Poor sleep quality: A wake-up call for the elderly at a tertiary care centre in Islamabad, Pakistan.

OBJECTIVE: To assess the burden of sleep disorders in the elderly, and the effects of various co-morbidities linked with sleep disorders. METHODS: The longitudinal cross-sectional study was conducted in different outpatient departments at a tertiary care centre in Islamabad, Pakistan, from June 2014 to June 2015, and comprised patients of either gender aged 60 years or above. Pittsburgh sleep quality index and Epworth sleepiness scale were used to measure the quality and patterns of sleep and daytime sleepiness in the elderly. Data was analysed using SPSS 21. RESULTS: Of the 1000 subjects, 638(63.8%) were males, and 362(36.2%) were females. The overall mean age was 66.96±7.05 years. Epworth sleepiness scale >10 was found in 265(26.5%) subjects, while Pittsburgh sleep quality index score in 516(51.6%) was >5. Sleep quality score in 578(57.8%) women was statistically significant compared to 478(47.8%) males (p<0.05). CONCLUSIONS: There was a significant burden of sleep-related disorders in the subjects.

Predicting Quality of Life Changes in Hemodialysis Patients Using Machine Learning: Generation of an Early Warning System.

Objective To predict changes in the quality of life scores of hemodialysis patients for the coming month and the development of an early warning system using machine learning Methods It was a prospective cohort study (one-month duration) at the dialysis center of a tertiary care hospital in Pakistan. The study started on 1st October 2016. About 78 patients have been enrolled till now. Bachelor of Medicine and Bachelor of Surgery (MBBS) qualified doctors administered a proforma with demographics and the validated Urdu version of World Health Organization Quality Of Life-BREF (WHOQOL-BREF). It was to be repeated after one month to the same patient by the same investigator. Simple statistics were computed using SPSS version 24 (IBM Corp., Armonk, NY) while machine learning was performed using R (version 3.0) and Orange (version 3.1). Results Using machine learning algorithms, two models (classification tree and Naïve Bayes) were generated to predict an increase or decrease of 5% in a patient's WHOQOL-BREF score over one month. The classification tree was selected as the most accurate model with an area under curve (AUC) of 83.3% (accuracy: 81.9%) for the prediction of 5% increase in QOL and an AUC of 76.2% (accuracy: 81.8%) for the prediction of 5% decrease in QOL over the coming month. The factors associated with an increase of QOL by 5% or more over the next month included younger age (<19 years) and higher iron sucrose doses (>278mg/month). Drops in psychological, physical, and social domain scores lead to a decrease of 5% or more in QOL scores over the following month. Conclusion An early warning system, dialysis data interpretation for algorithmic-prediction on quality of life (DIAL) was built for the early detection of deteriorating QOL scores in the hemodialysis population using machine learning algorithms. The model pointed out that working on psychological and environmental domains, in particular, may prevent the drop in QOL scores from occurring. DIAL, if implemented on a larger scale, is expected to help patients in terms of ensuring a better QOL and in reducing the financial burden in the long term.

Prevalence of Obesity in Carpal Tunnel Syndrome Patients: A Cross-Sectional Survey.

Carpal tunnel syndrome (CTS) is the most common compressive entrapment neuropathy caused by the compression of the median nerve at the wrist space known as the carpal tunnel. The epidemiologic factors related to CTS include genetic, medical, social, vocational, and demographic factors. The common symptoms experienced include pain, paresthesia, and numbness in the median nerve distribution. If left untreated, it can lead to irreversible median nerve damage, causing a loss of hand function. Body mass index (BMI) has been attributed as a risk factor for the development of CTS. We planned to determine the frequency of obesity among CTS patients in the neurophysiology department of a tertiary care center in Islamabad, Pakistan. The survey was designed as a cross-sectional descriptive study from March 2016 to August 2016 using a consecutive nonprobability sampling technique. A total of 112 patients with a mean age of 54 ± 5 years were included in the study. In the study population, 39 patients (35 percent) were males and 73 were females (65 percent). Based on BMI, 74 patients (66 percent) had a normal weight and 38 (34 percent) were obese. The frequency of obesity in our study was 34 percent, excluding the other comorbid conditions, which is quite high. Targeted therapy in those with CTS should also include weight reduction measures because obesity poses a cause-and-effect relationship for both the severity and the pathogenesis of CTS.

Spinal Schwannoma with Intradural Intramedullary Hemorrhage.

Patients with spinal abnormalities infrequently present with intradural intramedullary bleeding. The more common causes include spinal trauma, arteriovenous malformations and saccular aneurysms of spinal arteries. On occasion, spinal cord tumors either primary or metastatic may cause intramedullary bleed with ependymoma of the conus medullaris. Spinal nerve sheath tumors such as schwannomas only rarely cause intradural intramedullary bleed, especially in the absence of spinal cord or nerve root symptoms. We report a case of spinal intradural schwannoma presenting with acute onset of quadriparesis. Cerebral angiography studies were negative but magnetic resonance imaging (MRI) of the spine revealed a large hemorrhagic tumor in the thoracolumbar junction. However, we suggest that the patients with intradural intramedullary bleed should be evaluated for underlying spine disease.

Predicting Central Venous Pressure by Measuring Femoral Venous Diameter Using Ultrasonography.

OBJECTIVES: The objective of this exploratory study was to find out the correlation of femoral vein diameter (FVD) to central venous pressure (CVP) measurements and to derive a prediction equation to help ascertain the fluid volume status in a critical patient. PATIENTS AND METHODS: This was a single-centered prospective cohort study designed and conducted by the critical care department of Shifa International hospital in Islamabad, Pakistan. Patients were enrolled from the medical and surgical intensive care units. The inclusion criteria consisted of patients > 18 years of age, and an intrathoracic central venous catheterization (CVC) in place for producing CVP waveform through the transducer. Patients having contraindications to CVP placement and those unable to lie supine were excluded from the study. Critical Care fellows with sufficient training in performing venous ultrasonography measured the FVD. They were blinded to the CVP values of the same patients. RESULTS: The study included 108 patients. Among these 70/108 (64.8%) were males. Mean age was 53.85 (SD=16.74). The CVP and femoral vein diameter were measured in all patients. Mean CVP was 9.89 cmH2O (SD=3.46) and mean femoral vein diameter was 0.92 cm (SD=0.27). Multiple regression was used to generate a prediction model. FVD, age and sex of the patient were used as predictor variables to predict CVP diameter. The model was statistically significant with a p-value of < 0.000 and an F-value of 104.806. R-squared value for this model came out to be 0.744, thus the model was able to explain about 74.4% of the variance in the values observed for CVP. When controlled for age and sex, FVD was found highly correlated with CVP diameter with a p-value of < 0.000. A regression equation was derived that can be used to generate predicted values of CVP in millimeters of mercury with an R-square of 0.745 if FVD in centimeters is provided; CVP (cmH2O) = -0.039 + 10.718* FVD. CONCLUSIONS: FVD was found highly correlated to CVP measurements and it suggests an alternate non-invasive method of ascertaining the volume status in the critically ill.

Antibiogram of Medical Intensive Care Unit at Tertiary Care Hospital Setting of Pakistan.

OBJECTIVE:  To determine the frequency of micro-organisms causing sepsis as well as to determine the antibiotic susceptibility and resistance of microorganisms isolated in a medical intensive care unit. MATERIALS AND METHODS:  This is a cross-sectional analysis of 802 patients from a medical intensive care unit (ICU) of Shifa International Hospital, Islamabad, Pakistan over a one-year period from August 2015 to August 2016. Specimens collected were from blood, urine, endotracheal secretions, catheter tips, tissue, pus swabs, cerebrospinal fluid, ascites, bronchoalveolar lavage (BAL), and pleural fluid. All bacteria were identified by standard microbiological methods, and antibiotic sensitivity/resistance was performed using the disk diffusion technique, according to Clinical and Laboratory Standards Institute (CLSI) guidelines. Data was collected using a critical care unit electronic database and data analysis was done by using  the Statistical Package for Social Sciences (SPSS), version 20 (IBM SPSS Statistics, Armonk, NY). RESULTS:  Gram-negative bacteria were more frequent as compared to gram-positive bacteria. Most common bacterial isolates were Acinetobacter (15.3%), Escherichia coli (15.3%), Pseudomonas aeruginosa (13%), and Klebsiella pneumoniae (10.2%), whereas Enterococcus (7%) and methicillin-resistant staphylococcus aureus (MRSA) (6.2%) were the two most common gram-positive bacteria. For Acinetobacter, colistin was the most effective antibiotic (3% resistance). For E.coli, colistin (0%), tigecycline (0%), amikacin (7%), and carbapenems (10%) showed low resistance. Pseudomonas aeruginosa showed low resistance to colistin (7%). For Klebsiella pneumoniae, low resistance was seen for tigecycline (0%) and minocycline (16%). Overall, ICU mortality was 31.3%, including miscellaneous cases. CONCLUSION:  Gram-negative infections, especially by multidrug-resistant organisms, are on the rise in ICUs. Empirical antibiotics should be used according to the local unit specific data. Constant evaluation of current practice on basis of trends in multidrug resistance and antibiotic consumption patterns are essential.

Predictors of Prolonged Hospitalization in Patients with Fever.

OBJECTIVE:  The study was conducted to analyze the predictors of prolonged hospitalization in patients with fever. PATIENTS AND METHODS:  This was a prospective cohort study conducted from July - December 2015 at Ayub Teaching Hospital, Pakistan. Convenience sampling was used to enroll the patients who visited the hospital during the study duration. A sample size of 115 patients was calculated. It included patients who presented with a new onset fever which started in the last month, and the cause of fever was undiagnosed at the time of admission. Critical patients were excluded. Data for more than 30 variables was collected on a pro forma. Univariate regression methods were used to analyze the data in the Statistical Package for Social Sciences (SPSS), version 23. RESULTS:  A total of 115 patients were analyzed. Males constituted 66/115 (57.4%). The mean age for patients was 43.6 years (standard deviation (SD) = 20.2). On admission, low platelet counts (p = 0.001), high erythrocyte sedimentation rate (ESR) counts (p = 0.007), a high total leukocyte count (TLC) (p = 0.029), and involvement of nervous (p = 0.021), cardiovascular (p = 0.04), respiratory (p = 0.043), gastroenterological (p = 0.042), hematological (p = 0.028), or urogenital system (p = 0.016) were associated with a longer stay in the hospital. CONCLUSION:  Patients with an undiagnosed and new onset fever will have a longer hospital stay if, on admission, they have low platelet counts, a higher ESR, a high TLC, or involvement of nervous, cardiovascular, respiratory, gastrointestinal, hematological, or urogenital systems. An early identification of risk factors can lead to better treatment and may also lead to a decreased hospital stay.

Renal Infiltration by Diffuse Large B-Cell Lymphoma as a Rare Cause of Fanconi's Syndrome: A Case Report.

We report the case of a 16-year-old female patient with a known history of coeliac disease, who presented with the complaints of diarrhea, vomiting and generalized body weakness. On examination, she was found to have dehydration, decreased power in all her limbs, cervical lymphadenopathy and hepatosplenomegaly. Investigations showed severe hypokalemia, hyponatremia, hypomagnesemia, hypoglycemia and mildly enlarged kidneys on ultrasonography. Biopsy of the duodenum confirmed the flare up of coeliac disease, while cervical lymph node biopsy was positive for atypical lymphoid infiltrate and a morphology suggestive of non-Hodgkin's lymphoma. The immune profile performed on this sample confirmed the presence of activated/non-germinal center type of diffuse large B cell lymphoma (DLBCL), which was morphologically aggressive in type. The bone marrow biopsy was hypocellular and was negative for any infiltration. The patient was suspected to have developed infiltration of one or both kidneys leading to a rare presentation of Fanconi's syndrome. She was given first dose of rituximab on the 14th day of her admission. Unfortunately, she developed cardiopulmonary arrest and expired on the next day. We recommend screening for a possible renal involvement in patients with DLBCL and in patients with unusually deranged serum electrolytes as seen in Fanconi's syndrome. Renal biopsy is considered the gold standard modality for diagnosis and if possible, an earlier sample in a patient with newly developed acute kidney injury can save future complications.