Integration of Agro-Ecological and Groundwater Resources for the Assessment of Crop Suitability Potential Modeling: The Case of Limpopo Province, South Africa

A comprehensive subtropical fruit potential model (IUM) was established through novel integration of groundwater resources with multi-criterion predictive parameters. Equal-weights overlay was applied to reclassified and ranked rasters to institute IUM. Avocado and litchi had the least spatial extent that concealed the micro-climatic zones of high rainfall (>1000 mmpa) in Vhembe, Mopane, and Waterberg districts; meanwhile, mango and citrus were the crops with the most extensive province-wide distribution. Subsequent potential was apportioned in these sequences by constituency: Waterberg (1719019 ha), Mopane (977741 ha), Vhembe (764044 ha), Capricorn (579506 ha), and Sekhukhune (379968 ha). The IUM resulted in the demarcation of 8.7 million ha to produce the selected crops, which reflected an increase of 7.7 million from the rainfed suitability model. The integrated model would result in the creation of 10.87 million direct employments. The IUM expanded the agrarian sector with positive spinoffs for agribusiness development.

Associations between radiographic parameters in the reverse shoulder arthroplasty and patient outcomes

Background Various radiological parameters have been measured in the Reverse Shoulder Arthroplasty (RSA) and correlated to patient outcomes, to determine best baseplate position. Results remain unclear with respect to certain parameters such as inferior baseplate tilt. We have investigated our series of patients to clarify the relationship between radiological parameters and patient outcomes. Methods We conducted a UK based bi-centre retrospective review of 156 prostheses. Critical shoulder angle (CSA), RSA angle (RSAA), Overhang and Deltoid Lever Arm (DLA) were measured on preoperative and postoperative radiographs. Range of motion and Oxford Shoulder Score (OSS) (range 1–8 years) were obtained. We assessed for scapular notching at minimum 1 year follow up (n = 138). Results Decreased postoperative CSA and increased DLA were associated with higher OSSs (P = 0.001 and 0.019). Increased overhang and DLA were associated with increased flexion (P = 0.033 and 0.024 respectively). Multivariate analysis showed that CSA and DLA affected notching rate (P = 0.002 and 0.007). Conclusions Baseplate tilt in relation to the acromion (CSA) and DLA are the most predictive parameters for notching and OSS. We recommend considering a maximum CSA of 26 degrees to decrease notching rate and improve OSS. We recommend considering an Overhang of at least 6 mm to improve FF.

TRIPLE NEGATIVE BREAST CANCER, EXPERIENCE OF MILITARY HOSPITAL RABAT: ABOUT 52 CASES

Objective: to review the epidemiological, clinical, anatomopathological, biological, therapeutic and prognostic characteristics of this histo-prognostic subgroup, namely triple-negative breast cancer Material and Method: Our work consists of a retrospective study carried out at the military hospital of instruction Med v rabat between January 2010 and December 2017 on 52 cases of invasive breast carcinoma with a triple negative phenotype. Result: From an epidemiological point of view: a peak in frequency was noted between 45 and 50 years old, and 48.1% of patients still in genital activity. On the anatomo-pathological level: invasive ductal carcinoma is the most predominant type representing 68.3% of cases with an average tumor size of 30mm. Histopronostic grades II and III each represent 43.2% and 56.8% of cases. Therapeutically: more than 42.3% received conservative treatment and 57.7% underwent radical surgery of the Pateytype.Adjuvant systemic chemotherapy was given in 86.5% of cases and 5.8% received neoadjuvant chemotherapy On the evolutionary level, 17.3% or 9 cases developed systemic metastases with predilection for the lungs. Conclusion: Despite advances in treatments and the emergence of targeted therapies, breast cancer remains the leading cause of death in women. Current clinical and histological classifications do not fully establish the prognostic and predictive parameters of response to treatment.

Runout Number: A New Metric for Landslide Runout Characterization

ABSTRACT Landslide runout has traditionally been quantified by the height-to-length ratio, H/L, which, in many cases, is strongly influenced by the slope of the runout path. In this study, we propose an alternative mobility measure, the unitless Runout Number, measured as the landslide length divided by the square root of the landslide area, which characterizes landslide shape in terms of elongation. We used a database of 158 landslides of varying runout distances from locations in northern California, Oregon, and Washington state to compare the two runout measurement methods and explore their predictability using parameters that can be measured or estimated using geographic information systems. The Runout Number better describes the overall runout for several landslide and slope geometries. The two mobility measures show very little correlation to each other, indicating that the two parameters describe different landslide mobility mechanisms. When compared to predictive parameters shown by prior research to relate to landslide runout, the two runout measurement methods show different correlations. H/L correlates more strongly to initial slope angle, upslope contributing area, landslide area, and grain size distribution (percent clay, silt, total fines, and sand). The Runout Number correlates more strongly to planimetric curvature, upslope contributing area normalized by landslide area, and percent sand. Although these correlations are not necessarily strong enough for prediction, they indicate the validity of both runout measurement methods and the benefit of including both numbers when characterizing landslide mobility.

COVID-19 in lung transplant recipients—Risk prediction and outcomes

Patients after lung transplantation are at risk for life-threatening infections. Recently, several publications on COVID-19 outcomes in this patient population appeared, but knowledge on optimal treatment, mortality, outcomes, and appropriate risk predictors is limited. A retrospective analysis was performed in a German high-volume lung transplant center between 19th March 2020 and 18th May 2021. Impact of COVID-19 on physical and psychological health, clinical outcomes, and mortality were analyzed including follow-up visits up to 12 weeks after infection in survivors. Predictive parameters on survival were assessed using univariate and multivariate proportional hazards regression models. Out of 1,046 patients in follow-up, 31 acquired COVID-19 during the pandemic. 12 of 31 (39%) died and 26 (84%) were hospitalized. In survivors a significant decline in exercise capacity (p = 0.034), TLC (p = 0.02), and DLCO (p = 0.007) was observed at follow-up after 3 months. Anxiety, depression, and self-assessed quality of life remained stable. Charlson comorbidity index predicted mortality (HR 1.5, 1.1–2.2; p = 0.023). In recipients with pre-existing CLAD, mortality and clinical outcomes were inferior. However, pre-existing CLAD did not predict mortality. COVID-19 remains a life-threatening disease for lung transplant recipients, particularly in case comorbidities. Further studies on long term outcomes and impact on pre-existing CLAD are needed.

Ultrasound in Evaluation of Subclinical Enthesitis of Extensor Digitorum Tendon and Nail Unit Changes in Psoriasis

Background Subclinical inflammation at entheseal level has been detected in patients with psoriasis without previous history of arthropathy or Psoriatic arthritis (PsA). Ultrasound (US) is a valid and sensitive tool for the assessment of inflammatory involvement at entheseal level in PsA patients. Objective To detect subclinical arthritis or enthesitis at distal interphalangeal (DIP) fingers and nail unit changes in psoriatic patient for early detection of PsA Patients and Methods This study included 30 adult psoriatic patients and 30 healthy matched controls. All underwent history, clinical examination, Psoriasis Area and Severity Index (PASI), Nail Psoriasis Severity Index (NAPSI) score calculation and musculoskeletal US both grey and power Doppler (PD) assessed at enthesis of extensor digitorum tendon insertion at distal phalanx, DIP joints from 2nd to 5th finger bilaterally examined for detection of synovitis and over the nail for morpho-structural evaluation. Results Patient’s ages ranged from 18-65 years and controls 20-60 years (mean ±SD 45.07 ± 13.52, 38.37 ± 11.96 respectively), male to female ratio 1:2. DIP joint affection in the form of synovial hypertrophy and effusion with PD was found in 13.3% of cases. Enthesophyte with PD in 56.7% of cases. On comparison between NAPSI score by clinical examination versus US examination, the sensitivity of US was 100%, all cases clinically positive by NAPSI were positively affected by US (20 cases). Also 30% of cases were negative by NAPSI and were positive by US (7cases). Three cases were negative by both NAPSI and US. A significant positive correlation was observed between disease duration and NAPSI Score (r = 0.429, pvalue<0.05), similarly between presence of enthesophyte with PD and PASI Score (r = 0.547, pvalue<0.02). Conclusion Detection of subclinical enthesopathy at DIP joint by ultrasound is not infrequent, so it is an important tool for examining enthesis in psoriatic patients. The presence of a high PASI score and long disease duration could be considered as predictive parameters for the presence of psoriatic enthesitis ongoing to arthritis.

Development and validation of nomogram to predict severe illness requiring intensive care follow up in hospitalized COVID-19 cases

Background Early identification of severe COVID-19 patients who will need intensive care unit (ICU) follow-up and providing rapid, aggressive supportive care may reduce mortality and provide optimal use of medical resources. We aimed to develop and validate a nomogram to predict severe COVID-19 cases that would need ICU follow-up based on available and accessible patient values. Methods Patients hospitalized with laboratory-confirmed COVID-19 between March 15, 2020, and June 15, 2020, were enrolled in this retrospective study with 35 variables obtained upon admission considered. Univariate and multivariable logistic regression models were constructed to select potential predictive parameters using 1000 bootstrap samples. Afterward, a nomogram was developed with 5 variables selected from multivariable analysis. The nomogram model was evaluated by Area Under the Curve (AUC) and bias-corrected Harrell's C-index with 95% confidence interval, Hosmer–Lemeshow Goodness-of-fit test, and calibration curve analysis. Results Out of a total of 1022 patients, 686 cases without missing data were used to construct the nomogram. Of the 686, 104 needed ICU follow-up. The final model includes oxygen saturation, CRP, PCT, LDH, troponin as independent factors for the prediction of need for ICU admission. The model has good predictive power with an AUC of 0.93 (0.902–0.950) and a bias-corrected Harrell's C-index of 0.91 (0.899–0.947). Hosmer–Lemeshow test p-value was 0.826 and the model is well-calibrated (p = 0.1703). Conclusion We developed a simple, accessible, easy-to-use nomogram with good distinctive power for severe illness requiring ICU follow-up. Clinicians can easily predict the course of COVID-19 and decide the procedure and facility of further follow-up by using clinical and laboratory values of patients available upon admission.