Proactive project scheduling in an R&D department: a bi-objective genetic algorithm

In this paper, we present part of a study on stochastic, dynamic project scheduling in an R&D Department of a leading home appliances company in Turkey. The problem under consideration is the preemptive resource constrained multi-project scheduling problem with generalized precedence relations in a stochastic and dynamic environment. The model consists of three phases. Phase I of the model provides a systematic approach to assess uncertainty resulting in activity deviation distributions. In Phase II, proactive project scheduling is accomplished through two different scheduling approaches,which employ a bi-objective genetic algorithm. Phase III is the reactive project scheduling phase aiming at rescheduling the disrupted project activities. Here, we will limit our presentation to Phase II – the proactive project scheduling phase. The procedure is demonstrated through an implementation with real data covering 37 R&D projects. Computational study is performed to compare the two different scheduling approaches called single and multi-project scheduling approaches, as well as two different chromosome evaluation heuristics. Results are presented and discussed

Uncertainty assessment in project scheduling with data mining

During project execution, especially in a multi-project environment project activities are subject to risks that may cause delays or interruptions in the baseline schedules. This paper considers the resource constrained multi-project scheduling problem with generalized activity precedence relations requiring multi-skilled resources in a stochastic and dynamic environment present in the R&D department of a home appliances company and introduces a two-phase model incorporating data mining and project scheduling techniques. This paper presents the details of Phase I, uncertainty assessment phase, where Phase II corresponds to proactive project scheduling module. In the proposed uncertainty assessment approach models are developed to classify the projects and their activities with respect to resource usage deviation levels. In doing so, the proposed approach enables the project managers not only to predict the deviation level of projects before they actually start, but also to take needed precautions by detecting the most risky projects. Moreover, Phase I generates one of the main inputs of Phase II to obtain robust baseline project schedules and identifies the risky activities that need close monitoring. Details of the proposed approach are illustrated using R&D project data of a leading home appliances company. The results support the efficiency of the proposed approach

Management of patients with connective tissue disease-associated interstitial lung diseases during the COVID-19 pandemic

The novel coronavirus disease (COVID-19) is similar to connective tissue disease-associated interstitial lung diseases (CTD-ILD) in many aspects. However, patients with CTD-ILD have required particular attention during the pandemic since they are at high risk due to -immunosuppressive treatments. Thus, prompt decisions for diagnosis and treatment initiation have become more important than earlier for these patients during the pandemic. Radiological perspectives have become inevitable for the differential diagnosis of this group -during the pandemic, particularly to obtain rapid and accurate results that allow the physicians to start treatment immediately. However, in addition to radiological images, a definitive diagnosis also requires access to extensive information regarding patient history, including characteristics of comorbidities, and clinical and serological findings. Consequently, the differential diagnosis of COVID-19 and CTD-ILD can yield accurate treatment regimens that differ greatly between the 2 diseases, and also prevent the spread of the outbreak with COVID-19 patients treated under isolation

The Effect of Training About Sleep Hygiene on HbA1c Levels of Type 2 Diabetes Mellitus Patients: A Randomized Controlled Trial

Objective: In this study, we aimed to reveal whether training on sleep hygiene have an effect on blood glucose regulation of type 2 diabetes patients. Materials and methods: Those with even protocol numbers were included in the case group and those with odd numbers were included in the control group. Pittsburgh sleep quality index was applied face-to-face to all patients included in the study and at the first admission sleep hygiene training was given to the case group. HbA1c values were noted separately as first and second visit for both groups. Those with known sleep disorders and language or psychiatric problems that would prevent them from answering the questionnaire were excluded from the study. Differences between demographic and clinical features of groups were evaluated using chi-square and Student’s t-tests. Comparisons of the case and control groups before and after sleep hygiene training were evaluated using ANCOVA test adjusted for BMI and DM duration. Results: A total of 347 Type 2 diabetes patients included in this randomized controlled trial (113 case 234 control). Significant difference was observed in the HbA1c values measured before and after the training of the case group. The second mean HbA1c (8.13 ± 2.03 mmol/L) of the control group was significantly higher than the second mean HbA1c (7.51 ± 1.42 mmol/L) values of the case group (p = 0.004). Conclusions: Our study revealed that in addition to classical diabetes treatment, sleep hygiene training also has a positive effect on blood glucose regulation of patients

Factors affecting treatment success in community-acquired pneumonia

Background/aim: Treatment failure in hospitalized patients with community-acquired pneumonia is a major cause of mortality. The aim of this study was to evaluate the factors affecting treatment success in community-acquired pneumonia. Materials and methods: A total of 537 patients (mean age: 66.1 ± 15.8 years, 365 males) registered to the Turkish Thoracic Society Pneumonia Database were analyzed. Of these, clinical improvement or cure, defined as treatment success, was achieved in 477, whereas 60 patients had treatment failure and/or died. Results: Lower numbers of neutrophils (5989.9 ± 6237.3 vs. 8495.6 ± 7279.5/mm3 ), higher blood urea levels (66.1 ± 42.1 vs. 51.2 ± 38.2 mg/dL), higher Pneumonia Severity Index (PSI) scores (123.3 ± 42.6 vs. 96.3 ± 32.9), higher CURB-65 scores (2.7 ± 1.2 vs. 2.2 ± 0.9), lower PaO2 /FiO2 ratios (216.3 ± 86.8 vs. 269.9 ± 65.6), and the presence of multilobar (33.3% vs. 16.4%) and bilateral (41.7% vs. 18.9%) radiologic infiltrates were related to treatment failure. The PSI score and PaO2 /FiO2 ratio were independent parameters affecting treatment results in multivariate linear regression analysis (P < 0.001). Conclusion: The risk of treatment failure is high in patients with severe pneumonia and with respiratory failure. Effective treatment and close monitoring are required for these cases

Türkiye'de sağlık bakımı ile ilişkili pnömoni olgularının klinik özellikleri ve sonuçları

Giriş: Hastaneye yatış, hemodiyaliz programında bulunma, sağlık bakım evlerinde yaşama, önceki 30 günde evde yara bakımı öyküsü, ayaktan intravenöz tedavi ve kemoterapi öyküsü olan olgularda toplumda gelişen pnömoniler, sağlık bakımı ilişkili pnömoni (SBİP) olarak adlandırılmaktadır. Türkiye'de geniş bir popülasyonu kapsayan çalışmamızda, hastanede yatan toplumda gelişen pnömoni (TGP) ve SBİP olgularının başvuru özelliklerinin, laboratuvar verilerinin, etken dağılımlarının ve prognozlarının karşılaştırılması amaçlanmıştır.Materyal ve Metod: Türk Toraks Derneği Solunum Sistemi İnfeksiyonları Çalışma Grubu Pnömoni Veri Tabanı (TURCAP)'na yedi merkez tarafından kayıt edilmiş olan 785 (ortalama yaş 65.3 ± 16.4, 530 erkek) TGP ve SBİP olguları değerlendirilmiştir. Demografik özellikler, klinik öykü, pnömoni ağırlık skorları, laboratuvar ve radyolojik bulgular karşılaştırılmıştır.Bulgular: 785 olguda 207 (%26.4)'si SBİP ve 578 (%73.6)'i TGP tanısı almıştır. 207 SBİP olgusunun 140 (%67.6)'ının son 90 günde hastaneye yatış öyküsü olduğu, 28 (%3.6)'inin son 30 günde hemodiyaliz programına alındığı ve 22 (%10.6)'sinin sağlık bakım evinde kaldığı saptanmıştır. SBİP olgularında TGP'ye kıyasla komorbidite sıklığı artmış (%93.2'ye karşın %81.6; p= 0.001); PSI skoru yüksek (103.9 ± 37.2'ye karşın 94.6 ± 35.4; p= 0.002) saptanmıştır. Etken izolasyonu TGP'de %12.1 (70/578), SBİP'te %14.5 (30/207) oranında sağlanabilmiştir. Hastanede yatış süresi SBİP olgularında daha yüksek bulunmakla beraber (sırasıyla 8.6 ± 5.5'e karşın 7.5 ± 6.1 gün, p= 0.03); tedavi başarısı, yoğun bakımda kalış ve mortalite oranları açısından farklılık saptanmamıştır.Sonuç: TGP'ye kıyasla SBİP olgularında hastalık daha ağır seyretmekle beraber mortalitede fark izlenmemektedir. SBİP için mevcut kriterler olumsuz klinik sonuçları tahmin etmemektedir. Çok ilaca dirençli patojenlere yönelik lokal risk faktörleri tanımlayabilecek çalışmalara gereksinim vardır.Introduction: Pneumonia in cases with preceding hospitalization, hemodialysis, intravenous therapy, wound care, or chemotherapy within the prior 30 days and residence in nursing homes are defined as healthcare associated pneumonia (HCAP). The aim of this study was to compare the demographic and laboratory data, isolated causative agents and prognosis of patients with communityacquired pneumonia (CAP) and HCAP in a large population in Turkey. Materials and Methods: The data of 785 cases (average age 65.3 ± 16.4, 530 male) registered to Turkish Thoracic Society Respiratory Infections Study Group CAP database (TURCAP) were examined. The demographic data, clinical history, pneumonia severity scores (PSI), laboratory and radiologic findings of the CAP and HCAP patients were compared.Results: Out of 785 cases, 207 (26.4%) were diagnosed with HCAP and 578 (73.6%) with CAP. Among HCAP cases, 140/207 (67.6%) had preceding hospitalization in the last 90 days, 28/207 (13.5%) were on a hemodialysis program during the previous 30 days and 22/207 (10.6%) were staying in nursing homes. Patients with HCAP more frequently had comorbidities (93.2% vs. 81.6%; p= 0.001) and higher PSI scores (103.9 ± 37.2 vs. 94.6 ± 35.4; p= 0.002) compared to patients with CAP. A causative microorganism was isolated in only 12.1% (70/578) of CAP and 14.5% (30/207) of HCAP patients. The length of stay in hospital was higher in HCAP than CAP (8.6 ± 5.5 vs. 7.5 ± 6.1 days, p= 0.03); however the rates of treatment failure, intensive care unit admission and mortality were similar.Conclusion: In comparison to CAP, HCAP patients tend to have more severe disease, despite have no difference in mortality. The current criteria for HCAP do not predict worse clinical outcomes. Further work is required to define local risk factors for multidrugresistant pathogens