Emosi dan punca anak wanita Hiv/Aids berada di rumah perlindungan.

Anak kepada wanita HIV/AIDS distigma, didiskriminasi, disisihkan dan dilayan secara negatif oleh keluarga dan masyarakat. Jarang ada ahli keluarga yang mahu membela mereka.Wanita HIV selalunya terpaksa menghantar anak ke rumah perlindungan sebelum penyakit mereka meningkat ke tahap AIDS dan tak berupaya untuk menjaga anak sendiri. Rumah perlindungan difikirkan sebagai tempat yang paling sesuai apabila tidak ada ahli keluarga yang ingin menjaga anak mereka terutama yang HIV. Artikel ini mempunyai dua tujuan utama. Pertama, mengenalpasti alasan kanak-kanak HIV/AIDS berada di rumah perlindungan. Kedua, menyelami perasaan mereka setelah berada di rumah perlindungan. Perbincangan ini diasaskan kepada data yang didapati daripada temu bual mendalam dengan 12 orang kanak-kanak HIV/AIDS yang ditempatkan di dua rumah perlindungan di Kuala Lumpur, iaitu PERNIM (tujuh orang) dan Rumah Solehah (lima orang), yang dilakukan dalam tahun 2009 hingga 2010. Terdapat empat penyebab yang menyebabkan responden ditempatkan di PERNIM dan Rumah Solehah, iaitu (a) dihantar oleh ahli keluarga, (b) ditinggalkan di hospital oleh keluarga, (c) dibuang di tempat awam dan (d) ditemui oleh pekerja Jabatan Kebajikan Masyarakat terbiar di jalanan. Tanpa keluarga di sisi, kanak-kanak ini merasa sedih, ragu-ragu, takut,bimbang dan marah. Mereka tidak mendapat kasih sayang daripada ibu bapa dan keluarga sendiri seperti kanak-kanak lain. Namun begitu, mereka merasa gembira, bersyukur dan berterima kasih kerana masih ada orang yang sudi menjaga, merawat, mendidik, memberi makan dan memberi perlindungan kepada mereka. Di rumah perlindungan mereka dapat merasa kehidupan berkeluarga dan disayangi walaupun bukan daripada darah daging sendir

At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods

By September 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, however, developed with small unrepresentative samples and with methodological limitations. It is highly important to develop predictive tools for pulmonary embolism (PE) in COVID-19 patients as one of the most severe preventable complications of COVID-19. Early recognition can help provide life-saving targeted anti-coagulation therapy right at admission. Using a dataset of more than 800,000 COVID-19 patients from an international cohort, we propose a cost-sensitive gradient-boosted machine learning model that predicts occurrence of PE and death at admission. Logistic regression, Cox proportional hazards models, and Shapley values were used to identify key predictors for PE and death. Our prediction model had a test AUROC of 75.9% and 74.2%, and sensitivities of 67.5% and 72.7% for PE and all-cause mortality respectively on a highly diverse and held-out test set. The PE prediction model was also evaluated on patients in UK and Spain separately with test results of 74.5% AUROC, 63.5% sensitivity and 78.9% AUROC, 95.7% sensitivity. Age, sex, region of admission, comorbidities (chronic cardiac and pulmonary disease, dementia, diabetes, hypertension, cancer, obesity, smoking), and symptoms (any, confusion, chest pain, fatigue, headache, fever, muscle or joint pain, shortness of breath) were the most important clinical predictors at admission. Age, overall presence of symptoms, shortness of breath, and hypertension were found to be key predictors for PE using our extreme gradient boosted model. This analysis based on the, until now, largest global dataset for this set of problems can inform hospital prioritisation policy and guide long term clinical research and decision-making for COVID-19 patients globally. Our machine learning model developed from an international cohort can serve to better regulate hospital risk prioritisation of at-risk patients. © The Author(s) 2024