as well as a short focal registration camera. Thus, we are able to propose an accurate solution which does not require intrinsic variation models as in the case of zooming cameras. Moreover, the availability of the two views simultaneously in each rig allows for pose re-estimation between rigs as often as necessary. The algorithm has been successfully validated in an indoor setting, as well as on a difficult scene featuring a highly dense pilgrim crowd in Makkah.Comment: 13 pages, 6 figures, submitted to Machine Vision and Application